- f() - Method in class org.apache.spark.rdd.ZippedPartitionsRDD2
-
- f() - Method in class org.apache.spark.rdd.ZippedPartitionsRDD3
-
- f() - Method in class org.apache.spark.rdd.ZippedPartitionsRDD4
-
- f1Measure() - Method in class org.apache.spark.mllib.evaluation.MultilabelMetrics
-
Returns document-based f1-measure averaged by the number of documents
- f1Measure(double) - Method in class org.apache.spark.mllib.evaluation.MultilabelMetrics
-
Returns f1-measure for a given label (category)
- failed() - Method in class org.apache.spark.scheduler.TaskInfo
-
- FAILED() - Static method in class org.apache.spark.TaskState
-
- failedJobs() - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- failedStages() - Method in class org.apache.spark.scheduler.DAGScheduler
-
- failedStages() - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- FailedStageTable - Class in org.apache.spark.ui.jobs
-
- FailedStageTable(Seq<StageInfo>, String, JobProgressListener, boolean) - Constructor for class org.apache.spark.ui.jobs.FailedStageTable
-
- failedTasks() - Method in class org.apache.spark.ui.exec.ExecutorSummaryInfo
-
- failedTasks() - Method in class org.apache.spark.ui.jobs.UIData.ExecutorSummary
-
- failure() - Method in class org.apache.spark.partial.ApproximateActionListener
-
- failureReason() - Method in class org.apache.spark.scheduler.StageInfo
-
If the stage failed, the reason why.
- failuresBySlaveId() - Method in class org.apache.spark.scheduler.cluster.mesos.CoarseMesosSchedulerBackend
-
- FAIR() - Static method in class org.apache.spark.scheduler.SchedulingMode
-
- FAIR_SCHEDULER_PROPERTIES() - Method in class org.apache.spark.scheduler.FairSchedulableBuilder
-
- FairSchedulableBuilder - Class in org.apache.spark.scheduler
-
- FairSchedulableBuilder(Pool, SparkConf) - Constructor for class org.apache.spark.scheduler.FairSchedulableBuilder
-
- FairSchedulingAlgorithm - Class in org.apache.spark.scheduler
-
- FairSchedulingAlgorithm() - Constructor for class org.apache.spark.scheduler.FairSchedulingAlgorithm
-
- fakeClassTag() - Static method in class org.apache.spark.api.java.JavaSparkContext
-
Produces a ClassTag[T], which is actually just a casted ClassTag[AnyRef].
- fakeOutput(Seq<Attribute>) - Method in class org.apache.spark.sql.hive.HiveStrategies.ParquetConversion.PhysicalPlanHacks
-
- FakeParquetSerDe - Class in org.apache.spark.sql.hive.parquet
-
A placeholder that allows Spark SQL users to create metastore tables that are stored as
parquet files.
- FakeParquetSerDe() - Constructor for class org.apache.spark.sql.hive.parquet.FakeParquetSerDe
-
- FALSE() - Static method in class org.apache.spark.sql.hive.HiveQl
-
- FalsePositiveRate - Class in org.apache.spark.mllib.evaluation.binary
-
False positive rate.
- FalsePositiveRate() - Constructor for class org.apache.spark.mllib.evaluation.binary.FalsePositiveRate
-
- falsePositiveRate(double) - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
-
Returns false positive rate for a given label (category)
- fastSquaredDistance(VectorWithNorm, VectorWithNorm) - Static method in class org.apache.spark.mllib.clustering.KMeans
-
- fastSquaredDistance(Vector, double, Vector, double, double) - Static method in class org.apache.spark.mllib.util.MLUtils
-
Returns the squared Euclidean distance between two vectors.
- feature() - Method in class org.apache.spark.mllib.tree.model.Split
-
- featureArity() - Method in class org.apache.spark.mllib.tree.impl.DecisionTreeMetadata
-
- features() - Method in class org.apache.spark.mllib.regression.LabeledPoint
-
- featuresCol() - Method in interface org.apache.spark.ml.param.HasFeaturesCol
-
param for features column name
- featureSubset() - Method in class org.apache.spark.mllib.tree.RandomForest.NodeIndexInfo
-
- FeatureType - Class in org.apache.spark.mllib.tree.configuration
-
:: Experimental ::
Enum to describe whether a feature is "continuous" or "categorical"
- FeatureType() - Constructor for class org.apache.spark.mllib.tree.configuration.FeatureType
-
- featureType() - Method in class org.apache.spark.mllib.tree.model.Bin
-
- featureType() - Method in class org.apache.spark.mllib.tree.model.Split
-
- featureUpdate(int, int, double, double) - Method in class org.apache.spark.mllib.tree.impl.DTStatsAggregator
-
Faster version of update
.
- FetchFailed - Class in org.apache.spark
-
:: DeveloperApi ::
Task failed to fetch shuffle data from a remote node.
- FetchFailed(BlockManagerId, int, int, int, String) - Constructor for class org.apache.spark.FetchFailed
-
- fetchFile(String, File, SparkConf, SecurityManager, Configuration, long, boolean) - Static method in class org.apache.spark.util.Utils
-
Download a file to target directory.
- fetchPct() - Method in class org.apache.spark.scheduler.RuntimePercentage
-
- field() - Method in class org.apache.spark.storage.BroadcastBlockId
-
- FieldAccessFinder - Class in org.apache.spark.util
-
- FieldAccessFinder(Map<Class<?>, Set<String>>) - Constructor for class org.apache.spark.util.FieldAccessFinder
-
- FIFO() - Static method in class org.apache.spark.scheduler.SchedulingMode
-
- FIFOSchedulableBuilder - Class in org.apache.spark.scheduler
-
- FIFOSchedulableBuilder(Pool) - Constructor for class org.apache.spark.scheduler.FIFOSchedulableBuilder
-
- FIFOSchedulingAlgorithm - Class in org.apache.spark.scheduler
-
- FIFOSchedulingAlgorithm() - Constructor for class org.apache.spark.scheduler.FIFOSchedulingAlgorithm
-
- file() - Method in class org.apache.spark.storage.FileSegment
-
- file() - Method in class org.apache.spark.storage.TachyonFileSegment
-
- FileAppender - Class in org.apache.spark.util.logging
-
Continuously appends the data from an input stream into the given file.
- FileAppender(InputStream, File, int) - Constructor for class org.apache.spark.util.logging.FileAppender
-
- fileDir() - Method in class org.apache.spark.HttpFileServer
-
- fileExists(TachyonFile) - Method in class org.apache.spark.storage.TachyonBlockManager
-
- fileIndex() - Method in class org.apache.spark.util.FileLogger
-
- FileInputDStream<K,V,F extends org.apache.hadoop.mapreduce.InputFormat<K,V>> - Class in org.apache.spark.streaming.dstream
-
This class represents an input stream that monitors a Hadoop-compatible filesystem for new
files and creates a stream out of them.
- FileInputDStream(StreamingContext, String, Function1<Path, Object>, boolean, ClassTag<K>, ClassTag<V>, ClassTag<F>) - Constructor for class org.apache.spark.streaming.dstream.FileInputDStream
-
- FileInputDStream.FileInputDStreamCheckpointData - Class in org.apache.spark.streaming.dstream
-
A custom version of the DStreamCheckpointData that stores names of
Hadoop files as checkpoint data.
- FileInputDStream.FileInputDStreamCheckpointData() - Constructor for class org.apache.spark.streaming.dstream.FileInputDStream.FileInputDStreamCheckpointData
-
- FileLogger - Class in org.apache.spark.util
-
A generic class for logging information to file.
- FileLogger(String, SparkConf, Configuration, int, boolean, boolean, Option<FsPermission>) - Constructor for class org.apache.spark.util.FileLogger
-
- FileLogger(String, SparkConf, boolean, boolean) - Constructor for class org.apache.spark.util.FileLogger
-
- FileLogger(String, SparkConf, boolean) - Constructor for class org.apache.spark.util.FileLogger
-
- FileLogger(String, SparkConf) - Constructor for class org.apache.spark.util.FileLogger
-
- fileName() - Method in class org.apache.spark.sql.json.JSONRelation
-
- filePath() - Method in class org.apache.spark.scheduler.cluster.SimrSchedulerBackend
-
- filePath() - Method in class org.apache.spark.sql.hive.AddFile
-
- files() - Method in class org.apache.spark.SparkContext
-
- files() - Method in class org.apache.spark.sql.parquet.Partition
-
- fileSegment() - Method in class org.apache.spark.storage.BlockObjectWriter
-
Returns the file segment of committed data that this Writer has written.
- fileSegment() - Method in class org.apache.spark.storage.DiskBlockObjectWriter
-
- FileSegment - Class in org.apache.spark.storage
-
References a particular segment of a file (potentially the entire file),
based off an offset and a length.
- FileSegment(File, long, long) - Constructor for class org.apache.spark.storage.FileSegment
-
- fileStream(String) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
Create an input stream that monitors a Hadoop-compatible filesystem
for new files and reads them using the given key-value types and input format.
- fileStream(String, ClassTag<K>, ClassTag<V>, ClassTag<F>) - Method in class org.apache.spark.streaming.StreamingContext
-
Create a input stream that monitors a Hadoop-compatible filesystem
for new files and reads them using the given key-value types and input format.
- fileStream(String, Function1<Path, Object>, boolean, ClassTag<K>, ClassTag<V>, ClassTag<F>) - Method in class org.apache.spark.streaming.StreamingContext
-
Create a input stream that monitors a Hadoop-compatible filesystem
for new files and reads them using the given key-value types and input format.
- FileSystemHelper - Class in org.apache.spark.sql.parquet
-
- FileSystemHelper() - Constructor for class org.apache.spark.sql.parquet.FileSystemHelper
-
- fillObject(Iterator<Writable>, Deserializer, Seq<Tuple2<Attribute, Object>>, MutableRow) - Static method in class org.apache.spark.sql.hive.HadoopTableReader
-
Transform all given raw Writable
s into Row
s.
- filter(Function<Double, Boolean>) - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Return a new RDD containing only the elements that satisfy a predicate.
- filter(Function<Tuple2<K, V>, Boolean>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Return a new RDD containing only the elements that satisfy a predicate.
- filter(Function<T, Boolean>) - Method in class org.apache.spark.api.java.JavaRDD
-
Return a new RDD containing only the elements that satisfy a predicate.
- filter(Function1<Graph<VD, ED>, Graph<VD2, ED2>>, Function1<EdgeTriplet<VD2, ED2>, Object>, Function2<Object, VD2, Object>, ClassTag<VD2>, ClassTag<ED2>) - Method in class org.apache.spark.graphx.GraphOps
-
Filter the graph by computing some values to filter on, and applying the predicates.
- filter(Function1<EdgeTriplet<VD, ED>, Object>, Function2<Object, VD, Object>) - Method in class org.apache.spark.graphx.impl.EdgePartition
-
Construct a new edge partition containing only the edges matching epred
and where both
vertices match vpred
.
- filter(Function1<EdgeTriplet<VD, ED>, Object>, Function2<Object, VD, Object>) - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- filter(Function2<Object, VD, Object>) - Method in class org.apache.spark.graphx.impl.VertexPartitionBaseOps
-
Restrict the vertex set to the set of vertices satisfying the given predicate.
- filter(Function1<Tuple2<Object, VD>, Object>) - Method in class org.apache.spark.graphx.VertexRDD
-
Restricts the vertex set to the set of vertices satisfying the given predicate.
- filter(Params) - Method in class org.apache.spark.ml.param.ParamMap
-
Filters this param map for the given parent.
- filter(Function1<T, Object>) - Method in class org.apache.spark.rdd.RDD
-
Return a new RDD containing only the elements that satisfy a predicate.
- filter(Function<Row, Boolean>) - Method in class org.apache.spark.sql.api.java.JavaSchemaRDD
-
Return a new RDD containing only the elements that satisfy a predicate.
- Filter - Class in org.apache.spark.sql.execution
-
:: DeveloperApi ::
- Filter(Expression, SparkPlan) - Constructor for class org.apache.spark.sql.execution.Filter
-
- filter(Function1<Row, Object>) - Method in class org.apache.spark.sql.SchemaRDD
-
- Filter - Class in org.apache.spark.sql.sources
-
- Filter() - Constructor for class org.apache.spark.sql.sources.Filter
-
- filter() - Method in class org.apache.spark.storage.BlockManagerMessages.GetMatchingBlockIds
-
- filter(Function<T, Boolean>) - Method in class org.apache.spark.streaming.api.java.JavaDStream
-
Return a new DStream containing only the elements that satisfy a predicate.
- filter(Function<Tuple2<K, V>, Boolean>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream containing only the elements that satisfy a predicate.
- filter(Function1<T, Object>) - Method in class org.apache.spark.streaming.dstream.DStream
-
Return a new DStream containing only the elements that satisfy a predicate.
- filter(Function1<Tuple2<A, B>, Object>) - Method in class org.apache.spark.util.TimeStampedHashMap
-
- filter(Function1<Tuple2<A, B>, Object>) - Method in class org.apache.spark.util.TimeStampedWeakValueHashMap
-
- FilteredDStream<T> - Class in org.apache.spark.streaming.dstream
-
- FilteredDStream(DStream<T>, Function1<T, Object>, ClassTag<T>) - Constructor for class org.apache.spark.streaming.dstream.FilteredDStream
-
- FilteredRDD<T> - Class in org.apache.spark.rdd
-
- FilteredRDD(RDD<T>, Function1<T, Object>, ClassTag<T>) - Constructor for class org.apache.spark.rdd.FilteredRDD
-
- FilteringParquetRowInputFormat - Class in org.apache.spark.sql.parquet
-
We extend ParquetInputFormat in order to have more control over which
RecordFilter we want to use.
- FilteringParquetRowInputFormat() - Constructor for class org.apache.spark.sql.parquet.FilteringParquetRowInputFormat
-
- filterName() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.AddWebUIFilter
-
- filterParams() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.AddWebUIFilter
-
- filterWith(Function1<Object, A>, Function2<T, A, Object>) - Method in class org.apache.spark.rdd.RDD
-
Filters this RDD with p, where p takes an additional parameter of type A.
- finalRDD() - Method in class org.apache.spark.scheduler.JobSubmitted
-
- finalStage() - Method in class org.apache.spark.scheduler.ActiveJob
-
- findBestSplits(RDD<BaggedPoint<TreePoint>>, DecisionTreeMetadata, Node[], Map<Object, Node[]>, Map<Object, Map<Object, RandomForest.NodeIndexInfo>>, Split[][], Bin[][], Queue<Tuple2<Object, Node>>, TimeTracker, Option<NodeIdCache>) - Static method in class org.apache.spark.mllib.tree.DecisionTree
-
Given a group of nodes, this finds the best split for each node.
- findClass(String) - Method in class org.apache.spark.util.ParentClassLoader
-
- findClosest(TraversableOnce<VectorWithNorm>, VectorWithNorm) - Static method in class org.apache.spark.mllib.clustering.KMeans
-
Returns the index of the closest center to the given point, as well as the squared distance.
- findMaxTaskId(String, Configuration) - Static method in class org.apache.spark.sql.parquet.FileSystemHelper
-
Finds the maximum taskid in the output file names at the given path.
- findSplitsForContinuousFeature(double[], DecisionTreeMetadata, int) - Static method in class org.apache.spark.mllib.tree.DecisionTree
-
Find splits for a continuous feature
NOTE: Returned number of splits is set based on featureSamples
and
could be different from the specified numSplits
.
- findSynonyms(String, int) - Method in class org.apache.spark.mllib.feature.Word2VecModel
-
Find synonyms of a word
- findSynonyms(Vector, int) - Method in class org.apache.spark.mllib.feature.Word2VecModel
-
Find synonyms of the vector representation of a word
- finishAll() - Method in class org.apache.spark.ui.ConsoleProgressBar
-
Mark all the stages as finished, clear the progress bar if showed, then the progress will not
interweave with output of jobs.
- finished() - Method in class org.apache.spark.scheduler.ActiveJob
-
- finished() - Method in class org.apache.spark.scheduler.TaskInfo
-
- FINISHED() - Static method in class org.apache.spark.TaskState
-
- FINISHED_STATES() - Static method in class org.apache.spark.TaskState
-
- finishedTasks() - Method in class org.apache.spark.partial.ApproximateActionListener
-
- finishTime() - Method in class org.apache.spark.scheduler.TaskInfo
-
The time when the task has completed successfully (including the time to remotely fetch
results, if necessary).
- first() - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
- first() - Method in class org.apache.spark.api.java.JavaPairRDD
-
- first() - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return the first element in this RDD.
- first() - Method in class org.apache.spark.rdd.RDD
-
Return the first element in this RDD.
- FIRST_DELAY() - Method in class org.apache.spark.ui.ConsoleProgressBar
-
- firstAvailableClass(String, String) - Method in interface org.apache.spark.mapred.SparkHadoopMapRedUtil
-
- firstAvailableClass(String, String) - Method in interface org.apache.spark.mapreduce.SparkHadoopMapReduceUtil
-
- fit(SchemaRDD, ParamMap) - Method in class org.apache.spark.ml.classification.LogisticRegression
-
- fit(SchemaRDD, ParamPair<?>...) - Method in class org.apache.spark.ml.Estimator
-
Fits a single model to the input data with optional parameters.
- fit(JavaSchemaRDD, ParamPair<?>...) - Method in class org.apache.spark.ml.Estimator
-
Fits a single model to the input data with optional parameters.
- fit(SchemaRDD, Seq<ParamPair<?>>) - Method in class org.apache.spark.ml.Estimator
-
Fits a single model to the input data with optional parameters.
- fit(SchemaRDD, ParamMap) - Method in class org.apache.spark.ml.Estimator
-
Fits a single model to the input data with provided parameter map.
- fit(SchemaRDD, ParamMap[]) - Method in class org.apache.spark.ml.Estimator
-
Fits multiple models to the input data with multiple sets of parameters.
- fit(JavaSchemaRDD, Seq<ParamPair<?>>) - Method in class org.apache.spark.ml.Estimator
-
Fits a single model to the input data with optional parameters.
- fit(JavaSchemaRDD, ParamMap) - Method in class org.apache.spark.ml.Estimator
-
Fits a single model to the input data with provided parameter map.
- fit(JavaSchemaRDD, ParamMap[]) - Method in class org.apache.spark.ml.Estimator
-
Fits multiple models to the input data with multiple sets of parameters.
- fit(SchemaRDD, ParamMap) - Method in class org.apache.spark.ml.feature.StandardScaler
-
- fit(SchemaRDD, ParamMap) - Method in class org.apache.spark.ml.Pipeline
-
Fits the pipeline to the input dataset with additional parameters.
- fit(SchemaRDD, ParamMap) - Method in class org.apache.spark.ml.tuning.CrossValidator
-
- fit(RDD<Vector>) - Method in class org.apache.spark.mllib.feature.IDF
-
Computes the inverse document frequency.
- fit(JavaRDD<Vector>) - Method in class org.apache.spark.mllib.feature.IDF
-
Computes the inverse document frequency.
- fit(RDD<Vector>) - Method in class org.apache.spark.mllib.feature.StandardScaler
-
Computes the mean and variance and stores as a model to be used for later scaling.
- fit(RDD<S>) - Method in class org.apache.spark.mllib.feature.Word2Vec
-
Computes the vector representation of each word in vocabulary.
- fit(JavaRDD<S>) - Method in class org.apache.spark.mllib.feature.Word2Vec
-
Computes the vector representation of each word in vocabulary (Java version).
- fittingParamMap() - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- fittingParamMap() - Method in class org.apache.spark.ml.feature.StandardScalerModel
-
- fittingParamMap() - Method in class org.apache.spark.ml.Model
-
Fitting parameters, such that parent.fit(..., fittingParamMap) could reproduce the model.
- fittingParamMap() - Method in class org.apache.spark.ml.PipelineModel
-
- fittingParamMap() - Method in class org.apache.spark.ml.tuning.CrossValidatorModel
-
- FixedLengthBinaryInputFormat - Class in org.apache.spark.input
-
- FixedLengthBinaryInputFormat() - Constructor for class org.apache.spark.input.FixedLengthBinaryInputFormat
-
- FixedLengthBinaryRecordReader - Class in org.apache.spark.input
-
FixedLengthBinaryRecordReader is returned by FixedLengthBinaryInputFormat.
- FixedLengthBinaryRecordReader() - Constructor for class org.apache.spark.input.FixedLengthBinaryRecordReader
-
- flatMap(FlatMapFunction<T, U>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return a new RDD by first applying a function to all elements of this
RDD, and then flattening the results.
- flatMap(Function1<T, TraversableOnce<U>>, ClassTag<U>) - Method in class org.apache.spark.rdd.RDD
-
Return a new RDD by first applying a function to all elements of this
RDD, and then flattening the results.
- flatMap(FlatMapFunction<T, U>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Return a new DStream by applying a function to all elements of this DStream,
and then flattening the results
- flatMap(Function1<T, Traversable<U>>, ClassTag<U>) - Method in class org.apache.spark.streaming.dstream.DStream
-
Return a new DStream by applying a function to all elements of this DStream,
and then flattening the results
- FlatMapFunction<T,R> - Interface in org.apache.spark.api.java.function
-
A function that returns zero or more output records from each input record.
- FlatMapFunction2<T1,T2,R> - Interface in org.apache.spark.api.java.function
-
A function that takes two inputs and returns zero or more output records.
- FlatMappedDStream<T,U> - Class in org.apache.spark.streaming.dstream
-
- FlatMappedDStream(DStream<T>, Function1<T, Traversable<U>>, ClassTag<T>, ClassTag<U>) - Constructor for class org.apache.spark.streaming.dstream.FlatMappedDStream
-
- FlatMappedRDD<U,T> - Class in org.apache.spark.rdd
-
- FlatMappedRDD(RDD<T>, Function1<T, TraversableOnce<U>>, ClassTag<U>, ClassTag<T>) - Constructor for class org.apache.spark.rdd.FlatMappedRDD
-
- FlatMappedValuesRDD<K,V,U> - Class in org.apache.spark.rdd
-
- FlatMappedValuesRDD(RDD<? extends Product2<K, V>>, Function1<V, TraversableOnce<U>>) - Constructor for class org.apache.spark.rdd.FlatMappedValuesRDD
-
- flatMapToDouble(DoubleFlatMapFunction<T>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return a new RDD by first applying a function to all elements of this
RDD, and then flattening the results.
- flatMapToPair(PairFlatMapFunction<T, K2, V2>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return a new RDD by first applying a function to all elements of this
RDD, and then flattening the results.
- flatMapToPair(PairFlatMapFunction<T, K2, V2>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Return a new DStream by applying a function to all elements of this DStream,
and then flattening the results
- FlatMapValuedDStream<K,V,U> - Class in org.apache.spark.streaming.dstream
-
- FlatMapValuedDStream(DStream<Tuple2<K, V>>, Function1<V, TraversableOnce<U>>, ClassTag<K>, ClassTag<V>, ClassTag<U>) - Constructor for class org.apache.spark.streaming.dstream.FlatMapValuedDStream
-
- flatMapValues(Function<V, Iterable<U>>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Pass each value in the key-value pair RDD through a flatMap function without changing the
keys; this also retains the original RDD's partitioning.
- flatMapValues(Function1<V, TraversableOnce<U>>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Pass each value in the key-value pair RDD through a flatMap function without changing the
keys; this also retains the original RDD's partitioning.
- flatMapValues(Function<V, Iterable<U>>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying a flatmap function to the value of each key-value pairs in
'this' DStream without changing the key.
- flatMapValues(Function1<V, TraversableOnce<U>>, ClassTag<U>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying a flatmap function to the value of each key-value pairs in
'this' DStream without changing the key.
- flatMapWith(Function1<Object, A>, boolean, Function2<T, A, Seq<U>>, ClassTag<U>) - Method in class org.apache.spark.rdd.RDD
-
FlatMaps f over this RDD, where f takes an additional parameter of type A.
- FLOAT - Class in org.apache.spark.sql.columnar
-
- FLOAT() - Constructor for class org.apache.spark.sql.columnar.FLOAT
-
- FloatColumnAccessor - Class in org.apache.spark.sql.columnar
-
- FloatColumnAccessor(ByteBuffer) - Constructor for class org.apache.spark.sql.columnar.FloatColumnAccessor
-
- FloatColumnBuilder - Class in org.apache.spark.sql.columnar
-
- FloatColumnBuilder() - Constructor for class org.apache.spark.sql.columnar.FloatColumnBuilder
-
- FloatColumnStats - Class in org.apache.spark.sql.columnar
-
- FloatColumnStats() - Constructor for class org.apache.spark.sql.columnar.FloatColumnStats
-
- FloatParam - Class in org.apache.spark.ml.param
-
Specialized version of Param[Float
] for Java.
- FloatParam(Params, String, String, Option<Object>) - Constructor for class org.apache.spark.ml.param.FloatParam
-
- floatToFloatWritable(float) - Static method in class org.apache.spark.SparkContext
-
- FloatType - Static variable in class org.apache.spark.sql.api.java.DataType
-
Gets the FloatType object.
- FloatType - Class in org.apache.spark.sql.api.java
-
The data type representing float and Float values.
- floatWritableConverter() - Static method in class org.apache.spark.SparkContext
-
- floor(Duration) - Method in class org.apache.spark.streaming.Time
-
- FlumeBatchFetcher - Class in org.apache.spark.streaming.flume
-
- FlumeBatchFetcher(FlumePollingReceiver) - Constructor for class org.apache.spark.streaming.flume.FlumeBatchFetcher
-
- FlumeConnection - Class in org.apache.spark.streaming.flume
-
A wrapper around the transceiver and the Avro IPC API.
- FlumeConnection(NettyTransceiver, SparkFlumeProtocol.Callback) - Constructor for class org.apache.spark.streaming.flume.FlumeConnection
-
- FlumeEventServer - Class in org.apache.spark.streaming.flume
-
A simple server that implements Flume's Avro protocol.
- FlumeEventServer(FlumeReceiver) - Constructor for class org.apache.spark.streaming.flume.FlumeEventServer
-
- FlumeInputDStream<T> - Class in org.apache.spark.streaming.flume
-
- FlumeInputDStream(StreamingContext, String, int, StorageLevel, boolean, ClassTag<T>) - Constructor for class org.apache.spark.streaming.flume.FlumeInputDStream
-
- FlumePollingInputDStream<T> - Class in org.apache.spark.streaming.flume
-
A ReceiverInputDStream
that can be used to read data from several Flume agents running
SparkSink
s.
- FlumePollingInputDStream(StreamingContext, Seq<InetSocketAddress>, int, int, StorageLevel, ClassTag<T>) - Constructor for class org.apache.spark.streaming.flume.FlumePollingInputDStream
-
- FlumePollingReceiver - Class in org.apache.spark.streaming.flume
-
- FlumePollingReceiver(Seq<InetSocketAddress>, int, int, StorageLevel) - Constructor for class org.apache.spark.streaming.flume.FlumePollingReceiver
-
- FlumeReceiver - Class in org.apache.spark.streaming.flume
-
A NetworkReceiver which listens for events using the
Flume Avro interface.
- FlumeReceiver(String, int, StorageLevel, boolean) - Constructor for class org.apache.spark.streaming.flume.FlumeReceiver
-
- FlumeReceiver.CompressionChannelPipelineFactory - Class in org.apache.spark.streaming.flume
-
A Netty Pipeline factory that will decompress incoming data from
and the Netty client and compress data going back to the client.
- FlumeReceiver.CompressionChannelPipelineFactory() - Constructor for class org.apache.spark.streaming.flume.FlumeReceiver.CompressionChannelPipelineFactory
-
- FlumeUtils - Class in org.apache.spark.streaming.flume
-
- FlumeUtils() - Constructor for class org.apache.spark.streaming.flume.FlumeUtils
-
- flush() - Method in class org.apache.spark.serializer.JavaSerializationStream
-
- flush() - Method in class org.apache.spark.serializer.KryoSerializationStream
-
- flush() - Method in class org.apache.spark.serializer.SerializationStream
-
- flush() - Method in class org.apache.spark.storage.DiskBlockObjectWriter
-
- flush() - Method in class org.apache.spark.streaming.util.RateLimitedOutputStream
-
- flush() - Method in class org.apache.spark.util.FileLogger
-
Flush the writer to disk manually.
- FMeasure - Class in org.apache.spark.mllib.evaluation.binary
-
F-Measure.
- FMeasure(double) - Constructor for class org.apache.spark.mllib.evaluation.binary.FMeasure
-
- fMeasure(double, double) - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
-
Returns f-measure for a given label (category)
- fMeasure(double) - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
-
Returns f1-measure for a given label (category)
- fMeasure() - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
-
Returns f-measure
(equals to precision and recall because precision equals recall)
- fMeasureByThreshold(double) - Method in class org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
-
Returns the (threshold, F-Measure) curve.
- fMeasureByThreshold() - Method in class org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
-
Returns the (threshold, F-Measure) curve with beta = 1.0.
- fold(T, Function2<T, T, T>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Aggregate the elements of each partition, and then the results for all the partitions, using a
given associative function and a neutral "zero value".
- fold(T, Function2<T, T, T>) - Method in class org.apache.spark.rdd.RDD
-
Aggregate the elements of each partition, and then the results for all the partitions, using a
given associative function and a neutral "zero value".
- foldable() - Method in class org.apache.spark.sql.hive.HiveGenericUdf
-
- foldable() - Method in class org.apache.spark.sql.hive.HiveSimpleUdf
-
- foldByKey(V, Partitioner, Function2<V, V, V>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Merge the values for each key using an associative function and a neutral "zero value" which
may be added to the result an arbitrary number of times, and must not change the result
(e.g ., Nil for list concatenation, 0 for addition, or 1 for multiplication.).
- foldByKey(V, int, Function2<V, V, V>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Merge the values for each key using an associative function and a neutral "zero value" which
may be added to the result an arbitrary number of times, and must not change the result
(e.g ., Nil for list concatenation, 0 for addition, or 1 for multiplication.).
- foldByKey(V, Function2<V, V, V>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Merge the values for each key using an associative function and a neutral "zero value"
which may be added to the result an arbitrary number of times, and must not change the result
(e.g., Nil for list concatenation, 0 for addition, or 1 for multiplication.).
- foldByKey(V, Partitioner, Function2<V, V, V>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Merge the values for each key using an associative function and a neutral "zero value" which
may be added to the result an arbitrary number of times, and must not change the result
(e.g., Nil for list concatenation, 0 for addition, or 1 for multiplication.).
- foldByKey(V, int, Function2<V, V, V>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Merge the values for each key using an associative function and a neutral "zero value" which
may be added to the result an arbitrary number of times, and must not change the result
(e.g., Nil for list concatenation, 0 for addition, or 1 for multiplication.).
- foldByKey(V, Function2<V, V, V>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Merge the values for each key using an associative function and a neutral "zero value" which
may be added to the result an arbitrary number of times, and must not change the result
(e.g., Nil for list concatenation, 0 for addition, or 1 for multiplication.).
- forAttribute() - Method in class org.apache.spark.sql.columnar.PartitionStatistics
-
- foreach(VoidFunction<T>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Applies a function f to all elements of this RDD.
- foreach(Function1<Edge<ED>, BoxedUnit>) - Method in class org.apache.spark.graphx.impl.EdgePartition
-
Apply the function f to all edges in this partition.
- foreach(Function1<T, BoxedUnit>) - Method in class org.apache.spark.rdd.RDD
-
Applies a function f to all elements of this RDD.
- foreach(Function<R, Void>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Deprecated.
As of release 0.9.0, replaced by foreachRDD
- foreach(Function2<R, Time, Void>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Deprecated.
As of release 0.9.0, replaced by foreachRDD
- foreach(Function1<RDD<T>, BoxedUnit>) - Method in class org.apache.spark.streaming.dstream.DStream
-
Apply a function to each RDD in this DStream.
- foreach(Function2<RDD<T>, Time, BoxedUnit>) - Method in class org.apache.spark.streaming.dstream.DStream
-
Apply a function to each RDD in this DStream.
- foreach(Function1<Tuple2<A, B>, U>) - Method in class org.apache.spark.util.TimeStampedHashMap
-
- foreach(Function1<A, U>) - Method in class org.apache.spark.util.TimeStampedHashSet
-
- foreach(Function1<Tuple2<A, B>, U>) - Method in class org.apache.spark.util.TimeStampedWeakValueHashMap
-
- foreachActive(Function2<Object, Object, BoxedUnit>) - Method in class org.apache.spark.mllib.linalg.DenseVector
-
- foreachActive(Function2<Object, Object, BoxedUnit>) - Method in class org.apache.spark.mllib.linalg.SparseVector
-
- foreachActive(Function2<Object, Object, BoxedUnit>) - Method in interface org.apache.spark.mllib.linalg.Vector
-
Applies a function f
to all the active elements of dense and sparse vector.
- foreachAsync(VoidFunction<T>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
The asynchronous version of the foreach
action, which
applies a function f to all the elements of this RDD.
- foreachAsync(Function1<T, BoxedUnit>) - Method in class org.apache.spark.rdd.AsyncRDDActions
-
Applies a function f to all elements of this RDD.
- ForEachDStream<T> - Class in org.apache.spark.streaming.dstream
-
- ForEachDStream(DStream<T>, Function2<RDD<T>, Time, BoxedUnit>, ClassTag<T>) - Constructor for class org.apache.spark.streaming.dstream.ForEachDStream
-
- foreachListener(Function1<SparkListener, BoxedUnit>) - Method in interface org.apache.spark.scheduler.SparkListenerBus
-
Apply the given function to all attached listeners, catching and logging any exception.
- foreachPartition(VoidFunction<Iterator<T>>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Applies a function f to each partition of this RDD.
- foreachPartition(Function1<Iterator<T>, BoxedUnit>) - Method in class org.apache.spark.rdd.RDD
-
Applies a function f to each partition of this RDD.
- foreachPartitionAsync(VoidFunction<Iterator<T>>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
The asynchronous version of the foreachPartition
action, which
applies a function f to each partition of this RDD.
- foreachPartitionAsync(Function1<Iterator<T>, BoxedUnit>) - Method in class org.apache.spark.rdd.AsyncRDDActions
-
Applies a function f to each partition of this RDD.
- foreachRDD(Function<R, Void>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Apply a function to each RDD in this DStream.
- foreachRDD(Function2<R, Time, Void>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Apply a function to each RDD in this DStream.
- foreachRDD(Function1<RDD<T>, BoxedUnit>) - Method in class org.apache.spark.streaming.dstream.DStream
-
Apply a function to each RDD in this DStream.
- foreachRDD(Function2<RDD<T>, Time, BoxedUnit>) - Method in class org.apache.spark.streaming.dstream.DStream
-
Apply a function to each RDD in this DStream.
- foreachWith(Function1<Object, A>, Function2<T, A, BoxedUnit>) - Method in class org.apache.spark.rdd.RDD
-
Applies f to each element of this RDD, where f takes an additional parameter of type A.
- foreachWithinEdgePartition(int, boolean, boolean, Function1<Object, BoxedUnit>) - Method in class org.apache.spark.graphx.impl.RoutingTablePartition
-
Runs f
on each vertex id to be sent to the specified edge partition.
- formatDate(Date) - Static method in class org.apache.spark.ui.UIUtils
-
- formatDate(long) - Static method in class org.apache.spark.ui.UIUtils
-
- formatDuration(long) - Static method in class org.apache.spark.ui.UIUtils
-
- formatDurationVerbose(long) - Static method in class org.apache.spark.ui.UIUtils
-
Generate a verbose human-readable string representing a duration such as "5 second 35 ms"
- formatNumber(double) - Static method in class org.apache.spark.ui.UIUtils
-
Generate a human-readable string representing a number (e.g.
- formatter() - Method in class org.apache.spark.util.logging.SizeBasedRollingPolicy
-
- formatWindowsPath(String) - Static method in class org.apache.spark.util.Utils
-
Format a Windows path such that it can be safely passed to a URI.
- fraction() - Method in class org.apache.spark.sql.execution.Sample
-
- framework() - Method in class org.apache.spark.streaming.Checkpoint
-
- frameworkMessage(SchedulerDriver, Protos.ExecutorID, Protos.SlaveID, byte[]) - Method in class org.apache.spark.scheduler.cluster.mesos.CoarseMesosSchedulerBackend
-
- frameworkMessage(SchedulerDriver, Protos.ExecutorID, Protos.SlaveID, byte[]) - Method in class org.apache.spark.scheduler.cluster.mesos.MesosSchedulerBackend
-
- freeCores() - Method in class org.apache.spark.scheduler.cluster.ExecutorData
-
- freeMemory() - Method in class org.apache.spark.storage.MemoryStore
-
Free memory not occupied by existing blocks.
- fromAvroFlumeEvent(AvroFlumeEvent) - Static method in class org.apache.spark.streaming.flume.SparkFlumeEvent
-
- fromBreeze(Matrix<Object>) - Static method in class org.apache.spark.mllib.linalg.Matrices
-
Creates a Matrix instance from a breeze matrix.
- fromBreeze(Vector<Object>) - Static method in class org.apache.spark.mllib.linalg.Vectors
-
Creates a vector instance from a breeze vector.
- fromDataType(DataType, String, boolean, boolean) - Static method in class org.apache.spark.sql.parquet.ParquetTypesConverter
-
Converts a given Catalyst DataType
into
the corresponding Parquet Type
.
- fromDStream(DStream<T>, ClassTag<T>) - Static method in class org.apache.spark.streaming.api.java.JavaDStream
-
- fromEdgePartitions(RDD<Tuple2<Object, EdgePartition<ED, VD>>>, ClassTag<ED>, ClassTag<VD>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
Creates an EdgeRDD from already-constructed edge partitions.
- fromEdgePartitions(RDD<Tuple2<Object, EdgePartition<ED, VD>>>, VD, StorageLevel, StorageLevel, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.impl.GraphImpl
-
Create a graph from EdgePartitions, setting referenced vertices to `defaultVertexAttr`.
- fromEdges(RDD<Edge<ED>>, ClassTag<ED>, ClassTag<VD>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
Creates an EdgeRDD from a set of edges.
- fromEdges(RDD<Edge<ED>>, VD, StorageLevel, StorageLevel, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.Graph
-
Construct a graph from a collection of edges.
- fromEdges(EdgeRDD<?>, int, VD, ClassTag<VD>) - Static method in class org.apache.spark.graphx.VertexRDD
-
Constructs a VertexRDD
containing all vertices referred to in edges
.
- fromEdgeTuples(RDD<Tuple2<Object, Object>>, VD, Option<PartitionStrategy>, StorageLevel, StorageLevel, ClassTag<VD>) - Static method in class org.apache.spark.graphx.Graph
-
Construct a graph from a collection of edges encoded as vertex id pairs.
- fromExistingRDDs(VertexRDD<VD>, EdgeRDD<ED>, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.impl.GraphImpl
-
Create a graph from a VertexRDD and an EdgeRDD with the same replicated vertex type as the
vertices.
- fromInputDStream(InputDStream<T>, ClassTag<T>) - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- fromInputDStream(InputDStream<Tuple2<K, V>>, ClassTag<K>, ClassTag<V>) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- fromJava(Object, DataType) - Static method in class org.apache.spark.sql.execution.EvaluatePython
-
- fromJavaDStream(JavaDStream<Tuple2<K, V>>) - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- fromJavaRDD(JavaRDD<Tuple2<K, V>>) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
Convert a JavaRDD of key-value pairs to JavaPairRDD.
- fromMesos(Protos.TaskState) - Static method in class org.apache.spark.TaskState
-
- fromMsgs(int, Iterator<Tuple2<Object, Object>>) - Static method in class org.apache.spark.graphx.impl.RoutingTablePartition
-
Build a `RoutingTablePartition` from `RoutingTableMessage`s.
- fromPairDStream(DStream<Tuple2<K, V>>, ClassTag<K>, ClassTag<V>) - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- fromPrimitiveDataType(DataType) - Static method in class org.apache.spark.sql.parquet.ParquetTypesConverter
-
For a given Catalyst DataType
return
the name of the corresponding Parquet primitive type or None if the given type
is not primitive.
- fromRDD(RDD<Object>) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- fromRDD(RDD<Tuple2<K, V>>, ClassTag<K>, ClassTag<V>) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- fromRDD(RDD<T>, ClassTag<T>) - Static method in class org.apache.spark.api.java.JavaRDD
-
- fromRDD(RDD<T>, ClassTag<T>) - Static method in class org.apache.spark.mllib.rdd.RDDFunctions
-
Implicit conversion from an RDD to RDDFunctions.
- fromRdd(RDD<?>) - Static method in class org.apache.spark.storage.RDDInfo
-
- fromReceiverInputDStream(ReceiverInputDStream<Tuple2<K, V>>, ClassTag<K>, ClassTag<V>) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- fromReceiverInputDStream(ReceiverInputDStream<T>, ClassTag<T>) - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- fromSparkContext(SparkContext) - Static method in class org.apache.spark.api.java.JavaSparkContext
-
- fromStage(Stage, Option<Object>) - Static method in class org.apache.spark.scheduler.StageInfo
-
Construct a StageInfo from a Stage.
- fromString(String) - Static method in class org.apache.spark.mllib.tree.configuration.Algo
-
- fromString(String) - Static method in class org.apache.spark.mllib.tree.impurity.Impurities
-
- fromString(String) - Static method in class org.apache.spark.mllib.tree.loss.Losses
-
- fromString(String) - Static method in class org.apache.spark.storage.StorageLevel
-
:: DeveloperApi ::
Return the StorageLevel object with the specified name.
- fromWeakReference(WeakReference<V>) - Static method in class org.apache.spark.util.TimeStampedWeakValueHashMap
-
- fromWeakReferenceIterator(Iterator<Tuple2<K, WeakReference<V>>>) - Static method in class org.apache.spark.util.TimeStampedWeakValueHashMap
-
- fromWeakReferenceMap(Map<K, WeakReference<V>>) - Static method in class org.apache.spark.util.TimeStampedWeakValueHashMap
-
- fromWeakReferenceOption(Option<WeakReference<V>>) - Static method in class org.apache.spark.util.TimeStampedWeakValueHashMap
-
- fromWeakReferenceTuple(Tuple2<K, WeakReference<V>>) - Static method in class org.apache.spark.util.TimeStampedWeakValueHashMap
-
- fs() - Method in class org.apache.spark.rdd.CheckpointRDD
-
- fullOuterJoin(JavaPairRDD<K, W>, Partitioner) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Perform a full outer join of this
and other
.
- fullOuterJoin(JavaPairRDD<K, W>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Perform a full outer join of this
and other
.
- fullOuterJoin(JavaPairRDD<K, W>, int) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Perform a full outer join of this
and other
.
- fullOuterJoin(RDD<Tuple2<K, W>>, Partitioner) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Perform a full outer join of this
and other
.
- fullOuterJoin(RDD<Tuple2<K, W>>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Perform a full outer join of this
and other
.
- fullOuterJoin(RDD<Tuple2<K, W>>, int) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Perform a full outer join of this
and other
.
- fullOuterJoin(JavaPairDStream<K, W>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying 'full outer join' between RDDs of this
DStream and
other
DStream.
- fullOuterJoin(JavaPairDStream<K, W>, int) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying 'full outer join' between RDDs of this
DStream and
other
DStream.
- fullOuterJoin(JavaPairDStream<K, W>, Partitioner) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying 'full outer join' between RDDs of this
DStream and
other
DStream.
- fullOuterJoin(DStream<Tuple2<K, W>>, ClassTag<W>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying 'full outer join' between RDDs of this
DStream and
other
DStream.
- fullOuterJoin(DStream<Tuple2<K, W>>, int, ClassTag<W>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying 'full outer join' between RDDs of this
DStream and
other
DStream.
- fullOuterJoin(DStream<Tuple2<K, W>>, Partitioner, ClassTag<W>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying 'full outer join' between RDDs of this
DStream and
other
DStream.
- fullStackTrace() - Method in class org.apache.spark.ExceptionFailure
-
- func() - Method in class org.apache.spark.scheduler.ActiveJob
-
- func() - Method in class org.apache.spark.scheduler.JobSubmitted
-
- Function<T1,R> - Interface in org.apache.spark.api.java.function
-
Base interface for functions whose return types do not create special RDDs.
- function() - Method in class org.apache.spark.sql.hive.HiveGenericUdf
-
- function() - Method in class org.apache.spark.sql.hive.HiveSimpleUdf
-
- Function2<T1,T2,R> - Interface in org.apache.spark.api.java.function
-
A two-argument function that takes arguments of type T1 and T2 and returns an R.
- Function3<T1,T2,T3,R> - Interface in org.apache.spark.api.java.function
-
A three-argument function that takes arguments of type T1, T2 and T3 and returns an R.
- functionClassName() - Method in class org.apache.spark.sql.hive.HiveFunctionWrapper
-
- funcWrapper() - Method in class org.apache.spark.sql.hive.HiveGenericUdaf
-
- funcWrapper() - Method in class org.apache.spark.sql.hive.HiveGenericUdf
-
- funcWrapper() - Method in class org.apache.spark.sql.hive.HiveGenericUdtf
-
- funcWrapper() - Method in class org.apache.spark.sql.hive.HiveSimpleUdf
-
- funcWrapper() - Method in class org.apache.spark.sql.hive.HiveUdaf
-
- funcWrapper() - Method in class org.apache.spark.sql.hive.HiveUdafFunction
-
- FutureAction<T> - Interface in org.apache.spark
-
A future for the result of an action to support cancellation.
- gain() - Method in class org.apache.spark.mllib.tree.model.InformationGainStats
-
- gamma1() - Method in class org.apache.spark.graphx.lib.SVDPlusPlus.Conf
-
- gamma2() - Method in class org.apache.spark.graphx.lib.SVDPlusPlus.Conf
-
- gamma6() - Method in class org.apache.spark.graphx.lib.SVDPlusPlus.Conf
-
- gamma7() - Method in class org.apache.spark.graphx.lib.SVDPlusPlus.Conf
-
- GapSamplingIterator<T> - Class in org.apache.spark.util.random
-
- GapSamplingIterator(Iterator<T>, double, Random, double, ClassTag<T>) - Constructor for class org.apache.spark.util.random.GapSamplingIterator
-
- GapSamplingReplacementIterator<T> - Class in org.apache.spark.util.random
-
advance to first sample as part of object construction.
- GapSamplingReplacementIterator(Iterator<T>, double, Random, double, ClassTag<T>) - Constructor for class org.apache.spark.util.random.GapSamplingReplacementIterator
-
- gatherCompressibilityStats(Row, int) - Method in class org.apache.spark.sql.columnar.compression.BooleanBitSet.Encoder
-
- gatherCompressibilityStats(Row, int) - Method in interface org.apache.spark.sql.columnar.compression.CompressibleColumnBuilder
-
- gatherCompressibilityStats(Row, int) - Method in class org.apache.spark.sql.columnar.compression.DictionaryEncoding.Encoder
-
- gatherCompressibilityStats(Row, int) - Method in interface org.apache.spark.sql.columnar.compression.Encoder
-
- gatherCompressibilityStats(Row, int) - Method in class org.apache.spark.sql.columnar.compression.IntDelta.Encoder
-
- gatherCompressibilityStats(Row, int) - Method in class org.apache.spark.sql.columnar.compression.LongDelta.Encoder
-
- gatherCompressibilityStats(Row, int) - Method in class org.apache.spark.sql.columnar.compression.RunLengthEncoding.Encoder
-
- gatherStats(Row, int) - Method in class org.apache.spark.sql.columnar.BinaryColumnStats
-
- gatherStats(Row, int) - Method in class org.apache.spark.sql.columnar.BooleanColumnStats
-
- gatherStats(Row, int) - Method in class org.apache.spark.sql.columnar.ByteColumnStats
-
- gatherStats(Row, int) - Method in interface org.apache.spark.sql.columnar.ColumnStats
-
Gathers statistics information from row(ordinal)
.
- gatherStats(Row, int) - Method in class org.apache.spark.sql.columnar.DateColumnStats
-
- gatherStats(Row, int) - Method in class org.apache.spark.sql.columnar.DoubleColumnStats
-
- gatherStats(Row, int) - Method in class org.apache.spark.sql.columnar.FloatColumnStats
-
- gatherStats(Row, int) - Method in class org.apache.spark.sql.columnar.GenericColumnStats
-
- gatherStats(Row, int) - Method in class org.apache.spark.sql.columnar.IntColumnStats
-
- gatherStats(Row, int) - Method in class org.apache.spark.sql.columnar.LongColumnStats
-
- gatherStats(Row, int) - Method in class org.apache.spark.sql.columnar.NoopColumnStats
-
- gatherStats(Row, int) - Method in class org.apache.spark.sql.columnar.ShortColumnStats
-
- gatherStats(Row, int) - Method in class org.apache.spark.sql.columnar.StringColumnStats
-
- gatherStats(Row, int) - Method in class org.apache.spark.sql.columnar.TimestampColumnStats
-
- GC_TIME() - Static method in class org.apache.spark.ui.ToolTips
-
- gemm(boolean, boolean, double, Matrix, DenseMatrix, double, DenseMatrix) - Static method in class org.apache.spark.mllib.linalg.BLAS
-
C := alpha * A * B + beta * C
- gemm(double, Matrix, DenseMatrix, double, DenseMatrix) - Static method in class org.apache.spark.mllib.linalg.BLAS
-
C := alpha * A * B + beta * C
- gemv(boolean, double, Matrix, DenseVector, double, DenseVector) - Static method in class org.apache.spark.mllib.linalg.BLAS
-
y := alpha * A * x + beta * y
- gemv(double, Matrix, DenseVector, double, DenseVector) - Static method in class org.apache.spark.mllib.linalg.BLAS
-
y := alpha * A * x + beta * y
- GeneralHashedRelation - Class in org.apache.spark.sql.execution.joins
-
A general
HashedRelation
backed by a hash map that maps the key into a sequence of values.
- GeneralHashedRelation(HashMap<Row, CompactBuffer<Row>>) - Constructor for class org.apache.spark.sql.execution.joins.GeneralHashedRelation
-
- GeneralizedLinearAlgorithm<M extends GeneralizedLinearModel> - Class in org.apache.spark.mllib.regression
-
:: DeveloperApi ::
GeneralizedLinearAlgorithm implements methods to train a Generalized Linear Model (GLM).
- GeneralizedLinearAlgorithm() - Constructor for class org.apache.spark.mllib.regression.GeneralizedLinearAlgorithm
-
- GeneralizedLinearModel - Class in org.apache.spark.mllib.regression
-
:: DeveloperApi ::
GeneralizedLinearModel (GLM) represents a model trained using
GeneralizedLinearAlgorithm.
- GeneralizedLinearModel(Vector, double) - Constructor for class org.apache.spark.mllib.regression.GeneralizedLinearModel
-
- generate(String, String, int, int) - Static method in class org.apache.spark.examples.streaming.KinesisWordCountProducerASL
-
- Generate - Class in org.apache.spark.sql.execution
-
:: DeveloperApi ::
Applies a Generator
to a stream of input rows, combining the
output of each into a new stream of rows.
- Generate(Generator, boolean, boolean, SparkPlan) - Constructor for class org.apache.spark.sql.execution.Generate
-
- generate(Generator, boolean, boolean, Option<String>) - Method in class org.apache.spark.sql.SchemaRDD
-
:: Experimental ::
Applies the given Generator, or table generating function, to this relation.
- GeneratedAggregate - Class in org.apache.spark.sql.execution
-
:: DeveloperApi ::
Alternate version of aggregation that leverages projection and thus code generation.
- GeneratedAggregate(boolean, Seq<Expression>, Seq<NamedExpression>, SparkPlan) - Constructor for class org.apache.spark.sql.execution.GeneratedAggregate
-
- generatedRDDs() - Method in class org.apache.spark.streaming.dstream.DStream
-
- generateJob(Time) - Method in class org.apache.spark.streaming.dstream.DStream
-
Generate a SparkStreaming job for the given time.
- generateJob(Time) - Method in class org.apache.spark.streaming.dstream.ForEachDStream
-
- generateJobs(Time) - Method in class org.apache.spark.streaming.DStreamGraph
-
- GenerateJobs - Class in org.apache.spark.streaming.scheduler
-
- GenerateJobs(Time) - Constructor for class org.apache.spark.streaming.scheduler.GenerateJobs
-
- generateKMeansRDD(SparkContext, int, int, int, double, int) - Static method in class org.apache.spark.mllib.util.KMeansDataGenerator
-
Generate an RDD containing test data for KMeans.
- generateLinearInput(double, double[], int, int, double) - Static method in class org.apache.spark.mllib.util.LinearDataGenerator
-
- generateLinearInputAsList(double, double[], int, int, double) - Static method in class org.apache.spark.mllib.util.LinearDataGenerator
-
Return a Java List of synthetic data randomly generated according to a multi
collinear model.
- generateLinearRDD(SparkContext, int, int, double, int, double) - Static method in class org.apache.spark.mllib.util.LinearDataGenerator
-
Generate an RDD containing sample data for Linear Regression models - including Ridge, Lasso,
and uregularized variants.
- generateLogisticRDD(SparkContext, int, int, double, int, double) - Static method in class org.apache.spark.mllib.util.LogisticRegressionDataGenerator
-
Generate an RDD containing test data for LogisticRegression.
- generateRandomEdges(int, int, int, long) - Static method in class org.apache.spark.graphx.util.GraphGenerators
-
- generateRolledOverFileSuffix() - Method in interface org.apache.spark.util.logging.RollingPolicy
-
Get the desired name of the rollover file
- generateRolledOverFileSuffix() - Method in class org.apache.spark.util.logging.SizeBasedRollingPolicy
-
Get the desired name of the rollover file
- generateRolledOverFileSuffix() - Method in class org.apache.spark.util.logging.TimeBasedRollingPolicy
-
- generator() - Method in class org.apache.spark.mllib.rdd.RandomRDDPartition
-
- generator() - Method in class org.apache.spark.sql.execution.Generate
-
- GENERIC - Class in org.apache.spark.sql.columnar
-
- GENERIC() - Constructor for class org.apache.spark.sql.columnar.GENERIC
-
- GenericColumnAccessor - Class in org.apache.spark.sql.columnar
-
- GenericColumnAccessor(ByteBuffer) - Constructor for class org.apache.spark.sql.columnar.GenericColumnAccessor
-
- GenericColumnBuilder - Class in org.apache.spark.sql.columnar
-
- GenericColumnBuilder() - Constructor for class org.apache.spark.sql.columnar.GenericColumnBuilder
-
- GenericColumnStats - Class in org.apache.spark.sql.columnar
-
- GenericColumnStats() - Constructor for class org.apache.spark.sql.columnar.GenericColumnStats
-
- get(Object) - Method in class org.apache.spark.api.java.JavaUtils.SerializableMapWrapper
-
- get() - Method in interface org.apache.spark.FutureAction
-
Blocks and returns the result of this job.
- get() - Method in class org.apache.spark.JavaFutureActionWrapper
-
- get(long, TimeUnit) - Method in class org.apache.spark.JavaFutureActionWrapper
-
- get(Param<T>) - Method in class org.apache.spark.ml.param.ParamMap
-
Optionally returns the value associated with a param or its default.
- get(Param<T>) - Method in interface org.apache.spark.ml.param.Params
-
Gets the value of a parameter in the embedded param map.
- get(long) - Method in class org.apache.spark.partial.StudentTCacher
-
- get(String) - Method in class org.apache.spark.SparkConf
-
Get a parameter; throws a NoSuchElementException if it's not set
- get(String, String) - Method in class org.apache.spark.SparkConf
-
Get a parameter, falling back to a default if not set
- get() - Static method in class org.apache.spark.SparkEnv
-
Returns the SparkEnv.
- get(String) - Static method in class org.apache.spark.SparkFiles
-
Get the absolute path of a file added through SparkContext.addFile()
.
- get(int) - Method in class org.apache.spark.sql.api.java.Row
-
Returns the value of column `i`.
- get(Row) - Method in class org.apache.spark.sql.execution.joins.GeneralHashedRelation
-
- get(Row) - Method in interface org.apache.spark.sql.execution.joins.HashedRelation
-
- get(Row) - Method in class org.apache.spark.sql.execution.joins.UniqueKeyHashedRelation
-
- get() - Method in class org.apache.spark.sql.hive.DeferredObjectAdapter
-
- get(BlockId) - Method in class org.apache.spark.storage.BlockManager
-
Get a block from the block manager (either local or remote).
- get() - Static method in class org.apache.spark.TaskContext
-
Return the currently active TaskContext.
- get(A) - Method in class org.apache.spark.util.TimeStampedHashMap
-
- get(A) - Method in class org.apache.spark.util.TimeStampedWeakValueHashMap
-
- getAcceptanceResults(RDD<Tuple2<K, V>>, boolean, Map<K, Object>, Option<Map<K, Object>>, long) - Static method in class org.apache.spark.util.random.StratifiedSamplingUtils
-
Count the number of items instantly accepted and generate the waitlist for each stratum.
- getActiveJobIds() - Method in class org.apache.spark.api.java.JavaSparkStatusTracker
-
Returns an array containing the ids of all active jobs.
- getActiveJobIds() - Method in class org.apache.spark.SparkStatusTracker
-
Returns an array containing the ids of all active jobs.
- getActiveStageIds() - Method in class org.apache.spark.api.java.JavaSparkStatusTracker
-
Returns an array containing the ids of all active stages.
- getActiveStageIds() - Method in class org.apache.spark.SparkStatusTracker
-
Returns an array containing the ids of all active stages.
- getActorSystemHostPortForExecutor(String) - Method in class org.apache.spark.storage.BlockManagerMaster
-
- getAddressHostName(String) - Static method in class org.apache.spark.util.Utils
-
- getAkkaConf() - Method in class org.apache.spark.SparkConf
-
Get all akka conf variables set on this SparkConf
- getAlgo() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- getAll() - Method in class org.apache.spark.SparkConf
-
Get all parameters as a list of pairs
- getAllBlocks() - Method in class org.apache.spark.storage.DiskBlockManager
-
List all the blocks currently stored on disk by the disk manager.
- getAllConfs() - Method in interface org.apache.spark.sql.SQLConf
-
Return all the configuration properties that have been set (i.e.
- getAllFiles() - Method in class org.apache.spark.storage.DiskBlockManager
-
List all the files currently stored on disk by the disk manager.
- getAllPartitionsOf(Hive, Table) - Static method in class org.apache.spark.sql.hive.HiveShim
-
- getAllPools() - Method in class org.apache.spark.SparkContext
-
:: DeveloperApi ::
Return pools for fair scheduler
- getAppId() - Method in class org.apache.spark.SparkConf
-
Returns the Spark application id, valid in the Driver after TaskScheduler registration and
from the start in the Executor.
- getAppName() - Method in class org.apache.spark.ui.SparkUI
-
- getAst(String) - Static method in class org.apache.spark.sql.hive.HiveQl
-
Returns the AST for the given SQL string.
- getBasePath() - Method in class org.apache.spark.ui.WebUI
-
- getBernoulliSamplingFunction(RDD<Tuple2<K, V>>, Map<K, Object>, boolean, long) - Static method in class org.apache.spark.util.random.StratifiedSamplingUtils
-
Return the per partition sampling function used for sampling without replacement.
- getBinaryWritableConstantObjectInspector(Object) - Static method in class org.apache.spark.sql.hive.HiveShim
-
- getBlock(BlockId) - Method in class org.apache.spark.storage.StorageStatus
-
Return the given block stored in this block manager in O(1) time.
- getBlockData(BlockId) - Method in class org.apache.spark.storage.BlockManager
-
Interface to get local block data.
- getBlocksOfBatch(Time) - Method in class org.apache.spark.streaming.scheduler.ReceivedBlockTracker
-
Get the blocks allocated to the given batch.
- getBlocksOfBatch(Time) - Method in class org.apache.spark.streaming.scheduler.ReceiverTracker
-
Get the blocks for the given batch and all input streams.
- getBlocksOfBatchAndStream(Time, int) - Method in class org.apache.spark.streaming.scheduler.ReceivedBlockTracker
-
Get the blocks allocated to the given batch and stream.
- getBlocksOfBatchAndStream(Time, int) - Method in class org.apache.spark.streaming.scheduler.ReceiverTracker
-
Get the blocks allocated to the given batch and stream.
- getBlocksOfStream(int) - Method in class org.apache.spark.streaming.scheduler.AllocatedBlocks
-
- getBlockStatus(BlockId, boolean) - Method in class org.apache.spark.storage.BlockManagerMaster
-
Return the block's status on all block managers, if any.
- getBoolean(String, boolean) - Method in class org.apache.spark.SparkConf
-
Get a parameter as a boolean, falling back to a default if not set
- getBoolean(int) - Method in class org.apache.spark.sql.api.java.Row
-
Returns the value of column i
as a bool.
- getBooleanWritableConstantObjectInspector(Object) - Static method in class org.apache.spark.sql.hive.HiveShim
-
- getByte(int) - Method in class org.apache.spark.sql.api.java.Row
-
Returns the value of column i
as a byte.
- getBytes(BlockId) - Method in class org.apache.spark.storage.BlockStore
-
- getBytes(BlockId) - Method in class org.apache.spark.storage.DiskStore
-
- getBytes(FileSegment) - Method in class org.apache.spark.storage.DiskStore
-
- getBytes(BlockId) - Method in class org.apache.spark.storage.MemoryStore
-
- getBytes(BlockId) - Method in class org.apache.spark.storage.TachyonStore
-
- getByteWritableConstantObjectInspector(Object) - Static method in class org.apache.spark.sql.hive.HiveShim
-
- getCachedBlockManagerId(BlockManagerId) - Static method in class org.apache.spark.storage.BlockManagerId
-
- getCachedMetadata(String) - Static method in class org.apache.spark.rdd.HadoopRDD
-
The three methods below are helpers for accessing the local map, a property of the SparkEnv of
the local process.
- getCachedStorageLevel(StorageLevel) - Static method in class org.apache.spark.storage.StorageLevel
-
- getCalculator(double[], int) - Method in class org.apache.spark.mllib.tree.impurity.EntropyAggregator
-
- getCalculator(double[], int) - Method in class org.apache.spark.mllib.tree.impurity.GiniAggregator
-
- getCalculator(double[], int) - Method in class org.apache.spark.mllib.tree.impurity.ImpurityAggregator
-
- getCalculator(double[], int) - Method in class org.apache.spark.mllib.tree.impurity.VarianceAggregator
-
- getCallSite() - Method in class org.apache.spark.SparkContext
-
Capture the current user callsite and return a formatted version for printing.
- getCallSite(Function1<String, Object>) - Static method in class org.apache.spark.util.Utils
-
When called inside a class in the spark package, returns the name of the user code class
(outside the spark package) that called into Spark, as well as which Spark method they called.
- getCategoricalFeaturesInfo() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- getCheckpointDir() - Method in class org.apache.spark.api.java.JavaSparkContext
-
- getCheckpointDir() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- getCheckpointDir() - Method in class org.apache.spark.SparkContext
-
- getCheckpointFile() - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Gets the name of the file to which this RDD was checkpointed
- getCheckpointFile() - Method in class org.apache.spark.rdd.RDD
-
Gets the name of the file to which this RDD was checkpointed
- getCheckpointFile() - Method in class org.apache.spark.rdd.RDDCheckpointData
-
- getCheckpointFiles(String, FileSystem) - Static method in class org.apache.spark.streaming.Checkpoint
-
Get checkpoint files present in the give directory, ordered by oldest-first
- getCheckpointInterval() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- getClause(String, Seq<Node>) - Static method in class org.apache.spark.sql.hive.HiveQl
-
- getClauseOption(String, Seq<Node>) - Static method in class org.apache.spark.sql.hive.HiveQl
-
- getClientSideSplits(Configuration, List<Footer>, Long, Long, ReadSupport.ReadContext) - Method in class org.apache.spark.sql.parquet.FilteringParquetRowInputFormat
-
- getCombOp() - Static method in class org.apache.spark.util.random.StratifiedSamplingUtils
-
Returns the function used combine results returned by seqOp from different partitions.
- getCommandProcessor(String[], HiveConf) - Static method in class org.apache.spark.sql.hive.HiveShim
-
- getConf() - Method in class org.apache.spark.api.java.JavaSparkContext
-
Return a copy of this JavaSparkContext's configuration.
- getConf() - Method in class org.apache.spark.input.WholeCombineFileRecordReader
-
- getConf() - Method in class org.apache.spark.input.WholeTextFileInputFormat
-
- getConf() - Method in class org.apache.spark.input.WholeTextFileRecordReader
-
- getConf() - Method in class org.apache.spark.rdd.HadoopRDD
-
- getConf() - Method in class org.apache.spark.rdd.NewHadoopRDD
-
- getConf() - Method in class org.apache.spark.SparkContext
-
Return a copy of this SparkContext's configuration.
- getConf(String) - Method in interface org.apache.spark.sql.SQLConf
-
Return the value of Spark SQL configuration property for the given key.
- getConf(String, String) - Method in interface org.apache.spark.sql.SQLConf
-
Return the value of Spark SQL configuration property for the given key.
- getConnection() - Method in interface org.apache.spark.rdd.JdbcRDD.ConnectionFactory
-
- getConnections() - Method in class org.apache.spark.streaming.flume.FlumePollingReceiver
-
- getContextOrSparkClassLoader() - Static method in class org.apache.spark.util.Utils
-
Get the Context ClassLoader on this thread or, if not present, the ClassLoader that
loaded Spark.
- getConverter(int) - Method in class org.apache.spark.sql.parquet.CatalystArrayContainsNullConverter
-
- getConverter(int) - Method in class org.apache.spark.sql.parquet.CatalystArrayConverter
-
- getConverter(int) - Method in class org.apache.spark.sql.parquet.CatalystGroupConverter
-
- getConverter(int) - Method in class org.apache.spark.sql.parquet.CatalystMapConverter
-
- getConverter(int) - Method in class org.apache.spark.sql.parquet.CatalystNativeArrayConverter
-
- getConverter(int) - Method in class org.apache.spark.sql.parquet.CatalystPrimitiveRowConverter
-
- getCorrelationFromName(String) - Static method in class org.apache.spark.mllib.stat.correlation.Correlations
-
- getCreationSite() - Method in class org.apache.spark.rdd.RDD
-
- getCreationSite() - Static method in class org.apache.spark.streaming.dstream.DStream
-
Get the creation site of a DStream from the stack trace of when the DStream is created.
- getCurrentKey() - Method in class org.apache.spark.input.FixedLengthBinaryRecordReader
-
- getCurrentKey() - Method in class org.apache.spark.input.StreamBasedRecordReader
-
- getCurrentKey() - Method in class org.apache.spark.input.WholeTextFileRecordReader
-
- getCurrentRecord() - Method in class org.apache.spark.sql.parquet.CatalystConverter
-
Should only be called in the root (group) converter!
- getCurrentRecord() - Method in class org.apache.spark.sql.parquet.CatalystGroupConverter
-
- getCurrentRecord() - Method in class org.apache.spark.sql.parquet.CatalystPrimitiveRowConverter
-
- getCurrentRecord() - Method in class org.apache.spark.sql.parquet.RowRecordMaterializer
-
- getCurrentValue() - Method in class org.apache.spark.input.FixedLengthBinaryRecordReader
-
- getCurrentValue() - Method in class org.apache.spark.input.StreamBasedRecordReader
-
- getCurrentValue() - Method in class org.apache.spark.input.WholeTextFileRecordReader
-
- getDataLocationPath(Partition) - Static method in class org.apache.spark.sql.hive.HiveShim
-
- getDataType() - Method in class org.apache.spark.sql.api.java.StructField
-
- getDateWritableConstantObjectInspector(Object) - Static method in class org.apache.spark.sql.hive.HiveShim
-
- getDecimalWritableConstantObjectInspector(Object) - Static method in class org.apache.spark.sql.hive.HiveShim
-
- getDefaultPropertiesFile(Map<String, String>) - Static method in class org.apache.spark.util.Utils
-
Return the path of the default Spark properties file.
- getDefaultWorkFile(TaskAttemptContext, String) - Method in class org.apache.spark.sql.parquet.AppendingParquetOutputFormat
-
- getDelaySeconds(SparkConf) - Static method in class org.apache.spark.util.MetadataCleaner
-
- getDelaySeconds(SparkConf, Enumeration.Value) - Static method in class org.apache.spark.util.MetadataCleaner
-
- getDependencies() - Method in class org.apache.spark.rdd.CartesianRDD
-
- getDependencies() - Method in class org.apache.spark.rdd.CoalescedRDD
-
- getDependencies() - Method in class org.apache.spark.rdd.CoGroupedRDD
-
- getDependencies() - Method in class org.apache.spark.rdd.ShuffledRDD
-
- getDependencies() - Method in class org.apache.spark.rdd.SubtractedRDD
-
- getDependencies() - Method in class org.apache.spark.rdd.UnionRDD
-
- getDirName() - Method in class org.apache.spark.sql.hive.ShimFileSinkDesc
-
- getDiskWriter(BlockId, File, Serializer, int, ShuffleWriteMetrics) - Method in class org.apache.spark.storage.BlockManager
-
A short circuited method to get a block writer that can write data directly to disk.
- getDouble(String, double) - Method in class org.apache.spark.SparkConf
-
Get a parameter as a double, falling back to a default if not set
- getDouble(int) - Method in class org.apache.spark.sql.api.java.Row
-
Returns the value of column i
as a double.
- getDoubleWritableConstantObjectInspector(Object) - Static method in class org.apache.spark.sql.hive.HiveShim
-
- getElementType() - Method in class org.apache.spark.sql.api.java.ArrayType
-
- getEntrySet() - Method in class org.apache.spark.util.TimeStampedHashMap
-
- getenv(String) - Method in class org.apache.spark.SparkConf
-
By using this instead of System.getenv(), environment variables can be mocked
in unit tests.
- getEpoch() - Method in class org.apache.spark.MapOutputTracker
-
Called to get current epoch number.
- getEstimator() - Method in interface org.apache.spark.ml.tuning.CrossValidatorParams
-
- getEstimatorParamMaps() - Method in interface org.apache.spark.ml.tuning.CrossValidatorParams
-
- getEvaluator() - Method in interface org.apache.spark.ml.tuning.CrossValidatorParams
-
- getExecutorEnv() - Method in class org.apache.spark.SparkConf
-
Get all executor environment variables set on this SparkConf
- getExecutorMemoryStatus() - Method in class org.apache.spark.SparkContext
-
Return a map from the slave to the max memory available for caching and the remaining
memory available for caching.
- getExecutorsAliveOnHost(String) - Method in class org.apache.spark.scheduler.TaskSchedulerImpl
-
- getExecutorStorageStatus() - Method in class org.apache.spark.SparkContext
-
:: DeveloperApi ::
Return information about blocks stored in all of the slaves
- getExecutorThreadDump(String) - Method in class org.apache.spark.SparkContext
-
Called by the web UI to obtain executor thread dumps.
- getExternalTmpPath(Context, Path) - Static method in class org.apache.spark.sql.hive.HiveShim
-
- getFeatureOffset(int) - Method in class org.apache.spark.mllib.tree.impl.DTStatsAggregator
-
Pre-compute feature offset for use with featureUpdate
.
- getFeaturesCol() - Method in interface org.apache.spark.ml.param.HasFeaturesCol
-
- getField(Row, int) - Static method in class org.apache.spark.sql.columnar.BINARY
-
- getField(Row, int) - Static method in class org.apache.spark.sql.columnar.BOOLEAN
-
- getField(Row, int) - Static method in class org.apache.spark.sql.columnar.BYTE
-
- getField(Row, int) - Method in class org.apache.spark.sql.columnar.ColumnType
-
Returns row(ordinal)
.
- getField(Row, int) - Static method in class org.apache.spark.sql.columnar.DATE
-
- getField(Row, int) - Static method in class org.apache.spark.sql.columnar.DOUBLE
-
- getField(Row, int) - Static method in class org.apache.spark.sql.columnar.FLOAT
-
- getField(Row, int) - Static method in class org.apache.spark.sql.columnar.GENERIC
-
- getField(Row, int) - Static method in class org.apache.spark.sql.columnar.INT
-
- getField(Row, int) - Static method in class org.apache.spark.sql.columnar.LONG
-
- getField(Row, int) - Static method in class org.apache.spark.sql.columnar.SHORT
-
- getField(Row, int) - Static method in class org.apache.spark.sql.columnar.STRING
-
- getField(Row, int) - Static method in class org.apache.spark.sql.columnar.TIMESTAMP
-
- getFields() - Method in class org.apache.spark.sql.api.java.StructType
-
- getFile(long) - Static method in class org.apache.spark.broadcast.HttpBroadcast
-
- getFile(String) - Method in class org.apache.spark.storage.DiskBlockManager
-
Looks up a file by hashing it into one of our local subdirectories.
- getFile(BlockId) - Method in class org.apache.spark.storage.DiskBlockManager
-
- getFile(String) - Method in class org.apache.spark.storage.TachyonBlockManager
-
- getFile(BlockId) - Method in class org.apache.spark.storage.TachyonBlockManager
-
- getFilePath(File, String) - Static method in class org.apache.spark.util.Utils
-
Return the absolute path of a file in the given directory.
- getFileSegmentLocations(String, long, long, Configuration) - Static method in class org.apache.spark.streaming.util.HdfsUtils
-
Get the locations of the HDFS blocks containing the given file segment.
- getFileSystemForPath(Path, Configuration) - Static method in class org.apache.spark.streaming.util.HdfsUtils
-
- getFinalValue() - Method in class org.apache.spark.partial.PartialResult
-
Blocking method to wait for and return the final value.
- getFloat(int) - Method in class org.apache.spark.sql.api.java.Row
-
Returns the value of column i
as a float.
- getFloatWritableConstantObjectInspector(Object) - Static method in class org.apache.spark.sql.hive.HiveShim
-
- getFooters(JobContext) - Method in class org.apache.spark.sql.parquet.FilteringParquetRowInputFormat
-
- getFormattedClassName(Object) - Static method in class org.apache.spark.util.Utils
-
Return the class name of the given object, removing all dollar signs
- getFunctionInfo(String) - Method in class org.apache.spark.sql.hive.HiveFunctionRegistry
-
- getHadoopFileSystem(URI, Configuration) - Static method in class org.apache.spark.util.Utils
-
Return a Hadoop FileSystem with the scheme encoded in the given path.
- getHadoopFileSystem(String, Configuration) - Static method in class org.apache.spark.util.Utils
-
Return a Hadoop FileSystem with the scheme encoded in the given path.
- getHandlers() - Method in class org.apache.spark.metrics.sink.MetricsServlet
-
- getHandlers() - Method in class org.apache.spark.ui.WebUI
-
- getHiveFile(String) - Method in class org.apache.spark.sql.hive.test.TestHiveContext
-
- getHttpUser() - Method in class org.apache.spark.SecurityManager
-
Gets the user used for authenticating HTTP connections.
- getImpurity() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- getImpurityCalculator(int, int) - Method in class org.apache.spark.mllib.tree.impl.DTStatsAggregator
-
Get an ImpurityCalculator
for a given (node, feature, bin).
- getInputCol() - Method in interface org.apache.spark.ml.param.HasInputCol
-
- getInputStream(String, Configuration) - Static method in class org.apache.spark.streaming.util.HdfsUtils
-
- getInputStreams() - Method in class org.apache.spark.streaming.DStreamGraph
-
- getInstance(String) - Method in class org.apache.spark.metrics.MetricsConfig
-
- getInt(String, int) - Method in class org.apache.spark.SparkConf
-
Get a parameter as an integer, falling back to a default if not set
- getInt(int) - Method in class org.apache.spark.sql.api.java.Row
-
Returns the value of column i
as an int.
- getIntWritableConstantObjectInspector(Object) - Static method in class org.apache.spark.sql.hive.HiveShim
-
- getIteratorSize(Iterator<T>) - Static method in class org.apache.spark.util.Utils
-
Counts the number of elements of an iterator using a while loop rather than calling
TraversableOnce.size()
because it uses a for loop, which is slightly slower
in the current version of Scala.
- getJobIdsForGroup(String) - Method in class org.apache.spark.api.java.JavaSparkStatusTracker
-
Return a list of all known jobs in a particular job group.
- getJobIdsForGroup(String) - Method in class org.apache.spark.SparkStatusTracker
-
Return a list of all known jobs in a particular job group.
- getJobInfo(int) - Method in class org.apache.spark.api.java.JavaSparkStatusTracker
-
Returns job information, or null
if the job info could not be found or was garbage collected.
- getJobInfo(int) - Method in class org.apache.spark.SparkStatusTracker
-
Returns job information, or None
if the job info could not be found or was garbage collected.
- getKeyType() - Method in class org.apache.spark.sql.api.java.MapType
-
- getLabelCol() - Method in interface org.apache.spark.ml.param.HasLabelCol
-
- getLearningRate() - Method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
-
- getLeastGroupHash(String) - Method in class org.apache.spark.rdd.PartitionCoalescer
-
Sorts and gets the least element of the list associated with key in groupHash
The returned PartitionGroup is the least loaded of all groups that represent the machine "key"
- getLeftRightFeatureOffsets(int) - Method in class org.apache.spark.mllib.tree.impl.DTStatsAggregator
-
Pre-compute feature offset for use with featureUpdate
.
- getLocal(BlockId) - Method in class org.apache.spark.storage.BlockManager
-
Get block from local block manager.
- getLocalBytes(BlockId) - Method in class org.apache.spark.storage.BlockManager
-
Get block from the local block manager as serialized bytes.
- getLocalDir(SparkConf) - Static method in class org.apache.spark.util.Utils
-
Get the path of a temporary directory.
- getLocalFileWriter(Row) - Method in class org.apache.spark.sql.hive.SparkHiveDynamicPartitionWriterContainer
-
- getLocalFileWriter(Row) - Method in class org.apache.spark.sql.hive.SparkHiveWriterContainer
-
- getLocalityIndex(Enumeration.Value) - Method in class org.apache.spark.scheduler.TaskSetManager
-
Find the index in myLocalityLevels for a given locality.
- getLocalProperties() - Method in class org.apache.spark.SparkContext
-
- getLocalProperty(String) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Get a local property set in this thread, or null if it is missing.
- getLocalProperty(String) - Method in class org.apache.spark.SparkContext
-
Get a local property set in this thread, or null if it is missing.
- getLocation() - Method in class org.apache.spark.rdd.HadoopRDD.SplitInfoReflections
-
- getLocationInfo() - Method in class org.apache.spark.rdd.HadoopRDD.SplitInfoReflections
-
- getLocations(BlockId) - Method in class org.apache.spark.storage.BlockManagerMaster
-
Get locations of the blockId from the driver
- getLocations(BlockId[]) - Method in class org.apache.spark.storage.BlockManagerMaster
-
Get locations of multiple blockIds from the driver
- getLogDirPath(String, String) - Static method in class org.apache.spark.scheduler.EventLoggingListener
-
Return a file-system-safe path to the log directory for the given application.
- getLong(String, long) - Method in class org.apache.spark.SparkConf
-
Get a parameter as a long, falling back to a default if not set
- getLong(int) - Method in class org.apache.spark.sql.api.java.Row
-
Returns the value of column i
as a long.
- getLongWritableConstantObjectInspector(Object) - Static method in class org.apache.spark.sql.hive.HiveShim
-
- getLoss() - Method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
-
- getLowerBound(double, long, double) - Static method in class org.apache.spark.util.random.BinomialBounds
-
Returns a threshold p
such that if we conduct n Bernoulli trials with success rate = p
,
it is very unlikely to have more than fraction * n
successes.
- getLowerBound(double) - Static method in class org.apache.spark.util.random.PoissonBounds
-
Returns a lambda such that Pr[X > s] is very small, where X ~ Pois(lambda).
- GetMapOutputStatuses - Class in org.apache.spark
-
- GetMapOutputStatuses(int) - Constructor for class org.apache.spark.GetMapOutputStatuses
-
- getMatchingBlockIds(Function1<BlockId, Object>) - Method in class org.apache.spark.storage.BlockManager
-
Get the ids of existing blocks that match the given filter.
- getMatchingBlockIds(Function1<BlockId, Object>, boolean) - Method in class org.apache.spark.storage.BlockManagerMaster
-
Return a list of ids of existing blocks such that the ids match the given filter.
- getMaxBatchSize() - Method in class org.apache.spark.streaming.flume.FlumePollingReceiver
-
- getMaxBins() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- getMaxDepth() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- getMaxInputStreamRememberDuration() - Method in class org.apache.spark.streaming.DStreamGraph
-
Get the maximum remember duration across all the input streams.
- getMaxIter() - Method in interface org.apache.spark.ml.param.HasMaxIter
-
- getMaxMemoryInMB() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- getMaxResultSize(SparkConf) - Static method in class org.apache.spark.util.Utils
-
- getMemoryStatus() - Method in class org.apache.spark.storage.BlockManagerMaster
-
Return the memory status for each block manager, in the form of a map from
the block manager's id to two long values.
- getMessage() - Method in exception org.apache.spark.util.TaskCompletionListenerException
-
- getMetadata() - Method in class org.apache.spark.sql.api.java.StructField
-
- getMetricName() - Method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
-
- getMetricsSnapshot(HttpServletRequest) - Method in class org.apache.spark.metrics.sink.MetricsServlet
-
- getMinInfoGain() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- getMinInstancesPerNode() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- getModel(Estimator<M>) - Method in class org.apache.spark.ml.PipelineModel
-
Gets the model produced by the input estimator.
- getModifyAcls() - Method in class org.apache.spark.SecurityManager
-
- getName() - Method in class org.apache.spark.sql.api.java.StructField
-
- getNarrowAncestors() - Method in class org.apache.spark.rdd.RDD
-
Return the ancestors of the given RDD that are related to it only through a sequence of
narrow dependencies.
- getNewReceiverStreamId() - Method in class org.apache.spark.streaming.StreamingContext
-
- getNode(int, Node) - Static method in class org.apache.spark.mllib.tree.model.Node
-
Traces down from a root node to get the node with the given node index.
- getNumClasses() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- getNumFeatures() - Method in class org.apache.spark.ml.feature.HashingTF
-
- getNumFolds() - Method in interface org.apache.spark.ml.tuning.CrossValidatorParams
-
- getNumIterations() - Method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
-
- getObjectInspector() - Method in class org.apache.spark.sql.hive.parquet.FakeParquetSerDe
-
- getOption(String) - Method in class org.apache.spark.SparkConf
-
Get a parameter as an Option
- getOrCompute(RDD<T>, Partition, TaskContext, StorageLevel) - Method in class org.apache.spark.CacheManager
-
Gets or computes an RDD partition.
- getOrCompute(Time) - Method in class org.apache.spark.streaming.dstream.DStream
-
Get the RDD corresponding to the given time; either retrieve it from cache
or compute-and-cache it.
- getOrCreate(String, JavaStreamingContextFactory) - Static method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
Either recreate a StreamingContext from checkpoint data or create a new StreamingContext.
- getOrCreate(String, Configuration, JavaStreamingContextFactory) - Static method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
Either recreate a StreamingContext from checkpoint data or create a new StreamingContext.
- getOrCreate(String, Configuration, JavaStreamingContextFactory, boolean) - Static method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
Either recreate a StreamingContext from checkpoint data or create a new StreamingContext.
- getOrCreate(String, Function0<StreamingContext>, Configuration, boolean) - Static method in class org.apache.spark.streaming.StreamingContext
-
Either recreate a StreamingContext from checkpoint data or create a new StreamingContext.
- getOrCreateLocalRootDirs(SparkConf) - Static method in class org.apache.spark.util.Utils
-
Gets or creates the directories listed in spark.local.dir or SPARK_LOCAL_DIRS,
and returns only the directories that exist / could be created.
- getOutputCol() - Method in interface org.apache.spark.ml.param.HasOutputCol
-
- getOutputStream(String, Configuration) - Static method in class org.apache.spark.streaming.util.HdfsUtils
-
- getOutputStreams() - Method in class org.apache.spark.streaming.DStreamGraph
-
- getParam(String) - Method in interface org.apache.spark.ml.param.Params
-
Gets a param by its name.
- getParents(int) - Method in class org.apache.spark.NarrowDependency
-
Get the parent partitions for a child partition.
- getParents(int) - Method in class org.apache.spark.OneToOneDependency
-
- getParents(int) - Method in class org.apache.spark.RangeDependency
-
- getParents(int) - Method in class org.apache.spark.rdd.PruneDependency
-
- getPartition(long, long, int) - Method in class org.apache.spark.graphx.PartitionStrategy.CanonicalRandomVertexCut$
-
- getPartition(long, long, int) - Method in class org.apache.spark.graphx.PartitionStrategy.EdgePartition1D$
-
- getPartition(long, long, int) - Method in class org.apache.spark.graphx.PartitionStrategy.EdgePartition2D$
-
- getPartition(long, long, int) - Method in interface org.apache.spark.graphx.PartitionStrategy
-
Returns the partition number for a given edge.
- getPartition(long, long, int) - Method in class org.apache.spark.graphx.PartitionStrategy.RandomVertexCut$
-
- getPartition(Object) - Method in class org.apache.spark.HashPartitioner
-
- getPartition(Object) - Method in class org.apache.spark.mllib.recommendation.ALSPartitioner
-
- getPartition(Object) - Method in class org.apache.spark.Partitioner
-
- getPartition(Object) - Method in class org.apache.spark.RangePartitioner
-
- getPartitions() - Method in class org.apache.spark.mllib.rdd.RandomRDD
-
- getPartitions() - Method in class org.apache.spark.mllib.rdd.SlidingRDD
-
- getPartitions() - Method in class org.apache.spark.rdd.BinaryFileRDD
-
- getPartitions() - Method in class org.apache.spark.rdd.BlockRDD
-
- getPartitions() - Method in class org.apache.spark.rdd.CartesianRDD
-
- getPartitions() - Method in class org.apache.spark.rdd.CheckpointRDD
-
- getPartitions() - Method in class org.apache.spark.rdd.CoalescedRDD
-
- getPartitions() - Method in class org.apache.spark.rdd.CoGroupedRDD
-
- getPartitions() - Method in class org.apache.spark.rdd.EmptyRDD
-
- getPartitions() - Method in class org.apache.spark.rdd.FilteredRDD
-
- getPartitions() - Method in class org.apache.spark.rdd.FlatMappedRDD
-
- getPartitions() - Method in class org.apache.spark.rdd.FlatMappedValuesRDD
-
- getPartitions() - Method in class org.apache.spark.rdd.GlommedRDD
-
- getPartitions() - Method in class org.apache.spark.rdd.HadoopRDD
-
- getPartitions() - Method in class org.apache.spark.rdd.HadoopRDD.HadoopMapPartitionsWithSplitRDD
-
- getPartitions() - Method in class org.apache.spark.rdd.JdbcRDD
-
- getPartitions() - Method in class org.apache.spark.rdd.MapPartitionsRDD
-
- getPartitions() - Method in class org.apache.spark.rdd.MappedRDD
-
- getPartitions() - Method in class org.apache.spark.rdd.MappedValuesRDD
-
- getPartitions() - Method in class org.apache.spark.rdd.NewHadoopRDD
-
- getPartitions() - Method in class org.apache.spark.rdd.NewHadoopRDD.NewHadoopMapPartitionsWithSplitRDD
-
- getPartitions() - Method in class org.apache.spark.rdd.ParallelCollectionRDD
-
- getPartitions() - Method in class org.apache.spark.rdd.PartitionCoalescer
-
- getPartitions() - Method in class org.apache.spark.rdd.PartitionerAwareUnionRDD
-
- getPartitions() - Method in class org.apache.spark.rdd.PartitionwiseSampledRDD
-
- getPartitions() - Method in class org.apache.spark.rdd.PipedRDD
-
- getPartitions() - Method in class org.apache.spark.rdd.RDDCheckpointData
-
- getPartitions() - Method in class org.apache.spark.rdd.SampledRDD
-
- getPartitions() - Method in class org.apache.spark.rdd.ShuffledRDD
-
- getPartitions() - Method in class org.apache.spark.rdd.SubtractedRDD
-
- getPartitions() - Method in class org.apache.spark.rdd.UnionRDD
-
- getPartitions() - Method in class org.apache.spark.rdd.WholeTextFileRDD
-
- getPartitions() - Method in class org.apache.spark.rdd.ZippedPartitionsBaseRDD
-
- getPartitions() - Method in class org.apache.spark.rdd.ZippedWithIndexRDD
-
- getPartitions() - Method in class org.apache.spark.sql.SchemaRDD
-
- getPartitions() - Method in class org.apache.spark.streaming.rdd.WriteAheadLogBackedBlockRDD
-
- getPath() - Method in class org.apache.spark.input.PortableDataStream
-
- getPeers(BlockManagerId) - Method in class org.apache.spark.storage.BlockManagerMaster
-
Get ids of other nodes in the cluster from the driver
- getPendingTimes() - Method in class org.apache.spark.streaming.scheduler.JobScheduler
-
- getPersistentRDDs() - Method in class org.apache.spark.SparkContext
-
Returns an immutable map of RDDs that have marked themselves as persistent via cache() call.
- getPipeEnvVars() - Method in class org.apache.spark.rdd.HadoopPartition
-
Get any environment variables that should be added to the users environment when running pipes
- getPipeline() - Method in class org.apache.spark.streaming.flume.FlumeReceiver.CompressionChannelPipelineFactory
-
- getPointIterator(RandomRDDPartition<T>, ClassTag<T>) - Static method in class org.apache.spark.mllib.rdd.RandomRDD
-
- getPoissonSamplingFunction(RDD<Tuple2<K, V>>, Map<K, Object>, boolean, long, ClassTag<K>, ClassTag<V>) - Static method in class org.apache.spark.util.random.StratifiedSamplingUtils
-
Return the per partition sampling function used for sampling with replacement.
- getPoolForName(String) - Method in class org.apache.spark.SparkContext
-
:: DeveloperApi ::
Return the pool associated with the given name, if one exists
- getPrecision() - Method in class org.apache.spark.sql.api.java.DecimalType
-
Return the precision, or -1 if no precision is set
- getPredictionCol() - Method in interface org.apache.spark.ml.param.HasPredictionCol
-
- getPreferredLocations(Partition) - Method in class org.apache.spark.mllib.rdd.SlidingRDD
-
- getPreferredLocations(Partition) - Method in class org.apache.spark.rdd.BlockRDD
-
- getPreferredLocations(Partition) - Method in class org.apache.spark.rdd.CartesianRDD
-
- getPreferredLocations(Partition) - Method in class org.apache.spark.rdd.CheckpointRDD
-
- getPreferredLocations(Partition) - Method in class org.apache.spark.rdd.CoalescedRDD
-
Returns the preferred machine for the partition.
- getPreferredLocations(Partition) - Method in class org.apache.spark.rdd.HadoopRDD
-
- getPreferredLocations(Partition) - Method in class org.apache.spark.rdd.NewHadoopRDD
-
- getPreferredLocations(Partition) - Method in class org.apache.spark.rdd.ParallelCollectionRDD
-
- getPreferredLocations(Partition) - Method in class org.apache.spark.rdd.PartitionerAwareUnionRDD
-
- getPreferredLocations(Partition) - Method in class org.apache.spark.rdd.PartitionwiseSampledRDD
-
- getPreferredLocations(Partition) - Method in class org.apache.spark.rdd.RDDCheckpointData
-
- getPreferredLocations(Partition) - Method in class org.apache.spark.rdd.SampledRDD
-
- getPreferredLocations(Partition) - Method in class org.apache.spark.rdd.UnionRDD
-
- getPreferredLocations(Partition) - Method in class org.apache.spark.rdd.ZippedPartitionsBaseRDD
-
- getPreferredLocations(Partition) - Method in class org.apache.spark.rdd.ZippedWithIndexRDD
-
- getPreferredLocations(Partition) - Method in class org.apache.spark.streaming.rdd.WriteAheadLogBackedBlockRDD
-
Get the preferred location of the partition.
- getPreferredLocs(RDD<?>, int) - Method in class org.apache.spark.scheduler.DAGScheduler
-
Synchronized method that might be called from other threads.
- getPreferredLocs(RDD<?>, int) - Method in class org.apache.spark.SparkContext
-
Gets the locality information associated with the partition in a particular rdd
- getPrimitiveNullWritableConstantObjectInspector() - Static method in class org.apache.spark.sql.hive.HiveShim
-
- getProgress() - Method in class org.apache.spark.input.FixedLengthBinaryRecordReader
-
- getProgress() - Method in class org.apache.spark.input.StreamBasedRecordReader
-
- getProgress() - Method in class org.apache.spark.input.WholeTextFileRecordReader
-
- getPropertiesFromFile(String) - Static method in class org.apache.spark.util.Utils
-
Load properties present in the given file.
- getQuantileCalculationStrategy() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- getQuantiles(Traversable<Object>) - Method in class org.apache.spark.util.Distribution
-
Get the value of the distribution at the given probabilities.
- getRackForHost(String) - Method in class org.apache.spark.scheduler.TaskSchedulerImpl
-
- getRddBlockLocations(int, Seq<StorageStatus>) - Static method in class org.apache.spark.storage.StorageUtils
-
Return a mapping from block ID to its locations for each block that belongs to the given RDD.
- getRDDStorageInfo() - Method in class org.apache.spark.SparkContext
-
:: DeveloperApi ::
Return information about what RDDs are cached, if they are in mem or on disk, how much space
they take, etc.
- getReceiver() - Method in class org.apache.spark.streaming.dstream.PluggableInputDStream
-
- getReceiver() - Method in class org.apache.spark.streaming.dstream.RawInputDStream
-
- getReceiver() - Method in class org.apache.spark.streaming.dstream.ReceiverInputDStream
-
Gets the receiver object that will be sent to the worker nodes
to receive data.
- getReceiver() - Method in class org.apache.spark.streaming.dstream.SocketInputDStream
-
- getReceiver() - Method in class org.apache.spark.streaming.flume.FlumeInputDStream
-
- getReceiver() - Method in class org.apache.spark.streaming.flume.FlumePollingInputDStream
-
- getReceiver() - Method in class org.apache.spark.streaming.kafka.KafkaInputDStream
-
- getReceiver() - Method in class org.apache.spark.streaming.mqtt.MQTTInputDStream
-
- getReceiver() - Method in class org.apache.spark.streaming.twitter.TwitterInputDStream
-
- getReceiverInputStreams() - Method in class org.apache.spark.streaming.DStreamGraph
-
- getRecordLength(JobContext) - Static method in class org.apache.spark.input.FixedLengthBinaryInputFormat
-
Retrieves the record length property from a Hadoop configuration
- getReference(A) - Method in class org.apache.spark.util.TimeStampedWeakValueHashMap
-
- getRegParam() - Method in interface org.apache.spark.ml.param.HasRegParam
-
- getRemote(BlockId) - Method in class org.apache.spark.storage.BlockManager
-
Get block from remote block managers.
- getRemoteBytes(BlockId) - Method in class org.apache.spark.storage.BlockManager
-
Get block from remote block managers as serialized bytes.
- getResource(List<Protos.Resource>, String) - Method in class org.apache.spark.scheduler.cluster.mesos.MesosSchedulerBackend
-
Helper function to pull out a resource from a Mesos Resources protobuf
- getRestartTime(long) - Method in class org.apache.spark.streaming.util.RecurringTimer
-
Get the time when the timer will fire if it is restarted right now.
- getRootConverter() - Method in class org.apache.spark.sql.parquet.RowRecordMaterializer
-
- getRootDirectory() - Static method in class org.apache.spark.SparkFiles
-
Get the root directory that contains files added through SparkContext.addFile()
.
- getSaslUser() - Method in class org.apache.spark.SecurityManager
-
Gets the user used for authenticating SASL connections.
- getSaslUser(String) - Method in class org.apache.spark.SecurityManager
-
- getScale() - Method in class org.apache.spark.sql.api.java.DecimalType
-
Return the scale, or -1 if no precision is set
- getSchedulableByName(String) - Method in class org.apache.spark.scheduler.Pool
-
- getSchedulableByName(String) - Method in interface org.apache.spark.scheduler.Schedulable
-
- getSchedulableByName(String) - Method in class org.apache.spark.scheduler.TaskSetManager
-
- getSchedulingMode() - Method in class org.apache.spark.SparkContext
-
Return current scheduling mode
- getSchema(Configuration) - Static method in class org.apache.spark.sql.parquet.RowWriteSupport
-
- getScoreCol() - Method in interface org.apache.spark.ml.param.HasScoreCol
-
- getSecretKey() - Method in class org.apache.spark.SecurityManager
-
Gets the secret key.
- getSecretKey(String) - Method in class org.apache.spark.SecurityManager
-
- getSecurityManager() - Method in class org.apache.spark.ui.WebUI
-
- getSeqOp(boolean, Map<K, Object>, StratifiedSamplingUtils.RandomDataGenerator, Option<Map<K, Object>>) - Static method in class org.apache.spark.util.random.StratifiedSamplingUtils
-
Returns the function used by aggregate to collect sampling statistics for each partition.
- getSerDeStats() - Method in class org.apache.spark.sql.hive.parquet.FakeParquetSerDe
-
- getSerializedClass() - Method in class org.apache.spark.sql.hive.parquet.FakeParquetSerDe
-
- getSerializedMapOutputStatuses(int) - Method in class org.apache.spark.MapOutputTrackerMaster
-
- getSerializer(Serializer) - Static method in class org.apache.spark.serializer.Serializer
-
- getSerializer(Option<Serializer>) - Static method in class org.apache.spark.serializer.Serializer
-
- getServerStatuses(int, int) - Method in class org.apache.spark.MapOutputTracker
-
Called from executors to get the server URIs and output sizes of the map outputs of
a given shuffle.
- getServletHandlers() - Method in class org.apache.spark.metrics.MetricsSystem
-
Get any UI handlers used by this metrics system; can only be called after start().
- getShort(int) - Method in class org.apache.spark.sql.api.java.Row
-
Returns the value of column i
as a short.
- getShortWritableConstantObjectInspector(Object) - Static method in class org.apache.spark.sql.hive.HiveShim
-
- getSingle(BlockId) - Method in class org.apache.spark.storage.BlockManager
-
Read a block consisting of a single object.
- getSize(BlockId) - Method in class org.apache.spark.storage.BlockStore
-
Return the size of a block in bytes.
- getSize(BlockId) - Method in class org.apache.spark.storage.DiskStore
-
- getSize(BlockId) - Method in class org.apache.spark.storage.MemoryStore
-
- getSize(BlockId) - Method in class org.apache.spark.storage.TachyonStore
-
- getSizeForBlock(int) - Method in class org.apache.spark.scheduler.CompressedMapStatus
-
- getSizeForBlock(int) - Method in class org.apache.spark.scheduler.HighlyCompressedMapStatus
-
- getSizeForBlock(int) - Method in interface org.apache.spark.scheduler.MapStatus
-
Estimated size for the reduce block, in bytes.
- getSizesOfActiveStateTrackingCollections() - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- getSizesOfHardSizeLimitedCollections() - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- getSizesOfSoftSizeLimitedCollections() - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- getSortedRolledOverFiles(String, String) - Static method in class org.apache.spark.util.logging.RollingFileAppender
-
Get the sorted list of rolled over files.
- getSortedTaskSetQueue() - Method in class org.apache.spark.scheduler.Pool
-
- getSortedTaskSetQueue() - Method in interface org.apache.spark.scheduler.Schedulable
-
- getSortedTaskSetQueue() - Method in class org.apache.spark.scheduler.TaskSetManager
-
- getSparkClassLoader() - Static method in class org.apache.spark.util.Utils
-
Get the ClassLoader which loaded Spark.
- getSparkHome() - Method in class org.apache.spark.api.java.JavaSparkContext
-
Get Spark's home location from either a value set through the constructor,
or the spark.home Java property, or the SPARK_HOME environment variable
(in that order of preference).
- getSparkHome() - Method in class org.apache.spark.SparkContext
-
Get Spark's home location from either a value set through the constructor,
or the spark.home Java property, or the SPARK_HOME environment variable
(in that order of preference).
- getSparkOrYarnConfig(SparkConf, String, String) - Static method in class org.apache.spark.util.Utils
-
Return the value of a config either through the SparkConf or the Hadoop configuration
if this is Yarn mode.
- getSparkUI(StreamingContext) - Static method in class org.apache.spark.streaming.ui.StreamingTab
-
- getSplits(Configuration, List<Footer>) - Method in class org.apache.spark.sql.parquet.FilteringParquetRowInputFormat
-
- getStageInfo(int) - Method in class org.apache.spark.api.java.JavaSparkStatusTracker
-
Returns stage information, or null
if the stage info could not be found or was
garbage collected.
- getStageInfo(int) - Method in class org.apache.spark.SparkStatusTracker
-
Returns stage information, or None
if the stage info could not be found or was
garbage collected.
- getStages() - Method in class org.apache.spark.ml.Pipeline
-
- getStartTime() - Method in class org.apache.spark.streaming.util.RecurringTimer
-
Get the time when this timer will fire if it is started right now.
- getStatsSetupConstRawDataSize() - Static method in class org.apache.spark.sql.hive.HiveShim
-
- getStatsSetupConstTotalSize() - Static method in class org.apache.spark.sql.hive.HiveShim
-
- getStatus(BlockId) - Method in class org.apache.spark.storage.BlockManager
-
Get the BlockStatus for the block identified by the given ID, if it exists.
- getStatus(BlockId) - Method in class org.apache.spark.storage.BlockManagerInfo
-
- getStderr(Process, long) - Static method in class org.apache.spark.util.Utils
-
Return the stderr of a process after waiting for the process to terminate.
- getStorageLevel() - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Get the RDD's current storage level, or StorageLevel.NONE if none is set.
- getStorageLevel() - Method in class org.apache.spark.rdd.RDD
-
Get the RDD's current storage level, or StorageLevel.NONE if none is set.
- getStorageStatus() - Method in class org.apache.spark.storage.BlockManagerMaster
-
- getString(int) - Method in class org.apache.spark.sql.api.java.Row
-
Returns the value of column i
as a String.
- getStringWritableConstantObjectInspector(Object) - Static method in class org.apache.spark.sql.hive.HiveShim
-
- getSubsamplingRate() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- getSystemProperties() - Static method in class org.apache.spark.util.Utils
-
Returns the system properties map that is thread-safe to iterator over.
- getTableDesc(Class<? extends Deserializer>, Class<? extends InputFormat<?, ?>>, Class<?>, Properties) - Static method in class org.apache.spark.sql.hive.HiveShim
-
- getTabs() - Method in class org.apache.spark.ui.WebUI
-
- getTaskSideSplits(Configuration, List<Footer>, Long, Long, ReadSupport.ReadContext) - Method in class org.apache.spark.sql.parquet.FilteringParquetRowInputFormat
-
- getThreadDump() - Static method in class org.apache.spark.util.Utils
-
Return a thread dump of all threads' stacktraces.
- getThreadLocal() - Static method in class org.apache.spark.SparkEnv
-
Returns the ThreadLocal SparkEnv.
- getThreshold() - Method in interface org.apache.spark.ml.param.HasThreshold
-
- getTime() - Method in interface org.apache.spark.util.Clock
-
- getTime() - Static method in class org.apache.spark.util.SystemClock
-
- getTimeMillis() - Method in interface org.apache.spark.Clock
-
- getTimeMillis() - Method in class org.apache.spark.RealClock
-
- getTimeMillis() - Method in class org.apache.spark.TestClock
-
- getTimestamp(A) - Method in class org.apache.spark.util.TimeStampedHashMap
-
- getTimestamp(A) - Method in class org.apache.spark.util.TimeStampedWeakValueHashMap
-
- getTimeStampedValue(A) - Method in class org.apache.spark.util.TimeStampedHashMap
-
- getTimestampWritableConstantObjectInspector(Object) - Static method in class org.apache.spark.sql.hive.HiveShim
-
- GETTING_RESULT_TIME() - Static method in class org.apache.spark.ui.jobs.TaskDetailsClassNames
-
- GETTING_RESULT_TIME() - Static method in class org.apache.spark.ui.ToolTips
-
- gettingResult() - Method in class org.apache.spark.scheduler.TaskInfo
-
- GettingResultEvent - Class in org.apache.spark.scheduler
-
- GettingResultEvent(TaskInfo) - Constructor for class org.apache.spark.scheduler.GettingResultEvent
-
- gettingResultTime() - Method in class org.apache.spark.scheduler.TaskInfo
-
The time when the task started remotely getting the result.
- getTreeStrategy() - Method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
-
- getUIPort(SparkConf) - Static method in class org.apache.spark.ui.SparkUI
-
- getUnallocatedBlocks(int) - Method in class org.apache.spark.streaming.scheduler.ReceivedBlockTracker
-
Get blocks that have been added but not yet allocated to any batch.
- getUpperBound(double, long, double) - Static method in class org.apache.spark.util.random.BinomialBounds
-
Returns a threshold p
such that if we conduct n Bernoulli trials with success rate = p
,
it is very unlikely to have less than fraction * n
successes.
- getUpperBound(double) - Static method in class org.apache.spark.util.random.PoissonBounds
-
Returns a lambda such that Pr[X < s] is very small, where X ~ Pois(lambda).
- getUsedTimeMs(long) - Static method in class org.apache.spark.util.Utils
-
Return the string to tell how long has passed in milliseconds.
- getUseNodeIdCache() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- getValue(Row) - Method in class org.apache.spark.sql.execution.joins.UniqueKeyHashedRelation
-
- getValues(BlockId) - Method in class org.apache.spark.storage.BlockStore
-
- getValues(BlockId) - Method in class org.apache.spark.storage.DiskStore
-
- getValues(BlockId, Serializer) - Method in class org.apache.spark.storage.DiskStore
-
A version of getValues that allows a custom serializer.
- getValues(BlockId) - Method in class org.apache.spark.storage.MemoryStore
-
- getValues(BlockId) - Method in class org.apache.spark.storage.TachyonStore
-
- getValueType() - Method in class org.apache.spark.sql.api.java.MapType
-
- getVectorIterator(RandomRDDPartition<Object>, int) - Static method in class org.apache.spark.mllib.rdd.RandomRDD
-
- getVectors() - Method in class org.apache.spark.mllib.feature.Word2VecModel
-
Returns a map of words to their vector representations.
- getViewAcls() - Method in class org.apache.spark.SecurityManager
-
- Gini - Class in org.apache.spark.mllib.tree.impurity
-
:: Experimental ::
Class for calculating the
Gini impurity
during binary classification.
- Gini() - Constructor for class org.apache.spark.mllib.tree.impurity.Gini
-
- GiniAggregator - Class in org.apache.spark.mllib.tree.impurity
-
Class for updating views of a vector of sufficient statistics,
in order to compute impurity from a sample.
- GiniAggregator(int) - Constructor for class org.apache.spark.mllib.tree.impurity.GiniAggregator
-
- GiniCalculator - Class in org.apache.spark.mllib.tree.impurity
-
Stores statistics for one (node, feature, bin) for calculating impurity.
- GiniCalculator(double[]) - Constructor for class org.apache.spark.mllib.tree.impurity.GiniCalculator
-
- global() - Method in class org.apache.spark.sql.execution.ExternalSort
-
- global() - Method in class org.apache.spark.sql.execution.Sort
-
- glom() - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return an RDD created by coalescing all elements within each partition into an array.
- glom() - Method in class org.apache.spark.rdd.RDD
-
Return an RDD created by coalescing all elements within each partition into an array.
- glom() - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Return a new DStream in which each RDD is generated by applying glom() to each RDD of
this DStream.
- glom() - Method in class org.apache.spark.streaming.dstream.DStream
-
Return a new DStream in which each RDD is generated by applying glom() to each RDD of
this DStream.
- GlommedDStream<T> - Class in org.apache.spark.streaming.dstream
-
- GlommedDStream(DStream<T>, ClassTag<T>) - Constructor for class org.apache.spark.streaming.dstream.GlommedDStream
-
- GlommedRDD<T> - Class in org.apache.spark.rdd
-
- GlommedRDD(RDD<T>, ClassTag<T>) - Constructor for class org.apache.spark.rdd.GlommedRDD
-
- goodnessOfFit() - Method in class org.apache.spark.mllib.stat.test.ChiSqTest.NullHypothesis$
-
- grad() - Method in class org.apache.spark.mllib.optimization.NNLS.Workspace
-
- Gradient - Class in org.apache.spark.mllib.optimization
-
:: DeveloperApi ::
Class used to compute the gradient for a loss function, given a single data point.
- Gradient() - Constructor for class org.apache.spark.mllib.optimization.Gradient
-
- gradient(TreeEnsembleModel, LabeledPoint) - Static method in class org.apache.spark.mllib.tree.loss.AbsoluteError
-
Method to calculate the gradients for the gradient boosting calculation for least
absolute error calculation.
- gradient(TreeEnsembleModel, LabeledPoint) - Static method in class org.apache.spark.mllib.tree.loss.LogLoss
-
Method to calculate the loss gradients for the gradient boosting calculation for binary
classification
The gradient with respect to F(x) is: - 4 y / (1 + exp(2 y F(x)))
- gradient(TreeEnsembleModel, LabeledPoint) - Method in interface org.apache.spark.mllib.tree.loss.Loss
-
Method to calculate the gradients for the gradient boosting calculation.
- gradient(TreeEnsembleModel, LabeledPoint) - Static method in class org.apache.spark.mllib.tree.loss.SquaredError
-
Method to calculate the gradients for the gradient boosting calculation for least
squares error calculation.
- GradientBoostedTrees - Class in org.apache.spark.mllib.tree
-
:: Experimental ::
A class that implements
Stochastic Gradient Boosting
for regression and binary classification.
- GradientBoostedTrees(BoostingStrategy) - Constructor for class org.apache.spark.mllib.tree.GradientBoostedTrees
-
- GradientBoostedTreesModel - Class in org.apache.spark.mllib.tree.model
-
:: Experimental ::
Represents a gradient boosted trees model.
- GradientBoostedTreesModel(Enumeration.Value, DecisionTreeModel[], double[]) - Constructor for class org.apache.spark.mllib.tree.model.GradientBoostedTreesModel
-
- GradientDescent - Class in org.apache.spark.mllib.optimization
-
Class used to solve an optimization problem using Gradient Descent.
- GradientDescent(Gradient, Updater) - Constructor for class org.apache.spark.mllib.optimization.GradientDescent
-
- Graph<VD,ED> - Class in org.apache.spark.graphx
-
The Graph abstractly represents a graph with arbitrary objects
associated with vertices and edges.
- graph() - Method in class org.apache.spark.streaming.Checkpoint
-
- graph() - Method in class org.apache.spark.streaming.dstream.DStream
-
- graph() - Method in class org.apache.spark.streaming.StreamingContext
-
- GraphGenerators - Class in org.apache.spark.graphx.util
-
A collection of graph generating functions.
- GraphGenerators() - Constructor for class org.apache.spark.graphx.util.GraphGenerators
-
- GraphImpl<VD,ED> - Class in org.apache.spark.graphx.impl
-
An implementation of
Graph
to support computation on graphs.
- graphite() - Method in class org.apache.spark.metrics.sink.GraphiteSink
-
- GRAPHITE_DEFAULT_PERIOD() - Method in class org.apache.spark.metrics.sink.GraphiteSink
-
- GRAPHITE_DEFAULT_PREFIX() - Method in class org.apache.spark.metrics.sink.GraphiteSink
-
- GRAPHITE_DEFAULT_UNIT() - Method in class org.apache.spark.metrics.sink.GraphiteSink
-
- GRAPHITE_KEY_HOST() - Method in class org.apache.spark.metrics.sink.GraphiteSink
-
- GRAPHITE_KEY_PERIOD() - Method in class org.apache.spark.metrics.sink.GraphiteSink
-
- GRAPHITE_KEY_PORT() - Method in class org.apache.spark.metrics.sink.GraphiteSink
-
- GRAPHITE_KEY_PREFIX() - Method in class org.apache.spark.metrics.sink.GraphiteSink
-
- GRAPHITE_KEY_UNIT() - Method in class org.apache.spark.metrics.sink.GraphiteSink
-
- GraphiteSink - Class in org.apache.spark.metrics.sink
-
- GraphiteSink(Properties, MetricRegistry, SecurityManager) - Constructor for class org.apache.spark.metrics.sink.GraphiteSink
-
- GraphKryoRegistrator - Class in org.apache.spark.graphx
-
Registers GraphX classes with Kryo for improved performance.
- GraphKryoRegistrator() - Constructor for class org.apache.spark.graphx.GraphKryoRegistrator
-
- GraphLoader - Class in org.apache.spark.graphx
-
Provides utilities for loading
Graph
s from files.
- GraphLoader() - Constructor for class org.apache.spark.graphx.GraphLoader
-
- GraphOps<VD,ED> - Class in org.apache.spark.graphx
-
Contains additional functionality for
Graph
.
- GraphOps(Graph<VD, ED>, ClassTag<VD>, ClassTag<ED>) - Constructor for class org.apache.spark.graphx.GraphOps
-
- graphToGraphOps(Graph<VD, ED>, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.Graph
-
Implicitly extracts the
GraphOps
member from a graph.
- GraphXUtils - Class in org.apache.spark.graphx
-
- GraphXUtils() - Constructor for class org.apache.spark.graphx.GraphXUtils
-
- greater(Duration) - Method in class org.apache.spark.streaming.Duration
-
- greater(Time) - Method in class org.apache.spark.streaming.Time
-
- greaterEq(Duration) - Method in class org.apache.spark.streaming.Duration
-
- greaterEq(Time) - Method in class org.apache.spark.streaming.Time
-
- GreaterThan - Class in org.apache.spark.sql.sources
-
- GreaterThan(String, Object) - Constructor for class org.apache.spark.sql.sources.GreaterThan
-
- GreaterThanOrEqual - Class in org.apache.spark.sql.sources
-
- GreaterThanOrEqual(String, Object) - Constructor for class org.apache.spark.sql.sources.GreaterThanOrEqual
-
- gridGraph(SparkContext, int, int) - Static method in class org.apache.spark.graphx.util.GraphGenerators
-
Create rows
by cols
grid graph with each vertex connected to its
row+1 and col+1 neighbors.
- groupArr() - Method in class org.apache.spark.rdd.PartitionCoalescer
-
- groupBy(Function<T, U>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return an RDD of grouped elements.
- groupBy(Function<T, U>, int) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return an RDD of grouped elements.
- groupBy(Function1<T, K>, ClassTag<K>) - Method in class org.apache.spark.rdd.RDD
-
Return an RDD of grouped items.
- groupBy(Function1<T, K>, int, ClassTag<K>) - Method in class org.apache.spark.rdd.RDD
-
Return an RDD of grouped elements.
- groupBy(Function1<T, K>, Partitioner, ClassTag<K>, Ordering<K>) - Method in class org.apache.spark.rdd.RDD
-
Return an RDD of grouped items.
- groupBy(Seq<Expression>, Seq<Expression>) - Method in class org.apache.spark.sql.SchemaRDD
-
Performs a grouping followed by an aggregation.
- groupByKey(Partitioner) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Group the values for each key in the RDD into a single sequence.
- groupByKey(int) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Group the values for each key in the RDD into a single sequence.
- groupByKey() - Method in class org.apache.spark.api.java.JavaPairRDD
-
Group the values for each key in the RDD into a single sequence.
- groupByKey(Partitioner) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Group the values for each key in the RDD into a single sequence.
- groupByKey(int) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Group the values for each key in the RDD into a single sequence.
- groupByKey() - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Group the values for each key in the RDD into a single sequence.
- groupByKey() - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying groupByKey
to each RDD.
- groupByKey(int) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying groupByKey
to each RDD.
- groupByKey(Partitioner) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying groupByKey
on each RDD of this
DStream.
- groupByKey() - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying groupByKey
to each RDD.
- groupByKey(int) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying groupByKey
to each RDD.
- groupByKey(Partitioner) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying groupByKey
on each RDD.
- groupByKeyAndWindow(Duration) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying groupByKey
over a sliding window.
- groupByKeyAndWindow(Duration, Duration) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying groupByKey
over a sliding window.
- groupByKeyAndWindow(Duration, Duration, int) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying groupByKey
over a sliding window on this
DStream.
- groupByKeyAndWindow(Duration, Duration, Partitioner) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying groupByKey
over a sliding window on this
DStream.
- groupByKeyAndWindow(Duration) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying groupByKey
over a sliding window.
- groupByKeyAndWindow(Duration, Duration) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying groupByKey
over a sliding window.
- groupByKeyAndWindow(Duration, Duration, int) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying groupByKey
over a sliding window on this
DStream.
- groupByKeyAndWindow(Duration, Duration, Partitioner) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Create a new DStream by applying groupByKey
over a sliding window on this
DStream.
- groupByResultToJava(RDD<Tuple2<K, Iterable<T>>>, ClassTag<K>) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- GroupedCountEvaluator<T> - Class in org.apache.spark.partial
-
An ApproximateEvaluator for counts by key.
- GroupedCountEvaluator(int, double, ClassTag<T>) - Constructor for class org.apache.spark.partial.GroupedCountEvaluator
-
- groupEdges(Function2<ED, ED, ED>) - Method in class org.apache.spark.graphx.Graph
-
Merges multiple edges between two vertices into a single edge.
- groupEdges(Function2<ED, ED, ED>) - Method in class org.apache.spark.graphx.impl.EdgePartition
-
Merge all the edges with the same src and dest id into a single
edge using the merge
function
- groupEdges(Function2<ED, ED, ED>) - Method in class org.apache.spark.graphx.impl.GraphImpl
-
- GroupedMeanEvaluator<T> - Class in org.apache.spark.partial
-
An ApproximateEvaluator for means by key.
- GroupedMeanEvaluator(int, double) - Constructor for class org.apache.spark.partial.GroupedMeanEvaluator
-
- GroupedSumEvaluator<T> - Class in org.apache.spark.partial
-
An ApproximateEvaluator for sums by key.
- GroupedSumEvaluator(int, double) - Constructor for class org.apache.spark.partial.GroupedSumEvaluator
-
- groupHash() - Method in class org.apache.spark.rdd.PartitionCoalescer
-
- groupId() - Method in class org.apache.spark.scheduler.JobGroupCancelled
-
- groupingExpressions() - Method in class org.apache.spark.sql.execution.Aggregate
-
- groupingExpressions() - Method in class org.apache.spark.sql.execution.GeneratedAggregate
-
- groupWith(JavaPairRDD<K, W>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Alias for cogroup.
- groupWith(JavaPairRDD<K, W1>, JavaPairRDD<K, W2>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Alias for cogroup.
- groupWith(JavaPairRDD<K, W1>, JavaPairRDD<K, W2>, JavaPairRDD<K, W3>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Alias for cogroup.
- groupWith(RDD<Tuple2<K, W>>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Alias for cogroup.
- groupWith(RDD<Tuple2<K, W1>>, RDD<Tuple2<K, W2>>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Alias for cogroup.
- groupWith(RDD<Tuple2<K, W1>>, RDD<Tuple2<K, W2>>, RDD<Tuple2<K, W3>>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Alias for cogroup.
- groupWriter() - Method in class org.apache.spark.sql.parquet.TestGroupWriteSupport
-
- GrowableAccumulableParam<R,T> - Class in org.apache.spark
-
- GrowableAccumulableParam(Function1<R, Growable<T>>, ClassTag<R>) - Constructor for class org.apache.spark.GrowableAccumulableParam
-
- i() - Method in class org.apache.spark.mllib.linalg.distributed.MatrixEntry
-
- id() - Method in class org.apache.spark.Accumulable
-
- id() - Method in interface org.apache.spark.api.java.JavaRDDLike
-
A unique ID for this RDD (within its SparkContext).
- id() - Method in class org.apache.spark.broadcast.Broadcast
-
- id() - Method in class org.apache.spark.mllib.tree.model.Node
-
- id() - Method in class org.apache.spark.rdd.RDD
-
A unique ID for this RDD (within its SparkContext).
- id() - Method in class org.apache.spark.scheduler.AccumulableInfo
-
- id() - Method in class org.apache.spark.scheduler.Stage
-
- id() - Method in class org.apache.spark.scheduler.TaskInfo
-
- id() - Method in class org.apache.spark.scheduler.TaskSet
-
- id() - Method in class org.apache.spark.storage.RDDInfo
-
- id() - Method in class org.apache.spark.storage.TempLocalBlockId
-
- id() - Method in class org.apache.spark.storage.TempShuffleBlockId
-
- id() - Method in class org.apache.spark.storage.TestBlockId
-
- id() - Method in class org.apache.spark.streaming.dstream.ReceiverInputDStream
-
This is an unique identifier for the receiver input stream.
- id() - Method in class org.apache.spark.streaming.scheduler.Job
-
- id() - Method in class org.apache.spark.ui.exec.ExecutorSummaryInfo
-
- Identifiable - Interface in org.apache.spark.ml
-
Object with a unique id.
- IDF - Class in org.apache.spark.mllib.feature
-
:: Experimental ::
Inverse document frequency (IDF).
- IDF(int) - Constructor for class org.apache.spark.mllib.feature.IDF
-
- IDF() - Constructor for class org.apache.spark.mllib.feature.IDF
-
- idf() - Method in class org.apache.spark.mllib.feature.IDF.DocumentFrequencyAggregator
-
Returns the current IDF vector.
- idf() - Method in class org.apache.spark.mllib.feature.IDFModel
-
- IDF.DocumentFrequencyAggregator - Class in org.apache.spark.mllib.feature
-
Document frequency aggregator.
- IDF.DocumentFrequencyAggregator(int) - Constructor for class org.apache.spark.mllib.feature.IDF.DocumentFrequencyAggregator
-
- IDF.DocumentFrequencyAggregator() - Constructor for class org.apache.spark.mllib.feature.IDF.DocumentFrequencyAggregator
-
- IDFModel - Class in org.apache.spark.mllib.feature
-
:: Experimental ::
Represents an IDF model that can transform term frequency vectors.
- IDFModel(Vector) - Constructor for class org.apache.spark.mllib.feature.IDFModel
-
- IdGenerator - Class in org.apache.spark.util
-
A util used to get a unique generation ID.
- IdGenerator() - Constructor for class org.apache.spark.util.IdGenerator
-
- idx() - Method in class org.apache.spark.mllib.rdd.SlidingRDDPartition
-
- idx() - Method in class org.apache.spark.rdd.PartitionerAwareUnionRDDPartition
-
- idx() - Method in class org.apache.spark.rdd.ShuffledRDDPartition
-
- ifExists() - Method in class org.apache.spark.sql.hive.DropTable
-
- ifExists() - Method in class org.apache.spark.sql.hive.execution.DropTable
-
- Impurities - Class in org.apache.spark.mllib.tree.impurity
-
Factory for Impurity instances.
- Impurities() - Constructor for class org.apache.spark.mllib.tree.impurity.Impurities
-
- impurity() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- impurity() - Method in class org.apache.spark.mllib.tree.impl.DecisionTreeMetadata
-
- Impurity - Interface in org.apache.spark.mllib.tree.impurity
-
:: Experimental ::
Trait for calculating information gain.
- impurity() - Method in class org.apache.spark.mllib.tree.model.InformationGainStats
-
- impurity() - Method in class org.apache.spark.mllib.tree.model.Node
-
- impurityAggregator() - Method in class org.apache.spark.mllib.tree.impl.DTStatsAggregator
-
ImpurityAggregator
instance specifying the impurity type.
- ImpurityAggregator - Class in org.apache.spark.mllib.tree.impurity
-
Interface for updating views of a vector of sufficient statistics,
in order to compute impurity from a sample.
- ImpurityAggregator(int) - Constructor for class org.apache.spark.mllib.tree.impurity.ImpurityAggregator
-
- ImpurityCalculator - Class in org.apache.spark.mllib.tree.impurity
-
Stores statistics for one (node, feature, bin) for calculating impurity.
- ImpurityCalculator(double[]) - Constructor for class org.apache.spark.mllib.tree.impurity.ImpurityCalculator
-
- In() - Static method in class org.apache.spark.graphx.EdgeDirection
-
Edges arriving at a vertex.
- IN() - Static method in class org.apache.spark.sql.hive.HiveQl
-
- In - Class in org.apache.spark.sql.sources
-
- In(String, Object[]) - Constructor for class org.apache.spark.sql.sources.In
-
- increaseRunningTasks(int) - Method in class org.apache.spark.scheduler.Pool
-
- incrementEpoch() - Method in class org.apache.spark.MapOutputTrackerMaster
-
- inDegrees() - Method in class org.apache.spark.graphx.GraphOps
-
The in-degree of each vertex in the graph.
- independence() - Method in class org.apache.spark.mllib.stat.test.ChiSqTest.NullHypothesis$
-
- index() - Method in class org.apache.spark.graphx.impl.ShippableVertexPartition
-
- index() - Method in class org.apache.spark.graphx.impl.VertexPartition
-
- index() - Method in class org.apache.spark.graphx.impl.VertexPartitionBase
-
- index(int, int) - Method in class org.apache.spark.mllib.linalg.DenseMatrix
-
- index() - Method in class org.apache.spark.mllib.linalg.distributed.IndexedRow
-
- index(int, int) - Method in interface org.apache.spark.mllib.linalg.Matrix
-
Return the index for the (i, j)-th element in the backing array.
- index(int, int) - Method in class org.apache.spark.mllib.linalg.SparseMatrix
-
- index() - Method in class org.apache.spark.mllib.rdd.RandomRDDPartition
-
- index() - Method in class org.apache.spark.mllib.rdd.SlidingRDDPartition
-
- index() - Method in class org.apache.spark.mllib.recommendation.ALS.BlockStats
-
- index() - Method in interface org.apache.spark.Partition
-
Get the partition's index within its parent RDD
- index() - Method in class org.apache.spark.rdd.BlockRDDPartition
-
- index() - Method in class org.apache.spark.rdd.CartesianPartition
-
- index() - Method in class org.apache.spark.rdd.CheckpointRDDPartition
-
- index() - Method in class org.apache.spark.rdd.CoalescedRDDPartition
-
- index() - Method in class org.apache.spark.rdd.CoGroupPartition
-
- index() - Method in class org.apache.spark.rdd.HadoopPartition
-
- index() - Method in class org.apache.spark.rdd.JdbcPartition
-
- index() - Method in class org.apache.spark.rdd.NewHadoopPartition
-
- index() - Method in class org.apache.spark.rdd.ParallelCollectionPartition
-
- index() - Method in class org.apache.spark.rdd.PartitionerAwareUnionRDDPartition
-
- index() - Method in class org.apache.spark.rdd.PartitionPruningRDDPartition
-
- index() - Method in class org.apache.spark.rdd.PartitionwiseSampledRDDPartition
-
- index() - Method in class org.apache.spark.rdd.SampledRDDPartition
-
- index() - Method in class org.apache.spark.rdd.ShuffledRDDPartition
-
- index() - Method in class org.apache.spark.rdd.UnionPartition
-
- index() - Method in class org.apache.spark.rdd.ZippedPartitionsPartition
-
- index() - Method in class org.apache.spark.rdd.ZippedWithIndexRDDPartition
-
- index() - Method in class org.apache.spark.scheduler.TaskDescription
-
- index() - Method in class org.apache.spark.scheduler.TaskInfo
-
- index() - Method in class org.apache.spark.sql.parquet.CatalystArrayContainsNullConverter
-
- index() - Method in class org.apache.spark.sql.parquet.CatalystArrayConverter
-
- index() - Method in class org.apache.spark.sql.parquet.CatalystNativeArrayConverter
-
- index() - Method in class org.apache.spark.sql.parquet.CatalystPrimitiveRowConverter
-
- index() - Method in class org.apache.spark.streaming.rdd.WriteAheadLogBackedBlockRDDPartition
-
- IndexedRow - Class in org.apache.spark.mllib.linalg.distributed
-
- IndexedRow(long, Vector) - Constructor for class org.apache.spark.mllib.linalg.distributed.IndexedRow
-
- IndexedRowMatrix - Class in org.apache.spark.mllib.linalg.distributed
-
- IndexedRowMatrix(RDD<IndexedRow>, long, int) - Constructor for class org.apache.spark.mllib.linalg.distributed.IndexedRowMatrix
-
- IndexedRowMatrix(RDD<IndexedRow>) - Constructor for class org.apache.spark.mllib.linalg.distributed.IndexedRowMatrix
-
Alternative constructor leaving matrix dimensions to be determined automatically.
- indexOf(Object) - Method in class org.apache.spark.mllib.feature.HashingTF
-
Returns the index of the input term.
- indexSize() - Method in class org.apache.spark.graphx.impl.EdgePartition
-
The number of unique source vertices in the partition.
- indexToLevel(int) - Static method in class org.apache.spark.mllib.tree.model.Node
-
Return the level of a tree which the given node is in.
- indices() - Method in class org.apache.spark.mllib.linalg.SparseVector
-
- IndirectTaskResult<T> - Class in org.apache.spark.scheduler
-
A reference to a DirectTaskResult that has been stored in the worker's BlockManager.
- IndirectTaskResult(BlockId, int) - Constructor for class org.apache.spark.scheduler.IndirectTaskResult
-
- inferSchema(RDD<String>, double, String) - Static method in class org.apache.spark.sql.json.JsonRDD
-
- InformationGainStats - Class in org.apache.spark.mllib.tree.model
-
:: DeveloperApi ::
Information gain statistics for each split
- InformationGainStats(double, double, double, double, Predict, Predict) - Constructor for class org.apache.spark.mllib.tree.model.InformationGainStats
-
- init(RDD<BaggedPoint<TreePoint>>, int, Option<String>, int, int) - Static method in class org.apache.spark.mllib.tree.impl.NodeIdCache
-
Initialize the node Id cache with initial node Id values.
- init(Configuration, Map<String, String>, MessageType) - Method in class org.apache.spark.sql.parquet.RowReadSupport
-
- init(Configuration) - Method in class org.apache.spark.sql.parquet.RowWriteSupport
-
- init(Configuration) - Method in class org.apache.spark.sql.parquet.TestGroupWriteSupport
-
- initFrom(Iterator<Tuple2<Object, VD>>, ClassTag<VD>) - Static method in class org.apache.spark.graphx.impl.VertexPartitionBase
-
Construct the constituents of a VertexPartitionBase from the given vertices, merging duplicate
entries arbitrarily.
- initFrom(Iterator<Tuple2<Object, VD>>, Function2<VD, VD, VD>, ClassTag<VD>) - Static method in class org.apache.spark.graphx.impl.VertexPartitionBase
-
Construct the constituents of a VertexPartitionBase from the given vertices, merging duplicate
entries using mergeFunc
.
- INITIAL_ARRAY_SIZE() - Static method in class org.apache.spark.sql.parquet.CatalystArrayConverter
-
- initialCheckpoint() - Method in class org.apache.spark.streaming.StreamingContext
-
- initialHash() - Method in class org.apache.spark.rdd.PartitionCoalescer
-
- initialize(boolean, SparkConf, SecurityManager) - Method in interface org.apache.spark.broadcast.BroadcastFactory
-
- initialize(boolean, SparkConf, SecurityManager) - Static method in class org.apache.spark.broadcast.HttpBroadcast
-
- initialize(boolean, SparkConf, SecurityManager) - Method in class org.apache.spark.broadcast.HttpBroadcastFactory
-
- initialize(boolean, SparkConf, SecurityManager) - Method in class org.apache.spark.broadcast.TorrentBroadcastFactory
-
- initialize() - Method in class org.apache.spark.HttpFileServer
-
- initialize(InputSplit, TaskAttemptContext) - Method in class org.apache.spark.input.FixedLengthBinaryRecordReader
-
- initialize(InputSplit, TaskAttemptContext) - Method in class org.apache.spark.input.StreamBasedRecordReader
-
- initialize(InputSplit, TaskAttemptContext) - Method in class org.apache.spark.input.WholeTextFileRecordReader
-
- initialize() - Method in class org.apache.spark.metrics.MetricsConfig
-
- initialize(SchedulerBackend) - Method in class org.apache.spark.scheduler.TaskSchedulerImpl
-
- initialize(int, String, boolean) - Method in class org.apache.spark.sql.columnar.BasicColumnBuilder
-
- initialize() - Method in interface org.apache.spark.sql.columnar.ColumnAccessor
-
- initialize(int, String, boolean) - Method in interface org.apache.spark.sql.columnar.ColumnBuilder
-
Initializes with an approximate lower bound on the expected number of elements in this column.
- initialize() - Method in interface org.apache.spark.sql.columnar.compression.CompressibleColumnAccessor
-
- initialize(int, String, boolean) - Method in interface org.apache.spark.sql.columnar.compression.CompressibleColumnBuilder
-
- initialize() - Method in interface org.apache.spark.sql.columnar.NullableColumnAccessor
-
- initialize(int, String, boolean) - Method in interface org.apache.spark.sql.columnar.NullableColumnBuilder
-
- initialize(Configuration, Properties) - Method in class org.apache.spark.sql.hive.parquet.FakeParquetSerDe
-
- initialize(String) - Method in class org.apache.spark.storage.BlockManager
-
Initializes the BlockManager with the given appId.
- initialize(Time) - Method in class org.apache.spark.streaming.dstream.DStream
-
Initialize the DStream by setting the "zero" time, based on which
the validity of future times is calculated.
- initialize(String) - Method in class org.apache.spark.streaming.kinesis.KinesisRecordProcessor
-
The Kinesis Client Library calls this method during IRecordProcessor initialization.
- initialize() - Method in class org.apache.spark.ui.SparkUI
-
Initialize all components of the server.
- initialize() - Method in class org.apache.spark.ui.WebUI
-
Initialize all components of the server.
- Initialized() - Static method in class org.apache.spark.rdd.CheckpointState
-
- Initialized() - Method in class org.apache.spark.streaming.receiver.ReceiverSupervisor.ReceiverState
-
- Initialized() - Method in class org.apache.spark.streaming.StreamingContext.StreamingContextState$
-
- initializeIfNecessary() - Method in interface org.apache.spark.Logging
-
- initializeLocalJobConfFunc(String, TableDesc, JobConf) - Static method in class org.apache.spark.sql.hive.HadoopTableReader
-
Curried.
- initializeLogging() - Method in interface org.apache.spark.Logging
-
- initialValue() - Method in class org.apache.spark.partial.PartialResult
-
- initialValues() - Method in class org.apache.spark.sql.execution.AggregateEvaluation
-
- initLocalProperties() - Method in class org.apache.spark.SparkContext
-
- initNextRecordReader() - Method in class org.apache.spark.input.WholeCombineFileRecordReader
-
- InLinkBlock - Class in org.apache.spark.mllib.recommendation
-
In-link information for a user (or product) block.
- InLinkBlock(int[], Tuple2<int[], double[]>[][]) - Constructor for class org.apache.spark.mllib.recommendation.InLinkBlock
-
- InMemoryColumnarTableScan - Class in org.apache.spark.sql.columnar
-
- InMemoryColumnarTableScan(Seq<Attribute>, Seq<Expression>, InMemoryRelation) - Constructor for class org.apache.spark.sql.columnar.InMemoryColumnarTableScan
-
- inMemoryPartitionPruning() - Method in interface org.apache.spark.sql.SQLConf
-
When set to true, partition pruning for in-memory columnar tables is enabled.
- InMemoryRelation - Class in org.apache.spark.sql.columnar
-
- InMemoryRelation(Seq<Attribute>, boolean, int, StorageLevel, SparkPlan, Option<String>, RDD<CachedBatch>, Statistics) - Constructor for class org.apache.spark.sql.columnar.InMemoryRelation
-
- InMemoryScans() - Method in class org.apache.spark.sql.execution.SparkStrategies
-
- InnerClosureFinder - Class in org.apache.spark.util
-
- InnerClosureFinder(Set<Class<?>>) - Constructor for class org.apache.spark.util.InnerClosureFinder
-
- innerJoin(EdgeRDD<ED2>, Function4<Object, Object, ED, ED2, ED3>, ClassTag<ED2>, ClassTag<ED3>) - Method in class org.apache.spark.graphx.EdgeRDD
-
Inner joins this EdgeRDD with another EdgeRDD, assuming both are partitioned using the same
PartitionStrategy
.
- innerJoin(EdgePartition<ED2, ?>, Function4<Object, Object, ED, ED2, ED3>, ClassTag<ED2>, ClassTag<ED3>) - Method in class org.apache.spark.graphx.impl.EdgePartition
-
Apply f
to all edges present in both this
and other
and return a new EdgePartition
containing the resulting edges.
- innerJoin(EdgeRDD<ED2>, Function4<Object, Object, ED, ED2, ED3>, ClassTag<ED2>, ClassTag<ED3>) - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- innerJoin(Self, Function3<Object, VD, U, VD2>, ClassTag<U>, ClassTag<VD2>) - Method in class org.apache.spark.graphx.impl.VertexPartitionBaseOps
-
Inner join another VertexPartition.
- innerJoin(Iterator<Product2<Object, U>>, Function3<Object, VD, U, VD2>, ClassTag<U>, ClassTag<VD2>) - Method in class org.apache.spark.graphx.impl.VertexPartitionBaseOps
-
Inner join an iterator of messages.
- innerJoin(RDD<Tuple2<Object, U>>, Function3<Object, VD, U, VD2>, ClassTag<U>, ClassTag<VD2>) - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- innerJoin(RDD<Tuple2<Object, U>>, Function3<Object, VD, U, VD2>, ClassTag<U>, ClassTag<VD2>) - Method in class org.apache.spark.graphx.VertexRDD
-
Inner joins this VertexRDD with an RDD containing vertex attribute pairs.
- innerJoinKeepLeft(Iterator<Product2<Object, VD>>) - Method in class org.apache.spark.graphx.impl.VertexPartitionBaseOps
-
Similar to innerJoin, but vertices from the left side that don't appear in iter will remain in
the partition, hidden by the bitmask.
- innerZipJoin(VertexRDD<U>, Function3<Object, VD, U, VD2>, ClassTag<U>, ClassTag<VD2>) - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- innerZipJoin(VertexRDD<U>, Function3<Object, VD, U, VD2>, ClassTag<U>, ClassTag<VD2>) - Method in class org.apache.spark.graphx.VertexRDD
-
Efficiently inner joins this VertexRDD with another VertexRDD sharing the same index.
- input() - Method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- INPUT() - Static method in class org.apache.spark.ui.ToolTips
-
- inputBytes() - Method in class org.apache.spark.ui.jobs.UIData.ExecutorSummary
-
- inputBytes() - Method in class org.apache.spark.ui.jobs.UIData.StageUIData
-
- inputCol() - Method in interface org.apache.spark.ml.param.HasInputCol
-
param for input column name
- inputDStream() - Method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- inputDStream() - Method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- InputDStream<T> - Class in org.apache.spark.streaming.dstream
-
This is the abstract base class for all input streams.
- InputDStream(StreamingContext, ClassTag<T>) - Constructor for class org.apache.spark.streaming.dstream.InputDStream
-
- inputFormatClazz() - Method in class org.apache.spark.scheduler.InputFormatInfo
-
- inputFormatClazz() - Method in class org.apache.spark.scheduler.SplitInfo
-
- InputFormatInfo - Class in org.apache.spark.scheduler
-
:: DeveloperApi ::
Parses and holds information about inputFormat (and files) specified as a parameter.
- InputFormatInfo(Configuration, Class<?>, String) - Constructor for class org.apache.spark.scheduler.InputFormatInfo
-
- inputMetrics() - Method in class org.apache.spark.storage.BlockResult
-
- inputMetricsFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
-
- inputMetricsToJson(InputMetrics) - Static method in class org.apache.spark.util.JsonProtocol
-
- inputProjection() - Method in class org.apache.spark.sql.hive.HiveUdafFunction
-
- inputSplit() - Method in class org.apache.spark.rdd.HadoopPartition
-
- inputSplitWithLocationInfo() - Method in class org.apache.spark.rdd.HadoopRDD.SplitInfoReflections
-
- inRepoTests() - Method in class org.apache.spark.sql.hive.test.TestHiveContext
-
- insertInto(String, boolean) - Method in interface org.apache.spark.sql.SchemaRDDLike
-
:: Experimental ::
Adds the rows from this RDD to the specified table, optionally overwriting the existing data.
- insertInto(String) - Method in interface org.apache.spark.sql.SchemaRDDLike
-
:: Experimental ::
Appends the rows from this RDD to the specified table.
- InsertIntoHiveTable - Class in org.apache.spark.sql.hive.execution
-
:: DeveloperApi ::
- InsertIntoHiveTable(MetastoreRelation, Map<String, Option<String>>, SparkPlan, boolean, HiveContext) - Constructor for class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- InsertIntoHiveTable - Class in org.apache.spark.sql.hive
-
A logical plan representing insertion into Hive table.
- InsertIntoHiveTable(LogicalPlan, Map<String, Option<String>>, LogicalPlan, boolean) - Constructor for class org.apache.spark.sql.hive.InsertIntoHiveTable
-
- InsertIntoParquetTable - Class in org.apache.spark.sql.parquet
-
:: DeveloperApi ::
Operator that acts as a sink for queries on RDDs and can be used to
store the output inside a directory of Parquet files.
- InsertIntoParquetTable(ParquetRelation, SparkPlan, boolean) - Constructor for class org.apache.spark.sql.parquet.InsertIntoParquetTable
-
- inShutdown() - Static method in class org.apache.spark.util.Utils
-
Detect whether this thread might be executing a shutdown hook.
- inspectorToDataType(ObjectInspector) - Method in interface org.apache.spark.sql.hive.HiveInspectors
-
- instance() - Method in class org.apache.spark.metrics.MetricsSystem
-
- instance() - Static method in class org.apache.spark.mllib.tree.impurity.Entropy
-
Get this impurity instance.
- instance() - Static method in class org.apache.spark.mllib.tree.impurity.Gini
-
Get this impurity instance.
- instance() - Static method in class org.apache.spark.mllib.tree.impurity.Variance
-
Get this impurity instance.
- INSTANCE_REGEX() - Method in class org.apache.spark.metrics.MetricsConfig
-
- INT - Class in org.apache.spark.sql.columnar
-
- INT() - Constructor for class org.apache.spark.sql.columnar.INT
-
- intAccumulator(int) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Create an
Accumulator
integer variable, which tasks can "add" values
to using the
add
method.
- intAccumulator(int, String) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Create an
Accumulator
integer variable, which tasks can "add" values
to using the
add
method.
- IntColumnAccessor - Class in org.apache.spark.sql.columnar
-
- IntColumnAccessor(ByteBuffer) - Constructor for class org.apache.spark.sql.columnar.IntColumnAccessor
-
- IntColumnBuilder - Class in org.apache.spark.sql.columnar
-
- IntColumnBuilder() - Constructor for class org.apache.spark.sql.columnar.IntColumnBuilder
-
- IntColumnStats - Class in org.apache.spark.sql.columnar
-
- IntColumnStats() - Constructor for class org.apache.spark.sql.columnar.IntColumnStats
-
- IntDelta - Class in org.apache.spark.sql.columnar.compression
-
- IntDelta() - Constructor for class org.apache.spark.sql.columnar.compression.IntDelta
-
- IntDelta.Decoder - Class in org.apache.spark.sql.columnar.compression
-
- IntDelta.Decoder(ByteBuffer, NativeColumnType<IntegerType$>) - Constructor for class org.apache.spark.sql.columnar.compression.IntDelta.Decoder
-
- IntDelta.Encoder - Class in org.apache.spark.sql.columnar.compression
-
- IntDelta.Encoder() - Constructor for class org.apache.spark.sql.columnar.compression.IntDelta.Encoder
-
- IntegerHashSetSerializer - Class in org.apache.spark.sql.execution
-
- IntegerHashSetSerializer() - Constructor for class org.apache.spark.sql.execution.IntegerHashSetSerializer
-
- IntegerType - Static variable in class org.apache.spark.sql.api.java.DataType
-
Gets the IntegerType object.
- IntegerType - Class in org.apache.spark.sql.api.java
-
The data type representing int and Integer values.
- INTER_JOB_WAIT_MS() - Static method in class org.apache.spark.ui.UIWorkloadGenerator
-
- intercept() - Method in class org.apache.spark.mllib.classification.LogisticRegressionModel
-
- intercept() - Method in class org.apache.spark.mllib.classification.SVMModel
-
- intercept() - Method in class org.apache.spark.mllib.regression.GeneralizedLinearModel
-
- intercept() - Method in class org.apache.spark.mllib.regression.LassoModel
-
- intercept() - Method in class org.apache.spark.mllib.regression.LinearRegressionModel
-
- intercept() - Method in class org.apache.spark.mllib.regression.RidgeRegressionModel
-
- internalMap() - Method in class org.apache.spark.util.TimeStampedHashSet
-
- InterruptibleIterator<T> - Class in org.apache.spark
-
:: DeveloperApi ::
An iterator that wraps around an existing iterator to provide task killing functionality.
- InterruptibleIterator(TaskContext, Iterator<T>) - Constructor for class org.apache.spark.InterruptibleIterator
-
- interruptThread() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.KillTask
-
- interruptThread() - Method in class org.apache.spark.scheduler.local.KillTask
-
- Intersect - Class in org.apache.spark.sql.execution
-
:: DeveloperApi ::
Returns the rows in left that also appear in right using the built in spark
intersection function.
- Intersect(SparkPlan, SparkPlan) - Constructor for class org.apache.spark.sql.execution.Intersect
-
- intersect(SchemaRDD) - Method in class org.apache.spark.sql.SchemaRDD
-
Performs a relational intersect on two SchemaRDDs
- intersection(JavaDoubleRDD) - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Return the intersection of this RDD and another one.
- intersection(JavaPairRDD<K, V>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Return the intersection of this RDD and another one.
- intersection(JavaRDD<T>) - Method in class org.apache.spark.api.java.JavaRDD
-
Return the intersection of this RDD and another one.
- intersection(RDD<T>) - Method in class org.apache.spark.rdd.RDD
-
Return the intersection of this RDD and another one.
- intersection(RDD<T>, Partitioner, Ordering<T>) - Method in class org.apache.spark.rdd.RDD
-
Return the intersection of this RDD and another one.
- intersection(RDD<T>, int) - Method in class org.apache.spark.rdd.RDD
-
Return the intersection of this RDD and another one.
- intersection(JavaSchemaRDD) - Method in class org.apache.spark.sql.api.java.JavaSchemaRDD
-
Return the intersection of this RDD and another one.
- intersection(JavaSchemaRDD, Partitioner) - Method in class org.apache.spark.sql.api.java.JavaSchemaRDD
-
Return the intersection of this RDD and another one.
- intersection(JavaSchemaRDD, int) - Method in class org.apache.spark.sql.api.java.JavaSchemaRDD
-
Return the intersection of this RDD and another one.
- intersection(RDD<Row>) - Method in class org.apache.spark.sql.SchemaRDD
-
- intersection(RDD<Row>, Partitioner, Ordering<Row>) - Method in class org.apache.spark.sql.SchemaRDD
-
- intersection(RDD<Row>, int) - Method in class org.apache.spark.sql.SchemaRDD
-
- Interval - Class in org.apache.spark.streaming
-
- Interval(Time, Time) - Constructor for class org.apache.spark.streaming.Interval
-
- Interval(long, long) - Constructor for class org.apache.spark.streaming.Interval
-
- INTERVAL_DEFAULT() - Static method in class org.apache.spark.util.logging.RollingFileAppender
-
- INTERVAL_PROPERTY() - Static method in class org.apache.spark.util.logging.RollingFileAppender
-
- IntParam - Class in org.apache.spark.ml.param
-
Specialized version of Param[Int
] for Java.
- IntParam(Params, String, String, Option<Object>) - Constructor for class org.apache.spark.ml.param.IntParam
-
- IntParam - Class in org.apache.spark.util
-
An extractor object for parsing strings into integers.
- IntParam() - Constructor for class org.apache.spark.util.IntParam
-
- intToIntWritable(int) - Static method in class org.apache.spark.SparkContext
-
- intWritableConverter() - Static method in class org.apache.spark.SparkContext
-
- invalidateCache(LogicalPlan) - Method in interface org.apache.spark.sql.CacheManager
-
Invalidates the cache of any data that contains plan
.
- invalidInformationGainStats() - Static method in class org.apache.spark.mllib.tree.model.InformationGainStats
-
An
InformationGainStats
object to
denote that current split doesn't satisfies minimum info gain or
minimum number of instances per node.
- invoke(Class<?>, Object, String, Seq<Tuple2<Class<?>, Object>>) - Static method in class org.apache.spark.util.Utils
-
- invokedMethod(Object, Class<?>, String) - Static method in class org.apache.spark.graphx.util.BytecodeUtils
-
Test whether the given closure invokes the specified method in the specified class.
- isActive(long) - Method in class org.apache.spark.graphx.impl.EdgePartition
-
Look up vid in activeSet, throwing an exception if it is None.
- isAkkaConf(String) - Static method in class org.apache.spark.SparkConf
-
Return whether the given config is an akka config (e.g.
- isAllowed(Enumeration.Value, Enumeration.Value) - Static method in class org.apache.spark.scheduler.TaskLocality
-
- isApplicationCompleteFile(String) - Static method in class org.apache.spark.scheduler.EventLoggingListener
-
- isAuthenticationEnabled() - Method in class org.apache.spark.SecurityManager
-
Check to see if authentication for the Spark communication protocols is enabled
- isAvailable() - Method in class org.apache.spark.scheduler.Stage
-
- isBindCollision(Throwable) - Static method in class org.apache.spark.util.Utils
-
Return whether the exception is caused by an address-port collision when binding.
- isBroadcast() - Method in class org.apache.spark.storage.BlockId
-
- isCached(String) - Method in interface org.apache.spark.sql.CacheManager
-
Returns true if the table is currently cached in-memory.
- isCached() - Method in class org.apache.spark.storage.BlockStatus
-
- isCached() - Method in class org.apache.spark.storage.RDDInfo
-
- isCancelled() - Method in class org.apache.spark.ComplexFutureAction
-
- isCancelled() - Method in interface org.apache.spark.FutureAction
-
Returns whether the action has been cancelled.
- isCancelled() - Method in class org.apache.spark.JavaFutureActionWrapper
-
- isCancelled() - Method in class org.apache.spark.SimpleFutureAction
-
- isCategorical(int) - Method in class org.apache.spark.mllib.tree.impl.DecisionTreeMetadata
-
- isCheckpointed() - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return whether this RDD has been checkpointed or not
- isCheckpointed() - Method in class org.apache.spark.rdd.RDD
-
Return whether this RDD has been checkpointed or not
- isCheckpointed() - Method in class org.apache.spark.rdd.RDDCheckpointData
-
- isCheckpointPresent() - Method in class org.apache.spark.streaming.StreamingContext
-
- isClassification() - Method in class org.apache.spark.mllib.tree.impl.DecisionTreeMetadata
-
- isCompleted() - Method in class org.apache.spark.ComplexFutureAction
-
- isCompleted() - Method in interface org.apache.spark.FutureAction
-
Returns whether the action has already been completed with a value or an exception.
- isCompleted() - Method in class org.apache.spark.SimpleFutureAction
-
- isCompleted() - Method in class org.apache.spark.TaskContext
-
Whether the task has completed.
- isCompleted() - Method in class org.apache.spark.TaskContextImpl
-
- isCompressionCodecFile(String) - Static method in class org.apache.spark.scheduler.EventLoggingListener
-
- isContainsNull() - Method in class org.apache.spark.sql.api.java.ArrayType
-
- isContinuous(int) - Method in class org.apache.spark.mllib.tree.impl.DecisionTreeMetadata
-
- isDefined(long) - Method in class org.apache.spark.graphx.impl.VertexPartitionBase
-
- isDone() - Method in class org.apache.spark.JavaFutureActionWrapper
-
- isDriver() - Method in class org.apache.spark.broadcast.BroadcastManager
-
- isDriver() - Method in class org.apache.spark.storage.BlockManagerId
-
- isEmpty() - Method in class org.apache.spark.rdd.PartitionCoalescer.LocationIterator
-
- isEventLogEnabled() - Method in class org.apache.spark.SparkContext
-
- isEventLogFile(String) - Static method in class org.apache.spark.scheduler.EventLoggingListener
-
- isExecutorAlive(String) - Method in class org.apache.spark.scheduler.TaskSchedulerImpl
-
- isExecutorStartupConf(String) - Static method in class org.apache.spark.SparkConf
-
Return whether the given config should be passed to an executor on start-up.
- isExtended() - Method in class org.apache.spark.sql.hive.execution.DescribeHiveTableCommand
-
- isFairScheduler() - Method in class org.apache.spark.ui.jobs.JobsTab
-
- isFairScheduler() - Method in class org.apache.spark.ui.jobs.StagesTab
-
- isFatalError(Throwable) - Static method in class org.apache.spark.util.Utils
-
Returns true if the given exception was fatal.
- isFinished(Protos.TaskState) - Method in class org.apache.spark.scheduler.cluster.mesos.MesosSchedulerBackend
-
Check whether a Mesos task state represents a finished task
- isFinished(Enumeration.Value) - Static method in class org.apache.spark.TaskState
-
- isFixed() - Method in class org.apache.spark.sql.api.java.DecimalType
-
- isInitialized() - Method in class org.apache.spark.streaming.dstream.DStream
-
- isInitialValueFinal() - Method in class org.apache.spark.partial.PartialResult
-
- isInMemory() - Method in class org.apache.spark.rdd.HadoopRDD.SplitInfoReflections
-
- isInterrupted() - Method in class org.apache.spark.TaskContext
-
Whether the task has been killed.
- isInterrupted() - Method in class org.apache.spark.TaskContextImpl
-
- isLazy() - Method in class org.apache.spark.sql.execution.CacheTableCommand
-
- isLeaf() - Method in class org.apache.spark.mllib.tree.model.Node
-
- isLeftChild(int) - Static method in class org.apache.spark.mllib.tree.model.Node
-
Returns true if this is a left child.
- isLocal() - Method in class org.apache.spark.api.java.JavaSparkContext
-
- isLocal() - Method in class org.apache.spark.SparkContext
-
- isLocal() - Method in class org.apache.spark.storage.BlockManagerMasterActor
-
- isLogManagerEnabled() - Method in class org.apache.spark.streaming.scheduler.ReceivedBlockTracker
-
Check if the log manager is enabled.
- isMac() - Static method in class org.apache.spark.util.Utils
-
Whether the underlying operating system is Mac OS X.
- isMulticlass() - Method in class org.apache.spark.mllib.tree.impl.DecisionTreeMetadata
-
- isMulticlassClassification() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- isMulticlassWithCategoricalFeatures() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- isMulticlassWithCategoricalFeatures() - Method in class org.apache.spark.mllib.tree.impl.DecisionTreeMetadata
-
- isMultipleOf(Duration) - Method in class org.apache.spark.streaming.Duration
-
- isMultipleOf(Duration) - Method in class org.apache.spark.streaming.Time
-
- isNullable() - Method in class org.apache.spark.sql.api.java.StructField
-
- isNullAt(int) - Method in class org.apache.spark.sql.api.java.Row
-
Returns true if value at column `i` is NULL.
- isOpen() - Method in class org.apache.spark.storage.BlockObjectWriter
-
- isOpen() - Method in class org.apache.spark.storage.DiskBlockObjectWriter
-
- isParquetBinaryAsString() - Method in interface org.apache.spark.sql.SQLConf
-
When set to true, we always treat byte arrays in Parquet files as strings.
- isPrimitiveType(DataType) - Static method in class org.apache.spark.sql.parquet.ParquetTypesConverter
-
- isRDD() - Method in class org.apache.spark.storage.BlockId
-
- isReady() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend
-
- isReady() - Method in interface org.apache.spark.scheduler.SchedulerBackend
-
- isReceiverStarted() - Method in class org.apache.spark.streaming.receiver.ReceiverSupervisor
-
Check if receiver has been marked for stopping
- isReceiverStopped() - Method in class org.apache.spark.streaming.receiver.ReceiverSupervisor
-
Check if receiver has been marked for stopping
- isRegistered() - Method in class org.apache.spark.scheduler.cluster.mesos.CoarseMesosSchedulerBackend
-
- isRegistered() - Method in class org.apache.spark.scheduler.cluster.mesos.MesosSchedulerBackend
-
- isRunningInYarnContainer(SparkConf) - Static method in class org.apache.spark.util.Utils
-
- isRunningLocally() - Method in class org.apache.spark.TaskContext
-
- isRunningLocally() - Method in class org.apache.spark.TaskContextImpl
-
- isSet(Param<?>) - Method in interface org.apache.spark.ml.param.Params
-
Checks whether a param is explicitly set.
- isShuffle() - Method in class org.apache.spark.storage.BlockId
-
- isShuffleMap() - Method in class org.apache.spark.scheduler.Stage
-
- isSparkPortConf(String) - Static method in class org.apache.spark.SparkConf
-
Return true if the given config matches either spark.*.port
or spark.port.*
.
- isSparkVersionFile(String) - Static method in class org.apache.spark.scheduler.EventLoggingListener
-
- isSplitable(JobContext, Path) - Method in class org.apache.spark.input.FixedLengthBinaryInputFormat
-
Override of isSplitable to ensure initial computation of the record length
- isStarted() - Method in class org.apache.spark.streaming.receiver.Receiver
-
Check if the receiver has started or not.
- isStopped() - Method in class org.apache.spark.SparkEnv
-
- isStopped() - Method in class org.apache.spark.streaming.receiver.Receiver
-
Check if receiver has been marked for stopping.
- isSymlink(File) - Static method in class org.apache.spark.util.Utils
-
Check to see if file is a symbolic link.
- isTesting() - Static method in class org.apache.spark.util.Utils
-
Indicates whether Spark is currently running unit tests.
- isTimeValid(Time) - Method in class org.apache.spark.streaming.dstream.DStream
-
Checks whether the 'time' is valid wrt slideDuration for generating RDD
- isTimeValid(Time) - Method in class org.apache.spark.streaming.dstream.InputDStream
-
Checks whether the 'time' is valid wrt slideDuration for generating RDD.
- isTraceEnabled() - Method in interface org.apache.spark.Logging
-
- isUDAFBridgeRequired() - Method in class org.apache.spark.sql.hive.HiveUdafFunction
-
- isUnlimited() - Method in class org.apache.spark.sql.api.java.DecimalType
-
- isUnordered(int) - Method in class org.apache.spark.mllib.tree.impl.DecisionTreeMetadata
-
- isValid() - Method in class org.apache.spark.broadcast.Broadcast
-
Whether this Broadcast is actually usable.
- isValid() - Method in class org.apache.spark.rdd.BlockRDD
-
Whether this BlockRDD is actually usable.
- isValid() - Method in class org.apache.spark.storage.StorageLevel
-
- isValueContainsNull() - Method in class org.apache.spark.sql.api.java.MapType
-
- isWindows() - Static method in class org.apache.spark.util.Utils
-
Whether the underlying operating system is Windows.
- isWorthCompressing(Encoder<T>) - Method in interface org.apache.spark.sql.columnar.compression.CompressibleColumnBuilder
-
- isZero() - Method in class org.apache.spark.streaming.Duration
-
- isZombie() - Method in class org.apache.spark.scheduler.TaskSetManager
-
- it() - Method in class org.apache.spark.rdd.PartitionCoalescer.LocationIterator
-
- item() - Method in class org.apache.spark.streaming.receiver.SingleItemData
-
- iterator(Partition, TaskContext) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Internal method to this RDD; will read from cache if applicable, or otherwise compute it.
- iterator() - Method in class org.apache.spark.graphx.impl.EdgePartition
-
Get an iterator over the edges in this partition.
- iterator() - Method in class org.apache.spark.graphx.impl.RoutingTablePartition
-
Returns an iterator over all vertex ids stored in this `RoutingTablePartition`.
- iterator() - Method in class org.apache.spark.graphx.impl.VertexAttributeBlock
-
- iterator() - Method in class org.apache.spark.graphx.impl.VertexPartitionBase
-
- iterator() - Method in class org.apache.spark.rdd.ParallelCollectionPartition
-
- iterator(Partition, TaskContext) - Method in class org.apache.spark.rdd.RDD
-
Internal method to this RDD; will read from cache if applicable, or otherwise compute it.
- iterator() - Method in class org.apache.spark.storage.IteratorValues
-
- iterator() - Method in class org.apache.spark.streaming.receiver.IteratorBlock
-
- iterator() - Method in class org.apache.spark.streaming.receiver.IteratorData
-
- iterator() - Method in class org.apache.spark.util.BoundedPriorityQueue
-
- iterator() - Method in class org.apache.spark.util.TimeStampedHashMap
-
- iterator() - Method in class org.apache.spark.util.TimeStampedHashSet
-
- iterator() - Method in class org.apache.spark.util.TimeStampedWeakValueHashMap
-
- IteratorBlock - Class in org.apache.spark.streaming.receiver
-
class representing a block received as an Iterator
- IteratorBlock(Iterator<Object>) - Constructor for class org.apache.spark.streaming.receiver.IteratorBlock
-
- IteratorData<T> - Class in org.apache.spark.streaming.receiver
-
- IteratorData(Iterator<T>) - Constructor for class org.apache.spark.streaming.receiver.IteratorData
-
- IteratorValues - Class in org.apache.spark.storage
-
- IteratorValues(Iterator<Object>) - Constructor for class org.apache.spark.storage.IteratorValues
-
- main(String[]) - Static method in class org.apache.spark.examples.streaming.JavaKinesisWordCountASL
-
- main(String[]) - Static method in class org.apache.spark.examples.streaming.KinesisWordCountASL
-
- main(String[]) - Static method in class org.apache.spark.examples.streaming.KinesisWordCountProducerASL
-
- main(String[]) - Static method in class org.apache.spark.mllib.util.KMeansDataGenerator
-
- main(String[]) - Static method in class org.apache.spark.mllib.util.LinearDataGenerator
-
- main(String[]) - Static method in class org.apache.spark.mllib.util.LogisticRegressionDataGenerator
-
- main(String[]) - Static method in class org.apache.spark.mllib.util.MFDataGenerator
-
- main(String[]) - Static method in class org.apache.spark.mllib.util.SVMDataGenerator
-
- main(String[]) - Static method in class org.apache.spark.rdd.CheckpointRDD
-
- main(String[]) - Static method in class org.apache.spark.streaming.util.RawTextSender
-
- main(String[]) - Static method in class org.apache.spark.streaming.util.RecurringTimer
-
- main(String[]) - Static method in class org.apache.spark.ui.UIWorkloadGenerator
-
- main(String[]) - Static method in class org.apache.spark.util.random.XORShiftRandom
-
Main method for running benchmark
- makeBinarySearch(Ordering<K>, ClassTag<K>) - Static method in class org.apache.spark.util.CollectionsUtils
-
- makeCopy(Object[]) - Method in class org.apache.spark.sql.execution.SparkPlan
-
Overridden make copy also propogates sqlContext to copied plan.
- makeDriverRef(String, SparkConf, ActorSystem) - Static method in class org.apache.spark.util.AkkaUtils
-
- makeExecutorRef(String, SparkConf, String, int, ActorSystem) - Static method in class org.apache.spark.util.AkkaUtils
-
- makeOffers() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend.DriverActor
-
- makeOffers(String) - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend.DriverActor
-
- makeProgressBar(int, int, int, int, int) - Static method in class org.apache.spark.ui.UIUtils
-
- makeRDD(Seq<T>, int, ClassTag<T>) - Method in class org.apache.spark.SparkContext
-
Distribute a local Scala collection to form an RDD.
- makeRDD(Seq<Tuple2<T, Seq<String>>>, ClassTag<T>) - Method in class org.apache.spark.SparkContext
-
Distribute a local Scala collection to form an RDD, with one or more
location preferences (hostnames of Spark nodes) for each object.
- makeRDDForPartitionedTable(Seq<Partition>) - Method in class org.apache.spark.sql.hive.HadoopTableReader
-
- makeRDDForPartitionedTable(Map<Partition, Class<? extends Deserializer>>, Option<PathFilter>) - Method in class org.apache.spark.sql.hive.HadoopTableReader
-
Create a HadoopRDD for every partition key specified in the query.
- makeRDDForPartitionedTable(Seq<Partition>) - Method in interface org.apache.spark.sql.hive.TableReader
-
- makeRDDForTable(Table) - Method in class org.apache.spark.sql.hive.HadoopTableReader
-
- makeRDDForTable(Table, Class<? extends Deserializer>, Option<PathFilter>) - Method in class org.apache.spark.sql.hive.HadoopTableReader
-
Creates a Hadoop RDD to read data from the target table's data directory.
- makeRDDForTable(Table) - Method in interface org.apache.spark.sql.hive.TableReader
-
- ManualClock - Class in org.apache.spark.streaming.util
-
- ManualClock() - Constructor for class org.apache.spark.streaming.util.ManualClock
-
- map(Function<T, R>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return a new RDD by applying a function to all elements of this RDD.
- map(Function1<Edge<ED>, ED2>, ClassTag<ED2>) - Method in class org.apache.spark.graphx.impl.EdgePartition
-
Construct a new edge partition by applying the function f to all
edges in this partition.
- map(Iterator<ED2>, ClassTag<ED2>) - Method in class org.apache.spark.graphx.impl.EdgePartition
-
Construct a new edge partition by using the edge attributes
contained in the iterator.
- map(Function2<Object, VD, VD2>, ClassTag<VD2>) - Method in class org.apache.spark.graphx.impl.VertexPartitionBaseOps
-
Pass each vertex attribute along with the vertex id through a map
function and retain the original RDD's partitioning and index.
- map(Function1<R, T>) - Method in class org.apache.spark.partial.PartialResult
-
Transform this PartialResult into a PartialResult of type T.
- map(Function1<T, U>, ClassTag<U>) - Method in class org.apache.spark.rdd.RDD
-
Return a new RDD by applying a function to all elements of this RDD.
- map(Function<T, R>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Return a new DStream by applying a function to all elements of this DStream.
- map(Function1<T, U>, ClassTag<U>) - Method in class org.apache.spark.streaming.dstream.DStream
-
Return a new DStream by applying a function to all elements of this DStream.
- MAP_KEY_SCHEMA_NAME() - Static method in class org.apache.spark.sql.parquet.CatalystConverter
-
- MAP_OUTPUT_TRACKER() - Static method in class org.apache.spark.util.MetadataCleanerType
-
- MAP_SCHEMA_NAME() - Static method in class org.apache.spark.sql.parquet.CatalystConverter
-
- MAP_VALUE_SCHEMA_NAME() - Static method in class org.apache.spark.sql.parquet.CatalystConverter
-
- mapAsSerializableJavaMap(Map<A, B>) - Static method in class org.apache.spark.api.java.JavaUtils
-
- mapEdgePartitions(Function2<Object, EdgePartition<ED, VD>, EdgePartition<ED2, VD2>>, ClassTag<ED2>, ClassTag<VD2>) - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- mapEdges(Function1<Edge<ED>, ED2>, ClassTag<ED2>) - Method in class org.apache.spark.graphx.Graph
-
Transforms each edge attribute in the graph using the map function.
- mapEdges(Function2<Object, Iterator<Edge<ED>>, Iterator<ED2>>, ClassTag<ED2>) - Method in class org.apache.spark.graphx.Graph
-
Transforms each edge attribute using the map function, passing it a whole partition at a
time.
- mapEdges(Function2<Object, Iterator<Edge<ED>>, Iterator<ED2>>, ClassTag<ED2>) - Method in class org.apache.spark.graphx.impl.GraphImpl
-
- mapFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
-
-------------------------------- *
Util JSON deserialization methods |
---------------------------------
- mapId() - Method in class org.apache.spark.FetchFailed
-
- mapId() - Method in class org.apache.spark.storage.ShuffleBlockId
-
- mapId() - Method in class org.apache.spark.storage.ShuffleDataBlockId
-
- mapId() - Method in class org.apache.spark.storage.ShuffleIndexBlockId
-
- MapOutputTracker - Class in org.apache.spark
-
Class that keeps track of the location of the map output of
a stage.
- MapOutputTracker(SparkConf) - Constructor for class org.apache.spark.MapOutputTracker
-
- mapOutputTracker() - Method in class org.apache.spark.scheduler.TaskSchedulerImpl
-
- mapOutputTracker() - Method in class org.apache.spark.SparkEnv
-
- MapOutputTrackerMaster - Class in org.apache.spark
-
MapOutputTracker for the driver.
- MapOutputTrackerMaster(SparkConf) - Constructor for class org.apache.spark.MapOutputTrackerMaster
-
- MapOutputTrackerMasterActor - Class in org.apache.spark
-
Actor class for MapOutputTrackerMaster
- MapOutputTrackerMasterActor(MapOutputTrackerMaster, SparkConf) - Constructor for class org.apache.spark.MapOutputTrackerMasterActor
-
- MapOutputTrackerMessage - Interface in org.apache.spark
-
- MapOutputTrackerWorker - Class in org.apache.spark
-
MapOutputTracker for the executors, which fetches map output information from the driver's
MapOutputTrackerMaster.
- MapOutputTrackerWorker(SparkConf) - Constructor for class org.apache.spark.MapOutputTrackerWorker
-
- MapPartitionedDStream<T,U> - Class in org.apache.spark.streaming.dstream
-
- MapPartitionedDStream(DStream<T>, Function1<Iterator<T>, Iterator<U>>, boolean, ClassTag<T>, ClassTag<U>) - Constructor for class org.apache.spark.streaming.dstream.MapPartitionedDStream
-
- mapPartitions(FlatMapFunction<Iterator<T>, U>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return a new RDD by applying a function to each partition of this RDD.
- mapPartitions(FlatMapFunction<Iterator<T>, U>, boolean) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return a new RDD by applying a function to each partition of this RDD.
- mapPartitions(Function1<Iterator<T>, Iterator<U>>, boolean, ClassTag<U>) - Method in class org.apache.spark.rdd.RDD
-
Return a new RDD by applying a function to each partition of this RDD.
- mapPartitions(FlatMapFunction<Iterator<T>, U>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Return a new DStream in which each RDD is generated by applying mapPartitions() to each RDDs
of this DStream.
- mapPartitions(Function1<Iterator<T>, Iterator<U>>, boolean, ClassTag<U>) - Method in class org.apache.spark.streaming.dstream.DStream
-
Return a new DStream in which each RDD is generated by applying mapPartitions() to each RDDs
of this DStream.
- MapPartitionsRDD<U,T> - Class in org.apache.spark.rdd
-
- MapPartitionsRDD(RDD<T>, Function3<TaskContext, Object, Iterator<T>, Iterator<U>>, boolean, ClassTag<U>, ClassTag<T>) - Constructor for class org.apache.spark.rdd.MapPartitionsRDD
-
- mapPartitionsToDouble(DoubleFlatMapFunction<Iterator<T>>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return a new RDD by applying a function to each partition of this RDD.
- mapPartitionsToDouble(DoubleFlatMapFunction<Iterator<T>>, boolean) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return a new RDD by applying a function to each partition of this RDD.
- mapPartitionsToPair(PairFlatMapFunction<Iterator<T>, K2, V2>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return a new RDD by applying a function to each partition of this RDD.
- mapPartitionsToPair(PairFlatMapFunction<Iterator<T>, K2, V2>, boolean) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return a new RDD by applying a function to each partition of this RDD.
- mapPartitionsToPair(PairFlatMapFunction<Iterator<T>, K2, V2>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Return a new DStream in which each RDD is generated by applying mapPartitions() to each RDDs
of this DStream.
- mapPartitionsWithContext(Function2<TaskContext, Iterator<T>, Iterator<U>>, boolean, ClassTag<U>) - Method in class org.apache.spark.rdd.RDD
-
:: DeveloperApi ::
Return a new RDD by applying a function to each partition of this RDD.
- mapPartitionsWithIndex(Function2<Integer, Iterator<T>, Iterator<R>>, boolean) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return a new RDD by applying a function to each partition of this RDD, while tracking the index
of the original partition.
- mapPartitionsWithIndex(Function2<Object, Iterator<T>, Iterator<U>>, boolean, ClassTag<U>) - Method in class org.apache.spark.rdd.RDD
-
Return a new RDD by applying a function to each partition of this RDD, while tracking the index
of the original partition.
- mapPartitionsWithInputSplit(Function2<InputSplit, Iterator<Tuple2<K, V>>, Iterator<R>>, boolean) - Method in class org.apache.spark.api.java.JavaHadoopRDD
-
Maps over a partition, providing the InputSplit that was used as the base of the partition.
- mapPartitionsWithInputSplit(Function2<InputSplit, Iterator<Tuple2<K, V>>, Iterator<R>>, boolean) - Method in class org.apache.spark.api.java.JavaNewHadoopRDD
-
Maps over a partition, providing the InputSplit that was used as the base of the partition.
- mapPartitionsWithInputSplit(Function2<InputSplit, Iterator<Tuple2<K, V>>, Iterator<U>>, boolean, ClassTag<U>) - Method in class org.apache.spark.rdd.HadoopRDD
-
Maps over a partition, providing the InputSplit that was used as the base of the partition.
- mapPartitionsWithInputSplit(Function2<InputSplit, Iterator<Tuple2<K, V>>, Iterator<U>>, boolean, ClassTag<U>) - Method in class org.apache.spark.rdd.NewHadoopRDD
-
Maps over a partition, providing the InputSplit that was used as the base of the partition.
- mapPartitionsWithSplit(Function2<Object, Iterator<T>, Iterator<U>>, boolean, ClassTag<U>) - Method in class org.apache.spark.rdd.RDD
-
Return a new RDD by applying a function to each partition of this RDD, while tracking the index
of the original partition.
- MappedDStream<T,U> - Class in org.apache.spark.streaming.dstream
-
- MappedDStream(DStream<T>, Function1<T, U>, ClassTag<T>, ClassTag<U>) - Constructor for class org.apache.spark.streaming.dstream.MappedDStream
-
- MappedRDD<U,T> - Class in org.apache.spark.rdd
-
- MappedRDD(RDD<T>, Function1<T, U>, ClassTag<U>, ClassTag<T>) - Constructor for class org.apache.spark.rdd.MappedRDD
-
- MappedValuesRDD<K,V,U> - Class in org.apache.spark.rdd
-
- MappedValuesRDD(RDD<? extends Product2<K, V>>, Function1<V, U>) - Constructor for class org.apache.spark.rdd.MappedValuesRDD
-
- mapper() - Method in class org.apache.spark.metrics.sink.MetricsServlet
-
- MAPRED_REDUCE_TASKS() - Method in class org.apache.spark.sql.SQLConf.Deprecated$
-
- mapredInputFormat() - Method in class org.apache.spark.scheduler.InputFormatInfo
-
- mapreduceInputFormat() - Method in class org.apache.spark.scheduler.InputFormatInfo
-
- mapReduceTriplets(Function1<EdgeTriplet<VD, ED>, Iterator<Tuple2<Object, A>>>, Function2<A, A, A>, Option<Tuple2<VertexRDD<?>, EdgeDirection>>, ClassTag<A>) - Method in class org.apache.spark.graphx.Graph
-
Aggregates values from the neighboring edges and vertices of each vertex.
- mapReduceTriplets(Function1<EdgeTriplet<VD, ED>, Iterator<Tuple2<Object, A>>>, Function2<A, A, A>, Option<Tuple2<VertexRDD<?>, EdgeDirection>>, ClassTag<A>) - Method in class org.apache.spark.graphx.impl.GraphImpl
-
- mapSideCombine() - Method in class org.apache.spark.ShuffleDependency
-
- MapStatus - Interface in org.apache.spark.scheduler
-
Result returned by a ShuffleMapTask to a scheduler.
- mapToDouble(DoubleFunction<T>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return a new RDD by applying a function to all elements of this RDD.
- mapToJson(Map<String, String>) - Static method in class org.apache.spark.util.JsonProtocol
-
------------------------------ *
Util JSON serialization methods |
-------------------------------
- mapToPair(PairFunction<T, K2, V2>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return a new RDD by applying a function to all elements of this RDD.
- mapToPair(PairFunction<T, K2, V2>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Return a new DStream by applying a function to all elements of this DStream.
- mapTriplets(Function1<EdgeTriplet<VD, ED>, ED2>, ClassTag<ED2>) - Method in class org.apache.spark.graphx.Graph
-
Transforms each edge attribute using the map function, passing it the adjacent vertex
attributes as well.
- mapTriplets(Function1<EdgeTriplet<VD, ED>, ED2>, TripletFields, ClassTag<ED2>) - Method in class org.apache.spark.graphx.Graph
-
Transforms each edge attribute using the map function, passing it the adjacent vertex
attributes as well.
- mapTriplets(Function2<Object, Iterator<EdgeTriplet<VD, ED>>, Iterator<ED2>>, TripletFields, ClassTag<ED2>) - Method in class org.apache.spark.graphx.Graph
-
Transforms each edge attribute a partition at a time using the map function, passing it the
adjacent vertex attributes as well.
- mapTriplets(Function2<Object, Iterator<EdgeTriplet<VD, ED>>, Iterator<ED2>>, TripletFields, ClassTag<ED2>) - Method in class org.apache.spark.graphx.impl.GraphImpl
-
- MapType - Class in org.apache.spark.sql.api.java
-
The data type representing Maps.
- MapValuedDStream<K,V,U> - Class in org.apache.spark.streaming.dstream
-
- MapValuedDStream(DStream<Tuple2<K, V>>, Function1<V, U>, ClassTag<K>, ClassTag<V>, ClassTag<U>) - Constructor for class org.apache.spark.streaming.dstream.MapValuedDStream
-
- mapValues(Function<V, U>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Pass each value in the key-value pair RDD through a map function without changing the keys;
this also retains the original RDD's partitioning.
- mapValues(Function1<Edge<ED>, ED2>, ClassTag<ED2>) - Method in class org.apache.spark.graphx.EdgeRDD
-
Map the values in an edge partitioning preserving the structure but changing the values.
- mapValues(Function1<Edge<ED>, ED2>, ClassTag<ED2>) - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- mapValues(Function1<VD, VD2>, ClassTag<VD2>) - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- mapValues(Function2<Object, VD, VD2>, ClassTag<VD2>) - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- mapValues(Function1<VD, VD2>, ClassTag<VD2>) - Method in class org.apache.spark.graphx.VertexRDD
-
Maps each vertex attribute, preserving the index.
- mapValues(Function2<Object, VD, VD2>, ClassTag<VD2>) - Method in class org.apache.spark.graphx.VertexRDD
-
Maps each vertex attribute, additionally supplying the vertex ID.
- mapValues(Function1<V, U>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Pass each value in the key-value pair RDD through a map function without changing the keys;
this also retains the original RDD's partitioning.
- mapValues(Function<V, U>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying a map function to the value of each key-value pairs in
'this' DStream without changing the key.
- mapValues(Function1<V, U>, ClassTag<U>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying a map function to the value of each key-value pairs in
'this' DStream without changing the key.
- mapVertexPartitions(Function1<ShippableVertexPartition<VD>, ShippableVertexPartition<VD2>>, ClassTag<VD2>) - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- mapVertexPartitions(Function1<ShippableVertexPartition<VD>, ShippableVertexPartition<VD2>>, ClassTag<VD2>) - Method in class org.apache.spark.graphx.VertexRDD
-
Applies a function to each VertexPartition
of this RDD and returns a new VertexRDD.
- mapVertices(Function2<Object, VD, VD2>, ClassTag<VD2>, Predef.$eq$colon$eq<VD, VD2>) - Method in class org.apache.spark.graphx.Graph
-
Transforms each vertex attribute in the graph using the map function.
- mapVertices(Function2<Object, VD, VD2>, ClassTag<VD2>, Predef.$eq$colon$eq<VD, VD2>) - Method in class org.apache.spark.graphx.impl.GraphImpl
-
- mapWith(Function1<Object, A>, boolean, Function2<T, A, U>, ClassTag<U>) - Method in class org.apache.spark.rdd.RDD
-
Maps f over this RDD, where f takes an additional parameter of type A.
- markCheckpointed(RDD<?>) - Method in class org.apache.spark.rdd.RDD
-
Changes the dependencies of this RDD from its original parents to a new RDD (newRDD
)
created from the checkpoint file, and forget its old dependencies and partitions.
- MarkedForCheckpoint() - Static method in class org.apache.spark.rdd.CheckpointState
-
- markFailed(long) - Method in class org.apache.spark.scheduler.TaskInfo
-
- markFailure() - Method in class org.apache.spark.storage.BlockInfo
-
Mark this BlockInfo as ready but failed
- markForCheckpoint() - Method in class org.apache.spark.rdd.RDDCheckpointData
-
- markGettingResult(long) - Method in class org.apache.spark.scheduler.TaskInfo
-
- markInterrupted() - Method in class org.apache.spark.TaskContextImpl
-
Marks the task for interruption, i.e.
- markPartiallyConstructed(SparkContext, boolean) - Static method in class org.apache.spark.SparkContext
-
Called at the beginning of the SparkContext constructor to ensure that no SparkContext is
running.
- markReady(long) - Method in class org.apache.spark.storage.BlockInfo
-
Mark this BlockInfo as ready (i.e.
- markSuccessful(long) - Method in class org.apache.spark.scheduler.TaskInfo
-
- markTaskCompleted() - Method in class org.apache.spark.TaskContextImpl
-
Marks the task as completed and triggers the listeners.
- mask(Graph<VD2, ED2>, ClassTag<VD2>, ClassTag<ED2>) - Method in class org.apache.spark.graphx.Graph
-
Restricts the graph to only the vertices and edges that are also in other
, but keeps the
attributes from this graph.
- mask(Graph<VD2, ED2>, ClassTag<VD2>, ClassTag<ED2>) - Method in class org.apache.spark.graphx.impl.GraphImpl
-
- mask() - Method in class org.apache.spark.graphx.impl.ShippableVertexPartition
-
- mask() - Method in class org.apache.spark.graphx.impl.VertexPartition
-
- mask() - Method in class org.apache.spark.graphx.impl.VertexPartitionBase
-
- master() - Method in class org.apache.spark.api.java.JavaSparkContext
-
- master() - Method in class org.apache.spark.SparkContext
-
- master() - Method in class org.apache.spark.storage.BlockManager
-
- master() - Method in class org.apache.spark.storage.TachyonBlockManager
-
- master() - Method in class org.apache.spark.streaming.Checkpoint
-
- Matrices - Class in org.apache.spark.mllib.linalg
-
- Matrices() - Constructor for class org.apache.spark.mllib.linalg.Matrices
-
- Matrix - Interface in org.apache.spark.mllib.linalg
-
Trait for a local matrix.
- MatrixEntry - Class in org.apache.spark.mllib.linalg.distributed
-
:: Experimental ::
Represents an entry in an distributed matrix.
- MatrixEntry(long, long, double) - Constructor for class org.apache.spark.mllib.linalg.distributed.MatrixEntry
-
- MatrixFactorizationModel - Class in org.apache.spark.mllib.recommendation
-
Model representing the result of matrix factorization.
- MatrixFactorizationModel(int, RDD<Tuple2<Object, double[]>>, RDD<Tuple2<Object, double[]>>) - Constructor for class org.apache.spark.mllib.recommendation.MatrixFactorizationModel
-
- max(Comparator<T>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Returns the maximum element from this RDD as defined by the specified
Comparator[T].
- max() - Method in class org.apache.spark.mllib.stat.MultivariateOnlineSummarizer
-
- max() - Method in interface org.apache.spark.mllib.stat.MultivariateStatisticalSummary
-
Maximum value of each column.
- max(Ordering<T>) - Method in class org.apache.spark.rdd.RDD
-
Returns the max of this RDD as defined by the implicit Ordering[T].
- MAX() - Static method in class org.apache.spark.sql.hive.HiveQl
-
- max(Duration) - Method in class org.apache.spark.streaming.Duration
-
- max(Time) - Method in class org.apache.spark.streaming.Time
-
- max(long, long) - Static method in class org.apache.spark.streaming.util.RawTextHelper
-
- max() - Method in class org.apache.spark.util.StatCounter
-
- MAX_ATTEMPTS() - Method in class org.apache.spark.streaming.CheckpointWriter
-
- MAX_DICT_SIZE() - Static method in class org.apache.spark.sql.columnar.compression.DictionaryEncoding
-
- MAX_SLAVE_FAILURES() - Method in class org.apache.spark.scheduler.cluster.mesos.CoarseMesosSchedulerBackend
-
- maxAkkaFrameSize() - Method in class org.apache.spark.MapOutputTrackerMasterActor
-
- maxBatchSize() - Method in class org.apache.spark.streaming.flume.FlumePollingInputDStream
-
- maxBins() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- maxBins() - Method in class org.apache.spark.mllib.tree.impl.DecisionTreeMetadata
-
- maxCores() - Method in class org.apache.spark.scheduler.cluster.mesos.CoarseMesosSchedulerBackend
-
- maxCores() - Method in class org.apache.spark.scheduler.cluster.SimrSchedulerBackend
-
- maxCores() - Method in class org.apache.spark.scheduler.cluster.SparkDeploySchedulerBackend
-
- maxDepth() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- maxDepth() - Method in class org.apache.spark.mllib.tree.impl.DecisionTreeMetadata
-
- maxFrameSizeBytes(SparkConf) - Static method in class org.apache.spark.util.AkkaUtils
-
Returns the configured max frame size for Akka messages in bytes.
- maxIter() - Method in interface org.apache.spark.ml.param.HasMaxIter
-
param for max number of iterations
- maxIters() - Method in class org.apache.spark.graphx.lib.SVDPlusPlus.Conf
-
- maxMem() - Method in class org.apache.spark.scheduler.SparkListenerBlockManagerAdded
-
- maxMem() - Method in class org.apache.spark.storage.BlockManagerInfo
-
- maxMem() - Method in class org.apache.spark.storage.StorageStatus
-
- maxMemory() - Method in class org.apache.spark.ui.exec.ExecutorSummaryInfo
-
- maxMemoryInMB() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- maxMemSize() - Method in class org.apache.spark.storage.BlockManagerMessages.RegisterBlockManager
-
- maxNodesInLevel(int) - Static method in class org.apache.spark.mllib.tree.model.Node
-
Return the maximum number of nodes which can be in the given level of the tree.
- maxRegisteredWaitingTime() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend
-
- maxResultSize() - Method in class org.apache.spark.scheduler.TaskSetManager
-
- maxTaskFailures() - Method in class org.apache.spark.scheduler.TaskSchedulerImpl
-
- maxTaskFailures() - Method in class org.apache.spark.scheduler.TaskSetManager
-
- maxVal() - Method in class org.apache.spark.graphx.lib.SVDPlusPlus.Conf
-
- mean() - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Compute the mean of this RDD's elements.
- mean() - Method in class org.apache.spark.mllib.feature.StandardScalerModel
-
- mean() - Method in class org.apache.spark.mllib.random.PoissonGenerator
-
- mean() - Method in class org.apache.spark.mllib.stat.MultivariateOnlineSummarizer
-
- mean() - Method in interface org.apache.spark.mllib.stat.MultivariateStatisticalSummary
-
Sample mean vector.
- mean() - Method in class org.apache.spark.partial.BoundedDouble
-
- mean() - Method in class org.apache.spark.rdd.DoubleRDDFunctions
-
Compute the mean of this RDD's elements.
- mean() - Method in class org.apache.spark.util.StatCounter
-
- meanAbsoluteError() - Method in class org.apache.spark.mllib.evaluation.RegressionMetrics
-
Returns the mean absolute error, which is a risk function corresponding to the
expected value of the absolute error loss or l1-norm loss.
- meanApprox(long, Double) - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Return the approximate mean of the elements in this RDD.
- meanApprox(long) - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
:: Experimental ::
Approximate operation to return the mean within a timeout.
- meanApprox(long, double) - Method in class org.apache.spark.rdd.DoubleRDDFunctions
-
:: Experimental ::
Approximate operation to return the mean within a timeout.
- meanAveragePrecision() - Method in class org.apache.spark.mllib.evaluation.RankingMetrics
-
Returns the mean average precision (MAP) of all the queries.
- MeanEvaluator - Class in org.apache.spark.partial
-
An ApproximateEvaluator for means.
- MeanEvaluator(int, double) - Constructor for class org.apache.spark.partial.MeanEvaluator
-
- meanSquaredError() - Method in class org.apache.spark.mllib.evaluation.RegressionMetrics
-
Returns the mean squared error, which is a risk function corresponding to the
expected value of the squared error loss or quadratic loss.
- megabytesToString(long) - Static method in class org.apache.spark.util.Utils
-
Convert a quantity in megabytes to a human-readable string such as "4.0 MB".
- MEMORY_AND_DISK - Static variable in class org.apache.spark.api.java.StorageLevels
-
- MEMORY_AND_DISK() - Static method in class org.apache.spark.storage.StorageLevel
-
- MEMORY_AND_DISK_2 - Static variable in class org.apache.spark.api.java.StorageLevels
-
- MEMORY_AND_DISK_2() - Static method in class org.apache.spark.storage.StorageLevel
-
- MEMORY_AND_DISK_SER - Static variable in class org.apache.spark.api.java.StorageLevels
-
- MEMORY_AND_DISK_SER() - Static method in class org.apache.spark.storage.StorageLevel
-
- MEMORY_AND_DISK_SER_2 - Static variable in class org.apache.spark.api.java.StorageLevels
-
- MEMORY_AND_DISK_SER_2() - Static method in class org.apache.spark.storage.StorageLevel
-
- MEMORY_ONLY - Static variable in class org.apache.spark.api.java.StorageLevels
-
- MEMORY_ONLY() - Static method in class org.apache.spark.storage.StorageLevel
-
- MEMORY_ONLY_2 - Static variable in class org.apache.spark.api.java.StorageLevels
-
- MEMORY_ONLY_2() - Static method in class org.apache.spark.storage.StorageLevel
-
- MEMORY_ONLY_SER - Static variable in class org.apache.spark.api.java.StorageLevels
-
- MEMORY_ONLY_SER() - Static method in class org.apache.spark.storage.StorageLevel
-
- MEMORY_ONLY_SER_2 - Static variable in class org.apache.spark.api.java.StorageLevels
-
- MEMORY_ONLY_SER_2() - Static method in class org.apache.spark.storage.StorageLevel
-
- memoryBytesSpilled() - Method in class org.apache.spark.ui.jobs.UIData.ExecutorSummary
-
- memoryBytesSpilled() - Method in class org.apache.spark.ui.jobs.UIData.StageUIData
-
- MemoryEntry - Class in org.apache.spark.storage
-
- MemoryEntry(Object, long, boolean) - Constructor for class org.apache.spark.storage.MemoryEntry
-
- MemoryParam - Class in org.apache.spark.util
-
An extractor object for parsing JVM memory strings, such as "10g", into an Int representing
the number of megabytes.
- MemoryParam() - Constructor for class org.apache.spark.util.MemoryParam
-
- memoryStore() - Method in class org.apache.spark.storage.BlockManager
-
- MemoryStore - Class in org.apache.spark.storage
-
Stores blocks in memory, either as Arrays of deserialized Java objects or as
serialized ByteBuffers.
- MemoryStore(BlockManager, long) - Constructor for class org.apache.spark.storage.MemoryStore
-
- memoryStringToMb(String) - Static method in class org.apache.spark.util.Utils
-
Convert a Java memory parameter passed to -Xmx (such as 300m or 1g) to a number of megabytes.
- memoryUsed() - Method in class org.apache.spark.ui.exec.ExecutorSummaryInfo
-
- MemoryUtils - Class in org.apache.spark.scheduler.cluster.mesos
-
- MemoryUtils() - Constructor for class org.apache.spark.scheduler.cluster.mesos.MemoryUtils
-
- memRemaining() - Method in class org.apache.spark.storage.StorageStatus
-
Return the memory remaining in this block manager.
- memSize() - Method in class org.apache.spark.storage.BlockManagerMessages.UpdateBlockInfo
-
- memSize() - Method in class org.apache.spark.storage.BlockStatus
-
- memSize() - Method in class org.apache.spark.storage.RDDInfo
-
- memUsed() - Method in class org.apache.spark.storage.StorageStatus
-
Return the memory used by this block manager.
- memUsedByRdd(int) - Method in class org.apache.spark.storage.StorageStatus
-
Return the memory used by the given RDD in this block manager in O(1) time.
- merge(R) - Method in class org.apache.spark.Accumulable
-
Merge two accumulable objects together
- merge(IDF.DocumentFrequencyAggregator) - Method in class org.apache.spark.mllib.feature.IDF.DocumentFrequencyAggregator
-
Merges another.
- merge(MultivariateOnlineSummarizer) - Method in class org.apache.spark.mllib.stat.MultivariateOnlineSummarizer
-
Merge another MultivariateOnlineSummarizer, and update the statistical summary.
- merge(DTStatsAggregator) - Method in class org.apache.spark.mllib.tree.impl.DTStatsAggregator
-
Merge this aggregator with another, and returns this aggregator.
- merge(double[], int, int) - Method in class org.apache.spark.mllib.tree.impurity.ImpurityAggregator
-
Merge the stats from one bin into another.
- merge(int, U) - Method in interface org.apache.spark.partial.ApproximateEvaluator
-
- merge(int, long) - Method in class org.apache.spark.partial.CountEvaluator
-
- merge(int, OpenHashMap<T, Object>) - Method in class org.apache.spark.partial.GroupedCountEvaluator
-
- merge(int, HashMap<T, StatCounter>) - Method in class org.apache.spark.partial.GroupedMeanEvaluator
-
- merge(int, HashMap<T, StatCounter>) - Method in class org.apache.spark.partial.GroupedSumEvaluator
-
- merge(int, StatCounter) - Method in class org.apache.spark.partial.MeanEvaluator
-
- merge(int, StatCounter) - Method in class org.apache.spark.partial.SumEvaluator
-
- merge(Option<AcceptanceResult>) - Method in class org.apache.spark.util.random.AcceptanceResult
-
- merge(double) - Method in class org.apache.spark.util.StatCounter
-
Add a value into this StatCounter, updating the internal statistics.
- merge(TraversableOnce<Object>) - Method in class org.apache.spark.util.StatCounter
-
Add multiple values into this StatCounter, updating the internal statistics.
- merge(StatCounter) - Method in class org.apache.spark.util.StatCounter
-
Merge another StatCounter into this one, adding up the internal statistics.
- mergeCombiners() - Method in class org.apache.spark.Aggregator
-
- mergeForFeature(int, int, int) - Method in class org.apache.spark.mllib.tree.impl.DTStatsAggregator
-
For a given feature, merge the stats for two bins.
- mergeValue() - Method in class org.apache.spark.Aggregator
-
- MesosSchedulerBackend - Class in org.apache.spark.scheduler.cluster.mesos
-
A SchedulerBackend for running fine-grained tasks on Mesos.
- MesosSchedulerBackend(TaskSchedulerImpl, SparkContext, String) - Constructor for class org.apache.spark.scheduler.cluster.mesos.MesosSchedulerBackend
-
- message() - Method in class org.apache.spark.FetchFailed
-
- message() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterExecutorFailed
-
- message() - Method in class org.apache.spark.scheduler.ExecutorLossReason
-
- message() - Method in exception org.apache.spark.storage.BlockException
-
- message() - Method in class org.apache.spark.streaming.scheduler.ReportError
-
- metadata() - Method in class org.apache.spark.mllib.tree.impl.DTStatsAggregator
-
- MetadataBuilder - Class in org.apache.spark.sql.api.java
-
Builder for [[Metadata]].
- MetadataBuilder() - Constructor for class org.apache.spark.sql.api.java.MetadataBuilder
-
- metadataCleaner() - Method in class org.apache.spark.SparkContext
-
- MetadataCleaner - Class in org.apache.spark.util
-
Runs a timer task to periodically clean up metadata (e.g.
- MetadataCleaner(Enumeration.Value, Function1<Object, BoxedUnit>, SparkConf) - Constructor for class org.apache.spark.util.MetadataCleaner
-
- MetadataCleanerType - Class in org.apache.spark.util
-
- MetadataCleanerType() - Constructor for class org.apache.spark.util.MetadataCleanerType
-
- metastorePath() - Method in class org.apache.spark.sql.hive.LocalHiveContext
-
- metastorePath() - Method in class org.apache.spark.sql.hive.test.TestHiveContext
-
- MetastoreRelation - Class in org.apache.spark.sql.hive
-
- MetastoreRelation(String, String, Option<String>, Table, Seq<Partition>, SQLContext) - Constructor for class org.apache.spark.sql.hive.MetastoreRelation
-
- MetastoreRelation.SchemaAttribute - Class in org.apache.spark.sql.hive
-
- MetastoreRelation.SchemaAttribute(FieldSchema) - Constructor for class org.apache.spark.sql.hive.MetastoreRelation.SchemaAttribute
-
- method() - Method in class org.apache.spark.mllib.stat.test.ChiSqTestResult
-
- metricName() - Method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
-
param for metric name in evaluation
- metricRegistry() - Method in class org.apache.spark.metrics.source.JvmSource
-
- metricRegistry() - Method in interface org.apache.spark.metrics.source.Source
-
- metricRegistry() - Method in class org.apache.spark.scheduler.DAGSchedulerSource
-
- metricRegistry() - Method in class org.apache.spark.storage.BlockManagerSource
-
- metricRegistry() - Method in class org.apache.spark.streaming.StreamingSource
-
- metrics() - Method in class org.apache.spark.ExceptionFailure
-
- metrics() - Method in class org.apache.spark.scheduler.DirectTaskResult
-
- metrics() - Method in class org.apache.spark.scheduler.Task
-
- METRICS_CONF() - Method in class org.apache.spark.metrics.MetricsConfig
-
- MetricsConfig - Class in org.apache.spark.metrics
-
- MetricsConfig(Option<String>) - Constructor for class org.apache.spark.metrics.MetricsConfig
-
- MetricsServlet - Class in org.apache.spark.metrics.sink
-
- MetricsServlet(Properties, MetricRegistry, SecurityManager) - Constructor for class org.apache.spark.metrics.sink.MetricsServlet
-
- MetricsSystem - Class in org.apache.spark.metrics
-
Spark Metrics System, created by specific "instance", combined by source,
sink, periodically poll source metrics data to sink destinations.
- metricsSystem() - Method in class org.apache.spark.SparkContext
-
- metricsSystem() - Method in class org.apache.spark.SparkEnv
-
- MFDataGenerator - Class in org.apache.spark.mllib.util
-
:: DeveloperApi ::
Generate RDD(s) containing data for Matrix Factorization.
- MFDataGenerator() - Constructor for class org.apache.spark.mllib.util.MFDataGenerator
-
- microF1Measure() - Method in class org.apache.spark.mllib.evaluation.MultilabelMetrics
-
Returns micro-averaged label-based f1-measure
(equals to micro-averaged document-based f1-measure)
- microPrecision() - Method in class org.apache.spark.mllib.evaluation.MultilabelMetrics
-
Returns micro-averaged label-based precision
(equals to micro-averaged document-based precision)
- microRecall() - Method in class org.apache.spark.mllib.evaluation.MultilabelMetrics
-
Returns micro-averaged label-based recall
(equals to micro-averaged document-based recall)
- milliseconds() - Method in class org.apache.spark.streaming.Duration
-
- milliseconds(long) - Static method in class org.apache.spark.streaming.Durations
-
- Milliseconds - Class in org.apache.spark.streaming
-
Helper object that creates instance of
Duration
representing
a given number of milliseconds.
- Milliseconds() - Constructor for class org.apache.spark.streaming.Milliseconds
-
- milliseconds() - Method in class org.apache.spark.streaming.Time
-
- millisToString(long) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
Reformat a time interval in milliseconds to a prettier format for output
- min(Comparator<T>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Returns the minimum element from this RDD as defined by the specified
Comparator[T].
- min() - Method in class org.apache.spark.mllib.stat.MultivariateOnlineSummarizer
-
- min() - Method in interface org.apache.spark.mllib.stat.MultivariateStatisticalSummary
-
Minimum value of each column.
- min(Ordering<T>) - Method in class org.apache.spark.rdd.RDD
-
Returns the min of this RDD as defined by the implicit Ordering[T].
- MIN() - Static method in class org.apache.spark.sql.hive.HiveQl
-
- min(Duration) - Method in class org.apache.spark.streaming.Duration
-
- min(Time) - Method in class org.apache.spark.streaming.Time
-
- min() - Method in class org.apache.spark.util.StatCounter
-
- minDocFreq() - Method in class org.apache.spark.mllib.feature.IDF.DocumentFrequencyAggregator
-
- minDocFreq() - Method in class org.apache.spark.mllib.feature.IDF
-
- MINIMUM_INTERVAL_SECONDS() - Static method in class org.apache.spark.util.logging.TimeBasedRollingPolicy
-
- MINIMUM_SHARES_PROPERTY() - Method in class org.apache.spark.scheduler.FairSchedulableBuilder
-
- MINIMUM_SIZE_BYTES() - Static method in class org.apache.spark.util.logging.SizeBasedRollingPolicy
-
- minInfoGain() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- minInfoGain() - Method in class org.apache.spark.mllib.tree.impl.DecisionTreeMetadata
-
- minInstancesPerNode() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- minInstancesPerNode() - Method in class org.apache.spark.mllib.tree.impl.DecisionTreeMetadata
-
- MinMax() - Static method in class org.apache.spark.mllib.tree.configuration.QuantileStrategy
-
- minMemoryMapBytes() - Method in class org.apache.spark.storage.DiskStore
-
- minPollTime() - Method in class org.apache.spark.streaming.util.SystemClock
-
- minRegisteredRatio() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend
-
- minSamplingRate() - Static method in class org.apache.spark.util.random.BinomialBounds
-
- minShare() - Method in class org.apache.spark.scheduler.Pool
-
- minShare() - Method in interface org.apache.spark.scheduler.Schedulable
-
- minShare() - Method in class org.apache.spark.scheduler.TaskSetManager
-
- minus(Duration) - Method in class org.apache.spark.streaming.Duration
-
- minus(Time) - Method in class org.apache.spark.streaming.Time
-
- minus(Duration) - Method in class org.apache.spark.streaming.Time
-
- minutes() - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- minutes(long) - Static method in class org.apache.spark.streaming.Durations
-
- Minutes - Class in org.apache.spark.streaming
-
Helper object that creates instance of
Duration
representing
a given number of minutes.
- Minutes() - Constructor for class org.apache.spark.streaming.Minutes
-
- minVal() - Method in class org.apache.spark.graphx.lib.SVDPlusPlus.Conf
-
- MLUtils - Class in org.apache.spark.mllib.util
-
Helper methods to load, save and pre-process data used in ML Lib.
- MLUtils() - Constructor for class org.apache.spark.mllib.util.MLUtils
-
- Model<M extends Model<M>> - Class in org.apache.spark.ml
-
- Model() - Constructor for class org.apache.spark.ml.Model
-
- model() - Method in class org.apache.spark.mllib.regression.StreamingLinearRegressionWithSGD
-
- MODULE$ - Static variable in class org.apache.spark.graphx.impl.ShippableVertexPartition.ShippableVertexPartitionOpsConstructor$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.graphx.impl.VertexPartition.VertexPartitionOpsConstructor$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.graphx.PartitionStrategy.CanonicalRandomVertexCut$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.graphx.PartitionStrategy.EdgePartition1D$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.graphx.PartitionStrategy.EdgePartition2D$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.graphx.PartitionStrategy.RandomVertexCut$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.mllib.recommendation.ALS.BlockStats$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.mllib.stat.test.ChiSqTest.Method$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.mllib.stat.test.ChiSqTest.NullHypothesis$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.rdd.HadoopRDD.HadoopMapPartitionsWithSplitRDD$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.rdd.NewHadoopRDD.NewHadoopMapPartitionsWithSplitRDD$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.AddWebUIFilter$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.KillExecutors$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.KillTask$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.LaunchTask$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterClusterManager$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisteredExecutor$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterExecutor$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterExecutorFailed$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RemoveExecutor$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RequestExecutors$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RetrieveSparkProps$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.ReviveOffers$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.StatusUpdate$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.StopDriver$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.StopExecutor$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.StopExecutors$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.SparkContext.DoubleAccumulatorParam$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.SparkContext.FloatAccumulatorParam$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.SparkContext.IntAccumulatorParam$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.SparkContext.LongAccumulatorParam$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.sql.hive.HiveQl.Token$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.sql.SQLConf.Deprecated$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.BlockManagerHeartbeat$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.ExpireDeadHosts$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.GetActorSystemHostPortForExecutor$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.GetBlockStatus$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.GetLocations$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.GetLocationsMultipleBlockIds$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.GetMatchingBlockIds$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.GetMemoryStatus$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.GetPeers$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.GetStorageStatus$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.RegisterBlockManager$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.RemoveBlock$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.RemoveBroadcast$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.RemoveExecutor$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.RemoveRdd$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.RemoveShuffle$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.StopBlockManagerMaster$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.UpdateBlockInfo$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.ShuffleBlockFetcherIterator.FailureFetchResult$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.ShuffleBlockFetcherIterator.FetchRequest$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.ShuffleBlockFetcherIterator.SuccessFetchResult$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.streaming.util.WriteAheadLogManager.LogInfo$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.ui.JettyUtils.ServletParams$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.ui.jobs.UIData.JobUIData$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.ui.jobs.UIData.TaskUIData$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.util.Vector.VectorAccumParam$
-
Static reference to the singleton instance of this Scala object.
- MQTTInputDStream - Class in org.apache.spark.streaming.mqtt
-
Input stream that subscribe messages from a Mqtt Broker.
- MQTTInputDStream(StreamingContext, String, String, StorageLevel) - Constructor for class org.apache.spark.streaming.mqtt.MQTTInputDStream
-
- MQTTReceiver - Class in org.apache.spark.streaming.mqtt
-
- MQTTReceiver(String, String, StorageLevel) - Constructor for class org.apache.spark.streaming.mqtt.MQTTReceiver
-
- MQTTUtils - Class in org.apache.spark.streaming.mqtt
-
- MQTTUtils() - Constructor for class org.apache.spark.streaming.mqtt.MQTTUtils
-
- msDurationToString(long) - Static method in class org.apache.spark.util.Utils
-
Returns a human-readable string representing a duration such as "35ms"
- msg() - Method in class org.apache.spark.streaming.scheduler.DeregisterReceiver
-
- msg() - Method in class org.apache.spark.streaming.scheduler.ErrorReported
-
- MulticlassMetrics - Class in org.apache.spark.mllib.evaluation
-
::Experimental::
Evaluator for multiclass classification.
- MulticlassMetrics(RDD<Tuple2<Object, Object>>) - Constructor for class org.apache.spark.mllib.evaluation.MulticlassMetrics
-
- MultilabelMetrics - Class in org.apache.spark.mllib.evaluation
-
Evaluator for multilabel classification.
- MultilabelMetrics(RDD<Tuple2<double[], double[]>>) - Constructor for class org.apache.spark.mllib.evaluation.MultilabelMetrics
-
- multiply(Matrix) - Method in class org.apache.spark.mllib.linalg.distributed.IndexedRowMatrix
-
Multiply this matrix by a local matrix on the right.
- multiply(Matrix) - Method in class org.apache.spark.mllib.linalg.distributed.RowMatrix
-
Multiply this matrix by a local matrix on the right.
- multiply(DenseMatrix) - Method in interface org.apache.spark.mllib.linalg.Matrix
-
Convenience method for `Matrix`-`DenseMatrix` multiplication.
- multiply(DenseVector) - Method in interface org.apache.spark.mllib.linalg.Matrix
-
Convenience method for `Matrix`-`DenseVector` multiplication.
- multiply(double) - Method in class org.apache.spark.util.Vector
-
- multiplyGramianMatrixBy(DenseVector<Object>) - Method in class org.apache.spark.mllib.linalg.distributed.RowMatrix
-
Multiplies the Gramian matrix A^T A
by a dense vector on the right without computing A^T A
.
- MultivariateOnlineSummarizer - Class in org.apache.spark.mllib.stat
-
:: DeveloperApi ::
MultivariateOnlineSummarizer implements
MultivariateStatisticalSummary
to compute the mean,
variance, minimum, maximum, counts, and nonzero counts for samples in sparse or dense vector
format in a online fashion.
- MultivariateOnlineSummarizer() - Constructor for class org.apache.spark.mllib.stat.MultivariateOnlineSummarizer
-
- MultivariateStatisticalSummary - Interface in org.apache.spark.mllib.stat
-
Trait for multivariate statistical summary of a data matrix.
- mustCheckpoint() - Method in class org.apache.spark.streaming.dstream.DStream
-
- mustCheckpoint() - Method in class org.apache.spark.streaming.dstream.ReducedWindowedDStream
-
- mustCheckpoint() - Method in class org.apache.spark.streaming.dstream.StateDStream
-
- MutablePair<T1,T2> - Class in org.apache.spark.util
-
:: DeveloperApi ::
A tuple of 2 elements.
- MutablePair(T1, T2) - Constructor for class org.apache.spark.util.MutablePair
-
- MutablePair() - Constructor for class org.apache.spark.util.MutablePair
-
No-arg constructor for serialization
- MutableRowWriteSupport - Class in org.apache.spark.sql.parquet
-
- MutableRowWriteSupport() - Constructor for class org.apache.spark.sql.parquet.MutableRowWriteSupport
-
- myLocalityLevels() - Method in class org.apache.spark.scheduler.TaskSetManager
-
- myName() - Method in class org.apache.spark.util.InnerClosureFinder
-
- pageRank(double, double) - Method in class org.apache.spark.graphx.GraphOps
-
Run a dynamic version of PageRank returning a graph with vertex attributes containing the
PageRank and edge attributes containing the normalized edge weight.
- PageRank - Class in org.apache.spark.graphx.lib
-
PageRank algorithm implementation.
- PageRank() - Constructor for class org.apache.spark.graphx.lib.PageRank
-
- pages() - Method in class org.apache.spark.ui.WebUITab
-
- PairDStreamFunctions<K,V> - Class in org.apache.spark.streaming.dstream
-
Extra functions available on DStream of (key, value) pairs through an implicit conversion.
- PairDStreamFunctions(DStream<Tuple2<K, V>>, ClassTag<K>, ClassTag<V>, Ordering<K>) - Constructor for class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
- PairFlatMapFunction<T,K,V> - Interface in org.apache.spark.api.java.function
-
A function that returns zero or more key-value pair records from each input record.
- PairFunction<T,K,V> - Interface in org.apache.spark.api.java.function
-
A function that returns key-value pairs (Tuple2<K, V>), and can be used to
construct PairRDDs.
- pairFunToScalaFun(PairFunction<A, B, C>) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- PairRDDFunctions<K,V> - Class in org.apache.spark.rdd
-
Extra functions available on RDDs of (key, value) pairs through an implicit conversion.
- PairRDDFunctions(RDD<Tuple2<K, V>>, ClassTag<K>, ClassTag<V>, Ordering<K>) - Constructor for class org.apache.spark.rdd.PairRDDFunctions
-
- ParallelCollectionPartition<T> - Class in org.apache.spark.rdd
-
- ParallelCollectionPartition(long, int, Seq<T>, ClassTag<T>) - Constructor for class org.apache.spark.rdd.ParallelCollectionPartition
-
- ParallelCollectionRDD<T> - Class in org.apache.spark.rdd
-
- ParallelCollectionRDD(SparkContext, Seq<T>, int, Map<Object, Seq<String>>, ClassTag<T>) - Constructor for class org.apache.spark.rdd.ParallelCollectionRDD
-
- parallelism() - Method in class org.apache.spark.streaming.flume.FlumePollingInputDStream
-
- parallelize(List<T>, int) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Distribute a local Scala collection to form an RDD.
- parallelize(List<T>) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Distribute a local Scala collection to form an RDD.
- parallelize(Seq<T>, int, ClassTag<T>) - Method in class org.apache.spark.SparkContext
-
Distribute a local Scala collection to form an RDD.
- parallelizeDoubles(List<Double>, int) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Distribute a local Scala collection to form an RDD.
- parallelizeDoubles(List<Double>) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Distribute a local Scala collection to form an RDD.
- parallelizePairs(List<Tuple2<K, V>>, int) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Distribute a local Scala collection to form an RDD.
- parallelizePairs(List<Tuple2<K, V>>) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Distribute a local Scala collection to form an RDD.
- Param<T> - Class in org.apache.spark.ml.param
-
:: AlphaComponent ::
A param with self-contained documentation and optionally default value.
- Param(Params, String, String, Option<T>) - Constructor for class org.apache.spark.ml.param.Param
-
- param() - Method in class org.apache.spark.ml.param.ParamPair
-
- ParamGridBuilder - Class in org.apache.spark.ml.tuning
-
:: AlphaComponent ::
Builder for a param grid used in grid search-based model selection.
- ParamGridBuilder() - Constructor for class org.apache.spark.ml.tuning.ParamGridBuilder
-
- ParamMap - Class in org.apache.spark.ml.param
-
:: AlphaComponent ::
A param to value map.
- ParamMap(Map<Param<Object>, Object>) - Constructor for class org.apache.spark.ml.param.ParamMap
-
- ParamMap() - Constructor for class org.apache.spark.ml.param.ParamMap
-
Creates an empty param map.
- paramMap() - Method in interface org.apache.spark.ml.param.Params
-
Internal param map.
- ParamPair<T> - Class in org.apache.spark.ml.param
-
A param amd its value.
- ParamPair(Param<T>, T) - Constructor for class org.apache.spark.ml.param.ParamPair
-
- Params - Interface in org.apache.spark.ml.param
-
:: AlphaComponent ::
Trait for components that take parameters.
- params() - Method in interface org.apache.spark.ml.param.Params
-
Returns all params.
- parent() - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- parent() - Method in class org.apache.spark.ml.feature.StandardScalerModel
-
- parent() - Method in class org.apache.spark.ml.Model
-
The parent estimator that produced this model.
- parent() - Method in class org.apache.spark.ml.param.Param
-
- parent() - Method in class org.apache.spark.ml.PipelineModel
-
- parent() - Method in class org.apache.spark.ml.tuning.CrossValidatorModel
-
- parent() - Method in class org.apache.spark.mllib.rdd.SlidingRDD
-
- parent() - Method in class org.apache.spark.scheduler.Pool
-
- parent() - Method in interface org.apache.spark.scheduler.Schedulable
-
- parent() - Method in class org.apache.spark.scheduler.TaskSetManager
-
- parent() - Method in class org.apache.spark.sql.parquet.CatalystPrimitiveRowConverter
-
- parent() - Method in class org.apache.spark.streaming.ui.StreamingTab
-
- ParentClassLoader - Class in org.apache.spark.util
-
A class loader which makes findClass accesible to the child
- ParentClassLoader(ClassLoader) - Constructor for class org.apache.spark.util.ParentClassLoader
-
- parentIndex(int) - Static method in class org.apache.spark.mllib.tree.model.Node
-
Get the parent index of the given node, or 0 if it is the root.
- parentPartition() - Method in class org.apache.spark.rdd.UnionPartition
-
- parentRddIndex() - Method in class org.apache.spark.rdd.UnionPartition
-
- parentRememberDuration() - Method in class org.apache.spark.streaming.dstream.DStream
-
- parentRememberDuration() - Method in class org.apache.spark.streaming.dstream.ReducedWindowedDStream
-
- parentRememberDuration() - Method in class org.apache.spark.streaming.dstream.WindowedDStream
-
- parents() - Method in class org.apache.spark.rdd.CoalescedRDDPartition
-
- parents() - Method in class org.apache.spark.rdd.PartitionerAwareUnionRDDPartition
-
- parents() - Method in class org.apache.spark.scheduler.Stage
-
- parentsIndices() - Method in class org.apache.spark.rdd.CoalescedRDDPartition
-
- parentSplit() - Method in class org.apache.spark.rdd.PartitionPruningRDDPartition
-
- PARQUET_FILTER_DATA() - Static method in class org.apache.spark.sql.parquet.ParquetFilters
-
- parquetCompressionCodec() - Method in interface org.apache.spark.sql.SQLConf
-
The compression codec for writing to a Parquetfile
- ParquetConversion() - Method in interface org.apache.spark.sql.hive.HiveStrategies
-
- parquetFile(String) - Method in class org.apache.spark.sql.api.java.JavaSQLContext
-
- parquetFile(String) - Method in class org.apache.spark.sql.SQLContext
-
Loads a Parquet file, returning the result as a
SchemaRDD
.
- parquetFilterPushDown() - Method in interface org.apache.spark.sql.SQLConf
-
When true predicates will be passed to the parquet record reader when possible.
- ParquetFilters - Class in org.apache.spark.sql.parquet
-
- ParquetFilters() - Constructor for class org.apache.spark.sql.parquet.ParquetFilters
-
- ParquetOperations() - Method in class org.apache.spark.sql.execution.SparkStrategies
-
- ParquetRelation - Class in org.apache.spark.sql.parquet
-
Relation that consists of data stored in a Parquet columnar format.
- ParquetRelation(String, Option<Configuration>, SQLContext, Seq<Attribute>) - Constructor for class org.apache.spark.sql.parquet.ParquetRelation
-
- ParquetRelation2 - Class in org.apache.spark.sql.parquet
-
An alternative to
ParquetRelation
that plugs in using the data sources API.
- ParquetRelation2(String, SQLContext) - Constructor for class org.apache.spark.sql.parquet.ParquetRelation2
-
- parquetSchema() - Method in class org.apache.spark.sql.parquet.ParquetRelation
-
Schema derived from ParquetFile
- ParquetTableScan - Class in org.apache.spark.sql.parquet
-
:: DeveloperApi ::
Parquet table scan operator.
- ParquetTableScan(Seq<Attribute>, ParquetRelation, Seq<Expression>) - Constructor for class org.apache.spark.sql.parquet.ParquetTableScan
-
- ParquetTestData - Class in org.apache.spark.sql.parquet
-
- ParquetTestData() - Constructor for class org.apache.spark.sql.parquet.ParquetTestData
-
- ParquetTypeInfo - Class in org.apache.spark.sql.parquet
-
A class representing Parquet info fields we care about, for passing back to Parquet
- ParquetTypeInfo(PrimitiveType.PrimitiveTypeName, Option<OriginalType>, Option<DecimalMetadata>, Option<Object>) - Constructor for class org.apache.spark.sql.parquet.ParquetTypeInfo
-
- ParquetTypesConverter - Class in org.apache.spark.sql.parquet
-
- ParquetTypesConverter() - Constructor for class org.apache.spark.sql.parquet.ParquetTypesConverter
-
- parse(String) - Static method in class org.apache.spark.mllib.linalg.Vectors
-
Parses a string resulted from
Vector#toString
into
an
Vector
.
- parse(String) - Static method in class org.apache.spark.mllib.regression.LabeledPoint
-
Parses a string resulted from
LabeledPoint#toString
into
an
LabeledPoint
.
- parse(String) - Static method in class org.apache.spark.mllib.util.NumericParser
-
Parses a string into a Double, an Array[Double], or a Seq[Any].
- parseCompressionCodec(String) - Static method in class org.apache.spark.scheduler.EventLoggingListener
-
- parseDataType(String) - Method in class org.apache.spark.sql.SQLContext
-
Parses the data type in our internal string representation.
- parseDdl(String) - Static method in class org.apache.spark.sql.hive.HiveQl
-
- parseHostPort(String) - Static method in class org.apache.spark.util.Utils
-
- parseLoggingInfo(Path, FileSystem) - Static method in class org.apache.spark.scheduler.EventLoggingListener
-
Parse the event logging information associated with the logs in the given directory.
- parseLoggingInfo(String, FileSystem) - Static method in class org.apache.spark.scheduler.EventLoggingListener
-
Parse the event logging information associated with the logs in the given directory.
- parseNumeric(Object) - Static method in class org.apache.spark.mllib.linalg.Vectors
-
- parseSparkVersion(String) - Static method in class org.apache.spark.scheduler.EventLoggingListener
-
- parseSql(String) - Static method in class org.apache.spark.sql.hive.HiveQl
-
Returns a LogicalPlan for a given HiveQL string.
- parseStream(PortableDataStream) - Method in class org.apache.spark.input.StreamBasedRecordReader
-
Parse the stream (and close it afterwards) and return the value as in type T
- parseStream(PortableDataStream) - Method in class org.apache.spark.input.StreamRecordReader
-
- partial() - Method in class org.apache.spark.sql.execution.Aggregate
-
- partial() - Method in class org.apache.spark.sql.execution.Distinct
-
- partial() - Method in class org.apache.spark.sql.execution.GeneratedAggregate
-
- PartialResult<R> - Class in org.apache.spark.partial
-
- PartialResult(R, boolean) - Constructor for class org.apache.spark.partial.PartialResult
-
- Partition - Interface in org.apache.spark
-
An identifier for a partition in an RDD.
- partition() - Method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- partition() - Method in class org.apache.spark.sql.hive.InsertIntoHiveTable
-
- Partition - Class in org.apache.spark.sql.parquet
-
- Partition(Map<String, Object>, Seq<FileStatus>) - Constructor for class org.apache.spark.sql.parquet.Partition
-
- partitionBy(Partitioner) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Return a copy of the RDD partitioned using the specified partitioner.
- partitionBy(PartitionStrategy) - Method in class org.apache.spark.graphx.Graph
-
Repartitions the edges in the graph according to partitionStrategy
.
- partitionBy(PartitionStrategy, int) - Method in class org.apache.spark.graphx.Graph
-
Repartitions the edges in the graph according to partitionStrategy
.
- partitionBy(PartitionStrategy) - Method in class org.apache.spark.graphx.impl.GraphImpl
-
- partitionBy(PartitionStrategy, int) - Method in class org.apache.spark.graphx.impl.GraphImpl
-
- partitionBy(Partitioner) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Return a copy of the RDD partitioned using the specified partitioner.
- PartitionCoalescer - Class in org.apache.spark.rdd
-
Coalesce the partitions of a parent RDD (prev
) into fewer partitions, so that each partition of
this RDD computes one or more of the parent ones.
- PartitionCoalescer(int, RDD<?>, double) - Constructor for class org.apache.spark.rdd.PartitionCoalescer
-
- PartitionCoalescer.LocationIterator - Class in org.apache.spark.rdd
-
- PartitionCoalescer.LocationIterator(RDD<?>) - Constructor for class org.apache.spark.rdd.PartitionCoalescer.LocationIterator
-
- partitioner() - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
If partitionsRDD
already has a partitioner, use it.
- partitioner() - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- Partitioner - Class in org.apache.spark
-
An object that defines how the elements in a key-value pair RDD are partitioned by key.
- Partitioner() - Constructor for class org.apache.spark.Partitioner
-
- partitioner() - Method in class org.apache.spark.rdd.CoGroupedRDD
-
- partitioner() - Method in class org.apache.spark.rdd.FilteredRDD
-
- partitioner() - Method in class org.apache.spark.rdd.FlatMappedValuesRDD
-
- partitioner() - Method in class org.apache.spark.rdd.HadoopRDD.HadoopMapPartitionsWithSplitRDD
-
- partitioner() - Method in class org.apache.spark.rdd.MapPartitionsRDD
-
- partitioner() - Method in class org.apache.spark.rdd.MappedValuesRDD
-
- partitioner() - Method in class org.apache.spark.rdd.NewHadoopRDD.NewHadoopMapPartitionsWithSplitRDD
-
- partitioner() - Method in class org.apache.spark.rdd.PartitionerAwareUnionRDD
-
- partitioner() - Method in class org.apache.spark.rdd.PartitionwiseSampledRDD
-
- partitioner() - Method in class org.apache.spark.rdd.RDD
-
Optionally overridden by subclasses to specify how they are partitioned.
- partitioner() - Method in class org.apache.spark.rdd.ShuffledRDD
-
- partitioner() - Method in class org.apache.spark.rdd.SubtractedRDD
-
- partitioner() - Method in class org.apache.spark.rdd.ZippedPartitionsBaseRDD
-
- partitioner() - Method in class org.apache.spark.ShuffleDependency
-
- PartitionerAwareUnionRDD<T> - Class in org.apache.spark.rdd
-
Class representing an RDD that can take multiple RDDs partitioned by the same partitioner and
unify them into a single RDD while preserving the partitioner.
- PartitionerAwareUnionRDD(SparkContext, Seq<RDD<T>>, ClassTag<T>) - Constructor for class org.apache.spark.rdd.PartitionerAwareUnionRDD
-
- PartitionerAwareUnionRDDPartition - Class in org.apache.spark.rdd
-
Class representing partitions of PartitionerAwareUnionRDD, which maintains the list of
corresponding partitions of parent RDDs.
- PartitionerAwareUnionRDDPartition(Seq<RDD<?>>, int) - Constructor for class org.apache.spark.rdd.PartitionerAwareUnionRDDPartition
-
- partitionFilters() - Method in class org.apache.spark.sql.columnar.InMemoryColumnarTableScan
-
- PartitionGroup - Class in org.apache.spark.rdd
-
- PartitionGroup(Option<String>) - Constructor for class org.apache.spark.rdd.PartitionGroup
-
- partitionId() - Method in class org.apache.spark.scheduler.Task
-
- partitionId() - Method in class org.apache.spark.TaskContext
-
- partitionId() - Method in class org.apache.spark.TaskContextImpl
-
- partitioningAttributes() - Method in class org.apache.spark.sql.parquet.ParquetRelation
-
- partitionKeys() - Method in class org.apache.spark.sql.hive.MetastoreRelation
-
- partitionPruningPred() - Method in class org.apache.spark.sql.hive.execution.HiveTableScan
-
- PartitionPruningRDD<T> - Class in org.apache.spark.rdd
-
:: DeveloperApi ::
A RDD used to prune RDD partitions/partitions so we can avoid launching tasks on
all partitions.
- PartitionPruningRDD(RDD<T>, Function1<Object, Object>, ClassTag<T>) - Constructor for class org.apache.spark.rdd.PartitionPruningRDD
-
- PartitionPruningRDDPartition - Class in org.apache.spark.rdd
-
- PartitionPruningRDDPartition(int, Partition) - Constructor for class org.apache.spark.rdd.PartitionPruningRDDPartition
-
- partitions() - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Set of partitions in this RDD.
- partitions() - Method in class org.apache.spark.rdd.PruneDependency
-
- partitions() - Method in class org.apache.spark.rdd.RDD
-
Get the array of partitions of this RDD, taking into account whether the
RDD is checkpointed or not.
- partitions() - Method in class org.apache.spark.rdd.ZippedPartitionsPartition
-
- partitions() - Method in class org.apache.spark.scheduler.ActiveJob
-
- partitions() - Method in class org.apache.spark.scheduler.JobSubmitted
-
- partitions() - Method in class org.apache.spark.sql.hive.MetastoreRelation
-
- partitionSize(int) - Method in class org.apache.spark.graphx.impl.RoutingTablePartition
-
Returns the number of vertices that will be sent to the specified edge partition.
- partitionsRDD() - Method in class org.apache.spark.graphx.EdgeRDD
-
- partitionsRDD() - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- partitionsRDD() - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- partitionsRDD() - Method in class org.apache.spark.graphx.VertexRDD
-
- partitionStatistics() - Method in class org.apache.spark.sql.columnar.InMemoryRelation
-
- PartitionStatistics - Class in org.apache.spark.sql.columnar
-
- PartitionStatistics(Seq<Attribute>) - Constructor for class org.apache.spark.sql.columnar.PartitionStatistics
-
- PartitionStrategy - Interface in org.apache.spark.graphx
-
Represents the way edges are assigned to edge partitions based on their source and destination
vertex IDs.
- PartitionStrategy.CanonicalRandomVertexCut$ - Class in org.apache.spark.graphx
-
Assigns edges to partitions by hashing the source and destination vertex IDs in a canonical
direction, resulting in a random vertex cut that colocates all edges between two vertices,
regardless of direction.
- PartitionStrategy.CanonicalRandomVertexCut$() - Constructor for class org.apache.spark.graphx.PartitionStrategy.CanonicalRandomVertexCut$
-
- PartitionStrategy.EdgePartition1D$ - Class in org.apache.spark.graphx
-
Assigns edges to partitions using only the source vertex ID, colocating edges with the same
source.
- PartitionStrategy.EdgePartition1D$() - Constructor for class org.apache.spark.graphx.PartitionStrategy.EdgePartition1D$
-
- PartitionStrategy.EdgePartition2D$ - Class in org.apache.spark.graphx
-
Assigns edges to partitions using a 2D partitioning of the sparse edge adjacency matrix,
guaranteeing a 2 * sqrt(numParts)
bound on vertex replication.
- PartitionStrategy.EdgePartition2D$() - Constructor for class org.apache.spark.graphx.PartitionStrategy.EdgePartition2D$
-
- PartitionStrategy.RandomVertexCut$ - Class in org.apache.spark.graphx
-
Assigns edges to partitions by hashing the source and destination vertex IDs, resulting in a
random vertex cut that colocates all same-direction edges between two vertices.
- PartitionStrategy.RandomVertexCut$() - Constructor for class org.apache.spark.graphx.PartitionStrategy.RandomVertexCut$
-
- partitionToOps(VertexPartition<VD>, ClassTag<VD>) - Static method in class org.apache.spark.graphx.impl.VertexPartition
-
Implicit conversion to allow invoking VertexPartitionBase
operations directly on a
VertexPartition
.
- partitionValues() - Method in class org.apache.spark.rdd.ZippedPartitionsPartition
-
- partitionValues() - Method in class org.apache.spark.sql.parquet.Partition
-
- PartitionwiseSampledRDD<T,U> - Class in org.apache.spark.rdd
-
A RDD sampled from its parent RDD partition-wise.
- PartitionwiseSampledRDD(RDD<T>, RandomSampler<T, U>, boolean, long, ClassTag<T>, ClassTag<U>) - Constructor for class org.apache.spark.rdd.PartitionwiseSampledRDD
-
- PartitionwiseSampledRDDPartition - Class in org.apache.spark.rdd
-
- PartitionwiseSampledRDDPartition(Partition, long) - Constructor for class org.apache.spark.rdd.PartitionwiseSampledRDDPartition
-
- PassThrough - Class in org.apache.spark.sql.columnar.compression
-
- PassThrough() - Constructor for class org.apache.spark.sql.columnar.compression.PassThrough
-
- PassThrough.Decoder<T extends org.apache.spark.sql.catalyst.types.NativeType> - Class in org.apache.spark.sql.columnar.compression
-
- PassThrough.Decoder(ByteBuffer, NativeColumnType<T>) - Constructor for class org.apache.spark.sql.columnar.compression.PassThrough.Decoder
-
- PassThrough.Encoder<T extends org.apache.spark.sql.catalyst.types.NativeType> - Class in org.apache.spark.sql.columnar.compression
-
- PassThrough.Encoder(NativeColumnType<T>) - Constructor for class org.apache.spark.sql.columnar.compression.PassThrough.Encoder
-
- path() - Method in class org.apache.spark.scheduler.InputFormatInfo
-
- path() - Method in class org.apache.spark.scheduler.SplitInfo
-
- path() - Method in class org.apache.spark.sql.hive.AddJar
-
- path() - Method in class org.apache.spark.sql.hive.execution.AddFile
-
- path() - Method in class org.apache.spark.sql.hive.execution.AddJar
-
- path() - Method in class org.apache.spark.sql.parquet.ParquetRelation
-
- path() - Method in class org.apache.spark.sql.parquet.ParquetRelation2
-
- path() - Method in class org.apache.spark.streaming.util.WriteAheadLogFileSegment
-
- path() - Method in class org.apache.spark.streaming.util.WriteAheadLogManager.LogInfo
-
- PEARSON() - Static method in class org.apache.spark.mllib.stat.test.ChiSqTest
-
- PearsonCorrelation - Class in org.apache.spark.mllib.stat.correlation
-
Compute Pearson correlation for two RDDs of the type RDD[Double] or the correlation matrix
for an RDD of the type RDD[Vector].
- PearsonCorrelation() - Constructor for class org.apache.spark.mllib.stat.correlation.PearsonCorrelation
-
- pendingTasks() - Method in class org.apache.spark.scheduler.Stage
-
- pendingTasksWithNoPrefs() - Method in class org.apache.spark.scheduler.TaskSetManager
-
- pendingTimes() - Method in class org.apache.spark.streaming.Checkpoint
-
- percentiles() - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- percentilesHeader() - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- persist(StorageLevel) - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Set this RDD's storage level to persist its values across operations after the first time
it is computed.
- persist(StorageLevel) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Set this RDD's storage level to persist its values across operations after the first time
it is computed.
- persist(StorageLevel) - Method in class org.apache.spark.api.java.JavaRDD
-
Set this RDD's storage level to persist its values across operations after the first time
it is computed.
- persist(StorageLevel) - Method in class org.apache.spark.graphx.Graph
-
Caches the vertices and edges associated with this graph at the specified storage level,
ignoring any target storage levels previously set.
- persist(StorageLevel) - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
Persists the edge partitions at the specified storage level, ignoring any existing target
storage level.
- persist(StorageLevel) - Method in class org.apache.spark.graphx.impl.GraphImpl
-
- persist(StorageLevel) - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
Persists the vertex partitions at the specified storage level, ignoring any existing target
storage level.
- persist(StorageLevel) - Method in class org.apache.spark.rdd.RDD
-
Set this RDD's storage level to persist its values across operations after the first time
it is computed.
- persist() - Method in class org.apache.spark.rdd.RDD
-
Persist this RDD with the default storage level (`MEMORY_ONLY`).
- persist() - Method in class org.apache.spark.sql.api.java.JavaSchemaRDD
-
Persist this RDD with the default storage level (`MEMORY_ONLY`).
- persist(StorageLevel) - Method in class org.apache.spark.sql.api.java.JavaSchemaRDD
-
Set this RDD's storage level to persist its values across operations after the first time
it is computed.
- persist(StorageLevel) - Method in class org.apache.spark.sql.SchemaRDD
-
- persist() - Method in class org.apache.spark.streaming.api.java.JavaDStream
-
Persist RDDs of this DStream with the default storage level (MEMORY_ONLY_SER)
- persist(StorageLevel) - Method in class org.apache.spark.streaming.api.java.JavaDStream
-
Persist the RDDs of this DStream with the given storage level
- persist() - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Persist RDDs of this DStream with the default storage level (MEMORY_ONLY_SER)
- persist(StorageLevel) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Persist the RDDs of this DStream with the given storage level
- persist(StorageLevel) - Method in class org.apache.spark.streaming.dstream.DStream
-
Persist the RDDs of this DStream with the given storage level
- persist() - Method in class org.apache.spark.streaming.dstream.DStream
-
Persist RDDs of this DStream with the default storage level (MEMORY_ONLY_SER)
- persist(StorageLevel) - Method in class org.apache.spark.streaming.dstream.ReducedWindowedDStream
-
- persist(StorageLevel) - Method in class org.apache.spark.streaming.dstream.WindowedDStream
-
- persistentRdds() - Method in class org.apache.spark.SparkContext
-
- persistRDD(RDD<?>) - Method in class org.apache.spark.SparkContext
-
Register an RDD to be persisted in memory and/or disk storage
- PhysicalRDD - Class in org.apache.spark.sql.execution
-
- PhysicalRDD(Seq<Attribute>, RDD<Row>) - Constructor for class org.apache.spark.sql.execution.PhysicalRDD
-
- pi() - Method in class org.apache.spark.mllib.classification.NaiveBayesModel
-
- pickBin(Partition) - Method in class org.apache.spark.rdd.PartitionCoalescer
-
Takes a parent RDD partition and decides which of the partition groups to put it in
Takes locality into account, but also uses power of 2 choices to load balance
It strikes a balance between the two use the balanceSlack variable
- pickRandomVertex() - Method in class org.apache.spark.graphx.GraphOps
-
Picks a random vertex from the graph and returns its ID.
- pipe(String) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return an RDD created by piping elements to a forked external process.
- pipe(List<String>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return an RDD created by piping elements to a forked external process.
- pipe(List<String>, Map<String, String>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return an RDD created by piping elements to a forked external process.
- pipe(String) - Method in class org.apache.spark.rdd.RDD
-
Return an RDD created by piping elements to a forked external process.
- pipe(String, Map<String, String>) - Method in class org.apache.spark.rdd.RDD
-
Return an RDD created by piping elements to a forked external process.
- pipe(Seq<String>, Map<String, String>, Function1<Function1<String, BoxedUnit>, BoxedUnit>, Function2<T, Function1<String, BoxedUnit>, BoxedUnit>, boolean) - Method in class org.apache.spark.rdd.RDD
-
Return an RDD created by piping elements to a forked external process.
- PipedRDD<T> - Class in org.apache.spark.rdd
-
An RDD that pipes the contents of each parent partition through an external command
(printing them one per line) and returns the output as a collection of strings.
- PipedRDD(RDD<T>, Seq<String>, Map<String, String>, Function1<Function1<String, BoxedUnit>, BoxedUnit>, Function2<T, Function1<String, BoxedUnit>, BoxedUnit>, boolean, ClassTag<T>) - Constructor for class org.apache.spark.rdd.PipedRDD
-
- PipedRDD(RDD<T>, String, Map<String, String>, Function1<Function1<String, BoxedUnit>, BoxedUnit>, Function2<T, Function1<String, BoxedUnit>, BoxedUnit>, boolean, ClassTag<T>) - Constructor for class org.apache.spark.rdd.PipedRDD
-
- PipedRDD.NotEqualsFileNameFilter - Class in org.apache.spark.rdd
-
A FilenameFilter that accepts anything that isn't equal to the name passed in.
- PipedRDD.NotEqualsFileNameFilter(String) - Constructor for class org.apache.spark.rdd.PipedRDD.NotEqualsFileNameFilter
-
- Pipeline - Class in org.apache.spark.ml
-
:: AlphaComponent ::
A simple pipeline, which acts as an estimator.
- Pipeline() - Constructor for class org.apache.spark.ml.Pipeline
-
- PipelineModel - Class in org.apache.spark.ml
-
:: AlphaComponent ::
Represents a compiled pipeline.
- PipelineModel(Pipeline, ParamMap, Transformer[]) - Constructor for class org.apache.spark.ml.PipelineModel
-
- PipelineStage - Class in org.apache.spark.ml
-
- PipelineStage() - Constructor for class org.apache.spark.ml.PipelineStage
-
- plan() - Method in class org.apache.spark.sql.CachedData
-
- plan() - Method in class org.apache.spark.sql.execution.CacheTableCommand
-
- PluggableInputDStream<T> - Class in org.apache.spark.streaming.dstream
-
- PluggableInputDStream(StreamingContext, Receiver<T>, ClassTag<T>) - Constructor for class org.apache.spark.streaming.dstream.PluggableInputDStream
-
- plus(Duration) - Method in class org.apache.spark.streaming.Duration
-
- plus(Duration) - Method in class org.apache.spark.streaming.Time
-
- plusDot(Vector, Vector) - Method in class org.apache.spark.util.Vector
-
return (this + plus) dot other, but without creating any intermediate storage
- point() - Method in class org.apache.spark.mllib.feature.VocabWord
-
- pointCost(TraversableOnce<VectorWithNorm>, VectorWithNorm) - Static method in class org.apache.spark.mllib.clustering.KMeans
-
Returns the K-means cost of a given point against the given cluster centers.
- POINTS() - Static method in class org.apache.spark.mllib.clustering.StreamingKMeans
-
- PoissonBounds - Class in org.apache.spark.util.random
-
Utility functions that help us determine bounds on adjusted sampling rate to guarantee exact
sample sizes with high confidence when sampling with replacement.
- PoissonBounds() - Constructor for class org.apache.spark.util.random.PoissonBounds
-
- PoissonGenerator - Class in org.apache.spark.mllib.random
-
:: DeveloperApi ::
Generates i.i.d.
- PoissonGenerator(double) - Constructor for class org.apache.spark.mllib.random.PoissonGenerator
-
- poissonJavaRDD(JavaSparkContext, double, long, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- poissonJavaRDD(JavaSparkContext, double, long, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- poissonJavaRDD(JavaSparkContext, double, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- poissonJavaVectorRDD(JavaSparkContext, double, long, int, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- poissonJavaVectorRDD(JavaSparkContext, double, long, int, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- poissonJavaVectorRDD(JavaSparkContext, double, long, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- poissonRDD(SparkContext, double, long, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
Generates an RDD comprised of i.i.d.
- PoissonSampler<T> - Class in org.apache.spark.util.random
-
:: DeveloperApi ::
A sampler for sampling with replacement, based on values drawn from Poisson distribution.
- PoissonSampler(double, ClassTag<T>) - Constructor for class org.apache.spark.util.random.PoissonSampler
-
- poissonVectorRDD(SparkContext, double, long, int, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
Generates an RDD[Vector] with vectors containing i.i.d.
- POLL_TIMEOUT() - Static method in class org.apache.spark.scheduler.DAGScheduler
-
- pollDir() - Method in class org.apache.spark.metrics.sink.CsvSink
-
- pollPeriod() - Method in class org.apache.spark.metrics.sink.ConsoleSink
-
- pollPeriod() - Method in class org.apache.spark.metrics.sink.CsvSink
-
- pollPeriod() - Method in class org.apache.spark.metrics.sink.GraphiteSink
-
- pollUnit() - Method in class org.apache.spark.metrics.sink.ConsoleSink
-
- pollUnit() - Method in class org.apache.spark.metrics.sink.CsvSink
-
- pollUnit() - Method in class org.apache.spark.metrics.sink.GraphiteSink
-
- Pool - Class in org.apache.spark.scheduler
-
An Schedulable entity that represent collection of Pools or TaskSetManagers
- Pool(String, Enumeration.Value, int, int) - Constructor for class org.apache.spark.scheduler.Pool
-
- POOL_NAME_PROPERTY() - Method in class org.apache.spark.scheduler.FairSchedulableBuilder
-
- poolName() - Method in class org.apache.spark.scheduler.Pool
-
- PoolPage - Class in org.apache.spark.ui.jobs
-
Page showing specific pool details
- PoolPage(StagesTab) - Constructor for class org.apache.spark.ui.jobs.PoolPage
-
- POOLS_PROPERTY() - Method in class org.apache.spark.scheduler.FairSchedulableBuilder
-
- PoolTable - Class in org.apache.spark.ui.jobs
-
Table showing list of pools
- PoolTable(Seq<Schedulable>, StagesTab) - Constructor for class org.apache.spark.ui.jobs.PoolTable
-
- poolToActiveStages() - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- port() - Method in class org.apache.spark.metrics.sink.GraphiteSink
-
- port() - Method in class org.apache.spark.storage.BlockManagerId
-
- PortableDataStream - Class in org.apache.spark.input
-
A class that allows DataStreams to be serialized and moved around by not creating them
until they need to be read
- PortableDataStream(CombineFileSplit, TaskAttemptContext, Integer) - Constructor for class org.apache.spark.input.PortableDataStream
-
- portMaxRetries(SparkConf) - Static method in class org.apache.spark.util.Utils
-
Maximum number of retries when binding to a port before giving up.
- pos() - Method in interface org.apache.spark.sql.columnar.NullableColumnAccessor
-
- pos() - Method in interface org.apache.spark.sql.columnar.NullableColumnBuilder
-
- post(SparkListenerEvent) - Method in class org.apache.spark.scheduler.LiveListenerBus
-
- post(StreamingListenerEvent) - Method in class org.apache.spark.streaming.scheduler.StreamingListenerBus
-
- postStartHook() - Method in interface org.apache.spark.scheduler.TaskScheduler
-
- postStartHook() - Method in class org.apache.spark.scheduler.TaskSchedulerImpl
-
- postStop() - Method in class org.apache.spark.scheduler.DAGSchedulerEventProcessActor
-
- postToAll(SparkListenerEvent) - Method in interface org.apache.spark.scheduler.SparkListenerBus
-
Post an event to all attached listeners.
- pr() - Method in class org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
-
Returns the precision-recall curve, which is an RDD of (recall, precision),
NOT (precision, recall), with (0.0, 1.0) prepended to it.
- Precision - Class in org.apache.spark.mllib.evaluation.binary
-
Precision.
- Precision() - Constructor for class org.apache.spark.mllib.evaluation.binary.Precision
-
- precision(double) - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
-
Returns precision for a given label (category)
- precision() - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
-
Returns precision
- precision() - Method in class org.apache.spark.mllib.evaluation.MultilabelMetrics
-
Returns document-based precision averaged by the number of documents
- precision(double) - Method in class org.apache.spark.mllib.evaluation.MultilabelMetrics
-
Returns precision for a given label (category)
- precisionAt(int) - Method in class org.apache.spark.mllib.evaluation.RankingMetrics
-
Compute the average precision of all the queries, truncated at ranking position k.
- precisionByThreshold() - Method in class org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
-
Returns the (threshold, precision) curve.
- predicates() - Method in class org.apache.spark.sql.columnar.InMemoryColumnarTableScan
-
- predict(RDD<Vector>) - Method in interface org.apache.spark.mllib.classification.ClassificationModel
-
Predict values for the given data set using the model trained.
- predict(Vector) - Method in interface org.apache.spark.mllib.classification.ClassificationModel
-
Predict values for a single data point using the model trained.
- predict(JavaRDD<Vector>) - Method in interface org.apache.spark.mllib.classification.ClassificationModel
-
Predict values for examples stored in a JavaRDD.
- predict(RDD<Vector>) - Method in class org.apache.spark.mllib.classification.NaiveBayesModel
-
- predict(Vector) - Method in class org.apache.spark.mllib.classification.NaiveBayesModel
-
- predict(Vector) - Method in class org.apache.spark.mllib.clustering.KMeansModel
-
Returns the cluster index that a given point belongs to.
- predict(RDD<Vector>) - Method in class org.apache.spark.mllib.clustering.KMeansModel
-
Maps given points to their cluster indices.
- predict(JavaRDD<Vector>) - Method in class org.apache.spark.mllib.clustering.KMeansModel
-
Maps given points to their cluster indices.
- predict(int, int) - Method in class org.apache.spark.mllib.recommendation.MatrixFactorizationModel
-
Predict the rating of one user for one product.
- predict(RDD<Tuple2<Object, Object>>) - Method in class org.apache.spark.mllib.recommendation.MatrixFactorizationModel
-
Predict the rating of many users for many products.
- predict(JavaPairRDD<Integer, Integer>) - Method in class org.apache.spark.mllib.recommendation.MatrixFactorizationModel
-
Java-friendly version of MatrixFactorizationModel.predict
.
- predict(RDD<Vector>) - Method in class org.apache.spark.mllib.regression.GeneralizedLinearModel
-
Predict values for the given data set using the model trained.
- predict(Vector) - Method in class org.apache.spark.mllib.regression.GeneralizedLinearModel
-
Predict values for a single data point using the model trained.
- predict(RDD<Vector>) - Method in interface org.apache.spark.mllib.regression.RegressionModel
-
Predict values for the given data set using the model trained.
- predict(Vector) - Method in interface org.apache.spark.mllib.regression.RegressionModel
-
Predict values for a single data point using the model trained.
- predict(JavaRDD<Vector>) - Method in interface org.apache.spark.mllib.regression.RegressionModel
-
Predict values for examples stored in a JavaRDD.
- predict() - Method in class org.apache.spark.mllib.tree.impurity.EntropyCalculator
-
Prediction which should be made based on the sufficient statistics.
- predict() - Method in class org.apache.spark.mllib.tree.impurity.GiniCalculator
-
Prediction which should be made based on the sufficient statistics.
- predict() - Method in class org.apache.spark.mllib.tree.impurity.ImpurityCalculator
-
Prediction which should be made based on the sufficient statistics.
- predict() - Method in class org.apache.spark.mllib.tree.impurity.VarianceCalculator
-
Prediction which should be made based on the sufficient statistics.
- predict(Vector) - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel
-
Predict values for a single data point using the model trained.
- predict(RDD<Vector>) - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel
-
Predict values for the given data set using the model trained.
- predict(JavaRDD<Vector>) - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel
-
Predict values for the given data set using the model trained.
- predict() - Method in class org.apache.spark.mllib.tree.model.Node
-
- predict(Vector) - Method in class org.apache.spark.mllib.tree.model.Node
-
predict value if node is not leaf
- Predict - Class in org.apache.spark.mllib.tree.model
-
Predicted value for a node
- Predict(double, double) - Constructor for class org.apache.spark.mllib.tree.model.Predict
-
- predict() - Method in class org.apache.spark.mllib.tree.model.Predict
-
- predict(Vector) - Method in class org.apache.spark.mllib.tree.model.TreeEnsembleModel
-
Predict values for a single data point using the model trained.
- predict(RDD<Vector>) - Method in class org.apache.spark.mllib.tree.model.TreeEnsembleModel
-
Predict values for the given data set.
- predict(JavaRDD<Vector>) - Method in class org.apache.spark.mllib.tree.model.TreeEnsembleModel
-
- predictionCol() - Method in interface org.apache.spark.ml.param.HasPredictionCol
-
param for prediction column name
- predictOn(DStream<Vector>) - Method in class org.apache.spark.mllib.clustering.StreamingKMeans
-
Use the clustering model to make predictions on batches of data from a DStream.
- predictOn(DStream<Vector>) - Method in class org.apache.spark.mllib.regression.StreamingLinearAlgorithm
-
Use the model to make predictions on batches of data from a DStream
- predictOnValues(DStream<Tuple2<K, Vector>>, ClassTag<K>) - Method in class org.apache.spark.mllib.clustering.StreamingKMeans
-
Use the model to make predictions on the values of a DStream and carry over its keys.
- predictOnValues(DStream<Tuple2<K, Vector>>, ClassTag<K>) - Method in class org.apache.spark.mllib.regression.StreamingLinearAlgorithm
-
Use the model to make predictions on the values of a DStream and carry over its keys.
- preferredLocation() - Method in class org.apache.spark.rdd.CoalescedRDDPartition
-
- preferredLocation() - Method in class org.apache.spark.streaming.flume.FlumeReceiver
-
- preferredLocation() - Method in class org.apache.spark.streaming.receiver.Receiver
-
Override this to specify a preferred location (hostname).
- preferredLocations(Partition) - Method in class org.apache.spark.rdd.RDD
-
Get the preferred locations of a partition, taking into account whether the
RDD is checkpointed.
- preferredLocations() - Method in class org.apache.spark.rdd.UnionPartition
-
- preferredLocations() - Method in class org.apache.spark.rdd.ZippedPartitionsPartition
-
- preferredLocations() - Method in class org.apache.spark.scheduler.ResultTask
-
- preferredLocations() - Method in class org.apache.spark.scheduler.ShuffleMapTask
-
- preferredLocations() - Method in class org.apache.spark.scheduler.Task
-
- preferredNodeLocationData() - Method in class org.apache.spark.SparkContext
-
- prefix() - Method in class org.apache.spark.metrics.sink.GraphiteSink
-
- PREFIX() - Static method in class org.apache.spark.streaming.Checkpoint
-
- prefix() - Method in class org.apache.spark.ui.WebUIPage
-
- prefix() - Method in class org.apache.spark.ui.WebUITab
-
- prefLoc() - Method in class org.apache.spark.rdd.PartitionGroup
-
- pregel(A, int, EdgeDirection, Function3<Object, VD, A, VD>, Function1<EdgeTriplet<VD, ED>, Iterator<Tuple2<Object, A>>>, Function2<A, A, A>, ClassTag<A>) - Method in class org.apache.spark.graphx.GraphOps
-
Execute a Pregel-like iterative vertex-parallel abstraction.
- Pregel - Class in org.apache.spark.graphx
-
Implements a Pregel-like bulk-synchronous message-passing API.
- Pregel() - Constructor for class org.apache.spark.graphx.Pregel
-
- PreInsertionCasts() - Method in class org.apache.spark.sql.hive.HiveMetastoreCatalog
-
- prepare(int) - Method in class org.apache.spark.sql.hive.DeferredObjectAdapter
-
- prepareForRead(Configuration, Map<String, String>, MessageType, ReadSupport.ReadContext) - Method in class org.apache.spark.sql.parquet.RowReadSupport
-
- prepareForWrite(RecordConsumer) - Method in class org.apache.spark.sql.parquet.RowWriteSupport
-
- prepareForWrite(RecordConsumer) - Method in class org.apache.spark.sql.parquet.TestGroupWriteSupport
-
- prependBaseUri(String, String) - Static method in class org.apache.spark.ui.UIUtils
-
- preSetup() - Method in class org.apache.spark.SparkHadoopWriter
-
- preStart() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend.DriverActor
-
- preStart() - Method in class org.apache.spark.scheduler.DAGSchedulerEventProcessActor
-
- preStart() - Method in class org.apache.spark.storage.BlockManagerMasterActor
-
- preStart() - Method in class org.apache.spark.streaming.zeromq.ZeroMQReceiver
-
- prettyPrint() - Method in class org.apache.spark.streaming.Duration
-
- prev() - Method in class org.apache.spark.mllib.rdd.SlidingRDDPartition
-
- prev() - Method in class org.apache.spark.rdd.CoalescedRDD
-
- prev() - Method in class org.apache.spark.rdd.PartitionwiseSampledRDDPartition
-
- prev() - Method in class org.apache.spark.rdd.SampledRDDPartition
-
- prev() - Method in class org.apache.spark.rdd.ShuffledRDD
-
- prev() - Method in class org.apache.spark.rdd.ZippedWithIndexRDDPartition
-
- prevHandler() - Method in class org.apache.spark.util.SignalLoggerHandler
-
- primitiveType() - Method in class org.apache.spark.sql.parquet.ParquetTypeInfo
-
- print() - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Print the first ten elements of each RDD generated in this DStream.
- print() - Method in class org.apache.spark.streaming.dstream.DStream
-
Print the first ten elements of each RDD generated in this DStream.
- printSchema() - Method in interface org.apache.spark.sql.SchemaRDDLike
-
Prints out the schema.
- printStats() - Method in class org.apache.spark.streaming.scheduler.StatsReportListener
-
- prioritizeContainers(HashMap<K, ArrayBuffer<T>>) - Static method in class org.apache.spark.scheduler.TaskSchedulerImpl
-
Used to balance containers across hosts.
- priority() - Method in class org.apache.spark.scheduler.Pool
-
- priority() - Method in interface org.apache.spark.scheduler.Schedulable
-
- priority() - Method in class org.apache.spark.scheduler.TaskSet
-
- priority() - Method in class org.apache.spark.scheduler.TaskSetManager
-
- prob(double) - Method in class org.apache.spark.mllib.tree.impurity.EntropyCalculator
-
Probability of the label given by predict
.
- prob(double) - Method in class org.apache.spark.mllib.tree.impurity.GiniCalculator
-
Probability of the label given by predict
.
- prob(double) - Method in class org.apache.spark.mllib.tree.impurity.ImpurityCalculator
-
Probability of the label given by predict
, or -1 if no probability is available.
- prob() - Method in class org.apache.spark.mllib.tree.model.Predict
-
- probabilities() - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- PROCESS_LOCAL() - Static method in class org.apache.spark.scheduler.TaskLocality
-
- processingDelay() - Method in class org.apache.spark.streaming.scheduler.BatchInfo
-
Time taken for the all jobs of this batch to finish processing from the time they started
processing.
- processingDelay() - Method in class org.apache.spark.streaming.scheduler.JobSet
-
- processingDelayDistribution() - Method in class org.apache.spark.streaming.ui.StreamingJobProgressListener
-
- processingEndTime() - Method in class org.apache.spark.streaming.scheduler.BatchInfo
-
- processingStartTime() - Method in class org.apache.spark.streaming.scheduler.BatchInfo
-
- processRecords(List<Record>, IRecordProcessorCheckpointer) - Method in class org.apache.spark.streaming.kinesis.KinesisRecordProcessor
-
This method is called by the KCL when a batch of records is pulled from the Kinesis stream.
- processResults(ArrayList<Object>) - Static method in class org.apache.spark.sql.hive.HiveShim
-
- product() - Method in class org.apache.spark.mllib.recommendation.Rating
-
- productFeatures() - Method in class org.apache.spark.mllib.recommendation.MatrixFactorizationModel
-
- productToRowRdd(RDD<A>, StructType) - Static method in class org.apache.spark.sql.execution.RDDConversions
-
- progressBar() - Method in class org.apache.spark.SparkContext
-
- progressListener() - Method in class org.apache.spark.streaming.StreamingContext
-
- Project - Class in org.apache.spark.sql.execution
-
:: DeveloperApi ::
- Project(Seq<NamedExpression>, SparkPlan) - Constructor for class org.apache.spark.sql.execution.Project
-
- projectList() - Method in class org.apache.spark.sql.execution.Project
-
- properties() - Method in class org.apache.spark.metrics.MetricsConfig
-
- properties() - Method in class org.apache.spark.scheduler.ActiveJob
-
- properties() - Method in class org.apache.spark.scheduler.JobSubmitted
-
- properties() - Method in class org.apache.spark.scheduler.SparkListenerJobStart
-
- properties() - Method in class org.apache.spark.scheduler.SparkListenerStageSubmitted
-
- properties() - Method in class org.apache.spark.scheduler.TaskSet
-
- propertiesFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
-
- propertiesToJson(Properties) - Static method in class org.apache.spark.util.JsonProtocol
-
- property() - Method in class org.apache.spark.metrics.sink.ConsoleSink
-
- property() - Method in class org.apache.spark.metrics.sink.CsvSink
-
- property() - Method in class org.apache.spark.metrics.sink.GraphiteSink
-
- property() - Method in class org.apache.spark.metrics.sink.JmxSink
-
- property() - Method in class org.apache.spark.metrics.sink.MetricsServlet
-
- propertyCategories() - Method in class org.apache.spark.metrics.MetricsConfig
-
- propertyToOption(String) - Method in class org.apache.spark.metrics.sink.GraphiteSink
-
- provider() - Method in class org.apache.spark.sql.sources.CreateTableUsing
-
- proxyBase() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.AddWebUIFilter
-
- pruneColumns(Seq<Attribute>) - Method in class org.apache.spark.sql.parquet.ParquetTableScan
-
Applies a (candidate) projection.
- PruneDependency<T> - Class in org.apache.spark.rdd
-
Represents a dependency between the PartitionPruningRDD and its parent.
- PruneDependency(RDD<T>, Function1<Object, Object>) - Constructor for class org.apache.spark.rdd.PruneDependency
-
- PrunedFilteredScan - Class in org.apache.spark.sql.sources
-
::DeveloperApi::
A BaseRelation that can eliminate unneeded columns and filter using selected
predicates before producing an RDD containing all matching tuples as Row objects.
- PrunedFilteredScan() - Constructor for class org.apache.spark.sql.sources.PrunedFilteredScan
-
- PrunedScan - Class in org.apache.spark.sql.sources
-
::DeveloperApi::
A BaseRelation that can eliminate unneeded columns before producing an RDD
containing all of its tuples as Row objects.
- PrunedScan() - Constructor for class org.apache.spark.sql.sources.PrunedScan
-
- prunePartitions(Seq<Partition>) - Method in class org.apache.spark.sql.hive.execution.HiveTableScan
-
Prunes partitions not involve the query plan.
- Pseudorandom - Interface in org.apache.spark.util.random
-
:: DeveloperApi ::
A class with pseudorandom behavior.
- pushAndReportBlock(ReceivedBlock, Option<Object>, Option<StreamBlockId>) - Method in class org.apache.spark.streaming.receiver.ReceiverSupervisorImpl
-
Store block and report it to driver
- pushArrayBuffer(ArrayBuffer<?>, Option<Object>, Option<StreamBlockId>) - Method in class org.apache.spark.streaming.receiver.ReceiverSupervisor
-
Store an ArrayBuffer of received data as a data block into Spark's memory.
- pushArrayBuffer(ArrayBuffer<?>, Option<Object>, Option<StreamBlockId>) - Method in class org.apache.spark.streaming.receiver.ReceiverSupervisorImpl
-
Store an ArrayBuffer of received data as a data block into Spark's memory.
- pushBytes(ByteBuffer, Option<Object>, Option<StreamBlockId>) - Method in class org.apache.spark.streaming.receiver.ReceiverSupervisor
-
Store the bytes of received data as a data block into Spark's memory.
- pushBytes(ByteBuffer, Option<Object>, Option<StreamBlockId>) - Method in class org.apache.spark.streaming.receiver.ReceiverSupervisorImpl
-
Store the bytes of received data as a data block into Spark's memory.
- pushIterator(Iterator<Object>, Option<Object>, Option<StreamBlockId>) - Method in class org.apache.spark.streaming.receiver.ReceiverSupervisor
-
Store a iterator of received data as a data block into Spark's memory.
- pushIterator(Iterator<Object>, Option<Object>, Option<StreamBlockId>) - Method in class org.apache.spark.streaming.receiver.ReceiverSupervisorImpl
-
Store a iterator of received data as a data block into Spark's memory.
- pushSingle(Object) - Method in class org.apache.spark.streaming.receiver.ReceiverSupervisor
-
Push a single data item to backend data store.
- pushSingle(Object) - Method in class org.apache.spark.streaming.receiver.ReceiverSupervisorImpl
-
Push a single record of received data into block generator.
- put(ParamPair<?>...) - Method in class org.apache.spark.ml.param.ParamMap
-
Puts a list of param pairs (overwrites if the input params exists).
- put(Param<T>, T) - Method in class org.apache.spark.ml.param.ParamMap
-
Puts a (param, value) pair (overwrites if the input param exists).
- put(Seq<ParamPair<?>>) - Method in class org.apache.spark.ml.param.ParamMap
-
Puts a list of param pairs (overwrites if the input params exists).
- putAll(Map<A, B>) - Method in class org.apache.spark.util.TimeStampedHashMap
-
- putArray(BlockId, Object[], StorageLevel, boolean, Option<StorageLevel>) - Method in class org.apache.spark.storage.BlockManager
-
Put a new block of values to the block manager.
- putArray(BlockId, Object[], StorageLevel, boolean) - Method in class org.apache.spark.storage.BlockStore
-
- putArray(BlockId, Object[], StorageLevel, boolean) - Method in class org.apache.spark.storage.DiskStore
-
- putArray(BlockId, Object[], StorageLevel, boolean) - Method in class org.apache.spark.storage.MemoryStore
-
- putArray(BlockId, Object[], StorageLevel, boolean) - Method in class org.apache.spark.storage.TachyonStore
-
- putBlockData(BlockId, ManagedBuffer, StorageLevel) - Method in class org.apache.spark.storage.BlockManager
-
Put the block locally, using the given storage level.
- putBytes(BlockId, ByteBuffer, StorageLevel, boolean, Option<StorageLevel>) - Method in class org.apache.spark.storage.BlockManager
-
Put a new block of serialized bytes to the block manager.
- putBytes(BlockId, ByteBuffer, StorageLevel) - Method in class org.apache.spark.storage.BlockStore
-
- putBytes(BlockId, ByteBuffer, StorageLevel) - Method in class org.apache.spark.storage.DiskStore
-
- putBytes(BlockId, ByteBuffer, StorageLevel) - Method in class org.apache.spark.storage.MemoryStore
-
- putBytes(BlockId, ByteBuffer, StorageLevel) - Method in class org.apache.spark.storage.TachyonStore
-
- putCachedMetadata(String, Object) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- putIfAbsent(A, B) - Method in class org.apache.spark.util.TimeStampedHashMap
-
- putIfAbsent(A, B) - Method in class org.apache.spark.util.TimeStampedWeakValueHashMap
-
- putIterator(BlockId, Iterator<Object>, StorageLevel, boolean, Option<StorageLevel>) - Method in class org.apache.spark.storage.BlockManager
-
- putIterator(BlockId, Iterator<Object>, StorageLevel, boolean) - Method in class org.apache.spark.storage.BlockStore
-
Put in a block and, possibly, also return its content as either bytes or another Iterator.
- putIterator(BlockId, Iterator<Object>, StorageLevel, boolean) - Method in class org.apache.spark.storage.DiskStore
-
- putIterator(BlockId, Iterator<Object>, StorageLevel, boolean) - Method in class org.apache.spark.storage.MemoryStore
-
- putIterator(BlockId, Iterator<Object>, StorageLevel, boolean, boolean) - Method in class org.apache.spark.storage.MemoryStore
-
Attempt to put the given block in memory store.
- putIterator(BlockId, Iterator<Object>, StorageLevel, boolean) - Method in class org.apache.spark.storage.TachyonStore
-
- PutResult - Class in org.apache.spark.storage
-
Result of adding a block into a BlockStore.
- PutResult(long, Either<Iterator<Object>, ByteBuffer>, Seq<Tuple2<BlockId, BlockStatus>>) - Constructor for class org.apache.spark.storage.PutResult
-
- putSingle(BlockId, Object, StorageLevel, boolean) - Method in class org.apache.spark.storage.BlockManager
-
Write a block consisting of a single object.
- pValue() - Method in class org.apache.spark.mllib.stat.test.ChiSqTestResult
-
- pValue() - Method in interface org.apache.spark.mllib.stat.test.TestResult
-
The probability of obtaining a test statistic result at least as extreme as the one that was
actually observed, assuming that the null hypothesis is true.
- pythonExec() - Method in class org.apache.spark.sql.execution.PythonUDF
-
- pythonIncludes() - Method in class org.apache.spark.sql.execution.PythonUDF
-
- PythonUDF - Class in org.apache.spark.sql.execution
-
A serialized version of a Python lambda function.
- PythonUDF(String, byte[], Map<String, String>, List<String>, String, List<Broadcast<PythonBroadcast>>, Accumulator<List<byte[]>>, DataType, Seq<Expression>) - Constructor for class org.apache.spark.sql.execution.PythonUDF
-
- pyUDT() - Method in class org.apache.spark.mllib.linalg.VectorUDT
-
- pyUDT() - Method in class org.apache.spark.sql.test.ExamplePointUDT
-
- r2() - Method in class org.apache.spark.mllib.evaluation.RegressionMetrics
-
Returns R^2^, the coefficient of determination.
- RACK_LOCAL() - Static method in class org.apache.spark.scheduler.TaskLocality
-
- rand(int, int, Random) - Static method in class org.apache.spark.mllib.linalg.Matrices
-
Generate a DenseMatrix
consisting of i.i.d.
- RAND() - Static method in class org.apache.spark.sql.hive.HiveQl
-
- randn(int, int, Random) - Static method in class org.apache.spark.mllib.linalg.Matrices
-
Generate a DenseMatrix
consisting of i.i.d.
- RANDOM() - Static method in class org.apache.spark.mllib.clustering.KMeans
-
- random() - Static method in class org.apache.spark.util.Utils
-
- random(int, Random) - Static method in class org.apache.spark.util.Vector
-
Creates this
Vector
of given length containing random numbers
between 0.0 and 1.0.
- RandomDataGenerator<T> - Interface in org.apache.spark.mllib.random
-
:: DeveloperApi ::
Trait for random data generators that generate i.i.d.
- RandomForest - Class in org.apache.spark.mllib.tree
-
:: Experimental ::
A class that implements a Random Forest
learning algorithm for classification and regression.
- RandomForest(Strategy, int, String, int) - Constructor for class org.apache.spark.mllib.tree.RandomForest
-
- RandomForest.NodeIndexInfo - Class in org.apache.spark.mllib.tree
-
- RandomForest.NodeIndexInfo(int, Option<int[]>) - Constructor for class org.apache.spark.mllib.tree.RandomForest.NodeIndexInfo
-
- RandomForestModel - Class in org.apache.spark.mllib.tree.model
-
:: Experimental ::
Represents a random forest model.
- RandomForestModel(Enumeration.Value, DecisionTreeModel[]) - Constructor for class org.apache.spark.mllib.tree.model.RandomForestModel
-
- randomize(TraversableOnce<T>, ClassTag<T>) - Static method in class org.apache.spark.util.Utils
-
Shuffle the elements of a collection into a random order, returning the
result in a new collection.
- randomizeInPlace(Object, Random) - Static method in class org.apache.spark.util.Utils
-
Shuffle the elements of an array into a random order, modifying the
original array.
- randomRDD(SparkContext, RandomDataGenerator<T>, long, int, long, ClassTag<T>) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
:: DeveloperApi ::
Generates an RDD comprised of i.i.d.
- RandomRDD<T> - Class in org.apache.spark.mllib.rdd
-
- RandomRDD(SparkContext, long, int, RandomDataGenerator<T>, long, ClassTag<T>) - Constructor for class org.apache.spark.mllib.rdd.RandomRDD
-
- RandomRDDPartition<T> - Class in org.apache.spark.mllib.rdd
-
- RandomRDDPartition(int, int, RandomDataGenerator<T>, long) - Constructor for class org.apache.spark.mllib.rdd.RandomRDDPartition
-
- RandomRDDs - Class in org.apache.spark.mllib.random
-
:: Experimental ::
Generator methods for creating RDDs comprised of i.i.d.
- RandomRDDs() - Constructor for class org.apache.spark.mllib.random.RandomRDDs
-
- RandomSampler<T,U> - Interface in org.apache.spark.util.random
-
:: DeveloperApi ::
A pseudorandom sampler.
- randomSplit(double[]) - Method in class org.apache.spark.api.java.JavaRDD
-
Randomly splits this RDD with the provided weights.
- randomSplit(double[], long) - Method in class org.apache.spark.api.java.JavaRDD
-
Randomly splits this RDD with the provided weights.
- randomSplit(double[], long) - Method in class org.apache.spark.rdd.RDD
-
Randomly splits this RDD with the provided weights.
- randomVectorRDD(SparkContext, RandomDataGenerator<Object>, long, int, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
:: DeveloperApi ::
Generates an RDD[Vector] with vectors containing i.i.d.
- RandomVectorRDD - Class in org.apache.spark.mllib.rdd
-
- RandomVectorRDD(SparkContext, long, int, int, RandomDataGenerator<Object>, long) - Constructor for class org.apache.spark.mllib.rdd.RandomVectorRDD
-
- RangeDependency<T> - Class in org.apache.spark
-
:: DeveloperApi ::
Represents a one-to-one dependency between ranges of partitions in the parent and child RDDs.
- RangeDependency(RDD<T>, int, int, int) - Constructor for class org.apache.spark.RangeDependency
-
- RangePartitioner<K,V> - Class in org.apache.spark
-
A
Partitioner
that partitions sortable records by range into roughly
equal ranges.
- RangePartitioner(int, RDD<? extends Product2<K, V>>, boolean, Ordering<K>, ClassTag<K>) - Constructor for class org.apache.spark.RangePartitioner
-
- rank() - Method in class org.apache.spark.graphx.lib.SVDPlusPlus.Conf
-
- rank() - Method in class org.apache.spark.mllib.recommendation.MatrixFactorizationModel
-
- RankingMetrics<T> - Class in org.apache.spark.mllib.evaluation
-
::Experimental::
Evaluator for ranking algorithms.
- RankingMetrics(RDD<Tuple2<Object, Object>>, ClassTag<T>) - Constructor for class org.apache.spark.mllib.evaluation.RankingMetrics
-
- RateLimitedOutputStream - Class in org.apache.spark.streaming.util
-
- RateLimitedOutputStream(OutputStream, int) - Constructor for class org.apache.spark.streaming.util.RateLimitedOutputStream
-
- RateLimiter - Class in org.apache.spark.streaming.receiver
-
Provides waitToPush() method to limit the rate at which receivers consume data.
- RateLimiter(SparkConf) - Constructor for class org.apache.spark.streaming.receiver.RateLimiter
-
- Rating - Class in org.apache.spark.mllib.recommendation
-
:: Experimental ::
A more compact class to represent a rating than Tuple3[Int, Int, Double].
- Rating(int, int, double) - Constructor for class org.apache.spark.mllib.recommendation.Rating
-
- rating() - Method in class org.apache.spark.mllib.recommendation.Rating
-
- ratingsForBlock() - Method in class org.apache.spark.mllib.recommendation.InLinkBlock
-
- RawInputDStream<T> - Class in org.apache.spark.streaming.dstream
-
An input stream that reads blocks of serialized objects from a given network address.
- RawInputDStream(StreamingContext, String, int, StorageLevel, ClassTag<T>) - Constructor for class org.apache.spark.streaming.dstream.RawInputDStream
-
- RawNetworkReceiver - Class in org.apache.spark.streaming.dstream
-
- RawNetworkReceiver(String, int, StorageLevel) - Constructor for class org.apache.spark.streaming.dstream.RawNetworkReceiver
-
- rawSocketStream(String, int, StorageLevel) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
Create an input stream from network source hostname:port, where data is received
as serialized blocks (serialized using the Spark's serializer) that can be directly
pushed into the block manager without deserializing them.
- rawSocketStream(String, int) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
Create an input stream from network source hostname:port, where data is received
as serialized blocks (serialized using the Spark's serializer) that can be directly
pushed into the block manager without deserializing them.
- rawSocketStream(String, int, StorageLevel, ClassTag<T>) - Method in class org.apache.spark.streaming.StreamingContext
-
Create a input stream from network source hostname:port, where data is received
as serialized blocks (serialized using the Spark's serializer) that can be directly
pushed into the block manager without deserializing them.
- RawTextHelper - Class in org.apache.spark.streaming.util
-
- RawTextHelper() - Constructor for class org.apache.spark.streaming.util.RawTextHelper
-
- RawTextSender - Class in org.apache.spark.streaming.util
-
A helper program that sends blocks of Kryo-serialized text strings out on a socket at a
specified rate.
- RawTextSender() - Constructor for class org.apache.spark.streaming.util.RawTextSender
-
- rdd() - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
- rdd() - Method in class org.apache.spark.api.java.JavaPairRDD
-
- rdd() - Method in class org.apache.spark.api.java.JavaRDD
-
- rdd() - Method in interface org.apache.spark.api.java.JavaRDDLike
-
- rdd() - Method in class org.apache.spark.Dependency
-
- rdd() - Method in class org.apache.spark.NarrowDependency
-
- rdd() - Method in class org.apache.spark.rdd.CoalescedRDDPartition
-
- rdd() - Method in class org.apache.spark.rdd.NarrowCoGroupSplitDep
-
- RDD<T> - Class in org.apache.spark.rdd
-
A Resilient Distributed Dataset (RDD), the basic abstraction in Spark.
- RDD(SparkContext, Seq<Dependency<?>>, ClassTag<T>) - Constructor for class org.apache.spark.rdd.RDD
-
- RDD(RDD<?>, ClassTag<T>) - Constructor for class org.apache.spark.rdd.RDD
-
Construct an RDD with just a one-to-one dependency on one parent
- rdd() - Method in class org.apache.spark.scheduler.Stage
-
- rdd() - Method in class org.apache.spark.ShuffleDependency
-
- rdd() - Method in class org.apache.spark.sql.api.java.JavaSchemaRDD
-
- rdd() - Method in class org.apache.spark.sql.execution.ExistingRdd
-
- rdd() - Method in class org.apache.spark.sql.execution.LogicalRDD
-
- rdd() - Method in class org.apache.spark.sql.execution.PhysicalRDD
-
- RDD() - Static method in class org.apache.spark.storage.BlockId
-
- rdd1() - Method in class org.apache.spark.rdd.CartesianRDD
-
- rdd1() - Method in class org.apache.spark.rdd.SubtractedRDD
-
- rdd1() - Method in class org.apache.spark.rdd.ZippedPartitionsRDD2
-
- rdd1() - Method in class org.apache.spark.rdd.ZippedPartitionsRDD3
-
- rdd1() - Method in class org.apache.spark.rdd.ZippedPartitionsRDD4
-
- rdd2() - Method in class org.apache.spark.rdd.CartesianRDD
-
- rdd2() - Method in class org.apache.spark.rdd.SubtractedRDD
-
- rdd2() - Method in class org.apache.spark.rdd.ZippedPartitionsRDD2
-
- rdd2() - Method in class org.apache.spark.rdd.ZippedPartitionsRDD3
-
- rdd2() - Method in class org.apache.spark.rdd.ZippedPartitionsRDD4
-
- rdd3() - Method in class org.apache.spark.rdd.ZippedPartitionsRDD3
-
- rdd3() - Method in class org.apache.spark.rdd.ZippedPartitionsRDD4
-
- rdd4() - Method in class org.apache.spark.rdd.ZippedPartitionsRDD4
-
- RDDBlockId - Class in org.apache.spark.storage
-
- RDDBlockId(int, int) - Constructor for class org.apache.spark.storage.RDDBlockId
-
- rddBlocks() - Method in class org.apache.spark.storage.StorageStatus
-
Return the RDD blocks stored in this block manager.
- rddBlocks() - Method in class org.apache.spark.ui.exec.ExecutorSummaryInfo
-
- rddBlocksById(int) - Method in class org.apache.spark.storage.StorageStatus
-
Return the blocks that belong to the given RDD stored in this block manager.
- RDDCheckpointData<T> - Class in org.apache.spark.rdd
-
This class contains all the information related to RDD checkpointing.
- RDDCheckpointData(RDD<T>, ClassTag<T>) - Constructor for class org.apache.spark.rdd.RDDCheckpointData
-
- rddCleaned(int) - Method in interface org.apache.spark.CleanerListener
-
- RDDConversions - Class in org.apache.spark.sql.execution
-
:: DeveloperApi ::
- RDDConversions() - Constructor for class org.apache.spark.sql.execution.RDDConversions
-
- RDDFunctions<T> - Class in org.apache.spark.mllib.rdd
-
Machine learning specific RDD functions.
- RDDFunctions(RDD<T>, ClassTag<T>) - Constructor for class org.apache.spark.mllib.rdd.RDDFunctions
-
- rddId() - Method in class org.apache.spark.CleanRDD
-
- rddId() - Method in class org.apache.spark.rdd.ParallelCollectionPartition
-
- rddId() - Method in class org.apache.spark.scheduler.SparkListenerUnpersistRDD
-
- rddId() - Method in class org.apache.spark.storage.BlockManagerMessages.RemoveRdd
-
- rddId() - Method in class org.apache.spark.storage.RDDBlockId
-
- RDDInfo - Class in org.apache.spark.storage
-
- RDDInfo(int, String, int, StorageLevel) - Constructor for class org.apache.spark.storage.RDDInfo
-
- rddInfoFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
-
- rddInfoList() - Method in class org.apache.spark.ui.storage.StorageListener
-
Filter RDD info to include only those with cached partitions
- rddInfos() - Method in class org.apache.spark.scheduler.StageInfo
-
- rddInfoToJson(RDDInfo) - Static method in class org.apache.spark.util.JsonProtocol
-
- RDDPage - Class in org.apache.spark.ui.storage
-
Page showing storage details for a given RDD
- RDDPage(StorageTab) - Constructor for class org.apache.spark.ui.storage.RDDPage
-
- rdds() - Method in class org.apache.spark.rdd.CoGroupedRDD
-
- rdds() - Method in class org.apache.spark.rdd.PartitionerAwareUnionRDD
-
- rdds() - Method in class org.apache.spark.rdd.PartitionerAwareUnionRDDPartition
-
- rdds() - Method in class org.apache.spark.rdd.UnionRDD
-
- rdds() - Method in class org.apache.spark.rdd.ZippedPartitionsBaseRDD
-
- rddStorageLevel(int) - Method in class org.apache.spark.storage.StorageStatus
-
Return the storage level, if any, used by the given RDD in this block manager.
- rddToAsyncRDDActions(RDD<T>, ClassTag<T>) - Static method in class org.apache.spark.SparkContext
-
- rddToFileName(String, String, Time) - Static method in class org.apache.spark.streaming.StreamingContext
-
- rddToOrderedRDDFunctions(RDD<Tuple2<K, V>>, Ordering<K>, ClassTag<K>, ClassTag<V>) - Static method in class org.apache.spark.SparkContext
-
- rddToPairRDDFunctions(RDD<Tuple2<K, V>>, ClassTag<K>, ClassTag<V>, Ordering<K>) - Static method in class org.apache.spark.SparkContext
-
- rddToSequenceFileRDDFunctions(RDD<Tuple2<K, V>>, Function1<K, Writable>, ClassTag<K>, Function1<V, Writable>, ClassTag<V>) - Static method in class org.apache.spark.SparkContext
-
- read(Kryo, Input, Class<Iterable<?>>) - Method in class org.apache.spark.serializer.JavaIterableWrapperSerializer
-
- read(Kryo, Input, Class<BigDecimal>) - Method in class org.apache.spark.sql.execution.BigDecimalSerializer
-
- read(Kryo, Input, Class<HyperLogLog>) - Method in class org.apache.spark.sql.execution.HyperLogLogSerializer
-
- read(Kryo, Input, Class<IntegerHashSet>) - Method in class org.apache.spark.sql.execution.IntegerHashSetSerializer
-
- read(Kryo, Input, Class<LongHashSet>) - Method in class org.apache.spark.sql.execution.LongHashSetSerializer
-
- read(Kryo, Input, Class<OpenHashSet<?>>) - Method in class org.apache.spark.sql.execution.OpenHashSetSerializer
-
- read(String, SparkConf, Configuration) - Static method in class org.apache.spark.streaming.CheckpointReader
-
- read(WriteAheadLogFileSegment) - Method in class org.apache.spark.streaming.util.WriteAheadLogRandomReader
-
- read() - Method in class org.apache.spark.util.ByteBufferInputStream
-
- read(byte[]) - Method in class org.apache.spark.util.ByteBufferInputStream
-
- read(byte[], int, int) - Method in class org.apache.spark.util.ByteBufferInputStream
-
- readBatches() - Method in class org.apache.spark.sql.columnar.InMemoryColumnarTableScan
-
- readExternal(ObjectInput) - Method in class org.apache.spark.scheduler.CompressedMapStatus
-
- readExternal(ObjectInput) - Method in class org.apache.spark.scheduler.DirectTaskResult
-
- readExternal(ObjectInput) - Method in class org.apache.spark.scheduler.HighlyCompressedMapStatus
-
- readExternal(ObjectInput) - Method in class org.apache.spark.serializer.JavaSerializer
-
- readExternal(ObjectInput) - Method in class org.apache.spark.sql.hive.HiveFunctionWrapper
-
- readExternal(ObjectInput) - Method in class org.apache.spark.storage.BlockManagerId
-
- readExternal(ObjectInput) - Method in class org.apache.spark.storage.BlockManagerMessages.UpdateBlockInfo
-
- readExternal(ObjectInput) - Method in class org.apache.spark.storage.StorageLevel
-
- readExternal(ObjectInput) - Static method in class org.apache.spark.streaming.flume.EventTransformer
-
- readExternal(ObjectInput) - Method in class org.apache.spark.streaming.flume.SparkFlumeEvent
-
- readFromFile(Path, Broadcast<SerializableWritable<Configuration>>, TaskContext) - Static method in class org.apache.spark.rdd.CheckpointRDD
-
- readFromLog() - Method in class org.apache.spark.streaming.util.WriteAheadLogManager
-
Read all the existing logs from the log directory.
- readLock(Function0<A>) - Method in interface org.apache.spark.sql.CacheManager
-
Acquires a read lock on the cache for the duration of `f`.
- readMetaData(Path, Option<Configuration>) - Static method in class org.apache.spark.sql.parquet.ParquetTypesConverter
-
Try to read Parquet metadata at the given Path.
- readObject(ClassTag<T>) - Method in class org.apache.spark.serializer.DeserializationStream
-
- readObject(ClassTag<T>) - Method in class org.apache.spark.serializer.JavaDeserializationStream
-
- readObject(ClassTag<T>) - Method in class org.apache.spark.serializer.KryoDeserializationStream
-
- readPartitions() - Method in class org.apache.spark.sql.columnar.InMemoryColumnarTableScan
-
- readSchemaFromFile(Path, Option<Configuration>, boolean) - Static method in class org.apache.spark.sql.parquet.ParquetTypesConverter
-
Reads in Parquet Metadata from the given path and tries to extract the schema
(Catalyst attributes) from the application-specific key-value map.
- ready(Duration, CanAwait) - Method in class org.apache.spark.ComplexFutureAction
-
- ready(Duration, CanAwait) - Method in interface org.apache.spark.FutureAction
-
Blocks until this action completes.
- ready(Duration, CanAwait) - Method in class org.apache.spark.SimpleFutureAction
-
- RealClock - Class in org.apache.spark
-
A clock backed by a monotonically increasing time source.
- RealClock() - Constructor for class org.apache.spark.RealClock
-
- reason() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RemoveExecutor
-
- reason() - Method in class org.apache.spark.scheduler.CompletionEvent
-
- reason() - Method in class org.apache.spark.scheduler.SparkListenerTaskEnd
-
- reason() - Method in class org.apache.spark.scheduler.TaskSetFailed
-
- recache() - Method in class org.apache.spark.sql.columnar.InMemoryRelation
-
- Recall - Class in org.apache.spark.mllib.evaluation.binary
-
Recall.
- Recall() - Constructor for class org.apache.spark.mllib.evaluation.binary.Recall
-
- recall(double) - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
-
Returns recall for a given label (category)
- recall() - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
-
Returns recall
(equals to precision for multiclass classifier
because sum of all false positives is equal to sum
of all false negatives)
- recall() - Method in class org.apache.spark.mllib.evaluation.MultilabelMetrics
-
Returns document-based recall averaged by the number of documents
- recall(double) - Method in class org.apache.spark.mllib.evaluation.MultilabelMetrics
-
Returns recall for a given label (category)
- recallByThreshold() - Method in class org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
-
Returns the (threshold, recall) curve.
- receive() - Method in class org.apache.spark.scheduler.DAGSchedulerActorSupervisor
-
- receive() - Method in class org.apache.spark.scheduler.DAGSchedulerEventProcessActor
-
The main event loop of the DAG scheduler.
- receive() - Method in class org.apache.spark.streaming.dstream.SocketReceiver
-
Create a socket connection and receive data until receiver is stopped
- receive() - Method in class org.apache.spark.streaming.receiver.ActorReceiver.Supervisor
-
- receive() - Method in class org.apache.spark.streaming.zeromq.ZeroMQReceiver
-
- receive() - Method in interface org.apache.spark.util.ActorLogReceive
-
- ReceivedBlock - Interface in org.apache.spark.streaming.receiver
-
Trait representing a received block
- ReceivedBlockHandler - Interface in org.apache.spark.streaming.receiver
-
Trait that represents a class that handles the storage of blocks received by receiver
- receivedBlockInfo() - Method in class org.apache.spark.streaming.scheduler.AddBlock
-
- receivedBlockInfo() - Method in class org.apache.spark.streaming.scheduler.BatchInfo
-
- receivedBlockInfo() - Method in class org.apache.spark.streaming.scheduler.BlockAdditionEvent
-
- receivedBlockInfo() - Method in class org.apache.spark.streaming.scheduler.JobSet
-
- ReceivedBlockInfo - Class in org.apache.spark.streaming.scheduler
-
Information about blocks received by the receiver
- ReceivedBlockInfo(int, long, ReceivedBlockStoreResult) - Constructor for class org.apache.spark.streaming.scheduler.ReceivedBlockInfo
-
- ReceivedBlockStoreResult - Interface in org.apache.spark.streaming.receiver
-
Trait that represents the metadata related to storage of blocks
- ReceivedBlockTracker - Class in org.apache.spark.streaming.scheduler
-
Class that keep track of all the received blocks, and allocate them to batches
when required.
- ReceivedBlockTracker(SparkConf, Configuration, Seq<Object>, Clock, Option<String>) - Constructor for class org.apache.spark.streaming.scheduler.ReceivedBlockTracker
-
- ReceivedBlockTrackerLogEvent - Interface in org.apache.spark.streaming.scheduler
-
Trait representing any event in the ReceivedBlockTracker that updates its state.
- receivedRecordsDistributions() - Method in class org.apache.spark.streaming.ui.StreamingJobProgressListener
-
- Receiver<T> - Class in org.apache.spark.streaming.receiver
-
:: DeveloperApi ::
Abstract class of a receiver that can be run on worker nodes to receive external data.
- Receiver(StorageLevel) - Constructor for class org.apache.spark.streaming.receiver.Receiver
-
- receiverActor() - Method in class org.apache.spark.streaming.scheduler.RegisterReceiver
-
- receiverExecutor() - Method in class org.apache.spark.streaming.flume.FlumePollingReceiver
-
- ReceiverInfo - Class in org.apache.spark.streaming.scheduler
-
:: DeveloperApi ::
Class having information about a receiver
- ReceiverInfo(int, String, ActorRef, boolean, String, String, String) - Constructor for class org.apache.spark.streaming.scheduler.ReceiverInfo
-
- receiverInfo() - Method in class org.apache.spark.streaming.scheduler.StreamingListenerReceiverError
-
- receiverInfo() - Method in class org.apache.spark.streaming.scheduler.StreamingListenerReceiverStarted
-
- receiverInfo() - Method in class org.apache.spark.streaming.scheduler.StreamingListenerReceiverStopped
-
- receiverInfo(int) - Method in class org.apache.spark.streaming.ui.StreamingJobProgressListener
-
- receiverInputDStream() - Method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- receiverInputDStream() - Method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- ReceiverInputDStream<T> - Class in org.apache.spark.streaming.dstream
-
Abstract class for defining any
InputDStream
that has to start a receiver on worker nodes to receive external data.
- ReceiverInputDStream(StreamingContext, ClassTag<T>) - Constructor for class org.apache.spark.streaming.dstream.ReceiverInputDStream
-
- ReceiverMessage - Interface in org.apache.spark.streaming.receiver
-
Messages sent to the Receiver.
- ReceiverState() - Method in class org.apache.spark.streaming.receiver.ReceiverSupervisor
-
- receiverState() - Method in class org.apache.spark.streaming.receiver.ReceiverSupervisor
-
State of the receiver
- receiverStream(Receiver<T>) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
Create an input stream with any arbitrary user implemented receiver.
- receiverStream(Receiver<T>, ClassTag<T>) - Method in class org.apache.spark.streaming.StreamingContext
-
Create an input stream with any arbitrary user implemented receiver.
- ReceiverSupervisor - Class in org.apache.spark.streaming.receiver
-
Abstract class that is responsible for supervising a Receiver in the worker.
- ReceiverSupervisor(Receiver<?>, SparkConf) - Constructor for class org.apache.spark.streaming.receiver.ReceiverSupervisor
-
- ReceiverSupervisor.ReceiverState - Class in org.apache.spark.streaming.receiver
-
- ReceiverSupervisor.ReceiverState() - Constructor for class org.apache.spark.streaming.receiver.ReceiverSupervisor.ReceiverState
-
Enumeration to identify current state of the StreamingContext
- ReceiverSupervisorImpl - Class in org.apache.spark.streaming.receiver
-
Concrete implementation of
ReceiverSupervisor
which provides all the necessary functionality for handling the data received by
the receiver.
- ReceiverSupervisorImpl(Receiver<?>, SparkEnv, Configuration, Option<String>) - Constructor for class org.apache.spark.streaming.receiver.ReceiverSupervisorImpl
-
- receiverTracker() - Method in class org.apache.spark.streaming.scheduler.JobScheduler
-
- ReceiverTracker - Class in org.apache.spark.streaming.scheduler
-
This class manages the execution of the receivers of ReceiverInputDStreams.
- ReceiverTracker(StreamingContext, boolean) - Constructor for class org.apache.spark.streaming.scheduler.ReceiverTracker
-
- ReceiverTracker.ReceiverLauncher - Class in org.apache.spark.streaming.scheduler
-
This thread class runs all the receivers on the cluster.
- ReceiverTracker.ReceiverLauncher() - Constructor for class org.apache.spark.streaming.scheduler.ReceiverTracker.ReceiverLauncher
-
- ReceiverTrackerMessage - Interface in org.apache.spark.streaming.scheduler
-
Messages used by the NetworkReceiver and the ReceiverTracker to communicate
with each other.
- receiveWithLogging() - Method in class org.apache.spark.HeartbeatReceiver
-
- receiveWithLogging() - Method in class org.apache.spark.MapOutputTrackerMasterActor
-
- receiveWithLogging() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend.DriverActor
-
- receiveWithLogging() - Method in class org.apache.spark.scheduler.local.LocalActor
-
- receiveWithLogging() - Method in class org.apache.spark.storage.BlockManagerMasterActor
-
- receiveWithLogging() - Method in class org.apache.spark.storage.BlockManagerSlaveActor
-
- receiveWithLogging() - Method in interface org.apache.spark.util.ActorLogReceive
-
- recentExceptions() - Method in class org.apache.spark.scheduler.TaskSetManager
-
- recommendProducts(int, int) - Method in class org.apache.spark.mllib.recommendation.MatrixFactorizationModel
-
Recommends products to a user.
- recommendUsers(int, int) - Method in class org.apache.spark.mllib.recommendation.MatrixFactorizationModel
-
Recommends users to a product.
- recomputeLocality() - Method in class org.apache.spark.scheduler.TaskSetManager
-
- RECORD_LENGTH_PROPERTY() - Static method in class org.apache.spark.input.FixedLengthBinaryInputFormat
-
Property name to set in Hadoop JobConfs for record length
- recordProcessorFactory() - Method in class org.apache.spark.streaming.kinesis.KinesisReceiver
-
- RECORDS_BETWEEN_BYTES_READ_METRIC_UPDATES() - Static method in class org.apache.spark.rdd.HadoopRDD
-
Update the input bytes read metric each time this number of records has been read
- RECORDS_BETWEEN_BYTES_WRITTEN_METRIC_UPDATES() - Static method in class org.apache.spark.rdd.PairRDDFunctions
-
- RecurringTimer - Class in org.apache.spark.streaming.util
-
- RecurringTimer(Clock, long, Function1<Object, BoxedUnit>, String) - Constructor for class org.apache.spark.streaming.util.RecurringTimer
-
- RedirectThread - Class in org.apache.spark.util
-
A utility class to redirect the child process's stdout or stderr.
- RedirectThread(InputStream, OutputStream, String, boolean) - Constructor for class org.apache.spark.util.RedirectThread
-
- reduce(Function2<T, T, T>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Reduces the elements of this RDD using the specified commutative and associative binary
operator.
- reduce(Function2<T, T, T>) - Method in class org.apache.spark.rdd.RDD
-
Reduces the elements of this RDD using the specified commutative and
associative binary operator.
- reduce(Function2<T, T, T>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Return a new DStream in which each RDD has a single element generated by reducing each RDD
of this DStream.
- reduce(Function2<T, T, T>) - Method in class org.apache.spark.streaming.dstream.DStream
-
Return a new DStream in which each RDD has a single element generated by reducing each RDD
of this DStream.
- reduceByKey(Partitioner, Function2<V, V, V>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Merge the values for each key using an associative reduce function.
- reduceByKey(Function2<V, V, V>, int) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Merge the values for each key using an associative reduce function.
- reduceByKey(Function2<V, V, V>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Merge the values for each key using an associative reduce function.
- reduceByKey(Partitioner, Function2<V, V, V>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Merge the values for each key using an associative reduce function.
- reduceByKey(Function2<V, V, V>, int) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Merge the values for each key using an associative reduce function.
- reduceByKey(Function2<V, V, V>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Merge the values for each key using an associative reduce function.
- reduceByKey(Function2<V, V, V>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying reduceByKey
to each RDD.
- reduceByKey(Function2<V, V, V>, int) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying reduceByKey
to each RDD.
- reduceByKey(Function2<V, V, V>, Partitioner) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying reduceByKey
to each RDD.
- reduceByKey(Function2<V, V, V>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying reduceByKey
to each RDD.
- reduceByKey(Function2<V, V, V>, int) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying reduceByKey
to each RDD.
- reduceByKey(Function2<V, V, V>, Partitioner) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying reduceByKey
to each RDD.
- reduceByKeyAndWindow(Function2<V, V, V>, Duration) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Create a new DStream by applying reduceByKey
over a sliding window on this
DStream.
- reduceByKeyAndWindow(Function2<V, V, V>, Duration, Duration) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying reduceByKey
over a sliding window.
- reduceByKeyAndWindow(Function2<V, V, V>, Duration, Duration, int) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying reduceByKey
over a sliding window.
- reduceByKeyAndWindow(Function2<V, V, V>, Duration, Duration, Partitioner) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying reduceByKey
over a sliding window.
- reduceByKeyAndWindow(Function2<V, V, V>, Function2<V, V, V>, Duration, Duration) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by reducing over a using incremental computation.
- reduceByKeyAndWindow(Function2<V, V, V>, Function2<V, V, V>, Duration, Duration, int, Function<Tuple2<K, V>, Boolean>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying incremental reduceByKey
over a sliding window.
- reduceByKeyAndWindow(Function2<V, V, V>, Function2<V, V, V>, Duration, Duration, Partitioner, Function<Tuple2<K, V>, Boolean>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying incremental reduceByKey
over a sliding window.
- reduceByKeyAndWindow(Function2<V, V, V>, Duration) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying reduceByKey
over a sliding window on this
DStream.
- reduceByKeyAndWindow(Function2<V, V, V>, Duration, Duration) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying reduceByKey
over a sliding window.
- reduceByKeyAndWindow(Function2<V, V, V>, Duration, Duration, int) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying reduceByKey
over a sliding window.
- reduceByKeyAndWindow(Function2<V, V, V>, Duration, Duration, Partitioner) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying reduceByKey
over a sliding window.
- reduceByKeyAndWindow(Function2<V, V, V>, Function2<V, V, V>, Duration, Duration, int, Function1<Tuple2<K, V>, Object>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying incremental reduceByKey
over a sliding window.
- reduceByKeyAndWindow(Function2<V, V, V>, Function2<V, V, V>, Duration, Duration, Partitioner, Function1<Tuple2<K, V>, Object>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying incremental reduceByKey
over a sliding window.
- reduceByKeyLocally(Function2<V, V, V>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Merge the values for each key using an associative reduce function, but return the results
immediately to the master as a Map.
- reduceByKeyLocally(Function2<V, V, V>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Merge the values for each key using an associative reduce function, but return the results
immediately to the master as a Map.
- reduceByKeyToDriver(Function2<V, V, V>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Alias for reduceByKeyLocally
- reduceByWindow(Function2<T, T, T>, Duration, Duration) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Return a new DStream in which each RDD has a single element generated by reducing all
elements in a sliding window over this DStream.
- reduceByWindow(Function2<T, T, T>, Function2<T, T, T>, Duration, Duration) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Return a new DStream in which each RDD has a single element generated by reducing all
elements in a sliding window over this DStream.
- reduceByWindow(Function2<T, T, T>, Duration, Duration) - Method in class org.apache.spark.streaming.dstream.DStream
-
Return a new DStream in which each RDD has a single element generated by reducing all
elements in a sliding window over this DStream.
- reduceByWindow(Function2<T, T, T>, Function2<T, T, T>, Duration, Duration) - Method in class org.apache.spark.streaming.dstream.DStream
-
Return a new DStream in which each RDD has a single element generated by reducing all
elements in a sliding window over this DStream.
- reducedStream() - Method in class org.apache.spark.streaming.dstream.ReducedWindowedDStream
-
- ReducedWindowedDStream<K,V> - Class in org.apache.spark.streaming.dstream
-
- ReducedWindowedDStream(DStream<Tuple2<K, V>>, Function2<V, V, V>, Function2<V, V, V>, Option<Function1<Tuple2<K, V>, Object>>, Duration, Duration, Partitioner, ClassTag<K>, ClassTag<V>) - Constructor for class org.apache.spark.streaming.dstream.ReducedWindowedDStream
-
- reduceId() - Method in class org.apache.spark.FetchFailed
-
- reduceId() - Method in class org.apache.spark.storage.ShuffleBlockId
-
- reduceId() - Method in class org.apache.spark.storage.ShuffleDataBlockId
-
- reduceId() - Method in class org.apache.spark.storage.ShuffleIndexBlockId
-
- REGEX() - Static method in class org.apache.spark.streaming.Checkpoint
-
- REGEXP() - Static method in class org.apache.spark.sql.hive.HiveQl
-
- register(Accumulable<?, ?>, boolean) - Static method in class org.apache.spark.Accumulators
-
- register() - Method in class org.apache.spark.streaming.dstream.DStream
-
Register this streaming as an output stream.
- register(Logger) - Static method in class org.apache.spark.util.SignalLogger
-
Register a signal handler to log signals on UNIX-like systems.
- registerAsTable(String) - Method in interface org.apache.spark.sql.SchemaRDDLike
-
- registerBlockManager(BlockManagerId, long, ActorRef) - Method in class org.apache.spark.storage.BlockManagerMaster
-
Register the BlockManager's id with the driver.
- registerBroadcastForCleanup(Broadcast<T>) - Method in class org.apache.spark.ContextCleaner
-
Register a Broadcast for cleanup when it is garbage collected.
- registerClasses(Kryo) - Method in class org.apache.spark.graphx.GraphKryoRegistrator
-
- registerClasses(Kryo) - Method in interface org.apache.spark.serializer.KryoRegistrator
-
- registered(SchedulerDriver, Protos.FrameworkID, Protos.MasterInfo) - Method in class org.apache.spark.scheduler.cluster.mesos.CoarseMesosSchedulerBackend
-
- registered(SchedulerDriver, Protos.FrameworkID, Protos.MasterInfo) - Method in class org.apache.spark.scheduler.cluster.mesos.MesosSchedulerBackend
-
- registeredLock() - Method in class org.apache.spark.scheduler.cluster.mesos.CoarseMesosSchedulerBackend
-
- registeredLock() - Method in class org.apache.spark.scheduler.cluster.mesos.MesosSchedulerBackend
-
- registerFunction(String, UDF1<?, ?>, DataType) - Method in interface org.apache.spark.sql.api.java.UDFRegistration
-
- registerFunction(String, UDF2<?, ?, ?>, DataType) - Method in interface org.apache.spark.sql.api.java.UDFRegistration
-
- registerFunction(String, UDF3<?, ?, ?, ?>, DataType) - Method in interface org.apache.spark.sql.api.java.UDFRegistration
-
- registerFunction(String, UDF4<?, ?, ?, ?, ?>, DataType) - Method in interface org.apache.spark.sql.api.java.UDFRegistration
-
- registerFunction(String, UDF5<?, ?, ?, ?, ?, ?>, DataType) - Method in interface org.apache.spark.sql.api.java.UDFRegistration
-
- registerFunction(String, UDF6<?, ?, ?, ?, ?, ?, ?>, DataType) - Method in interface org.apache.spark.sql.api.java.UDFRegistration
-
- registerFunction(String, UDF7<?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in interface org.apache.spark.sql.api.java.UDFRegistration
-
- registerFunction(String, UDF8<?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in interface org.apache.spark.sql.api.java.UDFRegistration
-
- registerFunction(String, UDF9<?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in interface org.apache.spark.sql.api.java.UDFRegistration
-
- registerFunction(String, UDF10<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in interface org.apache.spark.sql.api.java.UDFRegistration
-
- registerFunction(String, UDF11<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in interface org.apache.spark.sql.api.java.UDFRegistration
-
- registerFunction(String, UDF12<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in interface org.apache.spark.sql.api.java.UDFRegistration
-
- registerFunction(String, UDF13<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in interface org.apache.spark.sql.api.java.UDFRegistration
-
- registerFunction(String, UDF14<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in interface org.apache.spark.sql.api.java.UDFRegistration
-
- registerFunction(String, UDF15<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in interface org.apache.spark.sql.api.java.UDFRegistration
-
- registerFunction(String, UDF16<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in interface org.apache.spark.sql.api.java.UDFRegistration
-
- registerFunction(String, UDF17<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in interface org.apache.spark.sql.api.java.UDFRegistration
-
- registerFunction(String, UDF18<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in interface org.apache.spark.sql.api.java.UDFRegistration
-
- registerFunction(String, UDF19<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in interface org.apache.spark.sql.api.java.UDFRegistration
-
- registerFunction(String, UDF20<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in interface org.apache.spark.sql.api.java.UDFRegistration
-
- registerFunction(String, UDF21<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in interface org.apache.spark.sql.api.java.UDFRegistration
-
- registerFunction(String, UDF22<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in interface org.apache.spark.sql.api.java.UDFRegistration
-
- registerFunction(String, Function1<?, T>, TypeTags.TypeTag<T>) - Method in interface org.apache.spark.sql.UDFRegistration
-
registerFunction 1-22 were generated by this script
- registerFunction(String, Function2<?, ?, T>, TypeTags.TypeTag<T>) - Method in interface org.apache.spark.sql.UDFRegistration
-
- registerFunction(String, Function3<?, ?, ?, T>, TypeTags.TypeTag<T>) - Method in interface org.apache.spark.sql.UDFRegistration
-
- registerFunction(String, Function4<?, ?, ?, ?, T>, TypeTags.TypeTag<T>) - Method in interface org.apache.spark.sql.UDFRegistration
-
- registerFunction(String, Function5<?, ?, ?, ?, ?, T>, TypeTags.TypeTag<T>) - Method in interface org.apache.spark.sql.UDFRegistration
-
- registerFunction(String, Function6<?, ?, ?, ?, ?, ?, T>, TypeTags.TypeTag<T>) - Method in interface org.apache.spark.sql.UDFRegistration
-
- registerFunction(String, Function7<?, ?, ?, ?, ?, ?, ?, T>, TypeTags.TypeTag<T>) - Method in interface org.apache.spark.sql.UDFRegistration
-
- registerFunction(String, Function8<?, ?, ?, ?, ?, ?, ?, ?, T>, TypeTags.TypeTag<T>) - Method in interface org.apache.spark.sql.UDFRegistration
-
- registerFunction(String, Function9<?, ?, ?, ?, ?, ?, ?, ?, ?, T>, TypeTags.TypeTag<T>) - Method in interface org.apache.spark.sql.UDFRegistration
-
- registerFunction(String, Function10<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, T>, TypeTags.TypeTag<T>) - Method in interface org.apache.spark.sql.UDFRegistration
-
- registerFunction(String, Function11<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, T>, TypeTags.TypeTag<T>) - Method in interface org.apache.spark.sql.UDFRegistration
-
- registerFunction(String, Function12<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, T>, TypeTags.TypeTag<T>) - Method in interface org.apache.spark.sql.UDFRegistration
-
- registerFunction(String, Function13<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, T>, TypeTags.TypeTag<T>) - Method in interface org.apache.spark.sql.UDFRegistration
-
- registerFunction(String, Function14<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, T>, TypeTags.TypeTag<T>) - Method in interface org.apache.spark.sql.UDFRegistration
-
- registerFunction(String, Function15<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, T>, TypeTags.TypeTag<T>) - Method in interface org.apache.spark.sql.UDFRegistration
-
- registerFunction(String, Function16<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, T>, TypeTags.TypeTag<T>) - Method in interface org.apache.spark.sql.UDFRegistration
-
- registerFunction(String, Function17<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, T>, TypeTags.TypeTag<T>) - Method in interface org.apache.spark.sql.UDFRegistration
-
- registerFunction(String, Function18<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, T>, TypeTags.TypeTag<T>) - Method in interface org.apache.spark.sql.UDFRegistration
-
- registerFunction(String, Function19<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, T>, TypeTags.TypeTag<T>) - Method in interface org.apache.spark.sql.UDFRegistration
-
- registerFunction(String, Function20<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, T>, TypeTags.TypeTag<T>) - Method in interface org.apache.spark.sql.UDFRegistration
-
- registerFunction(String, Function21<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, T>, TypeTags.TypeTag<T>) - Method in interface org.apache.spark.sql.UDFRegistration
-
- registerFunction(String, Function22<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, T>, TypeTags.TypeTag<T>) - Method in interface org.apache.spark.sql.UDFRegistration
-
- registerKryoClasses(SparkConf) - Static method in class org.apache.spark.graphx.GraphXUtils
-
Registers classes that GraphX uses with Kryo.
- registerKryoClasses(Class<?>[]) - Method in class org.apache.spark.SparkConf
-
Use Kryo serialization and register the given set of classes with Kryo.
- registerMapOutput(int, int, MapStatus) - Method in class org.apache.spark.MapOutputTrackerMaster
-
- registerMapOutputs(int, MapStatus[], boolean) - Method in class org.apache.spark.MapOutputTrackerMaster
-
Register multiple map output information for the given shuffle
- registerPython(String, byte[], Map<String, String>, List<String>, String, List<Broadcast<PythonBroadcast>>, Accumulator<List<byte[]>>, String) - Method in interface org.apache.spark.sql.UDFRegistration
-
- registerRDDAsTable(JavaSchemaRDD, String) - Method in class org.apache.spark.sql.api.java.JavaSQLContext
-
Registers the given RDD as a temporary table in the catalog.
- registerRDDAsTable(SchemaRDD, String) - Method in class org.apache.spark.sql.SQLContext
-
Registers the given RDD as a temporary table in the catalog.
- registerRDDForCleanup(RDD<?>) - Method in class org.apache.spark.ContextCleaner
-
Register a RDD for cleanup when it is garbage collected.
- RegisterReceiver - Class in org.apache.spark.streaming.scheduler
-
- RegisterReceiver(int, String, String, ActorRef) - Constructor for class org.apache.spark.streaming.scheduler.RegisterReceiver
-
- registerShuffle(int, int) - Method in class org.apache.spark.MapOutputTrackerMaster
-
- registerShuffleForCleanup(ShuffleDependency<?, ?, ?>) - Method in class org.apache.spark.ContextCleaner
-
Register a ShuffleDependency for cleanup when it is garbage collected.
- registerShutdownDeleteDir(File) - Static method in class org.apache.spark.util.Utils
-
- registerShutdownDeleteDir(TachyonFile) - Static method in class org.apache.spark.util.Utils
-
- registerSource(Source) - Method in class org.apache.spark.metrics.MetricsSystem
-
- registerTable(Seq<String>, LogicalPlan) - Method in class org.apache.spark.sql.hive.HiveMetastoreCatalog
-
UNIMPLEMENTED: It needs to be decided how we will persist in-memory tables to the metastore.
- registerTempTable(String) - Method in interface org.apache.spark.sql.SchemaRDDLike
-
Registers this RDD as a temporary table using the given name.
- registerTestTable(TestHiveContext.TestTable) - Method in class org.apache.spark.sql.hive.test.TestHiveContext
-
- registrationDone() - Method in class org.apache.spark.scheduler.cluster.SparkDeploySchedulerBackend
-
- registrationLock() - Method in class org.apache.spark.scheduler.cluster.SparkDeploySchedulerBackend
-
- registry() - Method in class org.apache.spark.metrics.sink.ConsoleSink
-
- registry() - Method in class org.apache.spark.metrics.sink.CsvSink
-
- registry() - Method in class org.apache.spark.metrics.sink.GraphiteSink
-
- registry() - Method in class org.apache.spark.metrics.sink.JmxSink
-
- registry() - Method in class org.apache.spark.metrics.sink.MetricsServlet
-
- regParam() - Method in interface org.apache.spark.ml.param.HasRegParam
-
param for regularization parameter
- Regression() - Static method in class org.apache.spark.mllib.tree.configuration.Algo
-
- RegressionMetrics - Class in org.apache.spark.mllib.evaluation
-
:: Experimental ::
Evaluator for regression.
- RegressionMetrics(RDD<Tuple2<Object, Object>>) - Constructor for class org.apache.spark.mllib.evaluation.RegressionMetrics
-
- RegressionModel - Interface in org.apache.spark.mllib.regression
-
- reindex() - Method in class org.apache.spark.graphx.impl.VertexPartitionBaseOps
-
Construct a new VertexPartition whose index contains only the vertices in the mask.
- reindex() - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- reindex() - Method in class org.apache.spark.graphx.VertexRDD
-
Construct a new VertexRDD that is indexed by only the visible vertices.
- relation() - Method in class org.apache.spark.sql.columnar.InMemoryColumnarTableScan
-
- relation() - Method in class org.apache.spark.sql.hive.execution.HiveTableScan
-
- relation() - Method in class org.apache.spark.sql.parquet.InsertIntoParquetTable
-
- relation() - Method in class org.apache.spark.sql.parquet.ParquetTableScan
-
- relation() - Method in class org.apache.spark.sql.sources.LogicalRelation
-
- RelationProvider - Interface in org.apache.spark.sql.sources
-
::DeveloperApi::
Implemented by objects that produce relations for a specific kind of data source.
- relativeDirection(long) - Method in class org.apache.spark.graphx.Edge
-
Return the relative direction of the edge to the corresponding
vertex.
- releasePythonWorker(String, Map<String, String>, Socket) - Method in class org.apache.spark.SparkEnv
-
- releaseUnrollMemoryForThisThread(long) - Method in class org.apache.spark.storage.MemoryStore
-
Release memory used by this thread for unrolling blocks.
- ReliableKafkaReceiver<K,V,U extends kafka.serializer.Decoder<?>,T extends kafka.serializer.Decoder<?>> - Class in org.apache.spark.streaming.kafka
-
ReliableKafkaReceiver offers the ability to reliably store data into BlockManager without loss.
- ReliableKafkaReceiver(Map<String, String>, Map<String, Object>, StorageLevel, ClassTag<K>, ClassTag<V>, ClassTag<U>, ClassTag<T>) - Constructor for class org.apache.spark.streaming.kafka.ReliableKafkaReceiver
-
- remainingMem() - Method in class org.apache.spark.storage.BlockManagerInfo
-
- remember(Duration) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
Sets each DStreams in this context to remember RDDs it generated in the last given duration.
- remember(Duration) - Method in class org.apache.spark.streaming.dstream.DStream
-
- remember(Duration) - Method in class org.apache.spark.streaming.DStreamGraph
-
- remember(Duration) - Method in class org.apache.spark.streaming.StreamingContext
-
Set each DStreams in this context to remember RDDs it generated in the last given duration.
- rememberDuration() - Method in class org.apache.spark.streaming.dstream.DStream
-
- rememberDuration() - Method in class org.apache.spark.streaming.DStreamGraph
-
- remove(String) - Method in class org.apache.spark.SparkConf
-
Remove a parameter from the configuration
- remove(BlockId) - Method in class org.apache.spark.storage.BlockStore
-
Remove a block, if it exists.
- remove(BlockId) - Method in class org.apache.spark.storage.DiskStore
-
- remove(BlockId) - Method in class org.apache.spark.storage.MemoryStore
-
- remove(BlockId) - Method in class org.apache.spark.storage.TachyonStore
-
- removeBlock(BlockId, boolean) - Method in class org.apache.spark.storage.BlockManager
-
Remove a block from both memory and disk.
- removeBlock(BlockId) - Method in class org.apache.spark.storage.BlockManagerInfo
-
- removeBlock(BlockId) - Method in class org.apache.spark.storage.BlockManagerMaster
-
Remove a block from the slaves that have it.
- removeBlock(BlockId) - Method in class org.apache.spark.storage.StorageStatus
-
Remove the given block from this storage status.
- removeBlocks() - Method in class org.apache.spark.rdd.BlockRDD
-
Remove the data blocks that this BlockRDD is made from.
- removeBroadcast(long, boolean) - Method in class org.apache.spark.storage.BlockManager
-
Remove all blocks belonging to the given broadcast.
- removeBroadcast(long, boolean, boolean) - Method in class org.apache.spark.storage.BlockManagerMaster
-
Remove all blocks belonging to the given broadcast.
- removeExecutor(String, String) - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend.DriverActor
-
- removeExecutor(String, String) - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend
-
- removeExecutor(String) - Method in class org.apache.spark.storage.BlockManagerMaster
-
Remove a dead executor from the driver actor.
- removeFile(TachyonFile) - Method in class org.apache.spark.storage.TachyonBlockManager
-
- removeFromDriver() - Method in class org.apache.spark.storage.BlockManagerMessages.RemoveBroadcast
-
- removeOutputLoc(int, BlockManagerId) - Method in class org.apache.spark.scheduler.Stage
-
- removeOutputsOnExecutor(String) - Method in class org.apache.spark.scheduler.Stage
-
Removes all shuffle outputs associated with this executor.
- removeRdd(int) - Method in class org.apache.spark.storage.BlockManager
-
Remove all blocks belonging to the given RDD.
- removeRdd(int, boolean) - Method in class org.apache.spark.storage.BlockManagerMaster
-
Remove all blocks belonging to the given RDD.
- removeRunningTask(long) - Method in class org.apache.spark.scheduler.TaskSetManager
-
If the given task ID is in the set of running tasks, removes it.
- removeSchedulable(Schedulable) - Method in class org.apache.spark.scheduler.Pool
-
- removeSchedulable(Schedulable) - Method in interface org.apache.spark.scheduler.Schedulable
-
- removeSchedulable(Schedulable) - Method in class org.apache.spark.scheduler.TaskSetManager
-
- removeShuffle(int, boolean) - Method in class org.apache.spark.storage.BlockManagerMaster
-
Remove all blocks belonging to the given shuffle.
- removeSource(Source) - Method in class org.apache.spark.metrics.MetricsSystem
-
- render(HttpServletRequest) - Method in class org.apache.spark.streaming.ui.StreamingPage
-
Render the page
- render(HttpServletRequest) - Method in class org.apache.spark.ui.env.EnvironmentPage
-
- render(HttpServletRequest) - Method in class org.apache.spark.ui.exec.ExecutorsPage
-
- render(HttpServletRequest) - Method in class org.apache.spark.ui.exec.ExecutorThreadDumpPage
-
- render(HttpServletRequest) - Method in class org.apache.spark.ui.jobs.AllJobsPage
-
- render(HttpServletRequest) - Method in class org.apache.spark.ui.jobs.AllStagesPage
-
- render(HttpServletRequest) - Method in class org.apache.spark.ui.jobs.JobPage
-
- render(HttpServletRequest) - Method in class org.apache.spark.ui.jobs.PoolPage
-
- render(HttpServletRequest) - Method in class org.apache.spark.ui.jobs.StagePage
-
- render(HttpServletRequest) - Method in class org.apache.spark.ui.storage.RDDPage
-
- render(HttpServletRequest) - Method in class org.apache.spark.ui.storage.StoragePage
-
- render(HttpServletRequest) - Method in class org.apache.spark.ui.WebUIPage
-
- renderJson(HttpServletRequest) - Method in class org.apache.spark.ui.WebUIPage
-
- repartition(int) - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Return a new RDD that has exactly numPartitions partitions.
- repartition(int) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Return a new RDD that has exactly numPartitions partitions.
- repartition(int) - Method in class org.apache.spark.api.java.JavaRDD
-
Return a new RDD that has exactly numPartitions partitions.
- repartition(int, Ordering<T>) - Method in class org.apache.spark.rdd.RDD
-
Return a new RDD that has exactly numPartitions partitions.
- repartition(int) - Method in class org.apache.spark.sql.api.java.JavaSchemaRDD
-
Return a new RDD that has exactly numPartitions
partitions.
- repartition(int, Ordering<Row>) - Method in class org.apache.spark.sql.SchemaRDD
-
- repartition(int) - Method in class org.apache.spark.streaming.api.java.JavaDStream
-
Return a new DStream with an increased or decreased level of parallelism.
- repartition(int) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream with an increased or decreased level of parallelism.
- repartition(int) - Method in class org.apache.spark.streaming.dstream.DStream
-
Return a new DStream with an increased or decreased level of parallelism.
- repartitionAndSortWithinPartitions(Partitioner) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Repartition the RDD according to the given partitioner and, within each resulting partition,
sort records by their keys.
- repartitionAndSortWithinPartitions(Partitioner, Comparator<K>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Repartition the RDD according to the given partitioner and, within each resulting partition,
sort records by their keys.
- repartitionAndSortWithinPartitions(Partitioner) - Method in class org.apache.spark.rdd.OrderedRDDFunctions
-
Repartition the RDD according to the given partitioner and, within each resulting partition,
sort records by their keys.
- replay() - Method in class org.apache.spark.scheduler.ReplayListenerBus
-
Replay each event in the order maintained in the given logs.
- ReplayListenerBus - Class in org.apache.spark.scheduler
-
A SparkListenerBus that replays logged events from persisted storage.
- ReplayListenerBus(Seq<Path>, FileSystem, Option<CompressionCodec>) - Constructor for class org.apache.spark.scheduler.ReplayListenerBus
-
- replicatedVertexView() - Method in class org.apache.spark.graphx.impl.GraphImpl
-
- ReplicatedVertexView<VD,ED> - Class in org.apache.spark.graphx.impl
-
Manages shipping vertex attributes to the edge partitions of an
EdgeRDD
.
- ReplicatedVertexView(EdgeRDDImpl<ED, VD>, boolean, boolean, ClassTag<VD>, ClassTag<ED>) - Constructor for class org.apache.spark.graphx.impl.ReplicatedVertexView
-
- replication() - Method in class org.apache.spark.storage.StorageLevel
-
- report() - Method in class org.apache.spark.metrics.MetricsSystem
-
- report() - Method in class org.apache.spark.metrics.sink.ConsoleSink
-
- report() - Method in class org.apache.spark.metrics.sink.CsvSink
-
- report() - Method in class org.apache.spark.metrics.sink.GraphiteSink
-
- report() - Method in class org.apache.spark.metrics.sink.JmxSink
-
- report() - Method in class org.apache.spark.metrics.sink.MetricsServlet
-
- report() - Method in interface org.apache.spark.metrics.sink.Sink
-
- reporter() - Method in class org.apache.spark.metrics.sink.ConsoleSink
-
- reporter() - Method in class org.apache.spark.metrics.sink.CsvSink
-
- reporter() - Method in class org.apache.spark.metrics.sink.GraphiteSink
-
- reporter() - Method in class org.apache.spark.metrics.sink.JmxSink
-
- reportError(String, Throwable) - Method in class org.apache.spark.streaming.receiver.Receiver
-
Report exceptions in receiving data.
- reportError(String, Throwable) - Method in class org.apache.spark.streaming.receiver.ReceiverSupervisor
-
Report errors.
- reportError(String, Throwable) - Method in class org.apache.spark.streaming.receiver.ReceiverSupervisorImpl
-
Report error to the receiver tracker
- reportError(String, Throwable) - Method in class org.apache.spark.streaming.scheduler.JobScheduler
-
- ReportError - Class in org.apache.spark.streaming.scheduler
-
- ReportError(int, String, String) - Constructor for class org.apache.spark.streaming.scheduler.ReportError
-
- requestedAttributes() - Method in class org.apache.spark.sql.hive.execution.HiveTableScan
-
- requestedPartitionOrdinals() - Method in class org.apache.spark.sql.parquet.ParquetTableScan
-
- requestedTotal() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RequestExecutors
-
- requestExecutors(int) - Method in interface org.apache.spark.ExecutorAllocationClient
-
Request an additional number of executors from the cluster manager.
- requestExecutors(int) - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend
-
Request an additional number of executors from the cluster manager.
- requestExecutors(int) - Method in class org.apache.spark.SparkContext
-
:: DeveloperApi ::
Request an additional number of executors from the cluster manager.
- requiredChildDistribution() - Method in class org.apache.spark.sql.execution.Aggregate
-
- requiredChildDistribution() - Method in class org.apache.spark.sql.execution.Distinct
-
- requiredChildDistribution() - Method in class org.apache.spark.sql.execution.ExternalSort
-
- requiredChildDistribution() - Method in class org.apache.spark.sql.execution.GeneratedAggregate
-
- requiredChildDistribution() - Method in class org.apache.spark.sql.execution.joins.BroadcastHashJoin
-
- requiredChildDistribution() - Method in class org.apache.spark.sql.execution.joins.HashOuterJoin
-
- requiredChildDistribution() - Method in class org.apache.spark.sql.execution.joins.LeftSemiJoinHash
-
- requiredChildDistribution() - Method in class org.apache.spark.sql.execution.joins.ShuffledHashJoin
-
- requiredChildDistribution() - Method in class org.apache.spark.sql.execution.Sort
-
- requiredChildDistribution() - Method in class org.apache.spark.sql.execution.SparkPlan
-
Specifies any partition requirements on the input data for this operator.
- reregister() - Method in class org.apache.spark.storage.BlockManager
-
Re-register with the master and report all blocks to it.
- reregisterBlockManager() - Method in class org.apache.spark.HeartbeatResponse
-
- reregistered(SchedulerDriver, Protos.MasterInfo) - Method in class org.apache.spark.scheduler.cluster.mesos.CoarseMesosSchedulerBackend
-
- reregistered(SchedulerDriver, Protos.MasterInfo) - Method in class org.apache.spark.scheduler.cluster.mesos.MesosSchedulerBackend
-
- res() - Method in class org.apache.spark.mllib.optimization.NNLS.Workspace
-
- reservedSizeBytes() - Static method in class org.apache.spark.util.AkkaUtils
-
Space reserved for extra data in an Akka message besides serialized task or task result.
- reserveUnrollMemoryForThisThread(long) - Method in class org.apache.spark.storage.MemoryStore
-
Reserve additional memory for unrolling blocks used by this thread.
- reservoirSampleAndCount(Iterator<T>, int, long, ClassTag<T>) - Static method in class org.apache.spark.util.random.SamplingUtils
-
Reservoir sampling implementation that also returns the input size.
- reset() - Method in class org.apache.spark.sql.hive.test.TestHiveContext
-
Resets the test instance by deleting any tables that have been created.
- resetIterator() - Method in class org.apache.spark.rdd.PartitionCoalescer.LocationIterator
-
- resolveClass(ObjectStreamClass) - Method in class org.apache.spark.streaming.ObjectInputStreamWithLoader
-
- resolved() - Method in class org.apache.spark.sql.hive.InsertIntoHiveTable
-
- resolveURI(String, boolean) - Static method in class org.apache.spark.util.Utils
-
Return a well-formed URI for the file described by a user input string.
- resolveURIs(String, boolean) - Static method in class org.apache.spark.util.Utils
-
Resolve a comma-separated list of paths.
- resourceOffer(String, String, Enumeration.Value) - Method in class org.apache.spark.scheduler.TaskSetManager
-
Respond to an offer of a single executor from the scheduler by finding a task
- resourceOffers(SchedulerDriver, List<Protos.Offer>) - Method in class org.apache.spark.scheduler.cluster.mesos.CoarseMesosSchedulerBackend
-
Method called by Mesos to offer resources on slaves.
- resourceOffers(SchedulerDriver, List<Protos.Offer>) - Method in class org.apache.spark.scheduler.cluster.mesos.MesosSchedulerBackend
-
Method called by Mesos to offer resources on slaves.
- resourceOffers(Seq<WorkerOffer>) - Method in class org.apache.spark.scheduler.TaskSchedulerImpl
-
Called by cluster manager to offer resources on slaves.
- resourcePool() - Static method in class org.apache.spark.sql.execution.SparkSqlSerializer
-
- responder() - Method in class org.apache.spark.streaming.flume.FlumeReceiver
-
- responder() - Method in class org.apache.spark.ui.JettyUtils.ServletParams
-
- restart(Time) - Method in class org.apache.spark.streaming.DStreamGraph
-
- restart(String) - Method in class org.apache.spark.streaming.receiver.Receiver
-
Restart the receiver.
- restart(String, Throwable) - Method in class org.apache.spark.streaming.receiver.Receiver
-
Restart the receiver.
- restart(String, Throwable, int) - Method in class org.apache.spark.streaming.receiver.Receiver
-
Restart the receiver.
- restartReceiver(String, Option<Throwable>) - Method in class org.apache.spark.streaming.receiver.ReceiverSupervisor
-
Restart receiver with delay
- restartReceiver(String, Option<Throwable>, int) - Method in class org.apache.spark.streaming.receiver.ReceiverSupervisor
-
Restart receiver with delay
- restore() - Method in class org.apache.spark.streaming.dstream.DStreamCheckpointData
-
Restore the checkpoint data.
- restore() - Method in class org.apache.spark.streaming.dstream.FileInputDStream.FileInputDStreamCheckpointData
-
- restoreCheckpointData() - Method in class org.apache.spark.streaming.dstream.DStream
-
Restore the RDDs in generatedRDDs from the checkpointData.
- restoreCheckpointData() - Method in class org.apache.spark.streaming.DStreamGraph
-
- RESUBMIT_TIMEOUT() - Static method in class org.apache.spark.scheduler.DAGScheduler
-
- resubmitFailedStages() - Method in class org.apache.spark.scheduler.DAGScheduler
-
Resubmit any failed stages.
- ResubmitFailedStages - Class in org.apache.spark.scheduler
-
- ResubmitFailedStages() - Constructor for class org.apache.spark.scheduler.ResubmitFailedStages
-
- Resubmitted - Class in org.apache.spark
-
:: DeveloperApi ::
A
ShuffleMapTask
that completed successfully earlier, but we
lost the executor before the stage completed.
- Resubmitted() - Constructor for class org.apache.spark.Resubmitted
-
- result(Duration, CanAwait) - Method in class org.apache.spark.ComplexFutureAction
-
- result(Duration, CanAwait) - Method in interface org.apache.spark.FutureAction
-
Awaits and returns the result (of type T) of this action.
- result() - Method in class org.apache.spark.scheduler.CompletionEvent
-
- result(Duration, CanAwait) - Method in class org.apache.spark.SimpleFutureAction
-
- result() - Method in class org.apache.spark.sql.execution.AggregateEvaluation
-
- result() - Method in class org.apache.spark.streaming.scheduler.Job
-
- RESULT_SERIALIZATION_TIME() - Static method in class org.apache.spark.ui.jobs.TaskDetailsClassNames
-
- RESULT_SERIALIZATION_TIME() - Static method in class org.apache.spark.ui.ToolTips
-
- resultAttribute() - Method in class org.apache.spark.sql.execution.Aggregate.ComputedAggregate
-
- resultAttribute() - Method in class org.apache.spark.sql.execution.EvaluatePython
-
- resultObject() - Method in class org.apache.spark.partial.ApproximateActionListener
-
- resultOfJob() - Method in class org.apache.spark.scheduler.Stage
-
For stages that are the final (consists of only ResultTasks), link to the ActiveJob.
- resultSetToObjectArray(ResultSet) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- ResultTask<T,U> - Class in org.apache.spark.scheduler
-
A task that sends back the output to the driver application.
- ResultTask(int, Broadcast<byte[]>, Partition, Seq<TaskLocation>, int) - Constructor for class org.apache.spark.scheduler.ResultTask
-
- ResultWithDroppedBlocks - Class in org.apache.spark.storage
-
- ResultWithDroppedBlocks(boolean, Seq<Tuple2<BlockId, BlockStatus>>) - Constructor for class org.apache.spark.storage.ResultWithDroppedBlocks
-
- retag(Class<T>) - Method in class org.apache.spark.rdd.RDD
-
Private API for changing an RDD's ClassTag.
- retag(ClassTag<T>) - Method in class org.apache.spark.rdd.RDD
-
Private API for changing an RDD's ClassTag.
- RETAINED_FILES_PROPERTY() - Static method in class org.apache.spark.util.logging.RollingFileAppender
-
- retainedCompletedBatches() - Method in class org.apache.spark.streaming.ui.StreamingJobProgressListener
-
- retainedJobs() - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- retainedStages() - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- retryRandom(Function0<T>, int, int) - Static method in class org.apache.spark.streaming.kinesis.KinesisRecordProcessor
-
Retry the given amount of times with a random backoff time (millis) less than the
given maxBackOffMillis
- retryWaitMs(SparkConf) - Static method in class org.apache.spark.util.AkkaUtils
-
Returns the configured number of milliseconds to wait on each retry
- returnInspector() - Method in class org.apache.spark.sql.hive.HiveSimpleUdf
-
- ReturnStatementFinder - Class in org.apache.spark.util
-
- ReturnStatementFinder() - Constructor for class org.apache.spark.util.ReturnStatementFinder
-
- reverse() - Method in class org.apache.spark.graphx.EdgeDirection
-
Reverse the direction of an edge.
- reverse() - Method in class org.apache.spark.graphx.EdgeRDD
-
Reverse all the edges in this RDD.
- reverse() - Method in class org.apache.spark.graphx.Graph
-
Reverses all edges in the graph.
- reverse() - Method in class org.apache.spark.graphx.impl.EdgePartition
-
Reverse all the edges in this partition.
- reverse() - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- reverse() - Method in class org.apache.spark.graphx.impl.GraphImpl
-
- reverse() - Method in class org.apache.spark.graphx.impl.ReplicatedVertexView
-
Return a new ReplicatedVertexView
where edges are reversed and shipping levels are swapped to
match.
- reverse() - Method in class org.apache.spark.graphx.impl.RoutingTablePartition
-
Returns a new RoutingTablePartition reflecting a reversal of all edge directions.
- reverseRoutingTables() - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- reverseRoutingTables() - Method in class org.apache.spark.graphx.VertexRDD
-
Returns a new
VertexRDD
reflecting a reversal of all edge directions in the corresponding
EdgeRDD
.
- revertPartialWritesAndClose() - Method in class org.apache.spark.storage.BlockObjectWriter
-
Reverts writes that haven't been flushed yet.
- revertPartialWritesAndClose() - Method in class org.apache.spark.storage.DiskBlockObjectWriter
-
- reviveOffers() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend
-
- reviveOffers() - Method in class org.apache.spark.scheduler.cluster.mesos.MesosSchedulerBackend
-
- reviveOffers() - Method in class org.apache.spark.scheduler.local.LocalActor
-
- reviveOffers() - Method in class org.apache.spark.scheduler.local.LocalBackend
-
- ReviveOffers - Class in org.apache.spark.scheduler.local
-
- ReviveOffers() - Constructor for class org.apache.spark.scheduler.local.ReviveOffers
-
- reviveOffers() - Method in interface org.apache.spark.scheduler.SchedulerBackend
-
- RidgeRegressionModel - Class in org.apache.spark.mllib.regression
-
Regression model trained using RidgeRegression.
- RidgeRegressionModel(Vector, double) - Constructor for class org.apache.spark.mllib.regression.RidgeRegressionModel
-
- RidgeRegressionWithSGD - Class in org.apache.spark.mllib.regression
-
Train a regression model with L2-regularization using Stochastic Gradient Descent.
- RidgeRegressionWithSGD() - Constructor for class org.apache.spark.mllib.regression.RidgeRegressionWithSGD
-
Construct a RidgeRegression object with default parameters: {stepSize: 1.0, numIterations: 100,
regParam: 0.01, miniBatchFraction: 1.0}.
- right() - Method in class org.apache.spark.sql.execution.Except
-
- right() - Method in class org.apache.spark.sql.execution.Intersect
-
- right() - Method in class org.apache.spark.sql.execution.joins.BroadcastHashJoin
-
- right() - Method in class org.apache.spark.sql.execution.joins.BroadcastNestedLoopJoin
-
- right() - Method in class org.apache.spark.sql.execution.joins.CartesianProduct
-
- right() - Method in interface org.apache.spark.sql.execution.joins.HashJoin
-
- right() - Method in class org.apache.spark.sql.execution.joins.HashOuterJoin
-
- right() - Method in class org.apache.spark.sql.execution.joins.LeftSemiJoinBNL
-
The Broadcast relation
- right() - Method in class org.apache.spark.sql.execution.joins.LeftSemiJoinHash
-
- right() - Method in class org.apache.spark.sql.execution.joins.ShuffledHashJoin
-
- rightChildIndex(int) - Static method in class org.apache.spark.mllib.tree.model.Node
-
Return the index of the right child of this node.
- rightImpurity() - Method in class org.apache.spark.mllib.tree.model.InformationGainStats
-
- rightKeys() - Method in class org.apache.spark.sql.execution.joins.BroadcastHashJoin
-
- rightKeys() - Method in interface org.apache.spark.sql.execution.joins.HashJoin
-
- rightKeys() - Method in class org.apache.spark.sql.execution.joins.HashOuterJoin
-
- rightKeys() - Method in class org.apache.spark.sql.execution.joins.LeftSemiJoinHash
-
- rightKeys() - Method in class org.apache.spark.sql.execution.joins.ShuffledHashJoin
-
- rightNode() - Method in class org.apache.spark.mllib.tree.model.Node
-
- rightOuterJoin(JavaPairRDD<K, W>, Partitioner) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Perform a right outer join of this
and other
.
- rightOuterJoin(JavaPairRDD<K, W>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Perform a right outer join of this
and other
.
- rightOuterJoin(JavaPairRDD<K, W>, int) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Perform a right outer join of this
and other
.
- rightOuterJoin(RDD<Tuple2<K, W>>, Partitioner) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Perform a right outer join of this
and other
.
- rightOuterJoin(RDD<Tuple2<K, W>>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Perform a right outer join of this
and other
.
- rightOuterJoin(RDD<Tuple2<K, W>>, int) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Perform a right outer join of this
and other
.
- rightOuterJoin(JavaPairDStream<K, W>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying 'right outer join' between RDDs of this
DStream and
other
DStream.
- rightOuterJoin(JavaPairDStream<K, W>, int) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying 'right outer join' between RDDs of this
DStream and
other
DStream.
- rightOuterJoin(JavaPairDStream<K, W>, Partitioner) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying 'right outer join' between RDDs of this
DStream and
other
DStream.
- rightOuterJoin(DStream<Tuple2<K, W>>, ClassTag<W>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying 'right outer join' between RDDs of this
DStream and
other
DStream.
- rightOuterJoin(DStream<Tuple2<K, W>>, int, ClassTag<W>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying 'right outer join' between RDDs of this
DStream and
other
DStream.
- rightOuterJoin(DStream<Tuple2<K, W>>, Partitioner, ClassTag<W>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying 'right outer join' between RDDs of this
DStream and
other
DStream.
- rightPredict() - Method in class org.apache.spark.mllib.tree.model.InformationGainStats
-
- RLIKE() - Static method in class org.apache.spark.sql.hive.HiveQl
-
- RMATa() - Static method in class org.apache.spark.graphx.util.GraphGenerators
-
- RMATb() - Static method in class org.apache.spark.graphx.util.GraphGenerators
-
- RMATc() - Static method in class org.apache.spark.graphx.util.GraphGenerators
-
- RMATd() - Static method in class org.apache.spark.graphx.util.GraphGenerators
-
- rmatGraph(SparkContext, int, int) - Static method in class org.apache.spark.graphx.util.GraphGenerators
-
A random graph generator using the R-MAT model, proposed in
"R-MAT: A Recursive Model for Graph Mining" by Chakrabarti et al.
- rnd() - Method in class org.apache.spark.rdd.PartitionCoalescer
-
- roc() - Method in class org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
-
Returns the receiver operating characteristic (ROC) curve,
which is an RDD of (false positive rate, true positive rate)
with (0.0, 0.0) prepended and (1.0, 1.0) appended to it.
- rolledOver() - Method in interface org.apache.spark.util.logging.RollingPolicy
-
Notify that rollover has occurred
- rolledOver() - Method in class org.apache.spark.util.logging.SizeBasedRollingPolicy
-
Rollover has occurred, so reset the counter
- rolledOver() - Method in class org.apache.spark.util.logging.TimeBasedRollingPolicy
-
Rollover has occurred, so find the next time to rollover
- RollingFileAppender - Class in org.apache.spark.util.logging
-
Continuously appends data from input stream into the given file, and rolls
over the file after the given interval.
- RollingFileAppender(InputStream, File, RollingPolicy, SparkConf, int) - Constructor for class org.apache.spark.util.logging.RollingFileAppender
-
- rollingPolicy() - Method in class org.apache.spark.util.logging.RollingFileAppender
-
- RollingPolicy - Interface in org.apache.spark.util.logging
-
- rolloverIntervalMillis() - Method in class org.apache.spark.util.logging.TimeBasedRollingPolicy
-
- rolloverSizeBytes() - Method in class org.apache.spark.util.logging.SizeBasedRollingPolicy
-
- rootHandler() - Method in class org.apache.spark.ui.ServerInfo
-
- rootMeanSquaredError() - Method in class org.apache.spark.mllib.evaluation.RegressionMetrics
-
Returns the root mean squared error, which is defined as the square root of
the mean squared error.
- rootPool() - Method in class org.apache.spark.scheduler.FairSchedulableBuilder
-
- rootPool() - Method in class org.apache.spark.scheduler.FIFOSchedulableBuilder
-
- rootPool() - Method in interface org.apache.spark.scheduler.SchedulableBuilder
-
- rootPool() - Method in interface org.apache.spark.scheduler.TaskScheduler
-
- rootPool() - Method in class org.apache.spark.scheduler.TaskSchedulerImpl
-
- routingTable() - Method in class org.apache.spark.graphx.impl.ShippableVertexPartition
-
- RoutingTablePartition - Class in org.apache.spark.graphx.impl
-
Stores the locations of edge-partition join sites for each vertex attribute in a particular
vertex partition.
- RoutingTablePartition(Tuple3<long[], BitSet, BitSet>[]) - Constructor for class org.apache.spark.graphx.impl.RoutingTablePartition
-
- Row - Class in org.apache.spark.sql.api.java
-
A result row from a Spark SQL query.
- Row(Row) - Constructor for class org.apache.spark.sql.api.java.Row
-
- row() - Method in class org.apache.spark.sql.api.java.Row
-
- rowIndices() - Method in class org.apache.spark.mllib.linalg.SparseMatrix
-
- RowMatrix - Class in org.apache.spark.mllib.linalg.distributed
-
:: Experimental ::
Represents a row-oriented distributed Matrix with no meaningful row indices.
- RowMatrix(RDD<Vector>, long, int) - Constructor for class org.apache.spark.mllib.linalg.distributed.RowMatrix
-
- RowMatrix(RDD<Vector>) - Constructor for class org.apache.spark.mllib.linalg.distributed.RowMatrix
-
Alternative constructor leaving matrix dimensions to be determined automatically.
- RowReadSupport - Class in org.apache.spark.sql.parquet
-
A parquet.hadoop.api.ReadSupport
for Row objects.
- RowReadSupport() - Constructor for class org.apache.spark.sql.parquet.RowReadSupport
-
- RowRecordMaterializer - Class in org.apache.spark.sql.parquet
-
A parquet.io.api.RecordMaterializer
for Rows.
- RowRecordMaterializer(CatalystConverter) - Constructor for class org.apache.spark.sql.parquet.RowRecordMaterializer
-
- RowRecordMaterializer(MessageType, Seq<Attribute>) - Constructor for class org.apache.spark.sql.parquet.RowRecordMaterializer
-
- rows() - Method in class org.apache.spark.mllib.linalg.distributed.IndexedRowMatrix
-
- rows() - Method in class org.apache.spark.mllib.linalg.distributed.RowMatrix
-
- rowToArray(Row, Seq<DataType>) - Static method in class org.apache.spark.sql.execution.EvaluatePython
-
Convert Row into Java Array (for pickled into Python)
- rowToJSON(StructType, JsonFactory, Row) - Static method in class org.apache.spark.sql.json.JsonRDD
-
Transforms a single Row to JSON using Jackson
- RowWriteSupport - Class in org.apache.spark.sql.parquet
-
A parquet.hadoop.api.WriteSupport
for Row ojects.
- RowWriteSupport() - Constructor for class org.apache.spark.sql.parquet.RowWriteSupport
-
- run(Function0<T>, ExecutionContext) - Method in class org.apache.spark.ComplexFutureAction
-
Executes some action enclosed in the closure.
- run(Graph<VD, ED>, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.lib.ConnectedComponents
-
Compute the connected component membership of each vertex and return a graph with the vertex
value containing the lowest vertex id in the connected component containing that vertex.
- run(Graph<VD, ED>, int, ClassTag<ED>) - Static method in class org.apache.spark.graphx.lib.LabelPropagation
-
Run static Label Propagation for detecting communities in networks.
- run(Graph<VD, ED>, int, double, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.lib.PageRank
-
Run PageRank for a fixed number of iterations returning a graph
with vertex attributes containing the PageRank and edge
attributes the normalized edge weight.
- run(Graph<VD, ED>, Seq<Object>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.lib.ShortestPaths
-
Computes shortest paths to the given set of landmark vertices.
- run(Graph<VD, ED>, int, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.lib.StronglyConnectedComponents
-
Compute the strongly connected component (SCC) of each vertex and return a graph with the
vertex value containing the lowest vertex id in the SCC containing that vertex.
- run(RDD<Edge<Object>>, SVDPlusPlus.Conf) - Static method in class org.apache.spark.graphx.lib.SVDPlusPlus
-
Implement SVD++ based on "Factorization Meets the Neighborhood:
a Multifaceted Collaborative Filtering Model",
available at http://public.research.att.com/~volinsky/netflix/kdd08koren.pdf
.
- run(Graph<VD, ED>, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.lib.TriangleCount
-
- run(RDD<LabeledPoint>) - Method in class org.apache.spark.mllib.classification.NaiveBayes
-
Run the algorithm with the configured parameters on an input RDD of LabeledPoint entries.
- run(RDD<Vector>) - Method in class org.apache.spark.mllib.clustering.KMeans
-
Train a K-means model on the given set of points; data
should be cached for high
performance, because this is an iterative algorithm.
- run(RDD<Rating>) - Method in class org.apache.spark.mllib.recommendation.ALS
-
Run ALS with the configured parameters on an input RDD of (user, product, rating) triples.
- run(JavaRDD<Rating>) - Method in class org.apache.spark.mllib.recommendation.ALS
-
Java-friendly version of ALS.run
.
- run(RDD<LabeledPoint>) - Method in class org.apache.spark.mllib.regression.GeneralizedLinearAlgorithm
-
Run the algorithm with the configured parameters on an input
RDD of LabeledPoint entries.
- run(RDD<LabeledPoint>, Vector) - Method in class org.apache.spark.mllib.regression.GeneralizedLinearAlgorithm
-
Run the algorithm with the configured parameters on an input RDD
of LabeledPoint entries starting from the initial weights provided.
- run(RDD<LabeledPoint>) - Method in class org.apache.spark.mllib.tree.DecisionTree
-
Method to train a decision tree model over an RDD
- run(RDD<LabeledPoint>) - Method in class org.apache.spark.mllib.tree.GradientBoostedTrees
-
Method to train a gradient boosting model
- run(JavaRDD<LabeledPoint>) - Method in class org.apache.spark.mllib.tree.GradientBoostedTrees
-
Java-friendly API for org.apache.spark.mllib.tree.GradientBoostedTrees!#run
.
- run(RDD<LabeledPoint>) - Method in class org.apache.spark.mllib.tree.RandomForest
-
Method to train a decision tree model over an RDD
- run() - Method in class org.apache.spark.rdd.PartitionCoalescer
-
Runs the packing algorithm and returns an array of PartitionGroups that if possible are
load balanced and grouped by locality
- run(long) - Method in class org.apache.spark.scheduler.Task
-
- run(SQLContext) - Method in interface org.apache.spark.sql.execution.RunnableCommand
-
- run(SQLContext) - Method in class org.apache.spark.sql.sources.CreateTableUsing
-
- run() - Method in class org.apache.spark.streaming.CheckpointWriter.CheckpointWriteHandler
-
- run() - Method in class org.apache.spark.streaming.flume.FlumeBatchFetcher
-
- run() - Method in class org.apache.spark.streaming.scheduler.Job
-
- run() - Method in class org.apache.spark.util.RedirectThread
-
- runApproximateJob(RDD<T>, Function2<TaskContext, Iterator<T>, U>, ApproximateEvaluator<U, R>, CallSite, long, Properties) - Method in class org.apache.spark.scheduler.DAGScheduler
-
- runApproximateJob(RDD<T>, Function2<TaskContext, Iterator<T>, U>, ApproximateEvaluator<U, R>, long) - Method in class org.apache.spark.SparkContext
-
:: DeveloperApi ::
Run a job that can return approximate results.
- runJob(RDD<T>, Function1<Iterator<T>, U>, Seq<Object>, Function2<Object, U, BoxedUnit>, Function0<R>) - Method in class org.apache.spark.ComplexFutureAction
-
Runs a Spark job.
- runJob(RDD<T>, Function2<TaskContext, Iterator<T>, U>, Seq<Object>, CallSite, boolean, Function2<Object, U, BoxedUnit>, Properties, ClassTag<U>) - Method in class org.apache.spark.scheduler.DAGScheduler
-
- runJob(RDD<T>, Function2<TaskContext, Iterator<T>, U>, Seq<Object>, boolean, Function2<Object, U, BoxedUnit>, ClassTag<U>) - Method in class org.apache.spark.SparkContext
-
Run a function on a given set of partitions in an RDD and pass the results to the given
handler function.
- runJob(RDD<T>, Function2<TaskContext, Iterator<T>, U>, Seq<Object>, boolean, ClassTag<U>) - Method in class org.apache.spark.SparkContext
-
Run a function on a given set of partitions in an RDD and return the results as an array.
- runJob(RDD<T>, Function1<Iterator<T>, U>, Seq<Object>, boolean, ClassTag<U>) - Method in class org.apache.spark.SparkContext
-
Run a job on a given set of partitions of an RDD, but take a function of type
Iterator[T] => U
instead of (TaskContext, Iterator[T]) => U
.
- runJob(RDD<T>, Function2<TaskContext, Iterator<T>, U>, ClassTag<U>) - Method in class org.apache.spark.SparkContext
-
Run a job on all partitions in an RDD and return the results in an array.
- runJob(RDD<T>, Function1<Iterator<T>, U>, ClassTag<U>) - Method in class org.apache.spark.SparkContext
-
Run a job on all partitions in an RDD and return the results in an array.
- runJob(RDD<T>, Function2<TaskContext, Iterator<T>, U>, Function2<Object, U, BoxedUnit>, ClassTag<U>) - Method in class org.apache.spark.SparkContext
-
Run a job on all partitions in an RDD and pass the results to a handler function.
- runJob(RDD<T>, Function1<Iterator<T>, U>, Function2<Object, U, BoxedUnit>, ClassTag<U>) - Method in class org.apache.spark.SparkContext
-
Run a job on all partitions in an RDD and pass the results to a handler function.
- runLBFGS(RDD<Tuple2<Object, Vector>>, Gradient, Updater, int, double, int, double, Vector) - Static method in class org.apache.spark.mllib.optimization.LBFGS
-
Run Limited-memory BFGS (L-BFGS) in parallel.
- RunLengthEncoding - Class in org.apache.spark.sql.columnar.compression
-
- RunLengthEncoding() - Constructor for class org.apache.spark.sql.columnar.compression.RunLengthEncoding
-
- RunLengthEncoding.Decoder<T extends org.apache.spark.sql.catalyst.types.NativeType> - Class in org.apache.spark.sql.columnar.compression
-
- RunLengthEncoding.Decoder(ByteBuffer, NativeColumnType<T>) - Constructor for class org.apache.spark.sql.columnar.compression.RunLengthEncoding.Decoder
-
- RunLengthEncoding.Encoder<T extends org.apache.spark.sql.catalyst.types.NativeType> - Class in org.apache.spark.sql.columnar.compression
-
- RunLengthEncoding.Encoder(NativeColumnType<T>) - Constructor for class org.apache.spark.sql.columnar.compression.RunLengthEncoding.Encoder
-
- runMiniBatchSGD(RDD<Tuple2<Object, Vector>>, Gradient, Updater, double, int, double, double, Vector) - Static method in class org.apache.spark.mllib.optimization.GradientDescent
-
Run stochastic gradient descent (SGD) in parallel using mini batches.
- RunnableCommand - Interface in org.apache.spark.sql.execution
-
- running() - Method in class org.apache.spark.scheduler.TaskInfo
-
- RUNNING() - Static method in class org.apache.spark.TaskState
-
- runningBatches() - Method in class org.apache.spark.streaming.ui.StreamingJobProgressListener
-
- runningLocally() - Method in class org.apache.spark.TaskContext
-
Deprecated.
- runningLocally() - Method in class org.apache.spark.TaskContextImpl
-
- runningStages() - Method in class org.apache.spark.scheduler.DAGScheduler
-
- runningTasks() - Method in class org.apache.spark.scheduler.Pool
-
- runningTasks() - Method in interface org.apache.spark.scheduler.Schedulable
-
- runningTasks() - Method in class org.apache.spark.scheduler.TaskSetManager
-
- runningTasksSet() - Method in class org.apache.spark.scheduler.TaskSetManager
-
- runSqlHive(String) - Method in class org.apache.spark.sql.hive.test.TestHiveContext
-
- runTask(TaskContext) - Method in class org.apache.spark.scheduler.ResultTask
-
- runTask(TaskContext) - Method in class org.apache.spark.scheduler.ShuffleMapTask
-
- runTask(TaskContext) - Method in class org.apache.spark.scheduler.Task
-
- RuntimePercentage - Class in org.apache.spark.scheduler
-
- RuntimePercentage(double, Option<Object>, double) - Constructor for class org.apache.spark.scheduler.RuntimePercentage
-
- runUntilConvergence(Graph<VD, ED>, double, double, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.lib.PageRank
-
Run a dynamic version of PageRank returning a graph with vertex attributes containing the
PageRank and edge attributes containing the normalized edge weight.
- s() - Method in class org.apache.spark.mllib.linalg.SingularValueDecomposition
-
- s1() - Method in class org.apache.spark.rdd.CartesianPartition
-
- s2() - Method in class org.apache.spark.rdd.CartesianPartition
-
- sameResult(LogicalPlan) - Method in class org.apache.spark.sql.execution.LogicalRDD
-
- sameResult(LogicalPlan) - Method in class org.apache.spark.sql.execution.SparkLogicalPlan
-
- sameResult(LogicalPlan) - Method in class org.apache.spark.sql.hive.MetastoreRelation
-
Only compare database and tablename, not alias.
- sameResult(LogicalPlan) - Method in class org.apache.spark.sql.sources.LogicalRelation
-
- sample(boolean, Double) - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Return a sampled subset of this RDD.
- sample(boolean, Double, long) - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Return a sampled subset of this RDD.
- sample(boolean, double) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Return a sampled subset of this RDD.
- sample(boolean, double, long) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Return a sampled subset of this RDD.
- sample(boolean, double) - Method in class org.apache.spark.api.java.JavaRDD
-
Return a sampled subset of this RDD.
- sample(boolean, double, long) - Method in class org.apache.spark.api.java.JavaRDD
-
Return a sampled subset of this RDD.
- sample(boolean, double, long) - Method in class org.apache.spark.rdd.RDD
-
Return a sampled subset of this RDD.
- Sample - Class in org.apache.spark.sql.execution
-
:: DeveloperApi ::
- Sample(double, boolean, long, SparkPlan) - Constructor for class org.apache.spark.sql.execution.Sample
-
- sample(boolean, double, long) - Method in class org.apache.spark.sql.SchemaRDD
-
:: Experimental ::
Returns a sampled version of the underlying dataset.
- sample(Iterator<T>) - Method in class org.apache.spark.util.random.BernoulliCellSampler
-
- sample(Iterator<T>) - Method in class org.apache.spark.util.random.BernoulliSampler
-
- sample(Iterator<T>) - Method in class org.apache.spark.util.random.PoissonSampler
-
- sample(Iterator<T>) - Method in interface org.apache.spark.util.random.RandomSampler
-
take a random sample
- sampleByKey(boolean, Map<K, Object>, long) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Return a subset of this RDD sampled by key (via stratified sampling).
- sampleByKey(boolean, Map<K, Object>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Return a subset of this RDD sampled by key (via stratified sampling).
- sampleByKey(boolean, Map<K, Object>, long) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Return a subset of this RDD sampled by key (via stratified sampling).
- sampleByKeyExact(boolean, Map<K, Object>, long) - Method in class org.apache.spark.api.java.JavaPairRDD
-
::Experimental::
Return a subset of this RDD sampled by key (via stratified sampling) containing exactly
math.ceil(numItems * samplingRate) for each stratum (group of pairs with the same key).
- sampleByKeyExact(boolean, Map<K, Object>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
::Experimental::
Return a subset of this RDD sampled by key (via stratified sampling) containing exactly
math.ceil(numItems * samplingRate) for each stratum (group of pairs with the same key).
- sampleByKeyExact(boolean, Map<K, Object>, long) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
::Experimental::
Return a subset of this RDD sampled by key (via stratified sampling) containing exactly
math.ceil(numItems * samplingRate) for each stratum (group of pairs with the same key).
- SampledRDD<T> - Class in org.apache.spark.rdd
-
- SampledRDD(RDD<T>, boolean, double, int, ClassTag<T>) - Constructor for class org.apache.spark.rdd.SampledRDD
-
- SampledRDDPartition - Class in org.apache.spark.rdd
-
- SampledRDDPartition(Partition, int) - Constructor for class org.apache.spark.rdd.SampledRDDPartition
-
- sampleLogNormal(double, double, int, long) - Static method in class org.apache.spark.graphx.util.GraphGenerators
-
Randomly samples from a log normal distribution whose corresponding normal distribution has
the given mean and standard deviation.
- sampleStdev() - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Compute the sample standard deviation of this RDD's elements (which corrects for bias in
estimating the standard deviation by dividing by N-1 instead of N).
- sampleStdev() - Method in class org.apache.spark.rdd.DoubleRDDFunctions
-
Compute the sample standard deviation of this RDD's elements (which corrects for bias in
estimating the standard deviation by dividing by N-1 instead of N).
- sampleStdev() - Method in class org.apache.spark.util.StatCounter
-
Return the sample standard deviation of the values, which corrects for bias in estimating the
variance by dividing by N-1 instead of N.
- sampleVariance() - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Compute the sample variance of this RDD's elements (which corrects for bias in
estimating the standard variance by dividing by N-1 instead of N).
- sampleVariance() - Method in class org.apache.spark.rdd.DoubleRDDFunctions
-
Compute the sample variance of this RDD's elements (which corrects for bias in
estimating the variance by dividing by N-1 instead of N).
- sampleVariance() - Method in class org.apache.spark.util.StatCounter
-
Return the sample variance, which corrects for bias in estimating the variance by dividing
by N-1 instead of N.
- samplingRatio() - Method in class org.apache.spark.sql.json.JSONRelation
-
- SamplingUtils - Class in org.apache.spark.util.random
-
- SamplingUtils() - Constructor for class org.apache.spark.util.random.SamplingUtils
-
- saveAsHadoopDataset(JobConf) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Output the RDD to any Hadoop-supported storage system, using a Hadoop JobConf object for
that storage system.
- saveAsHadoopDataset(JobConf) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Output the RDD to any Hadoop-supported storage system, using a Hadoop JobConf object for
that storage system.
- saveAsHadoopFile(String, Class<?>, Class<?>, Class<F>, JobConf) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Output the RDD to any Hadoop-supported file system.
- saveAsHadoopFile(String, Class<?>, Class<?>, Class<F>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Output the RDD to any Hadoop-supported file system.
- saveAsHadoopFile(String, Class<?>, Class<?>, Class<F>, Class<? extends CompressionCodec>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Output the RDD to any Hadoop-supported file system, compressing with the supplied codec.
- saveAsHadoopFile(String, ClassTag<F>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Output the RDD to any Hadoop-supported file system, using a Hadoop OutputFormat
class
supporting the key and value types K and V in this RDD.
- saveAsHadoopFile(String, Class<? extends CompressionCodec>, ClassTag<F>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Output the RDD to any Hadoop-supported file system, using a Hadoop OutputFormat
class
supporting the key and value types K and V in this RDD.
- saveAsHadoopFile(String, Class<?>, Class<?>, Class<? extends OutputFormat<?, ?>>, Class<? extends CompressionCodec>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Output the RDD to any Hadoop-supported file system, using a Hadoop OutputFormat
class
supporting the key and value types K and V in this RDD.
- saveAsHadoopFile(String, Class<?>, Class<?>, Class<? extends OutputFormat<?, ?>>, JobConf, Option<Class<? extends CompressionCodec>>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Output the RDD to any Hadoop-supported file system, using a Hadoop OutputFormat
class
supporting the key and value types K and V in this RDD.
- saveAsHadoopFiles(String, String) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Save each RDD in this
DStream as a Hadoop file.
- saveAsHadoopFiles(String, String, Class<?>, Class<?>, Class<? extends OutputFormat<?, ?>>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Save each RDD in this
DStream as a Hadoop file.
- saveAsHadoopFiles(String, String, Class<?>, Class<?>, Class<? extends OutputFormat<?, ?>>, JobConf) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Save each RDD in this
DStream as a Hadoop file.
- saveAsHadoopFiles(String, String, ClassTag<F>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Save each RDD in this
DStream as a Hadoop file.
- saveAsHadoopFiles(String, String, Class<?>, Class<?>, Class<? extends OutputFormat<?, ?>>, JobConf) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Save each RDD in this
DStream as a Hadoop file.
- saveAsHiveFile(RDD<Row>, Class<?>, ShimFileSinkDesc, SerializableWritable<JobConf>, SparkHiveWriterContainer) - Method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- saveAsLibSVMFile(RDD<LabeledPoint>, String) - Static method in class org.apache.spark.mllib.util.MLUtils
-
Save labeled data in LIBSVM format.
- saveAsNewAPIHadoopDataset(Configuration) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Output the RDD to any Hadoop-supported storage system, using
a Configuration object for that storage system.
- saveAsNewAPIHadoopDataset(Configuration) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Output the RDD to any Hadoop-supported storage system with new Hadoop API, using a Hadoop
Configuration object for that storage system.
- saveAsNewAPIHadoopFile(String, Class<?>, Class<?>, Class<F>, Configuration) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Output the RDD to any Hadoop-supported file system.
- saveAsNewAPIHadoopFile(String, Class<?>, Class<?>, Class<F>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Output the RDD to any Hadoop-supported file system.
- saveAsNewAPIHadoopFile(String, ClassTag<F>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Output the RDD to any Hadoop-supported file system, using a new Hadoop API OutputFormat
(mapreduce.OutputFormat) object supporting the key and value types K and V in this RDD.
- saveAsNewAPIHadoopFile(String, Class<?>, Class<?>, Class<? extends OutputFormat<?, ?>>, Configuration) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Output the RDD to any Hadoop-supported file system, using a new Hadoop API OutputFormat
(mapreduce.OutputFormat) object supporting the key and value types K and V in this RDD.
- saveAsNewAPIHadoopFiles(String, String) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Save each RDD in this
DStream as a Hadoop file.
- saveAsNewAPIHadoopFiles(String, String, Class<?>, Class<?>, Class<? extends OutputFormat<?, ?>>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Save each RDD in this
DStream as a Hadoop file.
- saveAsNewAPIHadoopFiles(String, String, Class<?>, Class<?>, Class<? extends OutputFormat<?, ?>>, Configuration) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Save each RDD in this
DStream as a Hadoop file.
- saveAsNewAPIHadoopFiles(String, String, ClassTag<F>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Save each RDD in this
DStream as a Hadoop file.
- saveAsNewAPIHadoopFiles(String, String, Class<?>, Class<?>, Class<? extends OutputFormat<?, ?>>, Configuration) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Save each RDD in this
DStream as a Hadoop file.
- saveAsObjectFile(String) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Save this RDD as a SequenceFile of serialized objects.
- saveAsObjectFile(String) - Method in class org.apache.spark.rdd.RDD
-
Save this RDD as a SequenceFile of serialized objects.
- saveAsObjectFiles(String, String) - Method in class org.apache.spark.streaming.dstream.DStream
-
Save each RDD in this DStream as a Sequence file of serialized objects.
- saveAsParquetFile(String) - Method in interface org.apache.spark.sql.SchemaRDDLike
-
Saves the contents of this SchemaRDD
as a parquet file, preserving the schema.
- saveAsSequenceFile(String, Option<Class<? extends CompressionCodec>>) - Method in class org.apache.spark.rdd.SequenceFileRDDFunctions
-
Output the RDD as a Hadoop SequenceFile using the Writable types we infer from the RDD's key
and value types.
- saveAsTable(String) - Method in interface org.apache.spark.sql.SchemaRDDLike
-
:: Experimental ::
Creates a table from the the contents of this SchemaRDD.
- saveAsTextFile(String) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Save this RDD as a text file, using string representations of elements.
- saveAsTextFile(String, Class<? extends CompressionCodec>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Save this RDD as a compressed text file, using string representations of elements.
- saveAsTextFile(String) - Method in class org.apache.spark.rdd.RDD
-
Save this RDD as a text file, using string representations of elements.
- saveAsTextFile(String, Class<? extends CompressionCodec>) - Method in class org.apache.spark.rdd.RDD
-
Save this RDD as a compressed text file, using string representations of elements.
- saveAsTextFiles(String, String) - Method in class org.apache.spark.streaming.dstream.DStream
-
Save each RDD in this DStream as at text file, using string representation
of elements.
- saveLabeledData(RDD<LabeledPoint>, String) - Static method in class org.apache.spark.mllib.util.MLUtils
-
- sc() - Method in class org.apache.spark.api.java.JavaSparkContext
-
- sc() - Method in class org.apache.spark.scheduler.DAGScheduler
-
- sc() - Method in class org.apache.spark.scheduler.TaskSchedulerImpl
-
- sc() - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
- sc() - Method in class org.apache.spark.streaming.StreamingContext
-
- sc() - Method in class org.apache.spark.ui.exec.ExecutorsTab
-
- sc() - Method in class org.apache.spark.ui.jobs.JobsTab
-
- sc() - Method in class org.apache.spark.ui.jobs.StagesTab
-
- sc() - Method in class org.apache.spark.ui.SparkUI
-
- scal(double, Vector) - Static method in class org.apache.spark.mllib.linalg.BLAS
-
x = a * x
- scalaIntToJavaLong(DStream<Object>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
- scalaTag() - Method in class org.apache.spark.sql.columnar.NativeColumnType
-
Scala TypeTag.
- scalaToJavaLong(JavaPairDStream<K, Object>, ClassTag<K>) - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- ScalaToJavaUDTWrapper<UserType> - Class in org.apache.spark.sql.api.java
-
Java wrapper for a Scala UserDefinedType
- ScalaToJavaUDTWrapper(UserDefinedType<UserType>) - Constructor for class org.apache.spark.sql.api.java.ScalaToJavaUDTWrapper
-
- scalaUDT() - Method in class org.apache.spark.sql.api.java.ScalaToJavaUDTWrapper
-
- Schedulable - Interface in org.apache.spark.scheduler
-
An interface for schedulable entities.
- SchedulableBuilder - Interface in org.apache.spark.scheduler
-
An interface to build Schedulable tree
buildPools: build the tree nodes(pools)
addTaskSetManager: build the leaf nodes(TaskSetManagers)
- schedulableBuilder() - Method in class org.apache.spark.scheduler.TaskSchedulerImpl
-
- schedulableNameToSchedulable() - Method in class org.apache.spark.scheduler.Pool
-
- schedulableQueue() - Method in class org.apache.spark.scheduler.Pool
-
- schedulableQueue() - Method in interface org.apache.spark.scheduler.Schedulable
-
- schedulableQueue() - Method in class org.apache.spark.scheduler.TaskSetManager
-
- scheduler() - Method in class org.apache.spark.streaming.StreamingContext
-
- SCHEDULER_DELAY() - Static method in class org.apache.spark.ui.jobs.TaskDetailsClassNames
-
- SCHEDULER_DELAY() - Static method in class org.apache.spark.ui.ToolTips
-
- schedulerAllocFile() - Method in class org.apache.spark.scheduler.FairSchedulableBuilder
-
- SchedulerBackend - Interface in org.apache.spark.scheduler
-
A backend interface for scheduling systems that allows plugging in different ones under
TaskSchedulerImpl.
- schedulerBackend() - Method in class org.apache.spark.SparkContext
-
- SCHEDULING_MODE_PROPERTY() - Method in class org.apache.spark.scheduler.FairSchedulableBuilder
-
- SchedulingAlgorithm - Interface in org.apache.spark.scheduler
-
An interface for sort algorithm
FIFO: FIFO algorithm between TaskSetManagers
FS: FS algorithm between Pools, and FIFO or FS within Pools
- schedulingDelay() - Method in class org.apache.spark.streaming.scheduler.BatchInfo
-
Time taken for the first job of this batch to start processing from the time this batch
was submitted to the streaming scheduler.
- schedulingDelayDistribution() - Method in class org.apache.spark.streaming.ui.StreamingJobProgressListener
-
- schedulingMode() - Method in class org.apache.spark.scheduler.Pool
-
- schedulingMode() - Method in interface org.apache.spark.scheduler.Schedulable
-
- SchedulingMode - Class in org.apache.spark.scheduler
-
"FAIR" and "FIFO" determines which policy is used
to order tasks amongst a Schedulable's sub-queues
"NONE" is used when the a Schedulable has no sub-queues.
- SchedulingMode() - Constructor for class org.apache.spark.scheduler.SchedulingMode
-
- schedulingMode() - Method in interface org.apache.spark.scheduler.TaskScheduler
-
- schedulingMode() - Method in class org.apache.spark.scheduler.TaskSchedulerImpl
-
- schedulingMode() - Method in class org.apache.spark.scheduler.TaskSetManager
-
- schedulingMode() - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- schedulingPool() - Method in class org.apache.spark.ui.jobs.UIData.StageUIData
-
- schema() - Method in class org.apache.spark.sql.api.java.JavaSchemaRDD
-
Returns the schema of this JavaSchemaRDD (represented by a StructType).
- schema() - Method in class org.apache.spark.sql.columnar.ColumnStatisticsSchema
-
- schema() - Method in class org.apache.spark.sql.columnar.PartitionStatistics
-
- schema() - Method in class org.apache.spark.sql.execution.AggregateEvaluation
-
- schema() - Method in class org.apache.spark.sql.json.JSONRelation
-
- schema() - Method in class org.apache.spark.sql.parquet.ParquetRelation2
-
- schema() - Method in class org.apache.spark.sql.SchemaRDD
-
Returns the schema of this SchemaRDD (represented by a StructType
).
- schema() - Method in class org.apache.spark.sql.sources.BaseRelation
-
- schemaRDD() - Method in class org.apache.spark.sql.api.java.JavaSchemaRDD
-
Returns the underlying Scala SchemaRDD.
- SchemaRDD - Class in org.apache.spark.sql
-
:: AlphaComponent ::
An RDD of Row
objects that has an associated schema.
- SchemaRDD(SQLContext, LogicalPlan) - Constructor for class org.apache.spark.sql.SchemaRDD
-
- SchemaRDDLike - Interface in org.apache.spark.sql
-
Contains functions that are shared between all SchemaRDD types (i.e., Scala, Java)
- schemaString() - Method in interface org.apache.spark.sql.SchemaRDDLike
-
Returns the schema as a string in the tree format.
- schemes() - Method in interface org.apache.spark.sql.columnar.compression.AllCompressionSchemes
-
- schemes() - Method in interface org.apache.spark.sql.columnar.compression.WithCompressionSchemes
-
- scoreCol() - Method in interface org.apache.spark.ml.param.HasScoreCol
-
param for score column name
- scratch() - Method in class org.apache.spark.mllib.optimization.NNLS.Workspace
-
- script() - Method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- Scripts() - Method in interface org.apache.spark.sql.hive.HiveStrategies
-
- ScriptTransformation - Class in org.apache.spark.sql.hive.execution
-
:: DeveloperApi ::
Transforms the input by forking and running the specified script.
- ScriptTransformation(Seq<Expression>, String, Seq<Attribute>, SparkPlan, HiveContext) - Constructor for class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- seconds() - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- seconds(long) - Static method in class org.apache.spark.streaming.Durations
-
- Seconds - Class in org.apache.spark.streaming
-
Helper object that creates instance of
Duration
representing
a given number of seconds.
- Seconds() - Constructor for class org.apache.spark.streaming.Seconds
-
- SecurityManager - Class in org.apache.spark
-
Spark class responsible for security.
- SecurityManager(SparkConf) - Constructor for class org.apache.spark.SecurityManager
-
- securityManager() - Method in class org.apache.spark.SparkEnv
-
- securityManager() - Method in class org.apache.spark.ui.SparkUI
-
- seed() - Method in class org.apache.spark.mllib.rdd.RandomRDDPartition
-
- seed() - Method in class org.apache.spark.rdd.PartitionwiseSampledRDDPartition
-
- seed() - Method in class org.apache.spark.rdd.SampledRDDPartition
-
- seed() - Method in class org.apache.spark.sql.execution.Sample
-
- seenNulls() - Method in interface org.apache.spark.sql.columnar.NullableColumnAccessor
-
- segment() - Method in class org.apache.spark.streaming.rdd.WriteAheadLogBackedBlockRDDPartition
-
- segment() - Method in class org.apache.spark.streaming.receiver.WriteAheadLogBasedStoreResult
-
- select(Seq<Expression>) - Method in class org.apache.spark.sql.SchemaRDD
-
Changes the output of this relation to the given expressions, similar to the SELECT
clause
in SQL.
- selectNodesToSplit(Queue<Tuple2<Object, Node>>, long, DecisionTreeMetadata, Random) - Static method in class org.apache.spark.mllib.tree.RandomForest
-
Pull nodes off of the queue, and collect a group of nodes to be split on this iteration.
- sender() - Method in class org.apache.spark.storage.BlockManagerMessages.RegisterBlockManager
-
- sendToDst(A) - Method in class org.apache.spark.graphx.EdgeContext
-
Sends a message to the destination vertex.
- sendToDst(A) - Method in class org.apache.spark.graphx.impl.AggregatingEdgeContext
-
- sendToSrc(A) - Method in class org.apache.spark.graphx.EdgeContext
-
Sends a message to the source vertex.
- sendToSrc(A) - Method in class org.apache.spark.graphx.impl.AggregatingEdgeContext
-
- sequenceFile(String, Class<K>, Class<V>, int) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Get an RDD for a Hadoop SequenceFile with given key and value types.
- sequenceFile(String, Class<K>, Class<V>) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Get an RDD for a Hadoop SequenceFile.
- sequenceFile(String, Class<K>, Class<V>, int) - Method in class org.apache.spark.SparkContext
-
Get an RDD for a Hadoop SequenceFile with given key and value types.
- sequenceFile(String, Class<K>, Class<V>) - Method in class org.apache.spark.SparkContext
-
Get an RDD for a Hadoop SequenceFile with given key and value types.
- sequenceFile(String, int, ClassTag<K>, ClassTag<V>, Function0<WritableConverter<K>>, Function0<WritableConverter<V>>) - Method in class org.apache.spark.SparkContext
-
Version of sequenceFile() for types implicitly convertible to Writables through a
WritableConverter.
- SequenceFileRDDFunctions<K,V> - Class in org.apache.spark.rdd
-
Extra functions available on RDDs of (key, value) pairs to create a Hadoop SequenceFile,
through an implicit conversion.
- SequenceFileRDDFunctions(RDD<Tuple2<K, V>>, Function1<K, Writable>, ClassTag<K>, Function1<V, Writable>, ClassTag<V>) - Constructor for class org.apache.spark.rdd.SequenceFileRDDFunctions
-
- ser() - Method in class org.apache.spark.scheduler.TaskSetManager
-
- ser() - Method in class org.apache.spark.sql.execution.KryoResourcePool
-
- SerializableBuffer - Class in org.apache.spark.util
-
A wrapper around a java.nio.ByteBuffer that is serializable through Java serialization, to make
it easier to pass ByteBuffers in case class messages.
- SerializableBuffer(ByteBuffer) - Constructor for class org.apache.spark.util.SerializableBuffer
-
- serializableHadoopSplit() - Method in class org.apache.spark.rdd.NewHadoopPartition
-
- SerializableWritable<T extends org.apache.hadoop.io.Writable> - Class in org.apache.spark
-
- SerializableWritable(T) - Constructor for class org.apache.spark.SerializableWritable
-
- SerializationStream - Class in org.apache.spark.serializer
-
:: DeveloperApi ::
A stream for writing serialized objects.
- SerializationStream() - Constructor for class org.apache.spark.serializer.SerializationStream
-
- serialize(Object) - Method in class org.apache.spark.mllib.linalg.VectorUDT
-
- serialize(T, ClassTag<T>) - Method in class org.apache.spark.serializer.JavaSerializerInstance
-
- serialize(T, ClassTag<T>) - Method in class org.apache.spark.serializer.KryoSerializerInstance
-
- serialize(T, ClassTag<T>) - Method in class org.apache.spark.serializer.SerializerInstance
-
- serialize(Object) - Method in class org.apache.spark.sql.api.java.JavaToScalaUDTWrapper
-
Convert the user type to a SQL datum
- serialize(Object) - Method in class org.apache.spark.sql.api.java.ScalaToJavaUDTWrapper
-
Convert the user type to a SQL datum
- serialize(Object) - Method in class org.apache.spark.sql.api.java.UserDefinedType
-
Convert the user type to a SQL datum
- serialize(T, ClassTag<T>) - Static method in class org.apache.spark.sql.execution.SparkSqlSerializer
-
- serialize(Object, ObjectInspector) - Method in class org.apache.spark.sql.hive.parquet.FakeParquetSerDe
-
- serialize(Object) - Method in class org.apache.spark.sql.test.ExamplePointUDT
-
- serialize(T) - Static method in class org.apache.spark.util.Utils
-
Serialize an object using Java serialization
- serializedData() - Method in class org.apache.spark.scheduler.local.StatusUpdate
-
- serializedTask() - Method in class org.apache.spark.scheduler.TaskDescription
-
- serializeFilterExpressions(Seq<Expression>, Configuration) - Static method in class org.apache.spark.sql.parquet.ParquetFilters
-
Note: Inside the Hadoop API we only have access to
Configuration
, not to
SparkContext
, so we cannot use broadcasts to convey
the actual filter predicate.
- serializeMapStatuses(MapStatus[]) - Static method in class org.apache.spark.MapOutputTracker
-
- serializePlan(Object, OutputStream) - Method in class org.apache.spark.sql.hive.HiveFunctionWrapper
-
- Serializer - Class in org.apache.spark.serializer
-
:: DeveloperApi ::
A serializer.
- Serializer() - Constructor for class org.apache.spark.serializer.Serializer
-
- serializer() - Method in class org.apache.spark.ShuffleDependency
-
- serializer() - Method in class org.apache.spark.SparkEnv
-
- SerializerInstance - Class in org.apache.spark.serializer
-
:: DeveloperApi ::
An instance of a serializer, for use by one thread at a time.
- SerializerInstance() - Constructor for class org.apache.spark.serializer.SerializerInstance
-
- serializeStream(OutputStream) - Method in class org.apache.spark.serializer.JavaSerializerInstance
-
- serializeStream(OutputStream) - Method in class org.apache.spark.serializer.KryoSerializerInstance
-
- serializeStream(OutputStream) - Method in class org.apache.spark.serializer.SerializerInstance
-
- serializeViaNestedStream(OutputStream, SerializerInstance, Function1<SerializationStream, BoxedUnit>) - Static method in class org.apache.spark.util.Utils
-
Serialize via nested stream using specific serializer
- serializeWithDependencies(Task<?>, HashMap<String, Object>, HashMap<String, Object>, SerializerInstance) - Static method in class org.apache.spark.scheduler.Task
-
Serialize a task and the current app dependencies (files and JARs added to the SparkContext)
- server() - Method in class org.apache.spark.streaming.flume.FlumeReceiver
-
- server() - Method in class org.apache.spark.ui.ServerInfo
-
- ServerInfo - Class in org.apache.spark.ui
-
- ServerInfo(Server, int, ContextHandlerCollection) - Constructor for class org.apache.spark.ui.ServerInfo
-
- ServerStateException - Exception in org.apache.spark
-
Exception type thrown by HttpServer when it is in the wrong state for an operation.
- ServerStateException(String) - Constructor for exception org.apache.spark.ServerStateException
-
- serverUri() - Method in class org.apache.spark.HttpFileServer
-
- SERVLET_DEFAULT_SAMPLE() - Method in class org.apache.spark.metrics.sink.MetricsServlet
-
- SERVLET_KEY_PATH() - Method in class org.apache.spark.metrics.sink.MetricsServlet
-
- SERVLET_KEY_SAMPLE() - Method in class org.apache.spark.metrics.sink.MetricsServlet
-
- servletPath() - Method in class org.apache.spark.metrics.sink.MetricsServlet
-
- servletShowSample() - Method in class org.apache.spark.metrics.sink.MetricsServlet
-
- set(long, long, int, int, VD, VD, ED) - Method in class org.apache.spark.graphx.impl.AggregatingEdgeContext
-
- set(Param<T>, T) - Method in interface org.apache.spark.ml.param.Params
-
Sets a parameter in the embedded param map.
- set(String, String) - Method in class org.apache.spark.SparkConf
-
Set a configuration variable.
- set(SparkEnv) - Static method in class org.apache.spark.SparkEnv
-
- set(Function0<Object>) - Method in class org.apache.spark.sql.hive.DeferredObjectAdapter
-
- setAcls(boolean) - Method in class org.apache.spark.SecurityManager
-
- setActiveContext(SparkContext, boolean) - Static method in class org.apache.spark.SparkContext
-
Called at the end of the SparkContext constructor to ensure that no other SparkContext has
raced with this constructor and started.
- setAdminAcls(String) - Method in class org.apache.spark.SecurityManager
-
Admin acls should be set before the view or modify acls.
- setAggregator(Aggregator<K, V, C>) - Method in class org.apache.spark.rdd.ShuffledRDD
-
Set aggregator for RDD's shuffle.
- setAlgo(String) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
Sets Algorithm using a String.
- setAll(Traversable<Tuple2<String, String>>) - Method in class org.apache.spark.SparkConf
-
Set multiple parameters together
- setAlpha(double) - Method in class org.apache.spark.mllib.recommendation.ALS
-
:: Experimental ::
Sets the constant used in computing confidence in implicit ALS.
- setAppName(String) - Method in class org.apache.spark.SparkConf
-
Set a name for your application.
- setAppName(String) - Method in class org.apache.spark.ui.SparkUI
-
Set the app name for this UI.
- setBatchDuration(Duration) - Method in class org.apache.spark.streaming.DStreamGraph
-
- setBlocks(int) - Method in class org.apache.spark.mllib.recommendation.ALS
-
Set the number of blocks for both user blocks and product blocks to parallelize the computation
into; pass -1 for an auto-configured number of blocks.
- setCallSite(String) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Pass-through to SparkContext.setCallSite.
- setCallSite(String) - Method in class org.apache.spark.SparkContext
-
Set the thread-local property for overriding the call sites
of actions and RDDs.
- setCallSite(CallSite) - Method in class org.apache.spark.SparkContext
-
Set the thread-local property for overriding the call sites
of actions and RDDs.
- setCategoricalFeaturesInfo(Map<Integer, Integer>) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
Sets categoricalFeaturesInfo using a Java Map.
- setCheckpointDir(String) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Set the directory under which RDDs are going to be checkpointed.
- setCheckpointDir(Option<String>) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- setCheckpointDir(String) - Method in class org.apache.spark.SparkContext
-
Set the directory under which RDDs are going to be checkpointed.
- setCheckpointInterval(int) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- setClock(Clock) - Method in class org.apache.spark.ExecutorAllocationManager
-
Use a different clock for this allocation manager.
- SetCommand - Class in org.apache.spark.sql.execution
-
:: DeveloperApi ::
- SetCommand(Option<Tuple2<String, Option<String>>>, Seq<Attribute>, SQLContext) - Constructor for class org.apache.spark.sql.execution.SetCommand
-
- setCompressCodec(String) - Method in class org.apache.spark.sql.hive.ShimFileSinkDesc
-
- setCompressed(boolean) - Method in class org.apache.spark.sql.hive.ShimFileSinkDesc
-
- setCompressType(String) - Method in class org.apache.spark.sql.hive.ShimFileSinkDesc
-
- setConf(Configuration) - Method in class org.apache.spark.input.WholeCombineFileRecordReader
-
- setConf(Configuration) - Method in class org.apache.spark.input.WholeTextFileInputFormat
-
- setConf(Configuration) - Method in class org.apache.spark.input.WholeTextFileRecordReader
-
- setConf(String, String) - Method in class org.apache.spark.sql.hive.HiveContext
-
- setConf(Properties) - Method in interface org.apache.spark.sql.SQLConf
-
Set Spark SQL configuration properties.
- setConf(String, String) - Method in interface org.apache.spark.sql.SQLConf
-
Set the given Spark SQL configuration property.
- setContext(StreamingContext) - Method in class org.apache.spark.streaming.dstream.DStream
-
- setContext(StreamingContext) - Method in class org.apache.spark.streaming.DStreamGraph
-
- setConvergenceTol(double) - Method in class org.apache.spark.mllib.optimization.LBFGS
-
Set the convergence tolerance of iterations for L-BFGS.
- setCustomHostname(String) - Static method in class org.apache.spark.util.Utils
-
Allow setting a custom host name because when we run on Mesos we need to use the same
hostname it reports to the master.
- setDAGScheduler(DAGScheduler) - Method in interface org.apache.spark.scheduler.TaskScheduler
-
- setDAGScheduler(DAGScheduler) - Method in class org.apache.spark.scheduler.TaskSchedulerImpl
-
- setDecayFactor(double) - Method in class org.apache.spark.mllib.clustering.StreamingKMeans
-
Set the decay factor directly (for forgetful algorithms).
- setDefaultClassLoader(ClassLoader) - Method in class org.apache.spark.serializer.Serializer
-
Sets a class loader for the serializer to use in deserialization.
- setDelaySeconds(SparkConf, Enumeration.Value, int) - Static method in class org.apache.spark.util.MetadataCleaner
-
- setDelaySeconds(SparkConf, int, boolean) - Static method in class org.apache.spark.util.MetadataCleaner
-
Set the default delay time (in seconds).
- setDestTableId(int) - Method in class org.apache.spark.sql.hive.ShimFileSinkDesc
-
- setEpsilon(double) - Method in class org.apache.spark.mllib.clustering.KMeans
-
Set the distance threshold within which we've consider centers to have converged.
- setEstimator(Estimator<?>) - Method in class org.apache.spark.ml.tuning.CrossValidator
-
- setEstimatorParamMaps(ParamMap[]) - Method in class org.apache.spark.ml.tuning.CrossValidator
-
- setEvaluator(Evaluator) - Method in class org.apache.spark.ml.tuning.CrossValidator
-
- setExecutorEnv(String, String) - Method in class org.apache.spark.SparkConf
-
Set an environment variable to be used when launching executors for this application.
- setExecutorEnv(Seq<Tuple2<String, String>>) - Method in class org.apache.spark.SparkConf
-
Set multiple environment variables to be used when launching executors.
- setExecutorEnv(Tuple2<String, String>[]) - Method in class org.apache.spark.SparkConf
-
Set multiple environment variables to be used when launching executors.
- setFailure(Exception) - Method in class org.apache.spark.partial.PartialResult
-
- setFeatureScaling(boolean) - Method in class org.apache.spark.mllib.regression.GeneralizedLinearAlgorithm
-
Set if the algorithm should use feature scaling to improve the convergence during optimization.
- setFeaturesCol(String) - Method in class org.apache.spark.ml.classification.LogisticRegression
-
- setFeaturesCol(String) - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- setField(MutableRow, int, byte[]) - Static method in class org.apache.spark.sql.columnar.BINARY
-
- setField(MutableRow, int, boolean) - Static method in class org.apache.spark.sql.columnar.BOOLEAN
-
- setField(MutableRow, int, byte) - Static method in class org.apache.spark.sql.columnar.BYTE
-
- setField(MutableRow, int, JvmType) - Method in class org.apache.spark.sql.columnar.ColumnType
-
Sets row(ordinal)
to field
.
- setField(MutableRow, int, Date) - Static method in class org.apache.spark.sql.columnar.DATE
-
- setField(MutableRow, int, double) - Static method in class org.apache.spark.sql.columnar.DOUBLE
-
- setField(MutableRow, int, float) - Static method in class org.apache.spark.sql.columnar.FLOAT
-
- setField(MutableRow, int, byte[]) - Static method in class org.apache.spark.sql.columnar.GENERIC
-
- setField(MutableRow, int, int) - Static method in class org.apache.spark.sql.columnar.INT
-
- setField(MutableRow, int, long) - Static method in class org.apache.spark.sql.columnar.LONG
-
- setField(MutableRow, int, short) - Static method in class org.apache.spark.sql.columnar.SHORT
-
- setField(MutableRow, int, String) - Static method in class org.apache.spark.sql.columnar.STRING
-
- setField(MutableRow, int, Timestamp) - Static method in class org.apache.spark.sql.columnar.TIMESTAMP
-
- setFinalValue(R) - Method in class org.apache.spark.partial.PartialResult
-
- setGradient(Gradient) - Method in class org.apache.spark.mllib.optimization.GradientDescent
-
Set the gradient function (of the loss function of one single data example)
to be used for SGD.
- setGradient(Gradient) - Method in class org.apache.spark.mllib.optimization.LBFGS
-
Set the gradient function (of the loss function of one single data example)
to be used for L-BFGS.
- setGraph(DStreamGraph) - Method in class org.apache.spark.streaming.dstream.DStream
-
- setHalfLife(double, String) - Method in class org.apache.spark.mllib.clustering.StreamingKMeans
-
Set the half life and time unit ("batches" or "points") for forgetful algorithms.
- setId(int) - Method in class org.apache.spark.streaming.scheduler.Job
-
- setIfMissing(String, String) - Method in class org.apache.spark.SparkConf
-
Set a parameter if it isn't already configured
- setImplicitPrefs(boolean) - Method in class org.apache.spark.mllib.recommendation.ALS
-
Sets whether to use implicit preference.
- setImpurity(Impurity) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- setInitialCenters(Vector[], double[]) - Method in class org.apache.spark.mllib.clustering.StreamingKMeans
-
Specify initial centers directly.
- setInitializationMode(String) - Method in class org.apache.spark.mllib.clustering.KMeans
-
Set the initialization algorithm.
- setInitializationSteps(int) - Method in class org.apache.spark.mllib.clustering.KMeans
-
Set the number of steps for the k-means|| initialization mode.
- setInitialWeights(Vector) - Method in class org.apache.spark.mllib.regression.StreamingLinearRegressionWithSGD
-
Set the initial weights.
- setInputCol(String) - Method in class org.apache.spark.ml.feature.StandardScaler
-
- setInputCol(String) - Method in class org.apache.spark.ml.feature.StandardScalerModel
-
- setInputCol(String) - Method in class org.apache.spark.ml.UnaryTransformer
-
- setIntercept(boolean) - Method in class org.apache.spark.mllib.regression.GeneralizedLinearAlgorithm
-
Set if the algorithm should add an intercept.
- setIntermediateRDDStorageLevel(StorageLevel) - Method in class org.apache.spark.mllib.recommendation.ALS
-
:: DeveloperApi ::
Sets storage level for intermediate RDDs (user/product in/out links).
- setIterations(int) - Method in class org.apache.spark.mllib.recommendation.ALS
-
Set the number of iterations to run.
- setJars(Seq<String>) - Method in class org.apache.spark.SparkConf
-
Set JAR files to distribute to the cluster.
- setJars(String[]) - Method in class org.apache.spark.SparkConf
-
Set JAR files to distribute to the cluster.
- setJobDescription(String) - Method in class org.apache.spark.SparkContext
-
Set a human readable description of the current job.
- setJobGroup(String, String, boolean) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Assigns a group ID to all the jobs started by this thread until the group ID is set to a
different value or cleared.
- setJobGroup(String, String) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Assigns a group ID to all the jobs started by this thread until the group ID is set to a
different value or cleared.
- setJobGroup(String, String, boolean) - Method in class org.apache.spark.SparkContext
-
Assigns a group ID to all the jobs started by this thread until the group ID is set to a
different value or cleared.
- setK(int) - Method in class org.apache.spark.mllib.clustering.KMeans
-
Set the number of clusters to create (k).
- setK(int) - Method in class org.apache.spark.mllib.clustering.StreamingKMeans
-
Set the number of clusters.
- setKeyOrdering(Ordering<K>) - Method in class org.apache.spark.rdd.ShuffledRDD
-
Set key ordering for RDD's shuffle.
- setLabelCol(String) - Method in class org.apache.spark.ml.classification.LogisticRegression
-
- setLabelCol(String) - Method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
-
- setLambda(double) - Method in class org.apache.spark.mllib.classification.NaiveBayes
-
Set the smoothing parameter.
- setLambda(double) - Method in class org.apache.spark.mllib.recommendation.ALS
-
Set the regularization parameter, lambda.
- setLearningRate(double) - Method in class org.apache.spark.mllib.feature.Word2Vec
-
Sets initial learning rate (default: 0.025).
- setLearningRate(double) - Method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
-
- setLocalProperties(Properties) - Method in class org.apache.spark.SparkContext
-
- setLocalProperty(String, String) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Set a local property that affects jobs submitted from this thread, such as the
Spark fair scheduler pool.
- setLocalProperty(String, String) - Method in class org.apache.spark.SparkContext
-
Set a local property that affects jobs submitted from this thread, such as the
Spark fair scheduler pool.
- setLocation(Table, CreateTableDesc) - Static method in class org.apache.spark.sql.hive.HiveShim
-
- setLoss(Loss) - Method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
-
- setMapSideCombine(boolean) - Method in class org.apache.spark.rdd.ShuffledRDD
-
Set mapSideCombine flag for RDD's shuffle.
- setMaster(String) - Method in class org.apache.spark.SparkConf
-
The master URL to connect to, such as "local" to run locally with one thread, "local[4]" to
run locally with 4 cores, or "spark://master:7077" to run on a Spark standalone cluster.
- setMaxBins(int) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- setMaxDepth(int) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- setMaxIter(int) - Method in class org.apache.spark.ml.classification.LogisticRegression
-
- setMaxIterations(int) - Method in class org.apache.spark.mllib.clustering.KMeans
-
Set maximum number of iterations to run.
- setMaxMemoryInMB(int) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- setMaxNumIterations(int) - Method in class org.apache.spark.mllib.optimization.LBFGS
-
- setMetricName(String) - Method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
-
- setMiniBatchFraction(double) - Method in class org.apache.spark.mllib.optimization.GradientDescent
-
:: Experimental ::
Set fraction of data to be used for each SGD iteration.
- setMiniBatchFraction(double) - Method in class org.apache.spark.mllib.regression.StreamingLinearRegressionWithSGD
-
Set the fraction of each batch to use for updates.
- setMinInfoGain(double) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- setMinInstancesPerNode(int) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- setMinPartitions(JobContext, int) - Method in class org.apache.spark.input.StreamFileInputFormat
-
Allow minPartitions set by end-user in order to keep compatibility with old Hadoop API
which is set through setMaxSplitSize
- setMinPartitions(JobContext, int) - Method in class org.apache.spark.input.WholeTextFileInputFormat
-
Allow minPartitions set by end-user in order to keep compatibility with old Hadoop API,
which is set through setMaxSplitSize
- setModifyAcls(Set<String>, String) - Method in class org.apache.spark.SecurityManager
-
Admin acls should be set before the view or modify acls.
- setName(String) - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Assign a name to this RDD
- setName(String) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Assign a name to this RDD
- setName(String) - Method in class org.apache.spark.api.java.JavaRDD
-
Assign a name to this RDD
- setName(String) - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- setName(String) - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- setName(String) - Method in class org.apache.spark.rdd.RDD
-
Assign a name to this RDD
- setName(String) - Method in class org.apache.spark.sql.api.java.JavaSchemaRDD
-
Assign a name to this RDD
- setNonnegative(boolean) - Method in class org.apache.spark.mllib.recommendation.ALS
-
Set whether the least-squares problems solved at each iteration should have
nonnegativity constraints.
- setNumClasses(int) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- setNumCorrections(int) - Method in class org.apache.spark.mllib.optimization.LBFGS
-
Set the number of corrections used in the LBFGS update.
- setNumFeatures(int) - Method in class org.apache.spark.ml.feature.HashingTF
-
- setNumFolds(int) - Method in class org.apache.spark.ml.tuning.CrossValidator
-
- setNumIterations(int) - Method in class org.apache.spark.mllib.feature.Word2Vec
-
Sets number of iterations (default: 1), which should be smaller than or equal to number of
partitions.
- setNumIterations(int) - Method in class org.apache.spark.mllib.optimization.GradientDescent
-
Set the number of iterations for SGD.
- setNumIterations(int) - Method in class org.apache.spark.mllib.optimization.LBFGS
-
Set the maximal number of iterations for L-BFGS.
- setNumIterations(int) - Method in class org.apache.spark.mllib.regression.StreamingLinearRegressionWithSGD
-
Set the number of iterations of gradient descent to run per update.
- setNumIterations(int) - Method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
-
- setNumPartitions(int) - Method in class org.apache.spark.mllib.feature.Word2Vec
-
Sets number of partitions (default: 1).
- setNumSplits(int, int) - Method in class org.apache.spark.mllib.tree.impl.DecisionTreeMetadata
-
Set number of splits for a continuous feature.
- setOutputCol(String) - Method in class org.apache.spark.ml.feature.StandardScaler
-
- setOutputCol(String) - Method in class org.apache.spark.ml.feature.StandardScalerModel
-
- setOutputCol(String) - Method in class org.apache.spark.ml.UnaryTransformer
-
- setPredictionCol(String) - Method in class org.apache.spark.ml.classification.LogisticRegression
-
- setPredictionCol(String) - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- setProductBlocks(int) - Method in class org.apache.spark.mllib.recommendation.ALS
-
Set the number of product blocks to parallelize the computation.
- setQuantileCalculationStrategy(Enumeration.Value) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- setRandomCenters(int, double, long) - Method in class org.apache.spark.mllib.clustering.StreamingKMeans
-
Initialize random centers, requiring only the number of dimensions.
- setRank(int) - Method in class org.apache.spark.mllib.recommendation.ALS
-
Set the rank of the feature matrices computed (number of features).
- setReceiverId(int) - Method in class org.apache.spark.streaming.receiver.Receiver
-
Set the ID of the DStream that this receiver is associated with.
- setRegParam(double) - Method in class org.apache.spark.ml.classification.LogisticRegression
-
- setRegParam(double) - Method in class org.apache.spark.mllib.optimization.GradientDescent
-
Set the regularization parameter.
- setRegParam(double) - Method in class org.apache.spark.mllib.optimization.LBFGS
-
Set the regularization parameter.
- setRest(long, int, VD, ED) - Method in class org.apache.spark.graphx.impl.AggregatingEdgeContext
-
- setRuns(int) - Method in class org.apache.spark.mllib.clustering.KMeans
-
:: Experimental ::
Set the number of runs of the algorithm to execute in parallel.
- setSchema(Seq<Attribute>, Configuration) - Static method in class org.apache.spark.sql.parquet.RowWriteSupport
-
- setScoreCol(String) - Method in class org.apache.spark.ml.classification.LogisticRegression
-
- setScoreCol(String) - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- setScoreCol(String) - Method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
-
- setSeed(long) - Method in class org.apache.spark.mllib.feature.Word2Vec
-
Sets random seed (default: a random long integer).
- setSeed(long) - Method in class org.apache.spark.mllib.random.PoissonGenerator
-
- setSeed(long) - Method in class org.apache.spark.mllib.random.StandardNormalGenerator
-
- setSeed(long) - Method in class org.apache.spark.mllib.random.UniformGenerator
-
- setSeed(long) - Method in class org.apache.spark.mllib.recommendation.ALS
-
Sets a random seed to have deterministic results.
- setSeed(long) - Method in class org.apache.spark.util.random.BernoulliCellSampler
-
- setSeed(long) - Method in class org.apache.spark.util.random.BernoulliSampler
-
- setSeed(long) - Method in class org.apache.spark.util.random.PoissonSampler
-
- setSeed(long) - Method in interface org.apache.spark.util.random.Pseudorandom
-
Set random seed.
- setSeed(long) - Method in class org.apache.spark.util.random.XORShiftRandom
-
- setSerializer(Serializer) - Method in class org.apache.spark.rdd.CoGroupedRDD
-
Set a serializer for this RDD's shuffle, or null to use the default (spark.serializer)
- setSerializer(Serializer) - Method in class org.apache.spark.rdd.ShuffledRDD
-
Set a serializer for this RDD's shuffle, or null to use the default (spark.serializer)
- setSerializer(Serializer) - Method in class org.apache.spark.rdd.SubtractedRDD
-
Set a serializer for this RDD's shuffle, or null to use the default (spark.serializer)
- setSparkHome(String) - Method in class org.apache.spark.SparkConf
-
Set the location where Spark is installed on worker nodes.
- setSrcOnly(long, int, VD) - Method in class org.apache.spark.graphx.impl.AggregatingEdgeContext
-
- setStages(PipelineStage[]) - Method in class org.apache.spark.ml.Pipeline
-
- setStepSize(double) - Method in class org.apache.spark.mllib.optimization.GradientDescent
-
Set the initial step size of SGD for the first step.
- setStepSize(double) - Method in class org.apache.spark.mllib.regression.StreamingLinearRegressionWithSGD
-
Set the step size for gradient descent.
- setStreamingLogLevels() - Static method in class org.apache.spark.examples.streaming.StreamingExamples
-
Set reasonable logging levels for streaming if the user has not configured log4j.
- setSubsamplingRate(double) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- setTableInfo(TableDesc) - Method in class org.apache.spark.sql.hive.ShimFileSinkDesc
-
- setTaskContext(TaskContext) - Static method in class org.apache.spark.TaskContextHelper
-
- setThreshold(double) - Method in class org.apache.spark.ml.classification.LogisticRegression
-
- setThreshold(double) - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- setThreshold(double) - Method in class org.apache.spark.mllib.classification.LogisticRegressionModel
-
:: Experimental ::
Sets the threshold that separates positive predictions from negative predictions.
- setThreshold(double) - Method in class org.apache.spark.mllib.classification.SVMModel
-
:: Experimental ::
Sets the threshold that separates positive predictions from negative predictions.
- setTime(long) - Method in class org.apache.spark.streaming.util.ManualClock
-
- settings() - Method in interface org.apache.spark.sql.SQLConf
-
Only low degree of contention is expected for conf, thus NOT using ConcurrentHashMap.
- setTreeStrategy(Strategy) - Method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
-
- setup(int, int, int) - Method in class org.apache.spark.SparkHadoopWriter
-
- setUpdater(Updater) - Method in class org.apache.spark.mllib.optimization.GradientDescent
-
Set the updater function to actually perform a gradient step in a given direction.
- setUpdater(Updater) - Method in class org.apache.spark.mllib.optimization.LBFGS
-
Set the updater function to actually perform a gradient step in a given direction.
- setupGroups(int) - Method in class org.apache.spark.rdd.PartitionCoalescer
-
Initializes targetLen partition groups and assigns a preferredLocation
This uses coupon collector to estimate how many preferredLocations it must rotate through
until it has seen most of the preferred locations (2 * n log(n))
- setUseNodeIdCache(boolean) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- setUserBlocks(int) - Method in class org.apache.spark.mllib.recommendation.ALS
-
Set the number of user blocks to parallelize the computation.
- setValidateData(boolean) - Method in class org.apache.spark.mllib.regression.GeneralizedLinearAlgorithm
-
Set if the algorithm should validate data before training.
- setValue(R) - Method in class org.apache.spark.Accumulable
-
Set the accumulator's value; only allowed on master
- setVectorSize(int) - Method in class org.apache.spark.mllib.feature.Word2Vec
-
Sets vector size (default: 100).
- setViewAcls(Set<String>, String) - Method in class org.apache.spark.SecurityManager
-
Admin acls should be set before the view or modify acls.
- setViewAcls(String, String) - Method in class org.apache.spark.SecurityManager
-
- shardId() - Method in class org.apache.spark.streaming.kinesis.KinesisRecordProcessor
-
- ShimFileSinkDesc - Class in org.apache.spark.sql.hive
-
- ShimFileSinkDesc(String, TableDesc, boolean) - Constructor for class org.apache.spark.sql.hive.ShimFileSinkDesc
-
- shippablePartitionToOps(ShippableVertexPartition<VD>, ClassTag<VD>) - Static method in class org.apache.spark.graphx.impl.ShippableVertexPartition
-
Implicit conversion to allow invoking VertexPartitionBase
operations directly on a
ShippableVertexPartition
.
- ShippableVertexPartition<VD> - Class in org.apache.spark.graphx.impl
-
A map from vertex id to vertex attribute that additionally stores edge partition join sites for
each vertex attribute, enabling joining with an
EdgeRDD
.
- ShippableVertexPartition(OpenHashSet<Object>, Object, BitSet, RoutingTablePartition, ClassTag<VD>) - Constructor for class org.apache.spark.graphx.impl.ShippableVertexPartition
-
- ShippableVertexPartition.ShippableVertexPartitionOpsConstructor$ - Class in org.apache.spark.graphx.impl
-
Implicit evidence that ShippableVertexPartition
is a member of the
VertexPartitionBaseOpsConstructor
typeclass.
- ShippableVertexPartition.ShippableVertexPartitionOpsConstructor$() - Constructor for class org.apache.spark.graphx.impl.ShippableVertexPartition.ShippableVertexPartitionOpsConstructor$
-
- ShippableVertexPartitionOps<VD> - Class in org.apache.spark.graphx.impl
-
- ShippableVertexPartitionOps(ShippableVertexPartition<VD>, ClassTag<VD>) - Constructor for class org.apache.spark.graphx.impl.ShippableVertexPartitionOps
-
- shipVertexAttributes(boolean, boolean) - Method in class org.apache.spark.graphx.impl.ShippableVertexPartition
-
Generate a VertexAttributeBlock
for each edge partition keyed on the edge partition ID.
- shipVertexAttributes(boolean, boolean) - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- shipVertexAttributes(boolean, boolean) - Method in class org.apache.spark.graphx.VertexRDD
-
Generates an RDD of vertex attributes suitable for shipping to the edge partitions.
- shipVertexIds() - Method in class org.apache.spark.graphx.impl.ShippableVertexPartition
-
Generate a VertexId
array for each edge partition keyed on the edge partition ID.
- shipVertexIds() - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- shipVertexIds() - Method in class org.apache.spark.graphx.VertexRDD
-
Generates an RDD of vertex IDs suitable for shipping to the edge partitions.
- SHORT - Class in org.apache.spark.sql.columnar
-
- SHORT() - Constructor for class org.apache.spark.sql.columnar.SHORT
-
- SHORT_FORM() - Static method in class org.apache.spark.util.CallSite
-
- ShortColumnAccessor - Class in org.apache.spark.sql.columnar
-
- ShortColumnAccessor(ByteBuffer) - Constructor for class org.apache.spark.sql.columnar.ShortColumnAccessor
-
- ShortColumnBuilder - Class in org.apache.spark.sql.columnar
-
- ShortColumnBuilder() - Constructor for class org.apache.spark.sql.columnar.ShortColumnBuilder
-
- ShortColumnStats - Class in org.apache.spark.sql.columnar
-
- ShortColumnStats() - Constructor for class org.apache.spark.sql.columnar.ShortColumnStats
-
- ShortestPaths - Class in org.apache.spark.graphx.lib
-
Computes shortest paths to the given set of landmark vertices, returning a graph where each
vertex attribute is a map containing the shortest-path distance to each reachable landmark.
- ShortestPaths() - Constructor for class org.apache.spark.graphx.lib.ShortestPaths
-
- shortForm() - Method in class org.apache.spark.util.CallSite
-
- shortParquetCompressionCodecNames() - Static method in class org.apache.spark.sql.parquet.ParquetRelation
-
- ShortType - Static variable in class org.apache.spark.sql.api.java.DataType
-
Gets the ShortType object.
- ShortType - Class in org.apache.spark.sql.api.java
-
The data type representing short and Short values.
- shouldCheckpoint() - Method in class org.apache.spark.streaming.kinesis.KinesisCheckpointState
-
Check if it's time to checkpoint based on the current time and the derived time
for the next checkpoint
- shouldRollover(long) - Method in interface org.apache.spark.util.logging.RollingPolicy
-
Whether rollover should be initiated at this moment
- shouldRollover(long) - Method in class org.apache.spark.util.logging.SizeBasedRollingPolicy
-
Should rollover if the next set of bytes is going to exceed the size limit
- shouldRollover(long) - Method in class org.apache.spark.util.logging.TimeBasedRollingPolicy
-
Should rollover if current time has exceeded next rollover time
- shouldSend() - Method in class org.apache.spark.mllib.recommendation.OutLinkBlock
-
- showBytesDistribution(String, Function2<TaskInfo, TaskMetrics, Option<Object>>, Seq<Tuple2<TaskInfo, TaskMetrics>>) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- showBytesDistribution(String, Option<Distribution>) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- showBytesDistribution(String, Distribution) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- showDistribution(String, Distribution, Function1<Object, String>) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- showDistribution(String, Option<Distribution>, Function1<Object, String>) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- showDistribution(String, Option<Distribution>, String) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- showDistribution(String, String, Function2<TaskInfo, TaskMetrics, Option<Object>>, Seq<Tuple2<TaskInfo, TaskMetrics>>) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- showMillisDistribution(String, Option<Distribution>) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- showMillisDistribution(String, Function2<TaskInfo, TaskMetrics, Option<Object>>, Seq<Tuple2<TaskInfo, TaskMetrics>>) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- showMillisDistribution(String, Function1<BatchInfo, Option<Object>>) - Method in class org.apache.spark.streaming.scheduler.StatsReportListener
-
- showQuantiles(PrintStream) - Method in class org.apache.spark.util.Distribution
-
- SHUFFLE() - Static method in class org.apache.spark.storage.BlockId
-
- SHUFFLE_BLOCK_MANAGER() - Static method in class org.apache.spark.util.MetadataCleanerType
-
- SHUFFLE_DATA() - Static method in class org.apache.spark.storage.BlockId
-
- SHUFFLE_INDEX() - Static method in class org.apache.spark.storage.BlockId
-
- SHUFFLE_READ() - Static method in class org.apache.spark.ui.ToolTips
-
- SHUFFLE_WRITE() - Static method in class org.apache.spark.ui.ToolTips
-
- ShuffleBlockFetcherIterator - Class in org.apache.spark.storage
-
An iterator that fetches multiple blocks.
- ShuffleBlockFetcherIterator(TaskContext, ShuffleClient, BlockManager, Seq<Tuple2<BlockManagerId, Seq<Tuple2<BlockId, Object>>>>, Serializer, long) - Constructor for class org.apache.spark.storage.ShuffleBlockFetcherIterator
-
- ShuffleBlockFetcherIterator.FailureFetchResult - Class in org.apache.spark.storage
-
Result of a fetch from a remote block unsuccessfully.
- ShuffleBlockFetcherIterator.FailureFetchResult(BlockId, Throwable) - Constructor for class org.apache.spark.storage.ShuffleBlockFetcherIterator.FailureFetchResult
-
- ShuffleBlockFetcherIterator.FailureFetchResult$ - Class in org.apache.spark.storage
-
- ShuffleBlockFetcherIterator.FailureFetchResult$() - Constructor for class org.apache.spark.storage.ShuffleBlockFetcherIterator.FailureFetchResult$
-
- ShuffleBlockFetcherIterator.FetchRequest - Class in org.apache.spark.storage
-
A request to fetch blocks from a remote BlockManager.
- ShuffleBlockFetcherIterator.FetchRequest(BlockManagerId, Seq<Tuple2<BlockId, Object>>) - Constructor for class org.apache.spark.storage.ShuffleBlockFetcherIterator.FetchRequest
-
- ShuffleBlockFetcherIterator.FetchRequest$ - Class in org.apache.spark.storage
-
- ShuffleBlockFetcherIterator.FetchRequest$() - Constructor for class org.apache.spark.storage.ShuffleBlockFetcherIterator.FetchRequest$
-
- ShuffleBlockFetcherIterator.FetchResult - Interface in org.apache.spark.storage
-
Result of a fetch from a remote block.
- ShuffleBlockFetcherIterator.SuccessFetchResult - Class in org.apache.spark.storage
-
Result of a fetch from a remote block successfully.
- ShuffleBlockFetcherIterator.SuccessFetchResult(BlockId, long, ManagedBuffer) - Constructor for class org.apache.spark.storage.ShuffleBlockFetcherIterator.SuccessFetchResult
-
- ShuffleBlockFetcherIterator.SuccessFetchResult$ - Class in org.apache.spark.storage
-
- ShuffleBlockFetcherIterator.SuccessFetchResult$() - Constructor for class org.apache.spark.storage.ShuffleBlockFetcherIterator.SuccessFetchResult$
-
- ShuffleBlockId - Class in org.apache.spark.storage
-
- ShuffleBlockId(int, int, int) - Constructor for class org.apache.spark.storage.ShuffleBlockId
-
- shuffleCleaned(int) - Method in interface org.apache.spark.CleanerListener
-
- shuffleClient() - Method in class org.apache.spark.storage.BlockManager
-
- ShuffleCoGroupSplitDep - Class in org.apache.spark.rdd
-
- ShuffleCoGroupSplitDep(ShuffleHandle) - Constructor for class org.apache.spark.rdd.ShuffleCoGroupSplitDep
-
- ShuffleDataBlockId - Class in org.apache.spark.storage
-
- ShuffleDataBlockId(int, int, int) - Constructor for class org.apache.spark.storage.ShuffleDataBlockId
-
- ShuffledDStream<K,V,C> - Class in org.apache.spark.streaming.dstream
-
- ShuffledDStream(DStream<Tuple2<K, V>>, Function1<V, C>, Function2<C, V, C>, Function2<C, C, C>, Partitioner, boolean, ClassTag<K>, ClassTag<V>, ClassTag<C>) - Constructor for class org.apache.spark.streaming.dstream.ShuffledDStream
-
- shuffleDep() - Method in class org.apache.spark.scheduler.Stage
-
- ShuffleDependency<K,V,C> - Class in org.apache.spark
-
:: DeveloperApi ::
Represents a dependency on the output of a shuffle stage.
- ShuffleDependency(RDD<? extends Product2<K, V>>, Partitioner, Option<Serializer>, Option<Ordering<K>>, Option<Aggregator<K, V, C>>, boolean) - Constructor for class org.apache.spark.ShuffleDependency
-
- ShuffledHashJoin - Class in org.apache.spark.sql.execution.joins
-
:: DeveloperApi ::
Performs an inner hash join of two child relations by first shuffling the data using the join
keys.
- ShuffledHashJoin(Seq<Expression>, Seq<Expression>, org.apache.spark.sql.execution.joins.BuildSide, SparkPlan, SparkPlan) - Constructor for class org.apache.spark.sql.execution.joins.ShuffledHashJoin
-
- ShuffledRDD<K,V,C> - Class in org.apache.spark.rdd
-
:: DeveloperApi ::
The resulting RDD from a shuffle (e.g.
- ShuffledRDD(RDD<? extends Product2<K, V>>, Partitioner) - Constructor for class org.apache.spark.rdd.ShuffledRDD
-
- ShuffledRDDPartition - Class in org.apache.spark.rdd
-
- ShuffledRDDPartition(int) - Constructor for class org.apache.spark.rdd.ShuffledRDDPartition
-
- shuffleHandle() - Method in class org.apache.spark.ShuffleDependency
-
- shuffleId() - Method in class org.apache.spark.CleanShuffle
-
- shuffleId() - Method in class org.apache.spark.FetchFailed
-
- shuffleId() - Method in class org.apache.spark.GetMapOutputStatuses
-
- shuffleId() - Method in class org.apache.spark.ShuffleDependency
-
- shuffleId() - Method in class org.apache.spark.storage.BlockManagerMessages.RemoveShuffle
-
- shuffleId() - Method in class org.apache.spark.storage.ShuffleBlockId
-
- shuffleId() - Method in class org.apache.spark.storage.ShuffleDataBlockId
-
- shuffleId() - Method in class org.apache.spark.storage.ShuffleIndexBlockId
-
- ShuffleIndexBlockId - Class in org.apache.spark.storage
-
- ShuffleIndexBlockId(int, int, int) - Constructor for class org.apache.spark.storage.ShuffleIndexBlockId
-
- shuffleManager() - Method in class org.apache.spark.SparkEnv
-
- ShuffleMapTask - Class in org.apache.spark.scheduler
-
A ShuffleMapTask divides the elements of an RDD into multiple buckets (based on a partitioner
specified in the ShuffleDependency).
- ShuffleMapTask(int, Broadcast<byte[]>, Partition, Seq<TaskLocation>) - Constructor for class org.apache.spark.scheduler.ShuffleMapTask
-
- ShuffleMapTask(int) - Constructor for class org.apache.spark.scheduler.ShuffleMapTask
-
A constructor used only in test suites.
- shuffleMemoryManager() - Method in class org.apache.spark.SparkEnv
-
- shuffleRead() - Method in class org.apache.spark.ui.jobs.UIData.ExecutorSummary
-
- shuffleReadBytes() - Method in class org.apache.spark.ui.jobs.UIData.StageUIData
-
- shuffleReadMetricsFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
-
- shuffleReadMetricsToJson(ShuffleReadMetrics) - Static method in class org.apache.spark.util.JsonProtocol
-
- shuffleServerId() - Method in class org.apache.spark.storage.BlockManager
-
- shuffleToMapStage() - Method in class org.apache.spark.scheduler.DAGScheduler
-
- shuffleWrite() - Method in class org.apache.spark.ui.jobs.UIData.ExecutorSummary
-
- shuffleWriteBytes() - Method in class org.apache.spark.ui.jobs.UIData.StageUIData
-
- shuffleWriteMetricsFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
-
- shuffleWriteMetricsToJson(ShuffleWriteMetrics) - Static method in class org.apache.spark.util.JsonProtocol
-
- shutdown(IRecordProcessorCheckpointer, ShutdownReason) - Method in class org.apache.spark.streaming.kinesis.KinesisRecordProcessor
-
Kinesis Client Library is shutting down this Worker for 1 of 2 reasons:
1) the stream is resharding by splitting or merging adjacent shards
(ShutdownReason.TERMINATE)
2) the failed or latent Worker has stopped sending heartbeats for whatever reason
(ShutdownReason.ZOMBIE)
- shutdownCallback() - Method in class org.apache.spark.scheduler.cluster.SparkDeploySchedulerBackend
-
- sideEffectResult() - Method in interface org.apache.spark.sql.execution.Command
-
A concrete command should override this lazy field to wrap up any side effects caused by the
command or any other computation that should be evaluated exactly once.
- SignalLogger - Class in org.apache.spark.util
-
Used to log signals received.
- SignalLogger() - Constructor for class org.apache.spark.util.SignalLogger
-
- SignalLoggerHandler - Class in org.apache.spark.util
-
- SignalLoggerHandler(String, Logger) - Constructor for class org.apache.spark.util.SignalLoggerHandler
-
- SimpleFutureAction<T> - Class in org.apache.spark
-
A
FutureAction
holding the result of an action that triggers a single job.
- SimpleFutureAction(JobWaiter<?>, Function0<T>) - Constructor for class org.apache.spark.SimpleFutureAction
-
- simpleString() - Method in class org.apache.spark.sql.sources.LogicalRelation
-
- SimpleUpdater - Class in org.apache.spark.mllib.optimization
-
:: DeveloperApi ::
A simple updater for gradient descent *without* any regularization.
- SimpleUpdater() - Constructor for class org.apache.spark.mllib.optimization.SimpleUpdater
-
- SimrSchedulerBackend - Class in org.apache.spark.scheduler.cluster
-
- SimrSchedulerBackend(TaskSchedulerImpl, SparkContext, String) - Constructor for class org.apache.spark.scheduler.cluster.SimrSchedulerBackend
-
- SingleItemData<T> - Class in org.apache.spark.streaming.receiver
-
- SingleItemData(T) - Constructor for class org.apache.spark.streaming.receiver.SingleItemData
-
- SingularValueDecomposition<UType,VType> - Class in org.apache.spark.mllib.linalg
-
:: Experimental ::
Represents singular value decomposition (SVD) factors.
- SingularValueDecomposition(UType, Vector, VType) - Constructor for class org.apache.spark.mllib.linalg.SingularValueDecomposition
-
- Sink - Interface in org.apache.spark.metrics.sink
-
- SINK_REGEX() - Static method in class org.apache.spark.metrics.MetricsSystem
-
- size() - Method in class org.apache.spark.api.java.JavaUtils.SerializableMapWrapper
-
- size() - Method in class org.apache.spark.graphx.impl.EdgePartition
-
The number of edges in this partition
- size() - Method in class org.apache.spark.graphx.impl.VertexPartitionBase
-
- size() - Method in class org.apache.spark.mllib.linalg.DenseVector
-
- size() - Method in class org.apache.spark.mllib.linalg.SparseVector
-
- size() - Method in interface org.apache.spark.mllib.linalg.Vector
-
Size of the vector.
- size() - Method in class org.apache.spark.mllib.rdd.RandomRDDPartition
-
- size() - Method in class org.apache.spark.rdd.PartitionGroup
-
- size() - Method in class org.apache.spark.scheduler.IndirectTaskResult
-
- size() - Method in class org.apache.spark.sql.parquet.CatalystArrayContainsNullConverter
-
- size() - Method in class org.apache.spark.sql.parquet.CatalystArrayConverter
-
- size() - Method in class org.apache.spark.sql.parquet.CatalystGroupConverter
-
- size() - Method in class org.apache.spark.sql.parquet.CatalystNativeArrayConverter
-
- size() - Method in class org.apache.spark.sql.parquet.CatalystPrimitiveRowConverter
-
- size() - Method in class org.apache.spark.storage.BlockInfo
-
- size() - Method in class org.apache.spark.storage.MemoryEntry
-
- size() - Method in class org.apache.spark.storage.PutResult
-
- size() - Method in class org.apache.spark.storage.ShuffleBlockFetcherIterator.FetchRequest
-
- size() - Method in class org.apache.spark.storage.ShuffleBlockFetcherIterator.SuccessFetchResult
-
- size() - Method in class org.apache.spark.util.BoundedPriorityQueue
-
- size() - Method in class org.apache.spark.util.TimeStampedHashMap
-
- size() - Method in class org.apache.spark.util.TimeStampedHashSet
-
- size() - Method in class org.apache.spark.util.TimeStampedWeakValueHashMap
-
- SIZE_DEFAULT() - Static method in class org.apache.spark.util.logging.RollingFileAppender
-
- SIZE_PROPERTY() - Static method in class org.apache.spark.util.logging.RollingFileAppender
-
- SizeBasedRollingPolicy - Class in org.apache.spark.util.logging
-
Defines a
RollingPolicy
by which files will be rolled
over after reaching a particular size.
- SizeBasedRollingPolicy(long, boolean) - Constructor for class org.apache.spark.util.logging.SizeBasedRollingPolicy
-
- SizeEstimator - Class in org.apache.spark.util
-
Estimates the sizes of Java objects (number of bytes of memory they occupy), for use in
memory-aware caches.
- SizeEstimator() - Constructor for class org.apache.spark.util.SizeEstimator
-
- sizeInBytes() - Method in class org.apache.spark.sql.columnar.ColumnStatisticsSchema
-
- sizeInBytes() - Method in interface org.apache.spark.sql.columnar.ColumnStats
-
- sizeInBytes() - Method in class org.apache.spark.sql.parquet.ParquetRelation2
-
- sizeInBytes() - Method in class org.apache.spark.sql.sources.BaseRelation
-
Returns an estimated size of this relation in bytes.
- sketch(RDD<K>, int, ClassTag<K>) - Static method in class org.apache.spark.RangePartitioner
-
Sketches the input RDD via reservoir sampling on each partition.
- skip(long) - Method in class org.apache.spark.util.ByteBufferInputStream
-
- skippedStages() - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- slack() - Method in class org.apache.spark.rdd.PartitionCoalescer
-
- slaveActor() - Method in class org.apache.spark.storage.BlockManagerInfo
-
- slaveIdsWithExecutors() - Method in class org.apache.spark.scheduler.cluster.mesos.CoarseMesosSchedulerBackend
-
- slaveIdsWithExecutors() - Method in class org.apache.spark.scheduler.cluster.mesos.MesosSchedulerBackend
-
- slaveLost(SchedulerDriver, Protos.SlaveID) - Method in class org.apache.spark.scheduler.cluster.mesos.CoarseMesosSchedulerBackend
-
- slaveLost(SchedulerDriver, Protos.SlaveID) - Method in class org.apache.spark.scheduler.cluster.mesos.MesosSchedulerBackend
-
- SlaveLost - Class in org.apache.spark.scheduler
-
- SlaveLost(String) - Constructor for class org.apache.spark.scheduler.SlaveLost
-
- slaveTimeout() - Method in class org.apache.spark.storage.BlockManagerMasterActor
-
- slice() - Method in class org.apache.spark.rdd.ParallelCollectionPartition
-
- slice(Seq<T>, int, ClassTag<T>) - Static method in class org.apache.spark.rdd.ParallelCollectionRDD
-
Slice a collection into numSlices sub-collections.
- slice(Time, Time) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Return all the RDDs between 'fromDuration' to 'toDuration' (both included)
- slice(Interval) - Method in class org.apache.spark.streaming.dstream.DStream
-
Return all the RDDs defined by the Interval object (both end times included)
- slice(Time, Time) - Method in class org.apache.spark.streaming.dstream.DStream
-
Return all the RDDs between 'fromTime' to 'toTime' (both included)
- slideDuration() - Method in class org.apache.spark.streaming.dstream.DStream
-
Time interval after which the DStream generates a RDD
- slideDuration() - Method in class org.apache.spark.streaming.dstream.FilteredDStream
-
- slideDuration() - Method in class org.apache.spark.streaming.dstream.FlatMappedDStream
-
- slideDuration() - Method in class org.apache.spark.streaming.dstream.FlatMapValuedDStream
-
- slideDuration() - Method in class org.apache.spark.streaming.dstream.ForEachDStream
-
- slideDuration() - Method in class org.apache.spark.streaming.dstream.GlommedDStream
-
- slideDuration() - Method in class org.apache.spark.streaming.dstream.InputDStream
-
- slideDuration() - Method in class org.apache.spark.streaming.dstream.MapPartitionedDStream
-
- slideDuration() - Method in class org.apache.spark.streaming.dstream.MappedDStream
-
- slideDuration() - Method in class org.apache.spark.streaming.dstream.MapValuedDStream
-
- slideDuration() - Method in class org.apache.spark.streaming.dstream.ReducedWindowedDStream
-
- slideDuration() - Method in class org.apache.spark.streaming.dstream.ShuffledDStream
-
- slideDuration() - Method in class org.apache.spark.streaming.dstream.StateDStream
-
- slideDuration() - Method in class org.apache.spark.streaming.dstream.TransformedDStream
-
- slideDuration() - Method in class org.apache.spark.streaming.dstream.UnionDStream
-
- slideDuration() - Method in class org.apache.spark.streaming.dstream.WindowedDStream
-
- sliding(int) - Method in class org.apache.spark.mllib.rdd.RDDFunctions
-
Returns a RDD from grouping items of its parent RDD in fixed size blocks by passing a sliding
window over them.
- SlidingRDD<T> - Class in org.apache.spark.mllib.rdd
-
Represents a RDD from grouping items of its parent RDD in fixed size blocks by passing a sliding
window over them.
- SlidingRDD(RDD<T>, int, ClassTag<T>) - Constructor for class org.apache.spark.mllib.rdd.SlidingRDD
-
- SlidingRDDPartition<T> - Class in org.apache.spark.mllib.rdd
-
- SlidingRDDPartition(int, Partition, Seq<T>) - Constructor for class org.apache.spark.mllib.rdd.SlidingRDDPartition
-
- SnappyCompressionCodec - Class in org.apache.spark.io
-
- SnappyCompressionCodec(SparkConf) - Constructor for class org.apache.spark.io.SnappyCompressionCodec
-
- SocketInputDStream<T> - Class in org.apache.spark.streaming.dstream
-
- SocketInputDStream(StreamingContext, String, int, Function1<InputStream, Iterator<T>>, StorageLevel, ClassTag<T>) - Constructor for class org.apache.spark.streaming.dstream.SocketInputDStream
-
- SocketReceiver<T> - Class in org.apache.spark.streaming.dstream
-
- SocketReceiver(String, int, Function1<InputStream, Iterator<T>>, StorageLevel, ClassTag<T>) - Constructor for class org.apache.spark.streaming.dstream.SocketReceiver
-
- socketStream(String, int, Function<InputStream, Iterable<T>>, StorageLevel) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
Create an input stream from network source hostname:port.
- socketStream(String, int, Function1<InputStream, Iterator<T>>, StorageLevel, ClassTag<T>) - Method in class org.apache.spark.streaming.StreamingContext
-
Create a input stream from TCP source hostname:port.
- socketTextStream(String, int, StorageLevel) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
Create an input stream from network source hostname:port.
- socketTextStream(String, int) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
Create an input stream from network source hostname:port.
- socketTextStream(String, int, StorageLevel) - Method in class org.apache.spark.streaming.StreamingContext
-
Create a input stream from TCP source hostname:port.
- solve(DoubleMatrix, DoubleMatrix, NNLS.Workspace) - Static method in class org.apache.spark.mllib.optimization.NNLS
-
Solve a least squares problem, possibly with nonnegativity constraints, by a modified
projected gradient method.
- solveLeastSquares(DoubleMatrix, DoubleMatrix, NNLS.Workspace) - Method in class org.apache.spark.mllib.recommendation.ALS
-
Given A^T A and A^T b, find the x minimising ||Ax - b||_2, possibly subject
to nonnegativity constraints if nonnegative
is true.
- Sort() - Static method in class org.apache.spark.mllib.tree.configuration.QuantileStrategy
-
- Sort - Class in org.apache.spark.sql.execution
-
:: DeveloperApi ::
Performs a sort on-heap.
- Sort(Seq<SortOrder>, boolean, SparkPlan) - Constructor for class org.apache.spark.sql.execution.Sort
-
- sortBy(Function<T, S>, boolean, int) - Method in class org.apache.spark.api.java.JavaRDD
-
Return this RDD sorted by the given key function.
- sortBy(Function1<T, K>, boolean, int, Ordering<K>, ClassTag<K>) - Method in class org.apache.spark.rdd.RDD
-
Return this RDD sorted by the given key function.
- sortByKey() - Method in class org.apache.spark.api.java.JavaPairRDD
-
Sort the RDD by key, so that each partition contains a sorted range of the elements in
ascending order.
- sortByKey(boolean) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Sort the RDD by key, so that each partition contains a sorted range of the elements.
- sortByKey(boolean, int) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Sort the RDD by key, so that each partition contains a sorted range of the elements.
- sortByKey(Comparator<K>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Sort the RDD by key, so that each partition contains a sorted range of the elements.
- sortByKey(Comparator<K>, boolean) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Sort the RDD by key, so that each partition contains a sorted range of the elements.
- sortByKey(Comparator<K>, boolean, int) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Sort the RDD by key, so that each partition contains a sorted range of the elements.
- sortByKey(boolean, int) - Method in class org.apache.spark.rdd.OrderedRDDFunctions
-
Sort the RDD by key, so that each partition contains a sorted range of the elements.
- sortOrder() - Method in class org.apache.spark.sql.execution.ExternalSort
-
- sortOrder() - Method in class org.apache.spark.sql.execution.Sort
-
- sortOrder() - Method in class org.apache.spark.sql.execution.TakeOrdered
-
- Source - Interface in org.apache.spark.metrics.source
-
- SOURCE_REGEX() - Static method in class org.apache.spark.metrics.MetricsSystem
-
- sourceName() - Method in class org.apache.spark.metrics.source.JvmSource
-
- sourceName() - Method in interface org.apache.spark.metrics.source.Source
-
- sourceName() - Method in class org.apache.spark.scheduler.DAGSchedulerSource
-
- sourceName() - Method in class org.apache.spark.storage.BlockManagerSource
-
- sourceName() - Method in class org.apache.spark.streaming.StreamingSource
-
- SPARK_CONTEXT() - Static method in class org.apache.spark.util.MetadataCleanerType
-
- SPARK_JOB_DESCRIPTION() - Static method in class org.apache.spark.SparkContext
-
- SPARK_JOB_GROUP_ID() - Static method in class org.apache.spark.SparkContext
-
- SPARK_JOB_INTERRUPT_ON_CANCEL() - Static method in class org.apache.spark.SparkContext
-
- SPARK_METADATA_KEY() - Static method in class org.apache.spark.sql.parquet.RowReadSupport
-
- SPARK_ROW_REQUESTED_SCHEMA() - Static method in class org.apache.spark.sql.parquet.RowReadSupport
-
- SPARK_ROW_SCHEMA() - Static method in class org.apache.spark.sql.parquet.RowWriteSupport
-
- SPARK_UNKNOWN_USER() - Static method in class org.apache.spark.SparkContext
-
- SPARK_VERSION_PREFIX() - Static method in class org.apache.spark.scheduler.EventLoggingListener
-
- SparkConf - Class in org.apache.spark
-
Configuration for a Spark application.
- SparkConf(boolean) - Constructor for class org.apache.spark.SparkConf
-
- SparkConf() - Constructor for class org.apache.spark.SparkConf
-
Create a SparkConf that loads defaults from system properties and the classpath
- sparkConf() - Method in class org.apache.spark.streaming.Checkpoint
-
- sparkConfPairs() - Method in class org.apache.spark.streaming.Checkpoint
-
- sparkContext() - Method in class org.apache.spark.rdd.RDD
-
The SparkContext that created this RDD.
- SparkContext - Class in org.apache.spark
-
Main entry point for Spark functionality.
- SparkContext(SparkConf) - Constructor for class org.apache.spark.SparkContext
-
- SparkContext() - Constructor for class org.apache.spark.SparkContext
-
Create a SparkContext that loads settings from system properties (for instance, when
launching with ./bin/spark-submit).
- SparkContext(SparkConf, Map<String, Set<SplitInfo>>) - Constructor for class org.apache.spark.SparkContext
-
:: DeveloperApi ::
Alternative constructor for setting preferred locations where Spark will create executors.
- SparkContext(String, String, SparkConf) - Constructor for class org.apache.spark.SparkContext
-
Alternative constructor that allows setting common Spark properties directly
- SparkContext(String, String, String, Seq<String>, Map<String, String>, Map<String, Set<SplitInfo>>) - Constructor for class org.apache.spark.SparkContext
-
Alternative constructor that allows setting common Spark properties directly
- SparkContext(String, String) - Constructor for class org.apache.spark.SparkContext
-
Alternative constructor that allows setting common Spark properties directly
- SparkContext(String, String, String) - Constructor for class org.apache.spark.SparkContext
-
Alternative constructor that allows setting common Spark properties directly
- SparkContext(String, String, String, Seq<String>) - Constructor for class org.apache.spark.SparkContext
-
Alternative constructor that allows setting common Spark properties directly
- sparkContext() - Method in class org.apache.spark.sql.parquet.ParquetRelation2
-
- sparkContext() - Method in class org.apache.spark.sql.SQLContext
-
- sparkContext() - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
The underlying SparkContext
- sparkContext() - Method in class org.apache.spark.streaming.StreamingContext
-
Return the associated Spark context
- SparkContext.DoubleAccumulatorParam$ - Class in org.apache.spark
-
- SparkContext.DoubleAccumulatorParam$() - Constructor for class org.apache.spark.SparkContext.DoubleAccumulatorParam$
-
- SparkContext.FloatAccumulatorParam$ - Class in org.apache.spark
-
- SparkContext.FloatAccumulatorParam$() - Constructor for class org.apache.spark.SparkContext.FloatAccumulatorParam$
-
- SparkContext.IntAccumulatorParam$ - Class in org.apache.spark
-
- SparkContext.IntAccumulatorParam$() - Constructor for class org.apache.spark.SparkContext.IntAccumulatorParam$
-
- SparkContext.LongAccumulatorParam$ - Class in org.apache.spark
-
- SparkContext.LongAccumulatorParam$() - Constructor for class org.apache.spark.SparkContext.LongAccumulatorParam$
-
- SparkDeploySchedulerBackend - Class in org.apache.spark.scheduler.cluster
-
- SparkDeploySchedulerBackend(TaskSchedulerImpl, SparkContext, String[]) - Constructor for class org.apache.spark.scheduler.cluster.SparkDeploySchedulerBackend
-
- SparkDriverExecutionException - Exception in org.apache.spark
-
Exception thrown when execution of some user code in the driver process fails, e.g.
- SparkDriverExecutionException(Throwable) - Constructor for exception org.apache.spark.SparkDriverExecutionException
-
- SparkEnv - Class in org.apache.spark
-
:: DeveloperApi ::
Holds all the runtime environment objects for a running Spark instance (either master or worker),
including the serializer, Akka actor system, block manager, map output tracker, etc.
- SparkEnv(String, ActorSystem, Serializer, Serializer, CacheManager, MapOutputTracker, ShuffleManager, BroadcastManager, BlockTransferService, BlockManager, SecurityManager, HttpFileServer, String, MetricsSystem, ShuffleMemoryManager, SparkConf) - Constructor for class org.apache.spark.SparkEnv
-
- sparkEventFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
-
--------------------------------------------------- *
JSON deserialization methods for SparkListenerEvents |
----------------------------------------------------
- sparkEventToJson(SparkListenerEvent) - Static method in class org.apache.spark.util.JsonProtocol
-
------------------------------------------------- *
JSON serialization methods for SparkListenerEvents |
--------------------------------------------------
- SparkException - Exception in org.apache.spark
-
- SparkException(String, Throwable) - Constructor for exception org.apache.spark.SparkException
-
- SparkException(String) - Constructor for exception org.apache.spark.SparkException
-
- SparkExitCode - Class in org.apache.spark.util
-
- SparkExitCode() - Constructor for class org.apache.spark.util.SparkExitCode
-
- SparkFiles - Class in org.apache.spark
-
Resolves paths to files added through SparkContext.addFile()
.
- SparkFiles() - Constructor for class org.apache.spark.SparkFiles
-
- sparkFilesDir() - Method in class org.apache.spark.SparkEnv
-
- SparkFlumeEvent - Class in org.apache.spark.streaming.flume
-
A wrapper class for AvroFlumeEvent's with a custom serialization format.
- SparkFlumeEvent() - Constructor for class org.apache.spark.streaming.flume.SparkFlumeEvent
-
- SparkHadoopMapReduceUtil - Interface in org.apache.spark.mapreduce
-
- SparkHadoopMapRedUtil - Interface in org.apache.spark.mapred
-
- SparkHadoopWriter - Class in org.apache.spark
-
Internal helper class that saves an RDD using a Hadoop OutputFormat.
- SparkHadoopWriter(JobConf) - Constructor for class org.apache.spark.SparkHadoopWriter
-
- SparkHiveDynamicPartitionWriterContainer - Class in org.apache.spark.sql.hive
-
- SparkHiveDynamicPartitionWriterContainer(JobConf, ShimFileSinkDesc, String[]) - Constructor for class org.apache.spark.sql.hive.SparkHiveDynamicPartitionWriterContainer
-
- SparkHiveWriterContainer - Class in org.apache.spark.sql.hive
-
Internal helper class that saves an RDD using a Hive OutputFormat.
- SparkHiveWriterContainer(JobConf, ShimFileSinkDesc) - Constructor for class org.apache.spark.sql.hive.SparkHiveWriterContainer
-
- sparkJavaOpts(SparkConf, Function1<String, Object>) - Static method in class org.apache.spark.util.Utils
-
Convert all spark properties set in the given SparkConf to a sequence of java options.
- SparkJobInfo - Interface in org.apache.spark
-
Exposes information about Spark Jobs.
- SparkJobInfoImpl - Class in org.apache.spark
-
- SparkJobInfoImpl(int, int[], JobExecutionStatus) - Constructor for class org.apache.spark.SparkJobInfoImpl
-
- SparkListener - Interface in org.apache.spark.scheduler
-
:: DeveloperApi ::
Interface for listening to events from the Spark scheduler.
- SparkListenerApplicationEnd - Class in org.apache.spark.scheduler
-
- SparkListenerApplicationEnd(long) - Constructor for class org.apache.spark.scheduler.SparkListenerApplicationEnd
-
- SparkListenerApplicationStart - Class in org.apache.spark.scheduler
-
- SparkListenerApplicationStart(String, Option<String>, long, String) - Constructor for class org.apache.spark.scheduler.SparkListenerApplicationStart
-
- SparkListenerBlockManagerAdded - Class in org.apache.spark.scheduler
-
- SparkListenerBlockManagerAdded(long, BlockManagerId, long) - Constructor for class org.apache.spark.scheduler.SparkListenerBlockManagerAdded
-
- SparkListenerBlockManagerRemoved - Class in org.apache.spark.scheduler
-
- SparkListenerBlockManagerRemoved(long, BlockManagerId) - Constructor for class org.apache.spark.scheduler.SparkListenerBlockManagerRemoved
-
- SparkListenerBus - Interface in org.apache.spark.scheduler
-
A SparkListenerEvent bus that relays events to its listeners
- SparkListenerEnvironmentUpdate - Class in org.apache.spark.scheduler
-
- SparkListenerEnvironmentUpdate(Map<String, Seq<Tuple2<String, String>>>) - Constructor for class org.apache.spark.scheduler.SparkListenerEnvironmentUpdate
-
- SparkListenerEvent - Interface in org.apache.spark.scheduler
-
- SparkListenerExecutorMetricsUpdate - Class in org.apache.spark.scheduler
-
Periodic updates from executors.
- SparkListenerExecutorMetricsUpdate(String, Seq<Tuple4<Object, Object, Object, TaskMetrics>>) - Constructor for class org.apache.spark.scheduler.SparkListenerExecutorMetricsUpdate
-
- SparkListenerJobEnd - Class in org.apache.spark.scheduler
-
- SparkListenerJobEnd(int, JobResult) - Constructor for class org.apache.spark.scheduler.SparkListenerJobEnd
-
- SparkListenerJobStart - Class in org.apache.spark.scheduler
-
- SparkListenerJobStart(int, Seq<StageInfo>, Properties) - Constructor for class org.apache.spark.scheduler.SparkListenerJobStart
-
- sparkListeners() - Method in interface org.apache.spark.scheduler.SparkListenerBus
-
- SparkListenerShutdown - Class in org.apache.spark.scheduler
-
An event used in the listener to shutdown the listener daemon thread.
- SparkListenerShutdown() - Constructor for class org.apache.spark.scheduler.SparkListenerShutdown
-
- SparkListenerStageCompleted - Class in org.apache.spark.scheduler
-
- SparkListenerStageCompleted(StageInfo) - Constructor for class org.apache.spark.scheduler.SparkListenerStageCompleted
-
- SparkListenerStageSubmitted - Class in org.apache.spark.scheduler
-
- SparkListenerStageSubmitted(StageInfo, Properties) - Constructor for class org.apache.spark.scheduler.SparkListenerStageSubmitted
-
- SparkListenerTaskEnd - Class in org.apache.spark.scheduler
-
- SparkListenerTaskEnd(int, int, String, TaskEndReason, TaskInfo, TaskMetrics) - Constructor for class org.apache.spark.scheduler.SparkListenerTaskEnd
-
- SparkListenerTaskGettingResult - Class in org.apache.spark.scheduler
-
- SparkListenerTaskGettingResult(TaskInfo) - Constructor for class org.apache.spark.scheduler.SparkListenerTaskGettingResult
-
- SparkListenerTaskStart - Class in org.apache.spark.scheduler
-
- SparkListenerTaskStart(int, int, TaskInfo) - Constructor for class org.apache.spark.scheduler.SparkListenerTaskStart
-
- SparkListenerUnpersistRDD - Class in org.apache.spark.scheduler
-
- SparkListenerUnpersistRDD(int) - Constructor for class org.apache.spark.scheduler.SparkListenerUnpersistRDD
-
- SparkLogicalPlan - Class in org.apache.spark.sql.execution
-
- SparkLogicalPlan(SparkPlan, SQLContext) - Constructor for class org.apache.spark.sql.execution.SparkLogicalPlan
-
- SparkPlan - Class in org.apache.spark.sql.execution
-
:: DeveloperApi ::
- SparkPlan() - Constructor for class org.apache.spark.sql.execution.SparkPlan
-
- sparkProperties() - Method in class org.apache.spark.ui.env.EnvironmentListener
-
- SparkSqlSerializer - Class in org.apache.spark.sql.execution
-
- SparkSqlSerializer(SparkConf) - Constructor for class org.apache.spark.sql.execution.SparkSqlSerializer
-
- SparkStageInfo - Interface in org.apache.spark
-
Exposes information about Spark Stages.
- SparkStageInfoImpl - Class in org.apache.spark
-
- SparkStageInfoImpl(int, int, long, String, int, int, int, int) - Constructor for class org.apache.spark.SparkStageInfoImpl
-
- SparkStatusTracker - Class in org.apache.spark
-
Low-level status reporting APIs for monitoring job and stage progress.
- SparkStatusTracker(SparkContext) - Constructor for class org.apache.spark.SparkStatusTracker
-
- SparkStrategies - Class in org.apache.spark.sql.execution
-
- SparkStrategies() - Constructor for class org.apache.spark.sql.execution.SparkStrategies
-
- SparkStrategies.BasicOperators - Class in org.apache.spark.sql.execution
-
- SparkStrategies.BasicOperators() - Constructor for class org.apache.spark.sql.execution.SparkStrategies.BasicOperators
-
- SparkStrategies.BroadcastNestedLoopJoin - Class in org.apache.spark.sql.execution
-
- SparkStrategies.BroadcastNestedLoopJoin() - Constructor for class org.apache.spark.sql.execution.SparkStrategies.BroadcastNestedLoopJoin
-
- SparkStrategies.CartesianProduct - Class in org.apache.spark.sql.execution
-
- SparkStrategies.CartesianProduct() - Constructor for class org.apache.spark.sql.execution.SparkStrategies.CartesianProduct
-
- SparkStrategies.CommandStrategy - Class in org.apache.spark.sql.execution
-
- SparkStrategies.CommandStrategy(SQLContext) - Constructor for class org.apache.spark.sql.execution.SparkStrategies.CommandStrategy
-
- SparkStrategies.HashAggregation - Class in org.apache.spark.sql.execution
-
- SparkStrategies.HashAggregation() - Constructor for class org.apache.spark.sql.execution.SparkStrategies.HashAggregation
-
- SparkStrategies.HashJoin - Class in org.apache.spark.sql.execution
-
- SparkStrategies.HashJoin() - Constructor for class org.apache.spark.sql.execution.SparkStrategies.HashJoin
-
Uses the ExtractEquiJoinKeys pattern to find joins where at least some of the predicates can be
evaluated by matching hash keys.
- SparkStrategies.InMemoryScans - Class in org.apache.spark.sql.execution
-
- SparkStrategies.InMemoryScans() - Constructor for class org.apache.spark.sql.execution.SparkStrategies.InMemoryScans
-
- SparkStrategies.LeftSemiJoin - Class in org.apache.spark.sql.execution
-
- SparkStrategies.LeftSemiJoin() - Constructor for class org.apache.spark.sql.execution.SparkStrategies.LeftSemiJoin
-
- SparkStrategies.ParquetOperations - Class in org.apache.spark.sql.execution
-
- SparkStrategies.ParquetOperations() - Constructor for class org.apache.spark.sql.execution.SparkStrategies.ParquetOperations
-
- SparkStrategies.TakeOrdered - Class in org.apache.spark.sql.execution
-
- SparkStrategies.TakeOrdered() - Constructor for class org.apache.spark.sql.execution.SparkStrategies.TakeOrdered
-
- SparkUI - Class in org.apache.spark.ui
-
Top level user interface for a Spark application.
- SparkUITab - Class in org.apache.spark.ui
-
- SparkUITab(SparkUI, String) - Constructor for class org.apache.spark.ui.SparkUITab
-
- SparkUncaughtExceptionHandler - Class in org.apache.spark.util
-
The default uncaught exception handler for Executors terminates the whole process, to avoid
getting into a bad state indefinitely.
- SparkUncaughtExceptionHandler() - Constructor for class org.apache.spark.util.SparkUncaughtExceptionHandler
-
- sparkUser() - Method in class org.apache.spark.api.java.JavaSparkContext
-
- sparkUser() - Method in class org.apache.spark.scheduler.ApplicationEventListener
-
- sparkUser() - Method in class org.apache.spark.scheduler.SparkListenerApplicationStart
-
- sparkUser() - Method in class org.apache.spark.SparkContext
-
- sparkVersion() - Method in class org.apache.spark.scheduler.EventLoggingInfo
-
- sparse(int, int, int[], int[], double[]) - Static method in class org.apache.spark.mllib.linalg.Matrices
-
Creates a column-major sparse matrix in Compressed Sparse Column (CSC) format.
- sparse(int, int[], double[]) - Static method in class org.apache.spark.mllib.linalg.Vectors
-
Creates a sparse vector providing its index array and value array.
- sparse(int, Seq<Tuple2<Object, Object>>) - Static method in class org.apache.spark.mllib.linalg.Vectors
-
Creates a sparse vector using unordered (index, value) pairs.
- sparse(int, Iterable<Tuple2<Integer, Double>>) - Static method in class org.apache.spark.mllib.linalg.Vectors
-
Creates a sparse vector using unordered (index, value) pairs in a Java friendly way.
- SparseMatrix - Class in org.apache.spark.mllib.linalg
-
Column-major sparse matrix.
- SparseMatrix(int, int, int[], int[], double[]) - Constructor for class org.apache.spark.mllib.linalg.SparseMatrix
-
- SparseVector - Class in org.apache.spark.mllib.linalg
-
A sparse vector represented by an index array and an value array.
- SparseVector(int, int[], double[]) - Constructor for class org.apache.spark.mllib.linalg.SparseVector
-
- SpearmanCorrelation - Class in org.apache.spark.mllib.stat.correlation
-
Compute Spearman's correlation for two RDDs of the type RDD[Double] or the correlation matrix
for an RDD of the type RDD[Vector].
- SpearmanCorrelation() - Constructor for class org.apache.spark.mllib.stat.correlation.SpearmanCorrelation
-
- speculatableTasks() - Method in class org.apache.spark.scheduler.TaskSetManager
-
- SPECULATION_INTERVAL() - Method in class org.apache.spark.scheduler.TaskSchedulerImpl
-
- SPECULATION_MULTIPLIER() - Method in class org.apache.spark.scheduler.TaskSetManager
-
- SPECULATION_QUANTILE() - Method in class org.apache.spark.scheduler.TaskSetManager
-
- speculative() - Method in class org.apache.spark.scheduler.TaskInfo
-
- split() - Method in class org.apache.spark.mllib.tree.impl.NodeIndexUpdater
-
- split() - Method in class org.apache.spark.mllib.tree.model.Node
-
- Split - Class in org.apache.spark.mllib.tree.model
-
:: DeveloperApi ::
Split applied to a feature
- Split(int, double, Enumeration.Value, List<Object>) - Constructor for class org.apache.spark.mllib.tree.model.Split
-
- split() - Method in class org.apache.spark.rdd.NarrowCoGroupSplitDep
-
- SPLIT_INFO_REFLECTIONS() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- splitAndCountPartitions(Iterator<String>) - Static method in class org.apache.spark.streaming.util.RawTextHelper
-
Splits lines and counts the words.
- splitCommandString(String) - Static method in class org.apache.spark.util.Utils
-
Split a string of potentially quoted arguments from the command line the way that a shell
would do it to determine arguments to a command.
- splitIdToFile(int) - Static method in class org.apache.spark.rdd.CheckpointRDD
-
- splitIndex() - Method in class org.apache.spark.rdd.NarrowCoGroupSplitDep
-
- splitIndex() - Method in class org.apache.spark.storage.RDDBlockId
-
- SplitInfo - Class in org.apache.spark.scheduler
-
- SplitInfo(Class<?>, String, String, long, Object) - Constructor for class org.apache.spark.scheduler.SplitInfo
-
- splitLocationInfo() - Method in class org.apache.spark.rdd.HadoopRDD.SplitInfoReflections
-
- splits() - Method in interface org.apache.spark.api.java.JavaRDDLike
-
- sql(String) - Method in class org.apache.spark.sql.api.java.JavaSQLContext
-
Executes a SQL query using Spark, returning the result as a SchemaRDD.
- sql(String) - Method in class org.apache.spark.sql.hive.api.java.JavaHiveContext
-
- sql() - Method in class org.apache.spark.sql.hive.execution.NativeCommand
-
- sql(String) - Method in class org.apache.spark.sql.hive.HiveContext
-
- sql(String) - Method in class org.apache.spark.sql.SQLContext
-
Executes a SQL query using Spark, returning the result as a SchemaRDD.
- SQLConf - Interface in org.apache.spark.sql
-
A trait that enables the setting and getting of mutable config parameters/hints.
- SQLConf.Deprecated$ - Class in org.apache.spark.sql
-
- SQLConf.Deprecated$() - Constructor for class org.apache.spark.sql.SQLConf.Deprecated$
-
- sqlContext() - Method in class org.apache.spark.sql.api.java.JavaSchemaRDD
-
- sqlContext() - Method in class org.apache.spark.sql.api.java.JavaSQLContext
-
- sqlContext() - Method in class org.apache.spark.sql.columnar.InMemoryColumnarTableScan
-
- sqlContext() - Method in class org.apache.spark.sql.execution.AddExchange
-
- sqlContext() - Method in class org.apache.spark.sql.json.JSONRelation
-
- sqlContext() - Method in class org.apache.spark.sql.parquet.ParquetRelation
-
- sqlContext() - Method in class org.apache.spark.sql.parquet.ParquetRelation2
-
- sqlContext() - Method in class org.apache.spark.sql.SchemaRDD
-
- sqlContext() - Method in interface org.apache.spark.sql.SchemaRDDLike
-
- sqlContext() - Method in class org.apache.spark.sql.sources.BaseRelation
-
- SQLContext - Class in org.apache.spark.sql
-
:: AlphaComponent ::
The entry point for running relational queries using Spark.
- SQLContext(SparkContext) - Constructor for class org.apache.spark.sql.SQLContext
-
- sqlType() - Method in class org.apache.spark.mllib.linalg.VectorUDT
-
- sqlType() - Method in class org.apache.spark.sql.api.java.JavaToScalaUDTWrapper
-
Underlying storage type for this UDT
- sqlType() - Method in class org.apache.spark.sql.api.java.ScalaToJavaUDTWrapper
-
Underlying storage type for this UDT
- sqlType() - Method in class org.apache.spark.sql.api.java.UserDefinedType
-
Underlying storage type for this UDT
- sqlType() - Method in class org.apache.spark.sql.test.ExamplePointUDT
-
- SQRT() - Static method in class org.apache.spark.sql.hive.HiveQl
-
- squaredDist(Vector) - Method in class org.apache.spark.util.Vector
-
- SquaredError - Class in org.apache.spark.mllib.tree.loss
-
:: DeveloperApi ::
Class for squared error loss calculation.
- SquaredError() - Constructor for class org.apache.spark.mllib.tree.loss.SquaredError
-
- SquaredL2Updater - Class in org.apache.spark.mllib.optimization
-
:: DeveloperApi ::
Updater for L2 regularized problems.
- SquaredL2Updater() - Constructor for class org.apache.spark.mllib.optimization.SquaredL2Updater
-
- Src - Static variable in class org.apache.spark.graphx.TripletFields
-
Expose the source and edge fields but not the destination field.
- srcAttr() - Method in class org.apache.spark.graphx.EdgeContext
-
The vertex attribute of the edge's source vertex.
- srcAttr() - Method in class org.apache.spark.graphx.EdgeTriplet
-
The source vertex attribute
- srcAttr() - Method in class org.apache.spark.graphx.impl.AggregatingEdgeContext
-
- srcId() - Method in class org.apache.spark.graphx.Edge
-
- srcId() - Method in class org.apache.spark.graphx.EdgeContext
-
The vertex id of the edge's source vertex.
- srcId() - Method in class org.apache.spark.graphx.impl.AggregatingEdgeContext
-
- srcId() - Method in class org.apache.spark.graphx.impl.EdgeWithLocalIds
-
- srdd() - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
- ssc() - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
- ssc() - Method in class org.apache.spark.streaming.dstream.DStream
-
- ssc() - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
- ssc() - Method in class org.apache.spark.streaming.scheduler.JobScheduler
-
- stackTrace() - Method in class org.apache.spark.ExceptionFailure
-
- stackTrace() - Method in class org.apache.spark.util.ThreadStackTrace
-
- stackTraceFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
-
- stackTraceToJson(StackTraceElement[]) - Static method in class org.apache.spark.util.JsonProtocol
-
- Stage - Class in org.apache.spark.scheduler
-
A stage is a set of independent tasks all computing the same function that need to run as part
of a Spark job, where all the tasks have the same shuffle dependencies.
- Stage(int, RDD<?>, int, Option<ShuffleDependency<?, ?, ?>>, List<Stage>, int, CallSite) - Constructor for class org.apache.spark.scheduler.Stage
-
- stageAttemptId() - Method in class org.apache.spark.scheduler.SparkListenerTaskEnd
-
- stageAttemptId() - Method in class org.apache.spark.scheduler.SparkListenerTaskStart
-
- StageCancelled - Class in org.apache.spark.scheduler
-
- StageCancelled(int) - Constructor for class org.apache.spark.scheduler.StageCancelled
-
- stageCompletedFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
-
- stageCompletedToJson(SparkListenerStageCompleted) - Static method in class org.apache.spark.util.JsonProtocol
-
- stageFailed(String) - Method in class org.apache.spark.scheduler.StageInfo
-
- stageId() - Method in class org.apache.spark.scheduler.Pool
-
- stageId() - Method in interface org.apache.spark.scheduler.Schedulable
-
- stageId() - Method in class org.apache.spark.scheduler.SparkListenerTaskEnd
-
- stageId() - Method in class org.apache.spark.scheduler.SparkListenerTaskStart
-
- stageId() - Method in class org.apache.spark.scheduler.StageCancelled
-
- stageId() - Method in class org.apache.spark.scheduler.StageInfo
-
- stageId() - Method in class org.apache.spark.scheduler.Task
-
- stageId() - Method in class org.apache.spark.scheduler.TaskSet
-
- stageId() - Method in class org.apache.spark.scheduler.TaskSetManager
-
- stageId() - Method in interface org.apache.spark.SparkStageInfo
-
- stageId() - Method in class org.apache.spark.SparkStageInfoImpl
-
- stageId() - Method in class org.apache.spark.TaskContext
-
- stageId() - Method in class org.apache.spark.TaskContextImpl
-
- stageIds() - Method in class org.apache.spark.scheduler.SparkListenerJobStart
-
- stageIds() - Method in interface org.apache.spark.SparkJobInfo
-
- stageIds() - Method in class org.apache.spark.SparkJobInfoImpl
-
- stageIds() - Method in class org.apache.spark.ui.jobs.UIData.JobUIData
-
- stageIdToActiveJobIds() - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- stageIdToData() - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- stageIdToInfo() - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- stageIdToStage() - Method in class org.apache.spark.scheduler.DAGScheduler
-
- stageInfo() - Method in class org.apache.spark.scheduler.SparkListenerStageCompleted
-
- stageInfo() - Method in class org.apache.spark.scheduler.SparkListenerStageSubmitted
-
- StageInfo - Class in org.apache.spark.scheduler
-
:: DeveloperApi ::
Stores information about a stage to pass from the scheduler to SparkListeners.
- StageInfo(int, int, String, int, Seq<RDDInfo>, String) - Constructor for class org.apache.spark.scheduler.StageInfo
-
- stageInfoFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
-
--------------------------------------------------------------------- *
JSON deserialization methods for classes SparkListenerEvents depend on |
----------------------------------------------------------------------
- stageInfos() - Method in class org.apache.spark.scheduler.SparkListenerJobStart
-
- stageInfoToJson(StageInfo) - Static method in class org.apache.spark.util.JsonProtocol
-
------------------------------------------------------------------- *
JSON serialization methods for classes SparkListenerEvents depend on |
--------------------------------------------------------------------
- StagePage - Class in org.apache.spark.ui.jobs
-
Page showing statistics and task list for a given stage
- StagePage(StagesTab) - Constructor for class org.apache.spark.ui.jobs.StagePage
-
- stages() - Method in class org.apache.spark.ml.Pipeline
-
param for pipeline stages
- stages() - Method in class org.apache.spark.ml.PipelineModel
-
- StagesTab - Class in org.apache.spark.ui.jobs
-
Web UI showing progress status of all stages in the given SparkContext.
- StagesTab(SparkUI) - Constructor for class org.apache.spark.ui.jobs.StagesTab
-
- stageSubmittedFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
-
- stageSubmittedToJson(SparkListenerStageSubmitted) - Static method in class org.apache.spark.util.JsonProtocol
-
- StageTableBase - Class in org.apache.spark.ui.jobs
-
Page showing list of all ongoing and recently finished stages
- StageTableBase(Seq<StageInfo>, String, JobProgressListener, boolean, boolean) - Constructor for class org.apache.spark.ui.jobs.StageTableBase
-
- StandardNormalGenerator - Class in org.apache.spark.mllib.random
-
:: DeveloperApi ::
Generates i.i.d.
- StandardNormalGenerator() - Constructor for class org.apache.spark.mllib.random.StandardNormalGenerator
-
- StandardScaler - Class in org.apache.spark.ml.feature
-
:: AlphaComponent ::
Standardizes features by removing the mean and scaling to unit variance using column summary
statistics on the samples in the training set.
- StandardScaler() - Constructor for class org.apache.spark.ml.feature.StandardScaler
-
- StandardScaler - Class in org.apache.spark.mllib.feature
-
:: Experimental ::
Standardizes features by removing the mean and scaling to unit variance using column summary
statistics on the samples in the training set.
- StandardScaler(boolean, boolean) - Constructor for class org.apache.spark.mllib.feature.StandardScaler
-
- StandardScaler() - Constructor for class org.apache.spark.mllib.feature.StandardScaler
-
- StandardScalerModel - Class in org.apache.spark.ml.feature
-
- StandardScalerModel(StandardScaler, ParamMap, StandardScalerModel) - Constructor for class org.apache.spark.ml.feature.StandardScalerModel
-
- StandardScalerModel - Class in org.apache.spark.mllib.feature
-
:: Experimental ::
Represents a StandardScaler model that can transform vectors.
- StandardScalerModel(boolean, boolean, Vector, Vector) - Constructor for class org.apache.spark.mllib.feature.StandardScalerModel
-
- StandardScalerParams - Interface in org.apache.spark.ml.feature
-
- starGraph(SparkContext, int) - Static method in class org.apache.spark.graphx.util.GraphGenerators
-
Create a star graph with vertex 0 being the center.
- start() - Method in class org.apache.spark.ContextCleaner
-
Start the cleaner.
- start() - Method in class org.apache.spark.ExecutorAllocationManager
-
Register for scheduler callbacks to decide when to add and remove executors.
- start() - Method in class org.apache.spark.HttpServer
-
- start() - Method in class org.apache.spark.metrics.MetricsSystem
-
- start() - Method in class org.apache.spark.metrics.sink.ConsoleSink
-
- start() - Method in class org.apache.spark.metrics.sink.CsvSink
-
- start() - Method in class org.apache.spark.metrics.sink.GraphiteSink
-
- start() - Method in class org.apache.spark.metrics.sink.JmxSink
-
- start() - Method in class org.apache.spark.metrics.sink.MetricsServlet
-
- start() - Method in interface org.apache.spark.metrics.sink.Sink
-
- start(String) - Method in class org.apache.spark.mllib.tree.impl.TimeTracker
-
Starts a new timer, or re-starts a stopped timer.
- start() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend
-
- start() - Method in class org.apache.spark.scheduler.cluster.mesos.CoarseMesosSchedulerBackend
-
- start() - Method in class org.apache.spark.scheduler.cluster.mesos.MesosSchedulerBackend
-
- start() - Method in class org.apache.spark.scheduler.cluster.SimrSchedulerBackend
-
- start() - Method in class org.apache.spark.scheduler.cluster.SparkDeploySchedulerBackend
-
- start() - Method in class org.apache.spark.scheduler.EventLoggingListener
-
Begin logging events.
- start() - Method in class org.apache.spark.scheduler.LiveListenerBus
-
Start sending events to attached listeners.
- start() - Method in class org.apache.spark.scheduler.local.LocalBackend
-
- start() - Method in interface org.apache.spark.scheduler.SchedulerBackend
-
- start() - Method in interface org.apache.spark.scheduler.TaskScheduler
-
- start() - Method in class org.apache.spark.scheduler.TaskSchedulerImpl
-
- start() - Method in class org.apache.spark.sql.parquet.CatalystArrayContainsNullConverter
-
- start() - Method in class org.apache.spark.sql.parquet.CatalystArrayConverter
-
- start() - Method in class org.apache.spark.sql.parquet.CatalystGroupConverter
-
- start() - Method in class org.apache.spark.sql.parquet.CatalystMapConverter
-
- start() - Method in class org.apache.spark.sql.parquet.CatalystNativeArrayConverter
-
- start() - Method in class org.apache.spark.sql.parquet.CatalystPrimitiveRowConverter
-
- start() - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
Start the execution of the streams.
- start() - Method in class org.apache.spark.streaming.dstream.ConstantInputDStream
-
- start() - Method in class org.apache.spark.streaming.dstream.FileInputDStream
-
- start() - Method in class org.apache.spark.streaming.dstream.InputDStream
-
Method called to start receiving data.
- start() - Method in class org.apache.spark.streaming.dstream.QueueInputDStream
-
- start() - Method in class org.apache.spark.streaming.dstream.ReceiverInputDStream
-
- start(Time) - Method in class org.apache.spark.streaming.DStreamGraph
-
- start() - Method in class org.apache.spark.streaming.receiver.BlockGenerator
-
Start block generating and pushing threads.
- start() - Method in class org.apache.spark.streaming.receiver.ReceiverSupervisor
-
Start the supervisor
- start() - Method in class org.apache.spark.streaming.scheduler.JobGenerator
-
Start generation of jobs
- start() - Method in class org.apache.spark.streaming.scheduler.JobScheduler
-
- start() - Method in class org.apache.spark.streaming.scheduler.ReceiverTracker.ReceiverLauncher
-
- start() - Method in class org.apache.spark.streaming.scheduler.ReceiverTracker
-
Start the actor and receiver execution thread.
- start() - Method in class org.apache.spark.streaming.scheduler.StreamingListenerBus
-
- start() - Method in class org.apache.spark.streaming.StreamingContext
-
Start the execution of the streams.
- start(long) - Method in class org.apache.spark.streaming.util.RecurringTimer
-
Start at the given start time.
- start() - Method in class org.apache.spark.streaming.util.RecurringTimer
-
Start at the earliest time it can start based on the period.
- start() - Method in class org.apache.spark.util.FileLogger
-
Start this logger by creating the logging directory.
- Started() - Method in class org.apache.spark.streaming.receiver.ReceiverSupervisor.ReceiverState
-
- Started() - Method in class org.apache.spark.streaming.StreamingContext.StreamingContextState$
-
- startIdx() - Method in class org.apache.spark.util.Distribution
-
- startIndex() - Method in class org.apache.spark.rdd.ZippedWithIndexRDDPartition
-
- startIndexInLevel(int) - Static method in class org.apache.spark.mllib.tree.model.Node
-
Return the index of the first node in the given level.
- startJettyServer(String, int, Seq<ServletContextHandler>, SparkConf, String) - Static method in class org.apache.spark.ui.JettyUtils
-
Attempt to start a Jetty server bound to the supplied hostName:port using the given
context handlers.
- startReceiver() - Method in class org.apache.spark.streaming.receiver.ReceiverSupervisor
-
Start receiver
- startServiceOnPort(int, Function1<Object, Tuple2<T, Object>>, SparkConf, String) - Static method in class org.apache.spark.util.Utils
-
Attempt to start a service on the given port, or fail after a number of attempts.
- startTime() - Method in class org.apache.spark.api.java.JavaSparkContext
-
- startTime() - Method in class org.apache.spark.partial.ApproximateActionListener
-
- startTime() - Method in class org.apache.spark.scheduler.ApplicationEventListener
-
- startTime() - Method in class org.apache.spark.SparkContext
-
- startTime() - Method in class org.apache.spark.streaming.DStreamGraph
-
- startTime() - Method in class org.apache.spark.streaming.util.WriteAheadLogManager.LogInfo
-
- startTime() - Method in class org.apache.spark.ui.jobs.UIData.JobUIData
-
- STARVATION_TIMEOUT() - Method in class org.apache.spark.scheduler.TaskSchedulerImpl
-
- statCounter() - Method in class org.apache.spark.util.Distribution
-
- StatCounter - Class in org.apache.spark.util
-
A class for tracking the statistics of a set of numbers (count, mean and variance) in a
numerically robust way.
- StatCounter(TraversableOnce<Object>) - Constructor for class org.apache.spark.util.StatCounter
-
- StatCounter() - Constructor for class org.apache.spark.util.StatCounter
-
Initialize the StatCounter with no values.
- state() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.StatusUpdate
-
- state() - Method in class org.apache.spark.scheduler.local.StatusUpdate
-
- state() - Method in class org.apache.spark.streaming.StreamingContext
-
- StateDStream<K,V,S> - Class in org.apache.spark.streaming.dstream
-
- StateDStream(DStream<Tuple2<K, V>>, Function1<Iterator<Tuple3<K, Seq<V>, Option<S>>>, Iterator<Tuple2<K, S>>>, Partitioner, boolean, ClassTag<K>, ClassTag<V>, ClassTag<S>) - Constructor for class org.apache.spark.streaming.dstream.StateDStream
-
- STATIC_RESOURCE_DIR() - Static method in class org.apache.spark.ui.SparkUI
-
- staticPageRank(int, double) - Method in class org.apache.spark.graphx.GraphOps
-
Run PageRank for a fixed number of iterations returning a graph with vertex attributes
containing the PageRank and edge attributes the normalized edge weight.
- statistic() - Method in class org.apache.spark.mllib.stat.test.ChiSqTestResult
-
- statistic() - Method in interface org.apache.spark.mllib.stat.test.TestResult
-
Test statistic.
- Statistics - Class in org.apache.spark.mllib.stat
-
API for statistical functions in MLlib.
- Statistics() - Constructor for class org.apache.spark.mllib.stat.Statistics
-
- statistics() - Method in class org.apache.spark.sql.columnar.InMemoryRelation
-
- statistics() - Method in class org.apache.spark.sql.execution.LogicalRDD
-
- statistics() - Method in class org.apache.spark.sql.execution.SparkLogicalPlan
-
- statistics() - Method in class org.apache.spark.sql.hive.MetastoreRelation
-
- statistics() - Method in class org.apache.spark.sql.parquet.ParquetRelation
-
- statistics() - Method in class org.apache.spark.sql.sources.LogicalRelation
-
- Statistics - Class in org.apache.spark.streaming.receiver
-
:: DeveloperApi ::
Statistics for querying the supervisor about state of workers.
- Statistics(int, int, int, String) - Constructor for class org.apache.spark.streaming.receiver.Statistics
-
- stats() - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Return a
StatCounter
object that captures the mean, variance and
count of the RDD's elements in one operation.
- stats() - Method in class org.apache.spark.mllib.tree.impurity.ImpurityCalculator
-
- stats() - Method in class org.apache.spark.mllib.tree.model.Node
-
- stats() - Method in class org.apache.spark.rdd.DoubleRDDFunctions
-
Return a
StatCounter
object that captures the mean, variance and
count of the RDD's elements in one operation.
- stats() - Method in class org.apache.spark.sql.columnar.CachedBatch
-
- StatsReportListener - Class in org.apache.spark.scheduler
-
:: DeveloperApi ::
Simple SparkListener that logs a few summary statistics when each stage completes
- StatsReportListener() - Constructor for class org.apache.spark.scheduler.StatsReportListener
-
- StatsReportListener - Class in org.apache.spark.streaming.scheduler
-
:: DeveloperApi ::
A simple StreamingListener that logs summary statistics across Spark Streaming batches
- StatsReportListener(int) - Constructor for class org.apache.spark.streaming.scheduler.StatsReportListener
-
- statsSize() - Method in class org.apache.spark.mllib.tree.impurity.ImpurityAggregator
-
- status() - Method in class org.apache.spark.scheduler.TaskInfo
-
- status() - Method in interface org.apache.spark.SparkJobInfo
-
- status() - Method in class org.apache.spark.SparkJobInfoImpl
-
- status() - Method in class org.apache.spark.ui.jobs.UIData.JobUIData
-
- statusTracker() - Method in class org.apache.spark.api.java.JavaSparkContext
-
- statusTracker() - Method in class org.apache.spark.SparkContext
-
- statusUpdate(SchedulerDriver, Protos.TaskStatus) - Method in class org.apache.spark.scheduler.cluster.mesos.CoarseMesosSchedulerBackend
-
- statusUpdate(SchedulerDriver, Protos.TaskStatus) - Method in class org.apache.spark.scheduler.cluster.mesos.MesosSchedulerBackend
-
- statusUpdate(long, Enumeration.Value, ByteBuffer) - Method in class org.apache.spark.scheduler.local.LocalBackend
-
- StatusUpdate - Class in org.apache.spark.scheduler.local
-
- StatusUpdate(long, Enumeration.Value, ByteBuffer) - Constructor for class org.apache.spark.scheduler.local.StatusUpdate
-
- statusUpdate(long, Enumeration.Value, ByteBuffer) - Method in class org.apache.spark.scheduler.TaskSchedulerImpl
-
- stdev() - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Compute the standard deviation of this RDD's elements.
- stdev() - Method in class org.apache.spark.rdd.DoubleRDDFunctions
-
Compute the standard deviation of this RDD's elements.
- stdev() - Method in class org.apache.spark.util.StatCounter
-
Return the standard deviation of the values.
- stop() - Method in class org.apache.spark.api.java.JavaSparkContext
-
Shut down the SparkContext.
- stop() - Method in interface org.apache.spark.broadcast.BroadcastFactory
-
- stop() - Method in class org.apache.spark.broadcast.BroadcastManager
-
- stop() - Static method in class org.apache.spark.broadcast.HttpBroadcast
-
- stop() - Method in class org.apache.spark.broadcast.HttpBroadcastFactory
-
- stop() - Method in class org.apache.spark.broadcast.TorrentBroadcastFactory
-
- stop() - Method in class org.apache.spark.ContextCleaner
-
Stop the cleaning thread and wait until the thread has finished running its current task.
- stop() - Method in class org.apache.spark.HttpFileServer
-
- stop() - Method in class org.apache.spark.HttpServer
-
- stop() - Method in class org.apache.spark.MapOutputTracker
-
Stop the tracker.
- stop() - Method in class org.apache.spark.MapOutputTrackerMaster
-
- stop() - Method in class org.apache.spark.metrics.MetricsSystem
-
- stop() - Method in class org.apache.spark.metrics.sink.ConsoleSink
-
- stop() - Method in class org.apache.spark.metrics.sink.CsvSink
-
- stop() - Method in class org.apache.spark.metrics.sink.GraphiteSink
-
- stop() - Method in class org.apache.spark.metrics.sink.JmxSink
-
- stop() - Method in class org.apache.spark.metrics.sink.MetricsServlet
-
- stop() - Method in interface org.apache.spark.metrics.sink.Sink
-
- stop(String) - Method in class org.apache.spark.mllib.tree.impl.TimeTracker
-
Stops a timer and returns the elapsed time in seconds.
- stop() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend
-
- stop() - Method in class org.apache.spark.scheduler.cluster.mesos.CoarseMesosSchedulerBackend
-
- stop() - Method in class org.apache.spark.scheduler.cluster.mesos.MesosSchedulerBackend
-
- stop() - Method in class org.apache.spark.scheduler.cluster.SimrSchedulerBackend
-
- stop() - Method in class org.apache.spark.scheduler.cluster.SparkDeploySchedulerBackend
-
- stop() - Method in class org.apache.spark.scheduler.DAGScheduler
-
- stop() - Method in class org.apache.spark.scheduler.EventLoggingListener
-
Stop logging events.
- stop() - Method in class org.apache.spark.scheduler.LiveListenerBus
-
- stop() - Method in class org.apache.spark.scheduler.local.LocalBackend
-
- stop() - Method in interface org.apache.spark.scheduler.SchedulerBackend
-
- stop() - Method in class org.apache.spark.scheduler.TaskResultGetter
-
- stop() - Method in interface org.apache.spark.scheduler.TaskScheduler
-
- stop() - Method in class org.apache.spark.scheduler.TaskSchedulerImpl
-
- stop() - Method in class org.apache.spark.SparkContext
-
Shut down the SparkContext.
- stop() - Method in class org.apache.spark.SparkEnv
-
- stop() - Method in class org.apache.spark.storage.BlockManager
-
- stop() - Method in class org.apache.spark.storage.BlockManagerMaster
-
Stop the driver actor, called only on the Spark driver node
- stop() - Method in class org.apache.spark.storage.DiskBlockManager
-
Cleanup local dirs and stop shuffle sender.
- stop() - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
Stop the execution of the streams.
- stop(boolean) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
Stop the execution of the streams.
- stop(boolean, boolean) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
Stop the execution of the streams.
- stop() - Method in class org.apache.spark.streaming.CheckpointWriter
-
- stop() - Method in class org.apache.spark.streaming.dstream.ConstantInputDStream
-
- stop() - Method in class org.apache.spark.streaming.dstream.FileInputDStream
-
- stop() - Method in class org.apache.spark.streaming.dstream.InputDStream
-
Method called to stop receiving data.
- stop() - Method in class org.apache.spark.streaming.dstream.QueueInputDStream
-
- stop() - Method in class org.apache.spark.streaming.dstream.ReceiverInputDStream
-
- stop() - Method in class org.apache.spark.streaming.DStreamGraph
-
- stop() - Method in class org.apache.spark.streaming.receiver.BlockGenerator
-
Stop all threads.
- stop(String) - Method in class org.apache.spark.streaming.receiver.Receiver
-
Stop the receiver completely.
- stop(String, Throwable) - Method in class org.apache.spark.streaming.receiver.Receiver
-
Stop the receiver completely due to an exception
- stop(String, Option<Throwable>) - Method in class org.apache.spark.streaming.receiver.ReceiverSupervisor
-
Mark the supervisor and the receiver for stopping
- stop() - Method in class org.apache.spark.streaming.receiver.WriteAheadLogBasedBlockHandler
-
- stop(boolean) - Method in class org.apache.spark.streaming.scheduler.JobGenerator
-
Stop generation of jobs.
- stop(boolean) - Method in class org.apache.spark.streaming.scheduler.JobScheduler
-
- stop() - Method in class org.apache.spark.streaming.scheduler.ReceivedBlockTracker
-
Stop the block tracker.
- stop(boolean) - Method in class org.apache.spark.streaming.scheduler.ReceiverTracker.ReceiverLauncher
-
- stop(boolean) - Method in class org.apache.spark.streaming.scheduler.ReceiverTracker
-
Stop the receiver execution thread.
- stop() - Method in class org.apache.spark.streaming.scheduler.StreamingListenerBus
-
- stop(boolean) - Method in class org.apache.spark.streaming.StreamingContext
-
Stop the execution of the streams immediately (does not wait for all received data
to be processed).
- stop(boolean, boolean) - Method in class org.apache.spark.streaming.StreamingContext
-
Stop the execution of the streams, with option of ensuring all received data
has been processed.
- stop(boolean) - Method in class org.apache.spark.streaming.util.RecurringTimer
-
Stop the timer, and return the last time the callback was made.
- stop() - Method in class org.apache.spark.streaming.util.WriteAheadLogManager
-
Stop the manager, close any open log writer
- stop() - Method in class org.apache.spark.ui.SparkUI
-
Stop the server behind this web interface.
- stop() - Method in class org.apache.spark.ui.WebUI
-
Stop the server behind this web interface.
- stop() - Method in class org.apache.spark.util.FileLogger
-
Close all open writers, streams, and file systems.
- stop() - Method in class org.apache.spark.util.logging.FileAppender
-
Stop the appender
- stop() - Method in class org.apache.spark.util.logging.RollingFileAppender
-
Stop the appender
- StopExecutor - Class in org.apache.spark.scheduler.local
-
- StopExecutor() - Constructor for class org.apache.spark.scheduler.local.StopExecutor
-
- stopExecutors() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend
-
- StopMapOutputTracker - Class in org.apache.spark
-
- StopMapOutputTracker() - Constructor for class org.apache.spark.StopMapOutputTracker
-
- Stopped() - Method in class org.apache.spark.streaming.receiver.ReceiverSupervisor.ReceiverState
-
- Stopped() - Method in class org.apache.spark.streaming.StreamingContext.StreamingContextState$
-
- stopping() - Method in class org.apache.spark.scheduler.cluster.SparkDeploySchedulerBackend
-
- stopReceiver(String, Option<Throwable>) - Method in class org.apache.spark.streaming.receiver.ReceiverSupervisor
-
Stop receiver
- StopReceiver - Class in org.apache.spark.streaming.receiver
-
- StopReceiver() - Constructor for class org.apache.spark.streaming.receiver.StopReceiver
-
- storageLevel() - Method in class org.apache.spark.sql.columnar.InMemoryRelation
-
- storageLevel() - Method in class org.apache.spark.storage.BlockManagerMessages.UpdateBlockInfo
-
- storageLevel() - Method in class org.apache.spark.storage.BlockStatus
-
- storageLevel() - Method in class org.apache.spark.storage.RDDInfo
-
- StorageLevel - Class in org.apache.spark.storage
-
:: DeveloperApi ::
Flags for controlling the storage of an RDD.
- StorageLevel() - Constructor for class org.apache.spark.storage.StorageLevel
-
- storageLevel() - Method in class org.apache.spark.streaming.dstream.DStream
-
- storageLevel() - Method in class org.apache.spark.streaming.receiver.Receiver
-
- storageLevelCache() - Static method in class org.apache.spark.storage.StorageLevel
-
:: DeveloperApi ::
Read StorageLevel object from ObjectInput stream.
- storageLevelFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
-
- StorageLevels - Class in org.apache.spark.api.java
-
Expose some commonly useful storage level constants.
- StorageLevels() - Constructor for class org.apache.spark.api.java.StorageLevels
-
- storageLevelToJson(StorageLevel) - Static method in class org.apache.spark.util.JsonProtocol
-
- storageListener() - Method in class org.apache.spark.ui.SparkUI
-
- StorageListener - Class in org.apache.spark.ui.storage
-
:: DeveloperApi ::
A SparkListener that prepares information to be displayed on the BlockManagerUI.
- StorageListener(StorageStatusListener) - Constructor for class org.apache.spark.ui.storage.StorageListener
-
- StoragePage - Class in org.apache.spark.ui.storage
-
Page showing list of RDD's currently stored in the cluster
- StoragePage(StorageTab) - Constructor for class org.apache.spark.ui.storage.StoragePage
-
- StorageStatus - Class in org.apache.spark.storage
-
:: DeveloperApi ::
Storage information for each BlockManager.
- StorageStatus(BlockManagerId, long) - Constructor for class org.apache.spark.storage.StorageStatus
-
- StorageStatus(BlockManagerId, long, Map<BlockId, BlockStatus>) - Constructor for class org.apache.spark.storage.StorageStatus
-
Create a storage status with an initial set of blocks, leaving the source unmodified.
- storageStatusList() - Method in class org.apache.spark.storage.StorageStatusListener
-
- storageStatusList() - Method in class org.apache.spark.ui.exec.ExecutorsListener
-
- storageStatusList() - Method in class org.apache.spark.ui.storage.StorageListener
-
- StorageStatusListener - Class in org.apache.spark.storage
-
:: DeveloperApi ::
A SparkListener that maintains executor storage status.
- StorageStatusListener() - Constructor for class org.apache.spark.storage.StorageStatusListener
-
- storageStatusListener() - Method in class org.apache.spark.ui.SparkUI
-
- StorageTab - Class in org.apache.spark.ui.storage
-
Web UI showing storage status of all RDD's in the given SparkContext.
- StorageTab(SparkUI) - Constructor for class org.apache.spark.ui.storage.StorageTab
-
- StorageUtils - Class in org.apache.spark.storage
-
Helper methods for storage-related objects.
- StorageUtils() - Constructor for class org.apache.spark.storage.StorageUtils
-
- store(Iterator<T>) - Method in interface org.apache.spark.streaming.receiver.ActorHelper
-
Store an iterator of received data as a data block into Spark's memory.
- store(ByteBuffer) - Method in interface org.apache.spark.streaming.receiver.ActorHelper
-
Store the bytes of received data as a data block into Spark's memory.
- store(T) - Method in interface org.apache.spark.streaming.receiver.ActorHelper
-
Store a single item of received data to Spark's memory.
- store(T) - Method in class org.apache.spark.streaming.receiver.Receiver
-
Store a single item of received data to Spark's memory.
- store(ArrayBuffer<T>) - Method in class org.apache.spark.streaming.receiver.Receiver
-
Store an ArrayBuffer of received data as a data block into Spark's memory.
- store(ArrayBuffer<T>, Object) - Method in class org.apache.spark.streaming.receiver.Receiver
-
Store an ArrayBuffer of received data as a data block into Spark's memory.
- store(Iterator<T>) - Method in class org.apache.spark.streaming.receiver.Receiver
-
Store an iterator of received data as a data block into Spark's memory.
- store(Iterator<T>, Object) - Method in class org.apache.spark.streaming.receiver.Receiver
-
Store an iterator of received data as a data block into Spark's memory.
- store(Iterator<T>) - Method in class org.apache.spark.streaming.receiver.Receiver
-
Store an iterator of received data as a data block into Spark's memory.
- store(Iterator<T>, Object) - Method in class org.apache.spark.streaming.receiver.Receiver
-
Store an iterator of received data as a data block into Spark's memory.
- store(ByteBuffer) - Method in class org.apache.spark.streaming.receiver.Receiver
-
Store the bytes of received data as a data block into Spark's memory.
- store(ByteBuffer, Object) - Method in class org.apache.spark.streaming.receiver.Receiver
-
Store the bytes of received data as a data block into Spark's memory.
- storeBlock(StreamBlockId, ReceivedBlock) - Method in class org.apache.spark.streaming.receiver.BlockManagerBasedBlockHandler
-
- storeBlock(StreamBlockId, ReceivedBlock) - Method in interface org.apache.spark.streaming.receiver.ReceivedBlockHandler
-
Store a received block with the given block id and return related metadata
- storeBlock(StreamBlockId, ReceivedBlock) - Method in class org.apache.spark.streaming.receiver.WriteAheadLogBasedBlockHandler
-
This implementation stores the block into the block manager as well as a write ahead log.
- Strategy - Class in org.apache.spark.mllib.tree.configuration
-
:: Experimental ::
Stores all the configuration options for tree construction
- Strategy(Enumeration.Value, Impurity, int, int, int, Enumeration.Value, Map<Object, Object>, int, double, int, double, boolean, Option<String>, int) - Constructor for class org.apache.spark.mllib.tree.configuration.Strategy
-
- Strategy(Enumeration.Value, Impurity, int, int, int, Map<Integer, Integer>) - Constructor for class org.apache.spark.mllib.tree.configuration.Strategy
-
- STRATEGY_DEFAULT() - Static method in class org.apache.spark.util.logging.RollingFileAppender
-
- STRATEGY_PROPERTY() - Static method in class org.apache.spark.util.logging.RollingFileAppender
-
- StratifiedSamplingUtils - Class in org.apache.spark.util.random
-
Auxiliary functions and data structures for the sampleByKey method in PairRDDFunctions.
- StratifiedSamplingUtils() - Constructor for class org.apache.spark.util.random.StratifiedSamplingUtils
-
- STREAM() - Static method in class org.apache.spark.storage.BlockId
-
- StreamBasedRecordReader<T> - Class in org.apache.spark.input
-
An abstract class of RecordReader
to reading files out as streams
- StreamBasedRecordReader(CombineFileSplit, TaskAttemptContext, Integer) - Constructor for class org.apache.spark.input.StreamBasedRecordReader
-
- StreamBlockId - Class in org.apache.spark.storage
-
- StreamBlockId(int, long) - Constructor for class org.apache.spark.storage.StreamBlockId
-
- streamed() - Method in class org.apache.spark.sql.execution.joins.LeftSemiJoinBNL
-
- streamedKeys() - Method in interface org.apache.spark.sql.execution.joins.HashJoin
-
- streamedPlan() - Method in interface org.apache.spark.sql.execution.joins.HashJoin
-
- StreamFileInputFormat<T> - Class in org.apache.spark.input
-
A general format for reading whole files in as streams, byte arrays,
or other functions to be added
- StreamFileInputFormat() - Constructor for class org.apache.spark.input.StreamFileInputFormat
-
- streamId() - Method in class org.apache.spark.storage.StreamBlockId
-
- streamId() - Method in class org.apache.spark.streaming.receiver.Receiver
-
Get the unique identifier the receiver input stream that this
receiver is associated with.
- streamId() - Method in class org.apache.spark.streaming.scheduler.DeregisterReceiver
-
- streamId() - Method in class org.apache.spark.streaming.scheduler.ReceivedBlockInfo
-
- streamId() - Method in class org.apache.spark.streaming.scheduler.ReceiverInfo
-
- streamId() - Method in class org.apache.spark.streaming.scheduler.RegisterReceiver
-
- streamId() - Method in class org.apache.spark.streaming.scheduler.ReportError
-
- streamIdToAllocatedBlocks() - Method in class org.apache.spark.streaming.scheduler.AllocatedBlocks
-
- StreamingContext - Class in org.apache.spark.streaming
-
Main entry point for Spark Streaming functionality.
- StreamingContext(SparkContext, Checkpoint, Duration) - Constructor for class org.apache.spark.streaming.StreamingContext
-
- StreamingContext(SparkContext, Duration) - Constructor for class org.apache.spark.streaming.StreamingContext
-
Create a StreamingContext using an existing SparkContext.
- StreamingContext(SparkConf, Duration) - Constructor for class org.apache.spark.streaming.StreamingContext
-
Create a StreamingContext by providing the configuration necessary for a new SparkContext.
- StreamingContext(String, String, Duration, String, Seq<String>, Map<String, String>) - Constructor for class org.apache.spark.streaming.StreamingContext
-
Create a StreamingContext by providing the details necessary for creating a new SparkContext.
- StreamingContext(String, Configuration) - Constructor for class org.apache.spark.streaming.StreamingContext
-
Recreate a StreamingContext from a checkpoint file.
- StreamingContext(String) - Constructor for class org.apache.spark.streaming.StreamingContext
-
Recreate a StreamingContext from a checkpoint file.
- StreamingContext.StreamingContextState$ - Class in org.apache.spark.streaming
-
Enumeration to identify current state of the StreamingContext
- StreamingContext.StreamingContextState$() - Constructor for class org.apache.spark.streaming.StreamingContext.StreamingContextState$
-
- StreamingContextState() - Method in class org.apache.spark.streaming.StreamingContext
-
Accessor for nested Scala object
- StreamingExamples - Class in org.apache.spark.examples.streaming
-
Utility functions for Spark Streaming examples.
- StreamingExamples() - Constructor for class org.apache.spark.examples.streaming.StreamingExamples
-
- StreamingJobProgressListener - Class in org.apache.spark.streaming.ui
-
- StreamingJobProgressListener(StreamingContext) - Constructor for class org.apache.spark.streaming.ui.StreamingJobProgressListener
-
- StreamingKMeans - Class in org.apache.spark.mllib.clustering
-
:: DeveloperApi ::
StreamingKMeans provides methods for configuring a
streaming k-means analysis, training the model on streaming,
and using the model to make predictions on streaming data.
- StreamingKMeans(int, double, String) - Constructor for class org.apache.spark.mllib.clustering.StreamingKMeans
-
- StreamingKMeans() - Constructor for class org.apache.spark.mllib.clustering.StreamingKMeans
-
- StreamingKMeansModel - Class in org.apache.spark.mllib.clustering
-
:: DeveloperApi ::
StreamingKMeansModel extends MLlib's KMeansModel for streaming
algorithms, so it can keep track of a continuously updated weight
associated with each cluster, and also update the model by
doing a single iteration of the standard k-means algorithm.
- StreamingKMeansModel(Vector[], double[]) - Constructor for class org.apache.spark.mllib.clustering.StreamingKMeansModel
-
- StreamingLinearAlgorithm<M extends GeneralizedLinearModel,A extends GeneralizedLinearAlgorithm<M>> - Class in org.apache.spark.mllib.regression
-
:: DeveloperApi ::
StreamingLinearAlgorithm implements methods for continuously
training a generalized linear model model on streaming data,
and using it for prediction on (possibly different) streaming data.
- StreamingLinearAlgorithm() - Constructor for class org.apache.spark.mllib.regression.StreamingLinearAlgorithm
-
- StreamingLinearRegressionWithSGD - Class in org.apache.spark.mllib.regression
-
Train or predict a linear regression model on streaming data.
- StreamingLinearRegressionWithSGD(double, int, double, Vector) - Constructor for class org.apache.spark.mllib.regression.StreamingLinearRegressionWithSGD
-
- StreamingLinearRegressionWithSGD() - Constructor for class org.apache.spark.mllib.regression.StreamingLinearRegressionWithSGD
-
Construct a StreamingLinearRegression object with default parameters:
{stepSize: 0.1, numIterations: 50, miniBatchFraction: 1.0}.
- StreamingListener - Interface in org.apache.spark.streaming.scheduler
-
:: DeveloperApi ::
A listener interface for receiving information about an ongoing streaming
computation.
- StreamingListenerBatchCompleted - Class in org.apache.spark.streaming.scheduler
-
- StreamingListenerBatchCompleted(BatchInfo) - Constructor for class org.apache.spark.streaming.scheduler.StreamingListenerBatchCompleted
-
- StreamingListenerBatchStarted - Class in org.apache.spark.streaming.scheduler
-
- StreamingListenerBatchStarted(BatchInfo) - Constructor for class org.apache.spark.streaming.scheduler.StreamingListenerBatchStarted
-
- StreamingListenerBatchSubmitted - Class in org.apache.spark.streaming.scheduler
-
- StreamingListenerBatchSubmitted(BatchInfo) - Constructor for class org.apache.spark.streaming.scheduler.StreamingListenerBatchSubmitted
-
- StreamingListenerBus - Class in org.apache.spark.streaming.scheduler
-
Asynchronously passes StreamingListenerEvents to registered StreamingListeners.
- StreamingListenerBus() - Constructor for class org.apache.spark.streaming.scheduler.StreamingListenerBus
-
- StreamingListenerEvent - Interface in org.apache.spark.streaming.scheduler
-
:: DeveloperApi ::
Base trait for events related to StreamingListener
- StreamingListenerReceiverError - Class in org.apache.spark.streaming.scheduler
-
- StreamingListenerReceiverError(ReceiverInfo) - Constructor for class org.apache.spark.streaming.scheduler.StreamingListenerReceiverError
-
- StreamingListenerReceiverStarted - Class in org.apache.spark.streaming.scheduler
-
- StreamingListenerReceiverStarted(ReceiverInfo) - Constructor for class org.apache.spark.streaming.scheduler.StreamingListenerReceiverStarted
-
- StreamingListenerReceiverStopped - Class in org.apache.spark.streaming.scheduler
-
- StreamingListenerReceiverStopped(ReceiverInfo) - Constructor for class org.apache.spark.streaming.scheduler.StreamingListenerReceiverStopped
-
- StreamingListenerShutdown - Class in org.apache.spark.streaming.scheduler
-
An event used in the listener to shutdown the listener daemon thread.
- StreamingListenerShutdown() - Constructor for class org.apache.spark.streaming.scheduler.StreamingListenerShutdown
-
- StreamingPage - Class in org.apache.spark.streaming.ui
-
Page for Spark Web UI that shows statistics of a streaming job
- StreamingPage(StreamingTab) - Constructor for class org.apache.spark.streaming.ui.StreamingPage
-
- StreamingSource - Class in org.apache.spark.streaming
-
- StreamingSource(StreamingContext) - Constructor for class org.apache.spark.streaming.StreamingSource
-
- StreamingTab - Class in org.apache.spark.streaming.ui
-
Spark Web UI tab that shows statistics of a streaming job.
- StreamingTab(StreamingContext) - Constructor for class org.apache.spark.streaming.ui.StreamingTab
-
- StreamInputFormat - Class in org.apache.spark.input
-
The format for the PortableDataStream files
- StreamInputFormat() - Constructor for class org.apache.spark.input.StreamInputFormat
-
- StreamRecordReader - Class in org.apache.spark.input
-
Reads the record in directly as a stream for other objects to manipulate and handle
- StreamRecordReader(CombineFileSplit, TaskAttemptContext, Integer) - Constructor for class org.apache.spark.input.StreamRecordReader
-
- streamSideKeyGenerator() - Method in interface org.apache.spark.sql.execution.joins.HashJoin
-
- STRING - Class in org.apache.spark.sql.columnar
-
- STRING() - Constructor for class org.apache.spark.sql.columnar.STRING
-
- StringColumnAccessor - Class in org.apache.spark.sql.columnar
-
- StringColumnAccessor(ByteBuffer) - Constructor for class org.apache.spark.sql.columnar.StringColumnAccessor
-
- StringColumnBuilder - Class in org.apache.spark.sql.columnar
-
- StringColumnBuilder() - Constructor for class org.apache.spark.sql.columnar.StringColumnBuilder
-
- StringColumnStats - Class in org.apache.spark.sql.columnar
-
- StringColumnStats() - Constructor for class org.apache.spark.sql.columnar.StringColumnStats
-
- stringifyPartialValue(Object) - Static method in class org.apache.spark.Accumulators
-
- stringifyValue(Object) - Static method in class org.apache.spark.Accumulators
-
- stringToText(String) - Static method in class org.apache.spark.SparkContext
-
- stringToTime(String) - Static method in class org.apache.spark.sql.types.util.DataTypeConversions
-
- StringType - Static variable in class org.apache.spark.sql.api.java.DataType
-
Gets the StringType object.
- StringType - Class in org.apache.spark.sql.api.java
-
The data type representing String values.
- stringWritableConverter() - Static method in class org.apache.spark.SparkContext
-
- stripDirectory(String) - Static method in class org.apache.spark.util.Utils
-
Strip the directory from a path name
- stronglyConnectedComponents(int) - Method in class org.apache.spark.graphx.GraphOps
-
Compute the strongly connected component (SCC) of each vertex and return a graph with the
vertex value containing the lowest vertex id in the SCC containing that vertex.
- StronglyConnectedComponents - Class in org.apache.spark.graphx.lib
-
Strongly connected components algorithm implementation.
- StronglyConnectedComponents() - Constructor for class org.apache.spark.graphx.lib.StronglyConnectedComponents
-
- StructField - Class in org.apache.spark.sql.api.java
-
A StructField object represents a field in a StructType object.
- StructType - Class in org.apache.spark.sql.api.java
-
The data type representing Rows.
- StudentTCacher - Class in org.apache.spark.partial
-
A utility class for caching Student's T distribution values for a given confidence level
and various sample sizes.
- StudentTCacher(double) - Constructor for class org.apache.spark.partial.StudentTCacher
-
- subDirsPerLocalDir() - Method in class org.apache.spark.storage.DiskBlockManager
-
- subgraph(Function1<EdgeTriplet<VD, ED>, Object>, Function2<Object, VD, Object>) - Method in class org.apache.spark.graphx.Graph
-
Restricts the graph to only the vertices and edges satisfying the predicates.
- subgraph(Function1<EdgeTriplet<VD, ED>, Object>, Function2<Object, VD, Object>) - Method in class org.apache.spark.graphx.impl.GraphImpl
-
- submissionTime() - Method in class org.apache.spark.scheduler.StageInfo
-
When this stage was submitted from the DAGScheduler to a TaskScheduler.
- submissionTime() - Method in interface org.apache.spark.SparkStageInfo
-
- submissionTime() - Method in class org.apache.spark.SparkStageInfoImpl
-
- submissionTime() - Method in class org.apache.spark.streaming.scheduler.BatchInfo
-
- submitJob(RDD<T>, Function2<TaskContext, Iterator<T>, U>, Seq<Object>, CallSite, boolean, Function2<Object, U, BoxedUnit>, Properties) - Method in class org.apache.spark.scheduler.DAGScheduler
-
Submit a job to the job scheduler and get a JobWaiter object back.
- submitJob(RDD<T>, Function1<Iterator<T>, U>, Seq<Object>, Function2<Object, U, BoxedUnit>, Function0<R>) - Method in class org.apache.spark.SparkContext
-
:: Experimental ::
Submit a job for execution and return a FutureJob holding the result.
- submitJobSet(JobSet) - Method in class org.apache.spark.streaming.scheduler.JobScheduler
-
- submitTasks(TaskSet) - Method in interface org.apache.spark.scheduler.TaskScheduler
-
- submitTasks(TaskSet) - Method in class org.apache.spark.scheduler.TaskSchedulerImpl
-
- subProperties(Properties, Regex) - Method in class org.apache.spark.metrics.MetricsConfig
-
- subsampleWeights() - Method in class org.apache.spark.mllib.tree.impl.BaggedPoint
-
- subsamplingFeatures() - Method in class org.apache.spark.mllib.tree.impl.DecisionTreeMetadata
-
Indicates if feature subsampling is being used.
- subsamplingRate() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- subsetAccuracy() - Method in class org.apache.spark.mllib.evaluation.MultilabelMetrics
-
Returns subset accuracy
(for equal sets of labels)
- SUBSTR() - Static method in class org.apache.spark.sql.hive.HiveQl
-
- subTestSchema() - Static method in class org.apache.spark.sql.parquet.ParquetTestData
-
- subTestSchemaFieldNames() - Static method in class org.apache.spark.sql.parquet.ParquetTestData
-
- subtract(JavaDoubleRDD) - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Return an RDD with the elements from this
that are not in other
.
- subtract(JavaDoubleRDD, int) - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Return an RDD with the elements from this
that are not in other
.
- subtract(JavaDoubleRDD, Partitioner) - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Return an RDD with the elements from this
that are not in other
.
- subtract(JavaPairRDD<K, V>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Return an RDD with the elements from this
that are not in other
.
- subtract(JavaPairRDD<K, V>, int) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Return an RDD with the elements from this
that are not in other
.
- subtract(JavaPairRDD<K, V>, Partitioner) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Return an RDD with the elements from this
that are not in other
.
- subtract(JavaRDD<T>) - Method in class org.apache.spark.api.java.JavaRDD
-
Return an RDD with the elements from this
that are not in other
.
- subtract(JavaRDD<T>, int) - Method in class org.apache.spark.api.java.JavaRDD
-
Return an RDD with the elements from this
that are not in other
.
- subtract(JavaRDD<T>, Partitioner) - Method in class org.apache.spark.api.java.JavaRDD
-
Return an RDD with the elements from this
that are not in other
.
- subtract(ImpurityCalculator) - Method in class org.apache.spark.mllib.tree.impurity.ImpurityCalculator
-
Subtract the stats from another calculator from this one, modifying and returning this
calculator.
- subtract(RDD<T>) - Method in class org.apache.spark.rdd.RDD
-
Return an RDD with the elements from this
that are not in other
.
- subtract(RDD<T>, int) - Method in class org.apache.spark.rdd.RDD
-
Return an RDD with the elements from this
that are not in other
.
- subtract(RDD<T>, Partitioner, Ordering<T>) - Method in class org.apache.spark.rdd.RDD
-
Return an RDD with the elements from this
that are not in other
.
- subtract(JavaSchemaRDD) - Method in class org.apache.spark.sql.api.java.JavaSchemaRDD
-
Return an RDD with the elements from this
that are not in other
.
- subtract(JavaSchemaRDD, int) - Method in class org.apache.spark.sql.api.java.JavaSchemaRDD
-
Return an RDD with the elements from this
that are not in other
.
- subtract(JavaSchemaRDD, Partitioner) - Method in class org.apache.spark.sql.api.java.JavaSchemaRDD
-
Return an RDD with the elements from this
that are not in other
.
- subtract(RDD<Row>) - Method in class org.apache.spark.sql.SchemaRDD
-
- subtract(RDD<Row>, int) - Method in class org.apache.spark.sql.SchemaRDD
-
- subtract(RDD<Row>, Partitioner, Ordering<Row>) - Method in class org.apache.spark.sql.SchemaRDD
-
- subtract(long, long) - Static method in class org.apache.spark.streaming.util.RawTextHelper
-
- subtract(Vector) - Method in class org.apache.spark.util.Vector
-
- subtractByKey(JavaPairRDD<K, W>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Return an RDD with the pairs from this
whose keys are not in other
.
- subtractByKey(JavaPairRDD<K, W>, int) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Return an RDD with the pairs from `this` whose keys are not in `other`.
- subtractByKey(JavaPairRDD<K, W>, Partitioner) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Return an RDD with the pairs from `this` whose keys are not in `other`.
- subtractByKey(RDD<Tuple2<K, W>>, ClassTag<W>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Return an RDD with the pairs from this
whose keys are not in other
.
- subtractByKey(RDD<Tuple2<K, W>>, int, ClassTag<W>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Return an RDD with the pairs from `this` whose keys are not in `other`.
- subtractByKey(RDD<Tuple2<K, W>>, Partitioner, ClassTag<W>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Return an RDD with the pairs from `this` whose keys are not in `other`.
- SubtractedRDD<K,V,W> - Class in org.apache.spark.rdd
-
An optimized version of cogroup for set difference/subtraction.
- SubtractedRDD(RDD<? extends Product2<K, V>>, RDD<? extends Product2<K, W>>, Partitioner, ClassTag<K>, ClassTag<V>, ClassTag<W>) - Constructor for class org.apache.spark.rdd.SubtractedRDD
-
- subtreeDepth() - Method in class org.apache.spark.mllib.tree.model.Node
-
Get depth of tree from this node.
- subtreeToString(int) - Method in class org.apache.spark.mllib.tree.model.Node
-
Recursive print function.
- succeededTasks() - Method in class org.apache.spark.ui.jobs.UIData.ExecutorSummary
-
- success() - Method in class org.apache.spark.storage.ResultWithDroppedBlocks
-
- Success - Class in org.apache.spark
-
:: DeveloperApi ::
Task succeeded.
- Success() - Constructor for class org.apache.spark.Success
-
- successful() - Method in class org.apache.spark.scheduler.TaskInfo
-
- successful() - Method in class org.apache.spark.scheduler.TaskSetManager
-
- SUCCESSFUL_JOB_OUTPUT_DIR_MARKER() - Static method in class org.apache.spark.sql.hive.SparkHiveDynamicPartitionWriterContainer
-
- sufficientResourcesRegistered() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend
-
- sufficientResourcesRegistered() - Method in class org.apache.spark.scheduler.cluster.SparkDeploySchedulerBackend
-
- sufficientResourcesRegistered() - Method in class org.apache.spark.scheduler.cluster.YarnSchedulerBackend
-
- sum() - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Add up the elements in this RDD.
- Sum() - Static method in class org.apache.spark.mllib.tree.configuration.EnsembleCombiningStrategy
-
- sum() - Method in class org.apache.spark.partial.CountEvaluator
-
- sum() - Method in class org.apache.spark.rdd.DoubleRDDFunctions
-
Add up the elements in this RDD.
- SUM() - Static method in class org.apache.spark.sql.hive.HiveQl
-
- sum() - Method in class org.apache.spark.util.StatCounter
-
- sum() - Method in class org.apache.spark.util.Vector
-
- sumApprox(long, Double) - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
:: Experimental ::
Approximate operation to return the sum within a timeout.
- sumApprox(long) - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
:: Experimental ::
Approximate operation to return the sum within a timeout.
- sumApprox(long, double) - Method in class org.apache.spark.rdd.DoubleRDDFunctions
-
:: Experimental ::
Approximate operation to return the sum within a timeout.
- SumEvaluator - Class in org.apache.spark.partial
-
An ApproximateEvaluator for sums.
- SumEvaluator(int, double) - Constructor for class org.apache.spark.partial.SumEvaluator
-
- summary(PrintStream) - Method in class org.apache.spark.util.Distribution
-
print a summary of this distribution to the given PrintStream.
- sums() - Method in class org.apache.spark.partial.GroupedCountEvaluator
-
- sums() - Method in class org.apache.spark.partial.GroupedMeanEvaluator
-
- sums() - Method in class org.apache.spark.partial.GroupedSumEvaluator
-
- supervisorStrategy() - Method in class org.apache.spark.scheduler.DAGSchedulerActorSupervisor
-
- supervisorStrategy() - Method in class org.apache.spark.streaming.receiver.ActorReceiver.Supervisor
-
- supportedFeatureSubsetStrategies() - Static method in class org.apache.spark.mllib.tree.RandomForest
-
List of supported feature subset sampling strategies.
- supports(ColumnType<?, ?>) - Static method in class org.apache.spark.sql.columnar.compression.BooleanBitSet
-
- supports(ColumnType<?, ?>) - Method in interface org.apache.spark.sql.columnar.compression.CompressionScheme
-
- supports(ColumnType<?, ?>) - Static method in class org.apache.spark.sql.columnar.compression.DictionaryEncoding
-
- supports(ColumnType<?, ?>) - Static method in class org.apache.spark.sql.columnar.compression.IntDelta
-
- supports(ColumnType<?, ?>) - Static method in class org.apache.spark.sql.columnar.compression.LongDelta
-
- supports(ColumnType<?, ?>) - Static method in class org.apache.spark.sql.columnar.compression.PassThrough
-
- supports(ColumnType<?, ?>) - Static method in class org.apache.spark.sql.columnar.compression.RunLengthEncoding
-
- SVDPlusPlus - Class in org.apache.spark.graphx.lib
-
Implementation of SVD++ algorithm.
- SVDPlusPlus() - Constructor for class org.apache.spark.graphx.lib.SVDPlusPlus
-
- SVDPlusPlus.Conf - Class in org.apache.spark.graphx.lib
-
Configuration parameters for SVDPlusPlus.
- SVDPlusPlus.Conf(int, int, double, double, double, double, double, double) - Constructor for class org.apache.spark.graphx.lib.SVDPlusPlus.Conf
-
- SVMDataGenerator - Class in org.apache.spark.mllib.util
-
:: DeveloperApi ::
Generate sample data used for SVM.
- SVMDataGenerator() - Constructor for class org.apache.spark.mllib.util.SVMDataGenerator
-
- SVMModel - Class in org.apache.spark.mllib.classification
-
Model for Support Vector Machines (SVMs).
- SVMModel(Vector, double) - Constructor for class org.apache.spark.mllib.classification.SVMModel
-
- SVMWithSGD - Class in org.apache.spark.mllib.classification
-
Train a Support Vector Machine (SVM) using Stochastic Gradient Descent.
- SVMWithSGD() - Constructor for class org.apache.spark.mllib.classification.SVMWithSGD
-
Construct a SVM object with default parameters: {stepSize: 1.0, numIterations: 100,
regParm: 0.01, miniBatchFraction: 1.0}.
- symlink(File, File) - Static method in class org.apache.spark.util.Utils
-
Creates a symlink.
- symmetricEigs(Function1<DenseVector<Object>, DenseVector<Object>>, int, int, double, int) - Static method in class org.apache.spark.mllib.linalg.EigenValueDecomposition
-
Compute the leading k eigenvalues and eigenvectors on a symmetric square matrix using ARPACK.
- SystemClock - Class in org.apache.spark.streaming.util
-
- SystemClock() - Constructor for class org.apache.spark.streaming.util.SystemClock
-
- SystemClock - Class in org.apache.spark.util
-
- SystemClock() - Constructor for class org.apache.spark.util.SystemClock
-
- systemProperties() - Method in class org.apache.spark.ui.env.EnvironmentListener
-
- systemProperty(Enumeration.Value) - Static method in class org.apache.spark.util.MetadataCleanerType
-
- t() - Method in class org.apache.spark.SerializableWritable
-
- table() - Method in class org.apache.spark.sql.hive.execution.DescribeHiveTableCommand
-
- table() - Method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- table() - Method in class org.apache.spark.sql.hive.InsertIntoHiveTable
-
- table() - Method in class org.apache.spark.sql.hive.MetastoreRelation
-
- table(String) - Method in class org.apache.spark.sql.SQLContext
-
Returns the specified table as a SchemaRDD
- TABLE_CLASS_NOT_STRIPED() - Static method in class org.apache.spark.ui.UIUtils
-
- TABLE_CLASS_STRIPED() - Static method in class org.apache.spark.ui.UIUtils
-
- tableDesc() - Method in class org.apache.spark.sql.hive.MetastoreRelation
-
- tableExists(Seq<String>) - Method in class org.apache.spark.sql.hive.HiveMetastoreCatalog
-
- tableInfo() - Method in class org.apache.spark.sql.hive.ShimFileSinkDesc
-
- tableName() - Method in class org.apache.spark.sql.columnar.InMemoryRelation
-
- tableName() - Method in class org.apache.spark.sql.execution.CacheTableCommand
-
- tableName() - Method in class org.apache.spark.sql.execution.UncacheTableCommand
-
- tableName() - Method in class org.apache.spark.sql.hive.AnalyzeTable
-
- tableName() - Method in class org.apache.spark.sql.hive.DropTable
-
- tableName() - Method in class org.apache.spark.sql.hive.execution.AnalyzeTable
-
- tableName() - Method in class org.apache.spark.sql.hive.execution.CreateTableAsSelect
-
- tableName() - Method in class org.apache.spark.sql.hive.execution.DropTable
-
- tableName() - Method in class org.apache.spark.sql.hive.MetastoreRelation
-
- tableName() - Method in class org.apache.spark.sql.sources.CreateTableUsing
-
- TableReader - Interface in org.apache.spark.sql.hive
-
A trait for subclasses that handle table scans.
- TableScan - Class in org.apache.spark.sql.sources
-
::DeveloperApi::
A BaseRelation that can produce all of its tuples as an RDD of Row objects.
- TableScan() - Constructor for class org.apache.spark.sql.sources.TableScan
-
- TachyonBlockManager - Class in org.apache.spark.storage
-
Creates and maintains the logical mapping between logical blocks and tachyon fs locations.
- TachyonBlockManager(BlockManager, String, String) - Constructor for class org.apache.spark.storage.TachyonBlockManager
-
- TachyonFileSegment - Class in org.apache.spark.storage
-
References a particular segment of a file (potentially the entire file), based off an offset and
a length.
- TachyonFileSegment(TachyonFile, long, long) - Constructor for class org.apache.spark.storage.TachyonFileSegment
-
- tachyonFolderName() - Method in class org.apache.spark.SparkContext
-
- tachyonSize() - Method in class org.apache.spark.storage.BlockManagerMessages.UpdateBlockInfo
-
- tachyonSize() - Method in class org.apache.spark.storage.BlockStatus
-
- tachyonSize() - Method in class org.apache.spark.storage.RDDInfo
-
- tachyonStore() - Method in class org.apache.spark.storage.BlockManager
-
- TachyonStore - Class in org.apache.spark.storage
-
Stores BlockManager blocks on Tachyon.
- TachyonStore(BlockManager, TachyonBlockManager) - Constructor for class org.apache.spark.storage.TachyonStore
-
- tail() - Method in class org.apache.spark.mllib.rdd.SlidingRDDPartition
-
- take(int) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Take the first num elements of the RDD.
- take(int) - Method in class org.apache.spark.rdd.RDD
-
Take the first num elements of the RDD.
- take(int) - Method in class org.apache.spark.sql.api.java.JavaSchemaRDD
-
- take(int) - Method in class org.apache.spark.sql.SchemaRDD
-
- takeAsync(int) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
The asynchronous version of the take
action, which returns a
future for retrieving the first num
elements of this RDD.
- takeAsync(int) - Method in class org.apache.spark.rdd.AsyncRDDActions
-
Returns a future for retrieving the first num elements of the RDD.
- takeOrdered(int, Comparator<T>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Returns the first k (smallest) elements from this RDD as defined by
the specified Comparator[T] and maintains the order.
- takeOrdered(int) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Returns the first k (smallest) elements from this RDD using the
natural ordering for T while maintain the order.
- takeOrdered(int, Ordering<T>) - Method in class org.apache.spark.rdd.RDD
-
Returns the first k (smallest) elements from this RDD as defined by the specified
implicit Ordering[T] and maintains the ordering.
- TakeOrdered() - Method in class org.apache.spark.sql.execution.SparkStrategies
-
- TakeOrdered - Class in org.apache.spark.sql.execution
-
:: DeveloperApi ::
Take the first limit elements as defined by the sortOrder.
- TakeOrdered(int, Seq<SortOrder>, SparkPlan) - Constructor for class org.apache.spark.sql.execution.TakeOrdered
-
- takeSample(boolean, int) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
- takeSample(boolean, int, long) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
- takeSample(boolean, int, long) - Method in class org.apache.spark.rdd.RDD
-
Return a fixed-size sampled subset of this RDD in an array
- targetStorageLevel() - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- targetStorageLevel() - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- task() - Method in class org.apache.spark.CleanupTaskWeakReference
-
- task() - Method in class org.apache.spark.scheduler.BeginEvent
-
- task() - Method in class org.apache.spark.scheduler.CompletionEvent
-
- Task<T> - Class in org.apache.spark.scheduler
-
A unit of execution.
- Task(int, int) - Constructor for class org.apache.spark.scheduler.Task
-
- TASK_DESERIALIZATION_TIME() - Static method in class org.apache.spark.ui.jobs.TaskDetailsClassNames
-
- TASK_DESERIALIZATION_TIME() - Static method in class org.apache.spark.ui.ToolTips
-
- TASK_SIZE_TO_WARN_KB() - Static method in class org.apache.spark.scheduler.TaskSetManager
-
- taskAttempts() - Method in class org.apache.spark.scheduler.TaskSetManager
-
- TaskCompletionListener - Interface in org.apache.spark.util
-
:: DeveloperApi ::
- TaskCompletionListenerException - Exception in org.apache.spark.util
-
Exception thrown when there is an exception in
executing the callback in TaskCompletionListener.
- TaskCompletionListenerException(Seq<String>) - Constructor for exception org.apache.spark.util.TaskCompletionListenerException
-
- TaskContext - Class in org.apache.spark
-
Contextual information about a task which can be read or mutated during
execution.
- TaskContext() - Constructor for class org.apache.spark.TaskContext
-
- TaskContextHelper - Class in org.apache.spark
-
This class exists to restrict the visibility of TaskContext setters.
- TaskContextHelper() - Constructor for class org.apache.spark.TaskContextHelper
-
- TaskContextImpl - Class in org.apache.spark
-
- TaskContextImpl(int, int, long, boolean, TaskMetrics) - Constructor for class org.apache.spark.TaskContextImpl
-
- taskData() - Method in class org.apache.spark.ui.jobs.UIData.StageUIData
-
- TaskDescription - Class in org.apache.spark.scheduler
-
Description of a task that gets passed onto executors to be executed, usually created by
TaskSetManager.resourceOffer
.
- TaskDescription(long, String, String, int, ByteBuffer) - Constructor for class org.apache.spark.scheduler.TaskDescription
-
- TaskDetailsClassNames - Class in org.apache.spark.ui.jobs
-
Names of the CSS classes corresponding to each type of task detail.
- TaskDetailsClassNames() - Constructor for class org.apache.spark.ui.jobs.TaskDetailsClassNames
-
- taskEnded(Task<?>, TaskEndReason, Object, Map<Object, Object>, TaskInfo, TaskMetrics) - Method in class org.apache.spark.scheduler.DAGScheduler
-
- taskEndFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
-
- TaskEndReason - Interface in org.apache.spark
-
:: DeveloperApi ::
Various possible reasons why a task ended.
- taskEndReasonFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
-
- taskEndReasonToJson(TaskEndReason) - Static method in class org.apache.spark.util.JsonProtocol
-
- taskEndToJson(SparkListenerTaskEnd) - Static method in class org.apache.spark.util.JsonProtocol
-
- TaskFailedReason - Interface in org.apache.spark
-
:: DeveloperApi ::
Various possible reasons why a task failed.
- taskGettingResult(TaskInfo) - Method in class org.apache.spark.scheduler.DAGScheduler
-
- taskGettingResultFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
-
- taskGettingResultToJson(SparkListenerTaskGettingResult) - Static method in class org.apache.spark.util.JsonProtocol
-
- taskId() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.KillTask
-
- taskId() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.StatusUpdate
-
- taskId() - Method in class org.apache.spark.scheduler.local.KillTask
-
- taskId() - Method in class org.apache.spark.scheduler.local.StatusUpdate
-
- taskId() - Method in class org.apache.spark.scheduler.TaskDescription
-
- taskId() - Method in class org.apache.spark.scheduler.TaskInfo
-
- taskId() - Method in class org.apache.spark.storage.TaskResultBlockId
-
- taskIdsOnSlave() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend
-
- taskIdToExecutorId() - Method in class org.apache.spark.scheduler.TaskSchedulerImpl
-
- taskIdToSlaveId() - Method in class org.apache.spark.scheduler.cluster.mesos.CoarseMesosSchedulerBackend
-
- taskIdToSlaveId() - Method in class org.apache.spark.scheduler.cluster.mesos.MesosSchedulerBackend
-
- taskIdToTaskSetId() - Method in class org.apache.spark.scheduler.TaskSchedulerImpl
-
- taskInfo() - Method in class org.apache.spark.scheduler.BeginEvent
-
- taskInfo() - Method in class org.apache.spark.scheduler.CompletionEvent
-
- taskInfo() - Method in class org.apache.spark.scheduler.GettingResultEvent
-
- taskInfo() - Method in class org.apache.spark.scheduler.SparkListenerTaskEnd
-
- taskInfo() - Method in class org.apache.spark.scheduler.SparkListenerTaskGettingResult
-
- taskInfo() - Method in class org.apache.spark.scheduler.SparkListenerTaskStart
-
- TaskInfo - Class in org.apache.spark.scheduler
-
:: DeveloperApi ::
Information about a running task attempt inside a TaskSet.
- TaskInfo(long, int, int, long, String, String, Enumeration.Value, boolean) - Constructor for class org.apache.spark.scheduler.TaskInfo
-
- taskInfo() - Method in class org.apache.spark.ui.jobs.UIData.TaskUIData
-
- taskInfoFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
-
- taskInfos() - Method in class org.apache.spark.scheduler.TaskSetManager
-
- taskInfoToJson(TaskInfo) - Static method in class org.apache.spark.util.JsonProtocol
-
- TaskKilled - Class in org.apache.spark
-
:: DeveloperApi ::
Task was killed intentionally and needs to be rescheduled.
- TaskKilled() - Constructor for class org.apache.spark.TaskKilled
-
- TaskKilledException - Exception in org.apache.spark
-
:: DeveloperApi ::
Exception thrown when a task is explicitly killed (i.e., task failure is expected).
- TaskKilledException() - Constructor for exception org.apache.spark.TaskKilledException
-
- taskLocality() - Method in class org.apache.spark.scheduler.TaskInfo
-
- TaskLocality - Class in org.apache.spark.scheduler
-
- TaskLocality() - Constructor for class org.apache.spark.scheduler.TaskLocality
-
- TaskLocation - Interface in org.apache.spark.scheduler
-
A location where a task should run.
- taskMetrics() - Method in class org.apache.spark.Heartbeat
-
- taskMetrics() - Method in class org.apache.spark.scheduler.CompletionEvent
-
- taskMetrics() - Method in class org.apache.spark.scheduler.SparkListenerExecutorMetricsUpdate
-
- taskMetrics() - Method in class org.apache.spark.scheduler.SparkListenerTaskEnd
-
- taskMetrics() - Method in class org.apache.spark.TaskContext
-
::DeveloperApi::
- taskMetrics() - Method in class org.apache.spark.TaskContextImpl
-
- taskMetrics() - Method in class org.apache.spark.ui.jobs.UIData.TaskUIData
-
- taskMetricsFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
-
- taskMetricsToJson(TaskMetrics) - Static method in class org.apache.spark.util.JsonProtocol
-
- TaskResult<T> - Interface in org.apache.spark.scheduler
-
- TASKRESULT() - Static method in class org.apache.spark.storage.BlockId
-
- TaskResultBlockId - Class in org.apache.spark.storage
-
- TaskResultBlockId(long) - Constructor for class org.apache.spark.storage.TaskResultBlockId
-
- TaskResultGetter - Class in org.apache.spark.scheduler
-
Runs a thread pool that deserializes and remotely fetches (if necessary) task results.
- TaskResultGetter(SparkEnv, TaskSchedulerImpl) - Constructor for class org.apache.spark.scheduler.TaskResultGetter
-
- taskResultGetter() - Method in class org.apache.spark.scheduler.TaskSchedulerImpl
-
- TaskResultLost - Class in org.apache.spark
-
:: DeveloperApi ::
The task finished successfully, but the result was lost from the executor's block manager before
it was fetched.
- TaskResultLost() - Constructor for class org.apache.spark.TaskResultLost
-
- taskRow(boolean, boolean, boolean, boolean, boolean, boolean, UIData.TaskUIData) - Method in class org.apache.spark.ui.jobs.StagePage
-
- tasks() - Method in class org.apache.spark.scheduler.TaskSet
-
- tasks() - Method in class org.apache.spark.scheduler.TaskSetManager
-
- taskScheduler() - Method in class org.apache.spark.scheduler.DAGScheduler
-
- TaskScheduler - Interface in org.apache.spark.scheduler
-
Low-level task scheduler interface, currently implemented exclusively by TaskSchedulerImpl.
- taskScheduler() - Method in class org.apache.spark.SparkContext
-
- TaskSchedulerImpl - Class in org.apache.spark.scheduler
-
Schedules tasks for multiple types of clusters by acting through a SchedulerBackend.
- TaskSchedulerImpl(SparkContext, int, boolean) - Constructor for class org.apache.spark.scheduler.TaskSchedulerImpl
-
- TaskSchedulerImpl(SparkContext) - Constructor for class org.apache.spark.scheduler.TaskSchedulerImpl
-
- TaskSet - Class in org.apache.spark.scheduler
-
A set of tasks submitted together to the low-level TaskScheduler, usually representing
missing partitions of a particular stage.
- TaskSet(Task<?>[], int, int, int, Properties) - Constructor for class org.apache.spark.scheduler.TaskSet
-
- taskSet() - Method in class org.apache.spark.scheduler.TaskSetFailed
-
- taskSet() - Method in class org.apache.spark.scheduler.TaskSetManager
-
- taskSetFailed(TaskSet, String) - Method in class org.apache.spark.scheduler.DAGScheduler
-
- TaskSetFailed - Class in org.apache.spark.scheduler
-
- TaskSetFailed(TaskSet, String) - Constructor for class org.apache.spark.scheduler.TaskSetFailed
-
- taskSetFinished(TaskSetManager) - Method in class org.apache.spark.scheduler.TaskSchedulerImpl
-
Called to indicate that all task attempts (including speculated tasks) associated with the
given TaskSetManager have completed, so state associated with the TaskSetManager should be
cleaned up.
- TaskSetManager - Class in org.apache.spark.scheduler
-
Schedules the tasks within a single TaskSet in the TaskSchedulerImpl.
- TaskSetManager(TaskSchedulerImpl, TaskSet, int, Clock) - Constructor for class org.apache.spark.scheduler.TaskSetManager
-
- taskSetSchedulingAlgorithm() - Method in class org.apache.spark.scheduler.Pool
-
- tasksSuccessful() - Method in class org.apache.spark.scheduler.TaskSetManager
-
- taskStarted(Task<?>, TaskInfo) - Method in class org.apache.spark.scheduler.DAGScheduler
-
- taskStartFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
-
- taskStartToJson(SparkListenerTaskStart) - Static method in class org.apache.spark.util.JsonProtocol
-
- TaskState - Class in org.apache.spark
-
- TaskState() - Constructor for class org.apache.spark.TaskState
-
- taskSucceeded(int, Object) - Method in class org.apache.spark.partial.ApproximateActionListener
-
- taskSucceeded(int, Object) - Method in interface org.apache.spark.scheduler.JobListener
-
- taskSucceeded(int, Object) - Method in class org.apache.spark.scheduler.JobWaiter
-
- taskTime() - Method in class org.apache.spark.ui.jobs.UIData.ExecutorSummary
-
- taskType() - Method in class org.apache.spark.scheduler.SparkListenerTaskEnd
-
- tellMaster() - Method in class org.apache.spark.storage.BlockInfo
-
- TempLocalBlockId - Class in org.apache.spark.storage
-
Id associated with temporary local data managed as blocks.
- TempLocalBlockId(UUID) - Constructor for class org.apache.spark.storage.TempLocalBlockId
-
- TempShuffleBlockId - Class in org.apache.spark.storage
-
Id associated with temporary shuffle data managed as blocks.
- TempShuffleBlockId(UUID) - Constructor for class org.apache.spark.storage.TempShuffleBlockId
-
- TerminalWidth() - Method in class org.apache.spark.ui.ConsoleProgressBar
-
- TEST() - Static method in class org.apache.spark.storage.BlockId
-
- TestBlockId - Class in org.apache.spark.storage
-
- TestBlockId(String) - Constructor for class org.apache.spark.storage.TestBlockId
-
- TestClock - Class in org.apache.spark
-
A clock that allows the caller to customize the time.
- TestClock(long) - Constructor for class org.apache.spark.TestClock
-
- testData() - Static method in class org.apache.spark.sql.parquet.ParquetTestData
-
- testDir() - Static method in class org.apache.spark.sql.parquet.ParquetTestData
-
- testFilterDir() - Static method in class org.apache.spark.sql.parquet.ParquetTestData
-
- testFilterSchema() - Static method in class org.apache.spark.sql.parquet.ParquetTestData
-
- TestGroupWriteSupport - Class in org.apache.spark.sql.parquet
-
- TestGroupWriteSupport(MessageType) - Constructor for class org.apache.spark.sql.parquet.TestGroupWriteSupport
-
- TestHive - Class in org.apache.spark.sql.hive.test
-
- TestHive() - Constructor for class org.apache.spark.sql.hive.test.TestHive
-
- TestHiveContext - Class in org.apache.spark.sql.hive.test
-
A locally running test instance of Spark's Hive execution engine.
- TestHiveContext(SparkContext) - Constructor for class org.apache.spark.sql.hive.test.TestHiveContext
-
- TestHiveContext.QueryExecution - Class in org.apache.spark.sql.hive.test
-
Override QueryExecution with special debug workflow.
- TestHiveContext.QueryExecution() - Constructor for class org.apache.spark.sql.hive.test.TestHiveContext.QueryExecution
-
- TestHiveContext.TestTable - Class in org.apache.spark.sql.hive.test
-
- TestHiveContext.TestTable(String, Seq<Function0<BoxedUnit>>) - Constructor for class org.apache.spark.sql.hive.test.TestHiveContext.TestTable
-
- testNestedData1() - Static method in class org.apache.spark.sql.parquet.ParquetTestData
-
- testNestedData2() - Static method in class org.apache.spark.sql.parquet.ParquetTestData
-
- testNestedDir1() - Static method in class org.apache.spark.sql.parquet.ParquetTestData
-
- testNestedDir2() - Static method in class org.apache.spark.sql.parquet.ParquetTestData
-
- testNestedDir3() - Static method in class org.apache.spark.sql.parquet.ParquetTestData
-
- testNestedDir4() - Static method in class org.apache.spark.sql.parquet.ParquetTestData
-
- testNestedSchema1() - Static method in class org.apache.spark.sql.parquet.ParquetTestData
-
- testNestedSchema2() - Static method in class org.apache.spark.sql.parquet.ParquetTestData
-
- testNestedSchema3() - Static method in class org.apache.spark.sql.parquet.ParquetTestData
-
- testNestedSchema4() - Static method in class org.apache.spark.sql.parquet.ParquetTestData
-
- TestResult<DF> - Interface in org.apache.spark.mllib.stat.test
-
:: Experimental ::
Trait for hypothesis test results.
- testSchema() - Static method in class org.apache.spark.sql.parquet.ParquetTestData
-
- testSchemaFieldNames() - Static method in class org.apache.spark.sql.parquet.ParquetTestData
-
- TestSQLContext - Class in org.apache.spark.sql.test
-
A SQLContext that can be used for local testing.
- TestSQLContext() - Constructor for class org.apache.spark.sql.test.TestSQLContext
-
- testTables() - Method in class org.apache.spark.sql.hive.test.TestHiveContext
-
A list of test tables and the DDL required to initialize them.
- testTempDir() - Method in class org.apache.spark.sql.hive.test.TestHiveContext
-
- TestUtils - Class in org.apache.spark
-
Utilities for tests.
- TestUtils() - Constructor for class org.apache.spark.TestUtils
-
- textFile(String) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Read a text file from HDFS, a local file system (available on all nodes), or any
Hadoop-supported file system URI, and return it as an RDD of Strings.
- textFile(String, int) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Read a text file from HDFS, a local file system (available on all nodes), or any
Hadoop-supported file system URI, and return it as an RDD of Strings.
- textFile(String, int) - Method in class org.apache.spark.SparkContext
-
Read a text file from HDFS, a local file system (available on all nodes), or any
Hadoop-supported file system URI, and return it as an RDD of Strings.
- textFileStream(String) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
Create an input stream that monitors a Hadoop-compatible filesystem
for new files and reads them as text files (using key as LongWritable, value
as Text and input format as TextInputFormat).
- textFileStream(String) - Method in class org.apache.spark.streaming.StreamingContext
-
Create a input stream that monitors a Hadoop-compatible filesystem
for new files and reads them as text files (using key as LongWritable, value
as Text and input format as TextInputFormat).
- textResponderToServlet(Function1<HttpServletRequest, String>) - Static method in class org.apache.spark.ui.JettyUtils
-
- theta() - Method in class org.apache.spark.mllib.classification.NaiveBayesModel
-
- thread() - Method in class org.apache.spark.streaming.scheduler.ReceiverTracker.ReceiverLauncher
-
- threadDumpEnabled() - Method in class org.apache.spark.ui.exec.ExecutorsTab
-
- threadId() - Method in class org.apache.spark.util.ThreadStackTrace
-
- threadName() - Method in class org.apache.spark.util.ThreadStackTrace
-
- ThreadStackTrace - Class in org.apache.spark.util
-
Used for shipping per-thread stacktraces from the executors to driver.
- ThreadStackTrace(long, String, Thread.State, String) - Constructor for class org.apache.spark.util.ThreadStackTrace
-
- threadState() - Method in class org.apache.spark.util.ThreadStackTrace
-
- threshold() - Method in interface org.apache.spark.ml.param.HasThreshold
-
param for threshold in (binary) prediction
- threshold() - Method in class org.apache.spark.mllib.tree.model.Split
-
- thresholds() - Method in class org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
-
Returns thresholds in descending order.
- threshTime() - Method in class org.apache.spark.streaming.receiver.CleanupOldBlocks
-
- throwBalls() - Method in class org.apache.spark.rdd.PartitionCoalescer
-
- tick(long) - Method in class org.apache.spark.TestClock
-
- time() - Method in class org.apache.spark.scheduler.SparkListenerApplicationEnd
-
- time() - Method in class org.apache.spark.scheduler.SparkListenerApplicationStart
-
- time() - Method in class org.apache.spark.scheduler.SparkListenerBlockManagerAdded
-
- time() - Method in class org.apache.spark.scheduler.SparkListenerBlockManagerRemoved
-
- time() - Method in class org.apache.spark.streaming.scheduler.BatchAllocationEvent
-
- time() - Method in class org.apache.spark.streaming.scheduler.ClearCheckpointData
-
- time() - Method in class org.apache.spark.streaming.scheduler.ClearMetadata
-
- time() - Method in class org.apache.spark.streaming.scheduler.DoCheckpoint
-
- time() - Method in class org.apache.spark.streaming.scheduler.GenerateJobs
-
- time() - Method in class org.apache.spark.streaming.scheduler.Job
-
- time() - Method in class org.apache.spark.streaming.scheduler.JobSet
-
- Time - Class in org.apache.spark.streaming
-
This is a simple class that represents an absolute instant of time.
- Time(long) - Constructor for class org.apache.spark.streaming.Time
-
- TimeBasedRollingPolicy - Class in org.apache.spark.util.logging
-
Defines a
RollingPolicy
by which files will be rolled
over at a fixed interval.
- TimeBasedRollingPolicy(long, String, boolean) - Constructor for class org.apache.spark.util.logging.TimeBasedRollingPolicy
-
- timeIt(int, Function0<BoxedUnit>, Option<Function0<BoxedUnit>>) - Static method in class org.apache.spark.util.Utils
-
Timing method based on iterations that permit JVM JIT optimization.
- timeout() - Method in class org.apache.spark.storage.BlockManagerMaster
-
- timeoutCheckingTask() - Method in class org.apache.spark.storage.BlockManagerMasterActor
-
- timeRunning(long) - Method in class org.apache.spark.scheduler.TaskInfo
-
- times(int) - Method in class org.apache.spark.streaming.Duration
-
- times() - Method in class org.apache.spark.streaming.scheduler.BatchCleanupEvent
-
- times(int, Function0<BoxedUnit>) - Static method in class org.apache.spark.util.Utils
-
Method executed for repeating a task for side effects.
- TIMESTAMP - Class in org.apache.spark.sql.columnar
-
- TIMESTAMP() - Constructor for class org.apache.spark.sql.columnar.TIMESTAMP
-
- timestamp() - Method in class org.apache.spark.util.TimeStampedValue
-
- TimestampColumnAccessor - Class in org.apache.spark.sql.columnar
-
- TimestampColumnAccessor(ByteBuffer) - Constructor for class org.apache.spark.sql.columnar.TimestampColumnAccessor
-
- TimestampColumnBuilder - Class in org.apache.spark.sql.columnar
-
- TimestampColumnBuilder() - Constructor for class org.apache.spark.sql.columnar.TimestampColumnBuilder
-
- TimestampColumnStats - Class in org.apache.spark.sql.columnar
-
- TimestampColumnStats() - Constructor for class org.apache.spark.sql.columnar.TimestampColumnStats
-
- TimeStampedHashMap<A,B> - Class in org.apache.spark.util
-
This is a custom implementation of scala.collection.mutable.Map which stores the insertion
timestamp along with each key-value pair.
- TimeStampedHashMap(boolean) - Constructor for class org.apache.spark.util.TimeStampedHashMap
-
- TimeStampedHashSet<A> - Class in org.apache.spark.util
-
- TimeStampedHashSet() - Constructor for class org.apache.spark.util.TimeStampedHashSet
-
- TimeStampedValue<V> - Class in org.apache.spark.util
-
- TimeStampedValue(V, long) - Constructor for class org.apache.spark.util.TimeStampedValue
-
- TimeStampedWeakValueHashMap<A,B> - Class in org.apache.spark.util
-
A wrapper of TimeStampedHashMap that ensures the values are weakly referenced and timestamped.
- TimeStampedWeakValueHashMap(boolean) - Constructor for class org.apache.spark.util.TimeStampedWeakValueHashMap
-
- TimestampType - Static variable in class org.apache.spark.sql.api.java.DataType
-
Gets the TimestampType object.
- TimestampType - Class in org.apache.spark.sql.api.java
-
The data type representing java.sql.Timestamp values.
- timeToLogFile(long, long) - Static method in class org.apache.spark.streaming.util.WriteAheadLogManager
-
- TimeTracker - Class in org.apache.spark.mllib.tree.impl
-
Time tracker implementation which holds labeled timers.
- TimeTracker() - Constructor for class org.apache.spark.mllib.tree.impl.TimeTracker
-
- timeUnit() - Method in class org.apache.spark.mllib.clustering.StreamingKMeans
-
- tmpPath() - Method in class org.apache.spark.scheduler.cluster.SimrSchedulerBackend
-
- to(Time, Duration) - Method in class org.apache.spark.streaming.Time
-
- toArray() - Method in interface org.apache.spark.api.java.JavaRDDLike
-
- toArray() - Method in class org.apache.spark.input.PortableDataStream
-
Read the file as a byte array
- toArray() - Method in class org.apache.spark.mllib.linalg.DenseMatrix
-
- toArray() - Method in class org.apache.spark.mllib.linalg.DenseVector
-
- toArray() - Method in interface org.apache.spark.mllib.linalg.Matrix
-
Converts to a dense array in column major.
- toArray() - Method in class org.apache.spark.mllib.linalg.SparseMatrix
-
- toArray() - Method in class org.apache.spark.mllib.linalg.SparseVector
-
- toArray() - Method in interface org.apache.spark.mllib.linalg.Vector
-
Converts the instance to a double array.
- toArray() - Method in class org.apache.spark.rdd.RDD
-
Return an array that contains all of the elements in this RDD.
- toArrays() - Method in class org.apache.spark.util.io.ByteArrayChunkOutputStream
-
- toAttribute() - Method in class org.apache.spark.sql.hive.MetastoreRelation.SchemaAttribute
-
- toBatchInfo() - Method in class org.apache.spark.streaming.scheduler.JobSet
-
- toBreeze() - Method in class org.apache.spark.mllib.linalg.DenseMatrix
-
- toBreeze() - Method in class org.apache.spark.mllib.linalg.DenseVector
-
- toBreeze() - Method in class org.apache.spark.mllib.linalg.distributed.CoordinateMatrix
-
Collects data and assembles a local matrix.
- toBreeze() - Method in interface org.apache.spark.mllib.linalg.distributed.DistributedMatrix
-
Collects data and assembles a local dense breeze matrix (for test only).
- toBreeze() - Method in class org.apache.spark.mllib.linalg.distributed.IndexedRowMatrix
-
- toBreeze() - Method in class org.apache.spark.mllib.linalg.distributed.RowMatrix
-
- toBreeze() - Method in interface org.apache.spark.mllib.linalg.Matrix
-
Converts to a breeze matrix.
- toBreeze() - Method in class org.apache.spark.mllib.linalg.SparseMatrix
-
- toBreeze() - Method in class org.apache.spark.mllib.linalg.SparseVector
-
- toBreeze() - Method in interface org.apache.spark.mllib.linalg.Vector
-
Converts the instance to a breeze vector.
- toCatalystDecimal(HiveDecimalObjectInspector, Object) - Static method in class org.apache.spark.sql.hive.HiveShim
-
- toDataType(String) - Static method in class org.apache.spark.sql.hive.HiveMetastoreTypes
-
- toDataType(Type, boolean) - Static method in class org.apache.spark.sql.parquet.ParquetTypesConverter
-
Converts a given Parquet Type
into the corresponding
DataType
.
- toDebugString() - Method in interface org.apache.spark.api.java.JavaRDDLike
-
A description of this RDD and its recursive dependencies for debugging.
- toDebugString() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel
-
Print the full model to a string.
- toDebugString() - Method in class org.apache.spark.mllib.tree.model.TreeEnsembleModel
-
Print the full model to a string.
- toDebugString() - Method in class org.apache.spark.rdd.RDD
-
A description of this RDD and its recursive dependencies for debugging.
- toDebugString() - Method in class org.apache.spark.SparkConf
-
Return a string listing all keys and values, one per line.
- toDense() - Method in class org.apache.spark.mllib.clustering.VectorWithNorm
-
Converts the vector to a dense vector.
- toEdgePartition() - Method in class org.apache.spark.graphx.impl.EdgePartitionBuilder
-
- toEdgePartition() - Method in class org.apache.spark.graphx.impl.ExistingEdgePartitionBuilder
-
- toEdgeTriplet() - Method in class org.apache.spark.graphx.EdgeContext
-
Converts the edge and vertex properties into an
EdgeTriplet
for convenience.
- toErrorString() - Method in class org.apache.spark.ExceptionFailure
-
- toErrorString() - Method in class org.apache.spark.ExecutorLostFailure
-
- toErrorString() - Method in class org.apache.spark.FetchFailed
-
- toErrorString() - Static method in class org.apache.spark.Resubmitted
-
- toErrorString() - Method in interface org.apache.spark.TaskFailedReason
-
Error message displayed in the web UI.
- toErrorString() - Static method in class org.apache.spark.TaskKilled
-
- toErrorString() - Static method in class org.apache.spark.TaskResultLost
-
- toErrorString() - Static method in class org.apache.spark.UnknownReason
-
- toFormattedString() - Method in class org.apache.spark.streaming.Duration
-
- toIndexedRowMatrix() - Method in class org.apache.spark.mllib.linalg.distributed.CoordinateMatrix
-
Converts to IndexedRowMatrix.
- toInspector(DataType) - Method in interface org.apache.spark.sql.hive.HiveInspectors
-
- toInspector(Expression) - Method in interface org.apache.spark.sql.hive.HiveInspectors
-
- toInt() - Method in class org.apache.spark.storage.StorageLevel
-
- toJava(Object, DataType) - Static method in class org.apache.spark.sql.execution.EvaluatePython
-
Helper for converting a Scala object to a java suitable for pyspark serialization.
- toJavaDStream() - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Convert to a JavaDStream
- toJavaRDD() - Method in class org.apache.spark.rdd.RDD
-
- toJavaSchemaRDD() - Method in class org.apache.spark.sql.SchemaRDD
-
Returns this RDD as a JavaSchemaRDD.
- toJSON() - Method in class org.apache.spark.sql.api.java.JavaSchemaRDD
-
Returns a new RDD with each row transformed to a JSON string.
- toJSON() - Method in class org.apache.spark.sql.SchemaRDD
-
Returns a new RDD with each row transformed to a JSON string.
- tokenize(String) - Static method in class org.apache.spark.rdd.PipedRDD
-
- Tokenizer - Class in org.apache.spark.ml.feature
-
:: AlphaComponent ::
A tokenizer that converts the input string to lowercase and then splits it by white spaces.
- Tokenizer() - Constructor for class org.apache.spark.ml.feature.Tokenizer
-
- toLocalIterator() - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return an iterator that contains all of the elements in this RDD.
- toLocalIterator() - Method in class org.apache.spark.rdd.RDD
-
Return an iterator that contains all of the elements in this RDD.
- toMap() - Method in class org.apache.spark.util.TimeStampedHashMap
-
- toMap() - Method in class org.apache.spark.util.TimeStampedWeakValueHashMap
-
- toMesos(Enumeration.Value) - Static method in class org.apache.spark.TaskState
-
- toMetastoreType(DataType) - Static method in class org.apache.spark.sql.hive.HiveMetastoreTypes
-
- toNodeSeq() - Method in class org.apache.spark.ui.jobs.ExecutorTable
-
- toNodeSeq() - Method in class org.apache.spark.ui.jobs.PoolTable
-
- toNodeSeq() - Method in class org.apache.spark.ui.jobs.StageTableBase
-
- ToolTips - Class in org.apache.spark.ui
-
- ToolTips() - Constructor for class org.apache.spark.ui.ToolTips
-
- toOps(ShippableVertexPartition<VD>, ClassTag<VD>) - Method in class org.apache.spark.graphx.impl.ShippableVertexPartition.ShippableVertexPartitionOpsConstructor$
-
- toOps(VertexPartition<VD>, ClassTag<VD>) - Method in class org.apache.spark.graphx.impl.VertexPartition.VertexPartitionOpsConstructor$
-
- toOps(T, ClassTag<VD>) - Method in interface org.apache.spark.graphx.impl.VertexPartitionBaseOpsConstructor
-
- top(int, Comparator<T>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Returns the top k (largest) elements from this RDD as defined by
the specified Comparator[T].
- top(int) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Returns the top k (largest) elements from this RDD using the
natural ordering for T.
- top(int, Ordering<T>) - Method in class org.apache.spark.rdd.RDD
-
- toPairDStreamFunctions(DStream<Tuple2<K, V>>, ClassTag<K>, ClassTag<V>, Ordering<K>) - Static method in class org.apache.spark.streaming.StreamingContext
-
- topK(Iterator<Tuple2<String, Object>>, int) - Static method in class org.apache.spark.streaming.util.RawTextHelper
-
Gets the top k words in terms of word counts.
- topNode() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel
-
- toPrimitiveDataType(PrimitiveType, boolean) - Static method in class org.apache.spark.sql.parquet.ParquetTypesConverter
-
- toRDD(JavaDoubleRDD) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- toRDD(JavaPairRDD<K, V>) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- toRDD(JavaRDD<T>) - Static method in class org.apache.spark.api.java.JavaRDD
-
- toRowMatrix() - Method in class org.apache.spark.mllib.linalg.distributed.CoordinateMatrix
-
Converts to RowMatrix, dropping row indices after grouping by row index.
- toRowMatrix() - Method in class org.apache.spark.mllib.linalg.distributed.IndexedRowMatrix
-
Drops row indices and converts this matrix to a
RowMatrix
.
- TorrentBroadcast<T> - Class in org.apache.spark.broadcast
-
A BitTorrent-like implementation of
Broadcast
.
- TorrentBroadcast(T, long, ClassTag<T>) - Constructor for class org.apache.spark.broadcast.TorrentBroadcast
-
- TorrentBroadcastFactory - Class in org.apache.spark.broadcast
-
A
Broadcast
implementation that uses a BitTorrent-like
protocol to do a distributed transfer of the broadcasted data to the executors.
- TorrentBroadcastFactory() - Constructor for class org.apache.spark.broadcast.TorrentBroadcastFactory
-
- toScalaFunction(Function<T, R>) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- toScalaFunction2(Function2<T1, T2, R>) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- toSchemaRDD() - Method in class org.apache.spark.sql.SchemaRDD
-
Returns this RDD as a SchemaRDD.
- toSeq() - Method in class org.apache.spark.ml.param.ParamMap
-
Converts this param map to a sequence of param pairs.
- toSparkContext(JavaSparkContext) - Static method in class org.apache.spark.api.java.JavaSparkContext
-
- toSplitInfo(Class<?>, String, InputSplit) - Static method in class org.apache.spark.scheduler.SplitInfo
-
- toSplitInfo(Class<?>, String, InputSplit) - Static method in class org.apache.spark.scheduler.SplitInfo
-
- toString() - Method in class org.apache.spark.Accumulable
-
- toString() - Method in class org.apache.spark.api.java.JavaRDD
-
- toString() - Method in class org.apache.spark.broadcast.Broadcast
-
- toString() - Method in class org.apache.spark.graphx.EdgeDirection
-
- toString() - Method in class org.apache.spark.graphx.EdgeTriplet
-
- toString() - Method in class org.apache.spark.ml.param.Param
-
- toString() - Method in class org.apache.spark.ml.param.ParamMap
-
- toString() - Method in class org.apache.spark.mllib.evaluation.binary.BinaryLabelCounter
-
- toString() - Method in class org.apache.spark.mllib.linalg.DenseVector
-
- toString() - Method in interface org.apache.spark.mllib.linalg.Matrix
-
A human readable representation of the matrix
- toString() - Method in class org.apache.spark.mllib.linalg.SparseVector
-
- toString() - Method in class org.apache.spark.mllib.regression.GeneralizedLinearModel
-
- toString() - Method in class org.apache.spark.mllib.regression.LabeledPoint
-
- toString() - Method in class org.apache.spark.mllib.stat.test.ChiSqTestResult
-
- toString() - Method in interface org.apache.spark.mllib.stat.test.TestResult
-
String explaining the hypothesis test result.
- toString() - Method in class org.apache.spark.mllib.tree.impl.TimeTracker
-
Print all timing results in seconds.
- toString() - Method in class org.apache.spark.mllib.tree.impurity.EntropyCalculator
-
- toString() - Method in class org.apache.spark.mllib.tree.impurity.GiniCalculator
-
- toString() - Method in class org.apache.spark.mllib.tree.impurity.VarianceCalculator
-
- toString() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel
-
Print a summary of the model.
- toString() - Method in class org.apache.spark.mllib.tree.model.InformationGainStats
-
- toString() - Method in class org.apache.spark.mllib.tree.model.Node
-
- toString() - Method in class org.apache.spark.mllib.tree.model.Predict
-
- toString() - Method in class org.apache.spark.mllib.tree.model.Split
-
- toString() - Method in class org.apache.spark.mllib.tree.model.TreeEnsembleModel
-
Print a summary of the model.
- toString() - Method in class org.apache.spark.partial.BoundedDouble
-
- toString() - Method in class org.apache.spark.partial.PartialResult
-
- toString() - Method in class org.apache.spark.rdd.RDD
-
- toString() - Method in class org.apache.spark.scheduler.ExecutorLossReason
-
- toString() - Method in class org.apache.spark.scheduler.HDFSCacheTaskLocation
-
- toString() - Method in class org.apache.spark.scheduler.HostTaskLocation
-
- toString() - Method in class org.apache.spark.scheduler.InputFormatInfo
-
- toString() - Method in class org.apache.spark.scheduler.ResultTask
-
- toString() - Method in class org.apache.spark.scheduler.ShuffleMapTask
-
- toString() - Method in class org.apache.spark.scheduler.SplitInfo
-
- toString() - Method in class org.apache.spark.scheduler.Stage
-
- toString() - Method in class org.apache.spark.scheduler.TaskDescription
-
- toString() - Method in class org.apache.spark.scheduler.TaskSet
-
- toString() - Method in class org.apache.spark.SerializableWritable
-
- toString() - Method in class org.apache.spark.sql.api.java.JavaSchemaRDD
-
- toString() - Method in class org.apache.spark.sql.api.java.Row
-
- toString() - Method in class org.apache.spark.sql.columnar.ColumnType
-
- toString() - Method in class org.apache.spark.sql.execution.PythonUDF
-
- toString() - Method in class org.apache.spark.sql.hive.HiveGenericUdaf
-
- toString() - Method in class org.apache.spark.sql.hive.HiveGenericUdf
-
- toString() - Method in class org.apache.spark.sql.hive.HiveGenericUdtf
-
- toString() - Method in class org.apache.spark.sql.hive.HiveSimpleUdf
-
- toString() - Method in class org.apache.spark.sql.hive.HiveUdaf
-
- toString() - Method in interface org.apache.spark.sql.SchemaRDDLike
-
- toString() - Method in class org.apache.spark.storage.BlockId
-
- toString() - Method in class org.apache.spark.storage.BlockManagerId
-
- toString() - Method in class org.apache.spark.storage.BlockManagerInfo
-
- toString() - Method in class org.apache.spark.storage.FileSegment
-
- toString() - Method in class org.apache.spark.storage.RDDInfo
-
- toString() - Method in class org.apache.spark.storage.StorageLevel
-
- toString() - Method in class org.apache.spark.storage.TachyonFileSegment
-
- toString() - Method in class org.apache.spark.streaming.dstream.DStreamCheckpointData
-
- toString() - Method in class org.apache.spark.streaming.dstream.FileInputDStream.FileInputDStreamCheckpointData
-
- toString() - Method in class org.apache.spark.streaming.Duration
-
- toString() - Method in class org.apache.spark.streaming.Interval
-
- toString() - Method in class org.apache.spark.streaming.scheduler.Job
-
- toString() - Method in class org.apache.spark.streaming.Time
-
- toString() - Method in class org.apache.spark.util.MutablePair
-
- toString() - Method in class org.apache.spark.util.StatCounter
-
- toString() - Method in class org.apache.spark.util.Vector
-
- totalCoreCount() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend
-
- totalCores() - Method in class org.apache.spark.scheduler.cluster.ExecutorData
-
- totalCores() - Method in class org.apache.spark.scheduler.local.LocalBackend
-
- totalCoresAcquired() - Method in class org.apache.spark.scheduler.cluster.mesos.CoarseMesosSchedulerBackend
-
- totalCount() - Method in class org.apache.spark.mllib.evaluation.binary.BinaryConfusionMatrixImpl
-
- totalDelay() - Method in class org.apache.spark.streaming.scheduler.BatchInfo
-
Time taken for all the jobs of this batch to finish processing from the time they
were submitted.
- totalDelay() - Method in class org.apache.spark.streaming.scheduler.JobSet
-
- totalDelayDistribution() - Method in class org.apache.spark.streaming.ui.StreamingJobProgressListener
-
- totalDuration() - Method in class org.apache.spark.ui.exec.ExecutorSummaryInfo
-
- totalExpectedCores() - Method in class org.apache.spark.scheduler.cluster.SparkDeploySchedulerBackend
-
- totalInputBytes() - Method in class org.apache.spark.ui.exec.ExecutorSummaryInfo
-
- totalNumNodes() - Method in class org.apache.spark.mllib.tree.model.TreeEnsembleModel
-
Get total number of nodes, summed over all trees in the forest.
- totalRegisteredExecutors() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend
-
- totalResultSize() - Method in class org.apache.spark.scheduler.TaskSetManager
-
- totalShuffleRead() - Method in class org.apache.spark.ui.exec.ExecutorSummaryInfo
-
- totalShuffleWrite() - Method in class org.apache.spark.ui.exec.ExecutorSummaryInfo
-
- totalTasks() - Method in class org.apache.spark.partial.ApproximateActionListener
-
- totalTasks() - Method in class org.apache.spark.ui.exec.ExecutorSummaryInfo
-
- toTuple() - Method in class org.apache.spark.graphx.EdgeTriplet
-
- toTypeInfo() - Method in class org.apache.spark.sql.hive.HiveInspectors.typeInfoConversions
-
- toWeakReference(V) - Static method in class org.apache.spark.util.TimeStampedWeakValueHashMap
-
- toWeakReferenceFunction(Function1<Tuple2<K, V>, R>) - Static method in class org.apache.spark.util.TimeStampedWeakValueHashMap
-
- toWeakReferenceTuple(Tuple2<K, V>) - Static method in class org.apache.spark.util.TimeStampedWeakValueHashMap
-
- trackerActor() - Method in class org.apache.spark.MapOutputTracker
-
Set to the MapOutputTrackerActor living on the driver.
- train(RDD<LabeledPoint>, int, double, double, Vector) - Static method in class org.apache.spark.mllib.classification.LogisticRegressionWithSGD
-
Train a logistic regression model given an RDD of (label, features) pairs.
- train(RDD<LabeledPoint>, int, double, double) - Static method in class org.apache.spark.mllib.classification.LogisticRegressionWithSGD
-
Train a logistic regression model given an RDD of (label, features) pairs.
- train(RDD<LabeledPoint>, int, double) - Static method in class org.apache.spark.mllib.classification.LogisticRegressionWithSGD
-
Train a logistic regression model given an RDD of (label, features) pairs.
- train(RDD<LabeledPoint>, int) - Static method in class org.apache.spark.mllib.classification.LogisticRegressionWithSGD
-
Train a logistic regression model given an RDD of (label, features) pairs.
- train(RDD<LabeledPoint>) - Static method in class org.apache.spark.mllib.classification.NaiveBayes
-
Trains a Naive Bayes model given an RDD of (label, features)
pairs.
- train(RDD<LabeledPoint>, double) - Static method in class org.apache.spark.mllib.classification.NaiveBayes
-
Trains a Naive Bayes model given an RDD of (label, features)
pairs.
- train(RDD<LabeledPoint>, int, double, double, double, Vector) - Static method in class org.apache.spark.mllib.classification.SVMWithSGD
-
Train a SVM model given an RDD of (label, features) pairs.
- train(RDD<LabeledPoint>, int, double, double, double) - Static method in class org.apache.spark.mllib.classification.SVMWithSGD
-
Train a SVM model given an RDD of (label, features) pairs.
- train(RDD<LabeledPoint>, int, double, double) - Static method in class org.apache.spark.mllib.classification.SVMWithSGD
-
Train a SVM model given an RDD of (label, features) pairs.
- train(RDD<LabeledPoint>, int) - Static method in class org.apache.spark.mllib.classification.SVMWithSGD
-
Train a SVM model given an RDD of (label, features) pairs.
- train(RDD<Vector>, int, int, int, String) - Static method in class org.apache.spark.mllib.clustering.KMeans
-
Trains a k-means model using the given set of parameters.
- train(RDD<Vector>, int, int) - Static method in class org.apache.spark.mllib.clustering.KMeans
-
Trains a k-means model using specified parameters and the default values for unspecified.
- train(RDD<Vector>, int, int, int) - Static method in class org.apache.spark.mllib.clustering.KMeans
-
Trains a k-means model using specified parameters and the default values for unspecified.
- train(RDD<Rating>, int, int, double, int, long) - Static method in class org.apache.spark.mllib.recommendation.ALS
-
Train a matrix factorization model given an RDD of ratings given by users to some products,
in the form of (userID, productID, rating) pairs.
- train(RDD<Rating>, int, int, double, int) - Static method in class org.apache.spark.mllib.recommendation.ALS
-
Train a matrix factorization model given an RDD of ratings given by users to some products,
in the form of (userID, productID, rating) pairs.
- train(RDD<Rating>, int, int, double) - Static method in class org.apache.spark.mllib.recommendation.ALS
-
Train a matrix factorization model given an RDD of ratings given by users to some products,
in the form of (userID, productID, rating) pairs.
- train(RDD<Rating>, int, int) - Static method in class org.apache.spark.mllib.recommendation.ALS
-
Train a matrix factorization model given an RDD of ratings given by users to some products,
in the form of (userID, productID, rating) pairs.
- train(RDD<LabeledPoint>, int, double, double, double, Vector) - Static method in class org.apache.spark.mllib.regression.LassoWithSGD
-
Train a Lasso model given an RDD of (label, features) pairs.
- train(RDD<LabeledPoint>, int, double, double, double) - Static method in class org.apache.spark.mllib.regression.LassoWithSGD
-
Train a Lasso model given an RDD of (label, features) pairs.
- train(RDD<LabeledPoint>, int, double, double) - Static method in class org.apache.spark.mllib.regression.LassoWithSGD
-
Train a Lasso model given an RDD of (label, features) pairs.
- train(RDD<LabeledPoint>, int) - Static method in class org.apache.spark.mllib.regression.LassoWithSGD
-
Train a Lasso model given an RDD of (label, features) pairs.
- train(RDD<LabeledPoint>, int, double, double, Vector) - Static method in class org.apache.spark.mllib.regression.LinearRegressionWithSGD
-
Train a Linear Regression model given an RDD of (label, features) pairs.
- train(RDD<LabeledPoint>, int, double, double) - Static method in class org.apache.spark.mllib.regression.LinearRegressionWithSGD
-
Train a LinearRegression model given an RDD of (label, features) pairs.
- train(RDD<LabeledPoint>, int, double) - Static method in class org.apache.spark.mllib.regression.LinearRegressionWithSGD
-
Train a LinearRegression model given an RDD of (label, features) pairs.
- train(RDD<LabeledPoint>, int) - Static method in class org.apache.spark.mllib.regression.LinearRegressionWithSGD
-
Train a LinearRegression model given an RDD of (label, features) pairs.
- train(RDD<LabeledPoint>, int, double, double, double, Vector) - Static method in class org.apache.spark.mllib.regression.RidgeRegressionWithSGD
-
Train a RidgeRegression model given an RDD of (label, features) pairs.
- train(RDD<LabeledPoint>, int, double, double, double) - Static method in class org.apache.spark.mllib.regression.RidgeRegressionWithSGD
-
Train a RidgeRegression model given an RDD of (label, features) pairs.
- train(RDD<LabeledPoint>, int, double, double) - Static method in class org.apache.spark.mllib.regression.RidgeRegressionWithSGD
-
Train a RidgeRegression model given an RDD of (label, features) pairs.
- train(RDD<LabeledPoint>, int) - Static method in class org.apache.spark.mllib.regression.RidgeRegressionWithSGD
-
Train a RidgeRegression model given an RDD of (label, features) pairs.
- train(RDD<LabeledPoint>) - Method in class org.apache.spark.mllib.tree.DecisionTree
-
Trains a decision tree model over an RDD.
- train(RDD<LabeledPoint>, BoostingStrategy) - Static method in class org.apache.spark.mllib.tree.GradientBoostedTrees
-
Method to train a gradient boosting model.
- train(JavaRDD<LabeledPoint>, BoostingStrategy) - Static method in class org.apache.spark.mllib.tree.GradientBoostedTrees
-
Java-friendly API for GradientBoostedTrees$.train(org.apache.spark.rdd.RDD<org.apache.spark.mllib.regression.LabeledPoint>, org.apache.spark.mllib.tree.configuration.BoostingStrategy)
- trainClassifier(RDD<LabeledPoint>, int, Map<Object, Object>, String, int, int) - Static method in class org.apache.spark.mllib.tree.DecisionTree
-
Method to train a decision tree model for binary or multiclass classification.
- trainClassifier(JavaRDD<LabeledPoint>, int, Map<Integer, Integer>, String, int, int) - Static method in class org.apache.spark.mllib.tree.DecisionTree
-
Java-friendly API for DecisionTree$.trainClassifier(org.apache.spark.rdd.RDD<org.apache.spark.mllib.regression.LabeledPoint>, int, scala.collection.immutable.Map<java.lang.Object, java.lang.Object>, java.lang.String, int, int)
- trainClassifier(RDD<LabeledPoint>, Strategy, int, String, int) - Static method in class org.apache.spark.mllib.tree.RandomForest
-
Method to train a decision tree model for binary or multiclass classification.
- trainClassifier(RDD<LabeledPoint>, int, Map<Object, Object>, int, String, String, int, int, int) - Static method in class org.apache.spark.mllib.tree.RandomForest
-
Method to train a decision tree model for binary or multiclass classification.
- trainClassifier(JavaRDD<LabeledPoint>, int, Map<Integer, Integer>, int, String, String, int, int, int) - Static method in class org.apache.spark.mllib.tree.RandomForest
-
Java-friendly API for RandomForest$.trainClassifier(org.apache.spark.rdd.RDD<org.apache.spark.mllib.regression.LabeledPoint>, org.apache.spark.mllib.tree.configuration.Strategy, int, java.lang.String, int)
- trainImplicit(RDD<Rating>, int, int, double, int, double, long) - Static method in class org.apache.spark.mllib.recommendation.ALS
-
Train a matrix factorization model given an RDD of 'implicit preferences' given by users
to some products, in the form of (userID, productID, preference) pairs.
- trainImplicit(RDD<Rating>, int, int, double, int, double) - Static method in class org.apache.spark.mllib.recommendation.ALS
-
Train a matrix factorization model given an RDD of 'implicit preferences' given by users
to some products, in the form of (userID, productID, preference) pairs.
- trainImplicit(RDD<Rating>, int, int, double, double) - Static method in class org.apache.spark.mllib.recommendation.ALS
-
Train a matrix factorization model given an RDD of 'implicit preferences' given by users to
some products, in the form of (userID, productID, preference) pairs.
- trainImplicit(RDD<Rating>, int, int) - Static method in class org.apache.spark.mllib.recommendation.ALS
-
Train a matrix factorization model given an RDD of 'implicit preferences' ratings given by
users to some products, in the form of (userID, productID, rating) pairs.
- trainOn(DStream<Vector>) - Method in class org.apache.spark.mllib.clustering.StreamingKMeans
-
Update the clustering model by training on batches of data from a DStream.
- trainOn(DStream<LabeledPoint>) - Method in class org.apache.spark.mllib.regression.StreamingLinearAlgorithm
-
Update the model by training on batches of data from a DStream.
- trainRegressor(RDD<LabeledPoint>, Map<Object, Object>, String, int, int) - Static method in class org.apache.spark.mllib.tree.DecisionTree
-
Method to train a decision tree model for regression.
- trainRegressor(JavaRDD<LabeledPoint>, Map<Integer, Integer>, String, int, int) - Static method in class org.apache.spark.mllib.tree.DecisionTree
-
Java-friendly API for DecisionTree$.trainRegressor(org.apache.spark.rdd.RDD<org.apache.spark.mllib.regression.LabeledPoint>, scala.collection.immutable.Map<java.lang.Object, java.lang.Object>, java.lang.String, int, int)
- trainRegressor(RDD<LabeledPoint>, Strategy, int, String, int) - Static method in class org.apache.spark.mllib.tree.RandomForest
-
Method to train a decision tree model for regression.
- trainRegressor(RDD<LabeledPoint>, Map<Object, Object>, int, String, String, int, int, int) - Static method in class org.apache.spark.mllib.tree.RandomForest
-
Method to train a decision tree model for regression.
- trainRegressor(JavaRDD<LabeledPoint>, Map<Integer, Integer>, int, String, String, int, int, int) - Static method in class org.apache.spark.mllib.tree.RandomForest
-
Java-friendly API for RandomForest$.trainRegressor(org.apache.spark.rdd.RDD<org.apache.spark.mllib.regression.LabeledPoint>, org.apache.spark.mllib.tree.configuration.Strategy, int, java.lang.String, int)
- transceiver() - Method in class org.apache.spark.streaming.flume.FlumeConnection
-
- transform(SchemaRDD, ParamMap) - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- transform(SchemaRDD, ParamMap) - Method in class org.apache.spark.ml.feature.StandardScalerModel
-
- transform(SchemaRDD, ParamMap) - Method in class org.apache.spark.ml.PipelineModel
-
- transform(SchemaRDD, ParamPair<?>...) - Method in class org.apache.spark.ml.Transformer
-
Transforms the dataset with optional parameters
- transform(JavaSchemaRDD, ParamPair<?>...) - Method in class org.apache.spark.ml.Transformer
-
Transforms the dataset with optional parameters.
- transform(SchemaRDD, Seq<ParamPair<?>>) - Method in class org.apache.spark.ml.Transformer
-
Transforms the dataset with optional parameters
- transform(SchemaRDD, ParamMap) - Method in class org.apache.spark.ml.Transformer
-
Transforms the dataset with provided parameter map as additional parameters.
- transform(JavaSchemaRDD, Seq<ParamPair<?>>) - Method in class org.apache.spark.ml.Transformer
-
Transforms the dataset with optional parameters.
- transform(JavaSchemaRDD, ParamMap) - Method in class org.apache.spark.ml.Transformer
-
Transforms the dataset with provided parameter map as additional parameters.
- transform(SchemaRDD, ParamMap) - Method in class org.apache.spark.ml.tuning.CrossValidatorModel
-
- transform(SchemaRDD, ParamMap) - Method in class org.apache.spark.ml.UnaryTransformer
-
- transform(Iterable<Object>) - Method in class org.apache.spark.mllib.feature.HashingTF
-
Transforms the input document into a sparse term frequency vector.
- transform(Iterable<?>) - Method in class org.apache.spark.mllib.feature.HashingTF
-
Transforms the input document into a sparse term frequency vector (Java version).
- transform(RDD<D>) - Method in class org.apache.spark.mllib.feature.HashingTF
-
Transforms the input document to term frequency vectors.
- transform(JavaRDD<D>) - Method in class org.apache.spark.mllib.feature.HashingTF
-
Transforms the input document to term frequency vectors (Java version).
- transform(RDD<Vector>) - Method in class org.apache.spark.mllib.feature.IDFModel
-
Transforms term frequency (TF) vectors to TF-IDF vectors.
- transform(JavaRDD<Vector>) - Method in class org.apache.spark.mllib.feature.IDFModel
-
Transforms term frequency (TF) vectors to TF-IDF vectors (Java version).
- transform(Vector) - Method in class org.apache.spark.mllib.feature.Normalizer
-
Applies unit length normalization on a vector.
- transform(Vector) - Method in class org.apache.spark.mllib.feature.StandardScalerModel
-
Applies standardization transformation on a vector.
- transform(Vector) - Method in interface org.apache.spark.mllib.feature.VectorTransformer
-
Applies transformation on a vector.
- transform(RDD<Vector>) - Method in interface org.apache.spark.mllib.feature.VectorTransformer
-
Applies transformation on an RDD[Vector].
- transform(JavaRDD<Vector>) - Method in interface org.apache.spark.mllib.feature.VectorTransformer
-
Applies transformation on an JavaRDD[Vector].
- transform(String) - Method in class org.apache.spark.mllib.feature.Word2VecModel
-
Transforms a word to its vector representation
- transform(PartialFunction<ASTNode, ASTNode>) - Method in class org.apache.spark.sql.hive.HiveQl.TransformableNode
-
Returns a copy of this node where rule
has been recursively applied to it and all of its
children.
- transform(Function<R, JavaRDD<U>>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Return a new DStream in which each RDD is generated by applying a function
on each RDD of 'this' DStream.
- transform(Function2<R, Time, JavaRDD<U>>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Return a new DStream in which each RDD is generated by applying a function
on each RDD of 'this' DStream.
- transform(List<JavaDStream<?>>, Function2<List<JavaRDD<?>>, Time, JavaRDD<T>>) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
Create a new DStream in which each RDD is generated by applying a function on RDDs of
the DStreams.
- transform(Function1<RDD<T>, RDD<U>>, ClassTag<U>) - Method in class org.apache.spark.streaming.dstream.DStream
-
Return a new DStream in which each RDD is generated by applying a function
on each RDD of 'this' DStream.
- transform(Function2<RDD<T>, Time, RDD<U>>, ClassTag<U>) - Method in class org.apache.spark.streaming.dstream.DStream
-
Return a new DStream in which each RDD is generated by applying a function
on each RDD of 'this' DStream.
- transform(Seq<DStream<?>>, Function2<Seq<RDD<?>>, Time, RDD<T>>, ClassTag<T>) - Method in class org.apache.spark.streaming.StreamingContext
-
Create a new DStream in which each RDD is generated by applying a function on RDDs of
the DStreams.
- TransformedDStream<U> - Class in org.apache.spark.streaming.dstream
-
- TransformedDStream(Seq<DStream<?>>, Function2<Seq<RDD<?>>, Time, RDD<U>>, ClassTag<U>) - Constructor for class org.apache.spark.streaming.dstream.TransformedDStream
-
- Transformer - Class in org.apache.spark.ml
-
:: AlphaComponent ::
Abstract class for transformers that transform one dataset into another.
- Transformer() - Constructor for class org.apache.spark.ml.Transformer
-
- transformSchema(StructType, ParamMap) - Method in class org.apache.spark.ml.classification.LogisticRegression
-
- transformSchema(StructType, ParamMap) - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- transformSchema(StructType, ParamMap) - Method in class org.apache.spark.ml.feature.StandardScaler
-
- transformSchema(StructType, ParamMap) - Method in class org.apache.spark.ml.feature.StandardScalerModel
-
- transformSchema(StructType, ParamMap) - Method in class org.apache.spark.ml.Pipeline
-
- transformSchema(StructType, ParamMap) - Method in class org.apache.spark.ml.PipelineModel
-
- transformSchema(StructType, ParamMap) - Method in class org.apache.spark.ml.PipelineStage
-
Derives the output schema from the input schema and parameters.
- transformSchema(StructType, ParamMap) - Method in class org.apache.spark.ml.tuning.CrossValidator
-
- transformSchema(StructType, ParamMap) - Method in class org.apache.spark.ml.tuning.CrossValidatorModel
-
- transformSchema(StructType, ParamMap) - Method in class org.apache.spark.ml.UnaryTransformer
-
- transformToPair(Function<R, JavaPairRDD<K2, V2>>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Return a new DStream in which each RDD is generated by applying a function
on each RDD of 'this' DStream.
- transformToPair(Function2<R, Time, JavaPairRDD<K2, V2>>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Return a new DStream in which each RDD is generated by applying a function
on each RDD of 'this' DStream.
- transformToPair(List<JavaDStream<?>>, Function2<List<JavaRDD<?>>, Time, JavaPairRDD<K, V>>) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
Create a new DStream in which each RDD is generated by applying a function on RDDs of
the DStreams.
- transformWith(JavaDStream<U>, Function3<R, JavaRDD<U>, Time, JavaRDD<W>>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Return a new DStream in which each RDD is generated by applying a function
on each RDD of 'this' DStream and 'other' DStream.
- transformWith(JavaPairDStream<K2, V2>, Function3<R, JavaPairRDD<K2, V2>, Time, JavaRDD<W>>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Return a new DStream in which each RDD is generated by applying a function
on each RDD of 'this' DStream and 'other' DStream.
- transformWith(DStream<U>, Function2<RDD<T>, RDD<U>, RDD<V>>, ClassTag<U>, ClassTag<V>) - Method in class org.apache.spark.streaming.dstream.DStream
-
Return a new DStream in which each RDD is generated by applying a function
on each RDD of 'this' DStream and 'other' DStream.
- transformWith(DStream<U>, Function3<RDD<T>, RDD<U>, Time, RDD<V>>, ClassTag<U>, ClassTag<V>) - Method in class org.apache.spark.streaming.dstream.DStream
-
Return a new DStream in which each RDD is generated by applying a function
on each RDD of 'this' DStream and 'other' DStream.
- transformWithToPair(JavaDStream<U>, Function3<R, JavaRDD<U>, Time, JavaPairRDD<K2, V2>>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Return a new DStream in which each RDD is generated by applying a function
on each RDD of 'this' DStream and 'other' DStream.
- transformWithToPair(JavaPairDStream<K2, V2>, Function3<R, JavaPairRDD<K2, V2>, Time, JavaPairRDD<K3, V3>>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Return a new DStream in which each RDD is generated by applying a function
on each RDD of 'this' DStream and 'other' DStream.
- transposeMultiply(DenseMatrix) - Method in interface org.apache.spark.mllib.linalg.Matrix
-
Convenience method for `Matrix`^T^-`DenseMatrix` multiplication.
- transposeMultiply(DenseVector) - Method in interface org.apache.spark.mllib.linalg.Matrix
-
Convenience method for `Matrix`^T^-`DenseVector` multiplication.
- treeAggregate(U, Function2<U, T, U>, Function2<U, U, U>, int, ClassTag<U>) - Method in class org.apache.spark.mllib.rdd.RDDFunctions
-
Aggregates the elements of this RDD in a multi-level tree pattern.
- TreeEnsembleModel - Class in org.apache.spark.mllib.tree.model
-
Represents a tree ensemble model.
- TreeEnsembleModel(Enumeration.Value, DecisionTreeModel[], double[], Enumeration.Value) - Constructor for class org.apache.spark.mllib.tree.model.TreeEnsembleModel
-
- TreePoint - Class in org.apache.spark.mllib.tree.impl
-
Internal representation of LabeledPoint for DecisionTree.
- TreePoint(double, int[]) - Constructor for class org.apache.spark.mllib.tree.impl.TreePoint
-
- treeReduce(Function2<T, T, T>, int) - Method in class org.apache.spark.mllib.rdd.RDDFunctions
-
Reduces the elements of this RDD in a multi-level tree pattern.
- trees() - Method in class org.apache.spark.mllib.tree.model.GradientBoostedTreesModel
-
- trees() - Method in class org.apache.spark.mllib.tree.model.RandomForestModel
-
- treeStrategy() - Method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
-
- treeWeights() - Method in class org.apache.spark.mllib.tree.model.GradientBoostedTreesModel
-
- triangleCount() - Method in class org.apache.spark.graphx.GraphOps
-
Compute the number of triangles passing through each vertex.
- TriangleCount - Class in org.apache.spark.graphx.lib
-
Compute the number of triangles passing through each vertex.
- TriangleCount() - Constructor for class org.apache.spark.graphx.lib.TriangleCount
-
- TripletFields - Class in org.apache.spark.graphx
-
Represents a subset of the fields of an [[EdgeTriplet]] or [[EdgeContext]].
- TripletFields() - Constructor for class org.apache.spark.graphx.TripletFields
-
Constructs a default TripletFields in which all fields are included.
- TripletFields(boolean, boolean, boolean) - Constructor for class org.apache.spark.graphx.TripletFields
-
- tripletIterator(boolean, boolean) - Method in class org.apache.spark.graphx.impl.EdgePartition
-
Get an iterator over the edge triplets in this partition.
- triplets() - Method in class org.apache.spark.graphx.Graph
-
An RDD containing the edge triplets, which are edges along with the vertex data associated with
the adjacent vertices.
- triplets() - Method in class org.apache.spark.graphx.impl.GraphImpl
-
Return a RDD that brings edges together with their source and destination vertices.
- TRUE() - Static method in class org.apache.spark.sql.hive.HiveQl
-
- truePositiveRate(double) - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
-
Returns true positive rate for a given label (category)
- tryLog(Function0<T>) - Static method in class org.apache.spark.util.Utils
-
Executes the given block in a Try, logging any uncaught exceptions.
- tryOrExit(Function0<BoxedUnit>) - Static method in class org.apache.spark.util.Utils
-
Execute a block of code that evaluates to Unit, forwarding any uncaught exceptions to the
default UncaughtExceptionHandler
- tryOrIOException(Function0<BoxedUnit>) - Static method in class org.apache.spark.util.Utils
-
Execute a block of code that evaluates to Unit, re-throwing any non-fatal uncaught
exceptions as IOException.
- tryOrIOException(Function0<T>) - Static method in class org.apache.spark.util.Utils
-
Execute a block of code that returns a value, re-throwing any non-fatal uncaught
exceptions as IOException.
- tryUncacheQuery(SchemaRDD, boolean) - Method in interface org.apache.spark.sql.CacheManager
-
Tries to remove the data for the given SchemaRDD from the cache if it's cached
- TwitterInputDStream - Class in org.apache.spark.streaming.twitter
-
- TwitterInputDStream(StreamingContext, Option<Authorization>, Seq<String>, StorageLevel) - Constructor for class org.apache.spark.streaming.twitter.TwitterInputDStream
-
- TwitterReceiver - Class in org.apache.spark.streaming.twitter
-
- TwitterReceiver(Authorization, Seq<String>, StorageLevel) - Constructor for class org.apache.spark.streaming.twitter.TwitterReceiver
-
- TwitterUtils - Class in org.apache.spark.streaming.twitter
-
- TwitterUtils() - Constructor for class org.apache.spark.streaming.twitter.TwitterUtils
-
- typ() - Method in class org.apache.spark.streaming.scheduler.RegisterReceiver
-
- typeId() - Method in class org.apache.spark.sql.columnar.ColumnType
-
- typeId() - Static method in class org.apache.spark.sql.columnar.compression.BooleanBitSet
-
- typeId() - Method in interface org.apache.spark.sql.columnar.compression.CompressionScheme
-
- typeId() - Static method in class org.apache.spark.sql.columnar.compression.DictionaryEncoding
-
- typeId() - Static method in class org.apache.spark.sql.columnar.compression.IntDelta
-
- typeId() - Static method in class org.apache.spark.sql.columnar.compression.LongDelta
-
- typeId() - Static method in class org.apache.spark.sql.columnar.compression.PassThrough
-
- typeId() - Static method in class org.apache.spark.sql.columnar.compression.RunLengthEncoding
-
- U() - Method in class org.apache.spark.mllib.linalg.SingularValueDecomposition
-
- udf() - Method in class org.apache.spark.sql.execution.BatchPythonEvaluation
-
- udf() - Method in class org.apache.spark.sql.execution.EvaluatePython
-
- UDF1<T1,R> - Interface in org.apache.spark.sql.api.java
-
A Spark SQL UDF that has 1 arguments.
- UDF10<T1,T2,T3,T4,T5,T6,T7,T8,T9,T10,R> - Interface in org.apache.spark.sql.api.java
-
A Spark SQL UDF that has 10 arguments.
- UDF11<T1,T2,T3,T4,T5,T6,T7,T8,T9,T10,T11,R> - Interface in org.apache.spark.sql.api.java
-
A Spark SQL UDF that has 11 arguments.
- UDF12<T1,T2,T3,T4,T5,T6,T7,T8,T9,T10,T11,T12,R> - Interface in org.apache.spark.sql.api.java
-
A Spark SQL UDF that has 12 arguments.
- UDF13<T1,T2,T3,T4,T5,T6,T7,T8,T9,T10,T11,T12,T13,R> - Interface in org.apache.spark.sql.api.java
-
A Spark SQL UDF that has 13 arguments.
- UDF14<T1,T2,T3,T4,T5,T6,T7,T8,T9,T10,T11,T12,T13,T14,R> - Interface in org.apache.spark.sql.api.java
-
A Spark SQL UDF that has 14 arguments.
- UDF15<T1,T2,T3,T4,T5,T6,T7,T8,T9,T10,T11,T12,T13,T14,T15,R> - Interface in org.apache.spark.sql.api.java
-
A Spark SQL UDF that has 15 arguments.
- UDF16<T1,T2,T3,T4,T5,T6,T7,T8,T9,T10,T11,T12,T13,T14,T15,T16,R> - Interface in org.apache.spark.sql.api.java
-
A Spark SQL UDF that has 16 arguments.
- UDF17<T1,T2,T3,T4,T5,T6,T7,T8,T9,T10,T11,T12,T13,T14,T15,T16,T17,R> - Interface in org.apache.spark.sql.api.java
-
A Spark SQL UDF that has 17 arguments.
- UDF18<T1,T2,T3,T4,T5,T6,T7,T8,T9,T10,T11,T12,T13,T14,T15,T16,T17,T18,R> - Interface in org.apache.spark.sql.api.java
-
A Spark SQL UDF that has 18 arguments.
- UDF19<T1,T2,T3,T4,T5,T6,T7,T8,T9,T10,T11,T12,T13,T14,T15,T16,T17,T18,T19,R> - Interface in org.apache.spark.sql.api.java
-
A Spark SQL UDF that has 19 arguments.
- UDF2<T1,T2,R> - Interface in org.apache.spark.sql.api.java
-
A Spark SQL UDF that has 2 arguments.
- UDF20<T1,T2,T3,T4,T5,T6,T7,T8,T9,T10,T11,T12,T13,T14,T15,T16,T17,T18,T19,T20,R> - Interface in org.apache.spark.sql.api.java
-
A Spark SQL UDF that has 20 arguments.
- UDF21<T1,T2,T3,T4,T5,T6,T7,T8,T9,T10,T11,T12,T13,T14,T15,T16,T17,T18,T19,T20,T21,R> - Interface in org.apache.spark.sql.api.java
-
A Spark SQL UDF that has 21 arguments.
- UDF22<T1,T2,T3,T4,T5,T6,T7,T8,T9,T10,T11,T12,T13,T14,T15,T16,T17,T18,T19,T20,T21,T22,R> - Interface in org.apache.spark.sql.api.java
-
A Spark SQL UDF that has 22 arguments.
- UDF3<T1,T2,T3,R> - Interface in org.apache.spark.sql.api.java
-
A Spark SQL UDF that has 3 arguments.
- UDF4<T1,T2,T3,T4,R> - Interface in org.apache.spark.sql.api.java
-
A Spark SQL UDF that has 4 arguments.
- UDF5<T1,T2,T3,T4,T5,R> - Interface in org.apache.spark.sql.api.java
-
A Spark SQL UDF that has 5 arguments.
- UDF6<T1,T2,T3,T4,T5,T6,R> - Interface in org.apache.spark.sql.api.java
-
A Spark SQL UDF that has 6 arguments.
- UDF7<T1,T2,T3,T4,T5,T6,T7,R> - Interface in org.apache.spark.sql.api.java
-
A Spark SQL UDF that has 7 arguments.
- UDF8<T1,T2,T3,T4,T5,T6,T7,T8,R> - Interface in org.apache.spark.sql.api.java
-
A Spark SQL UDF that has 8 arguments.
- UDF9<T1,T2,T3,T4,T5,T6,T7,T8,T9,R> - Interface in org.apache.spark.sql.api.java
-
A Spark SQL UDF that has 9 arguments.
- UDFRegistration - Interface in org.apache.spark.sql.api.java
-
A collection of functions that allow Java users to register UDFs.
- UDFRegistration - Interface in org.apache.spark.sql
-
Functions for registering scala lambda functions as UDFs in a SQLContext.
- UDTWrappers - Class in org.apache.spark.sql.api.java
-
- UDTWrappers() - Constructor for class org.apache.spark.sql.api.java.UDTWrappers
-
- ui() - Method in class org.apache.spark.SparkContext
-
- uid() - Method in interface org.apache.spark.ml.Identifiable
-
A unique id for the object.
- UIData - Class in org.apache.spark.ui.jobs
-
- UIData() - Constructor for class org.apache.spark.ui.jobs.UIData
-
- UIData.ExecutorSummary - Class in org.apache.spark.ui.jobs
-
- UIData.ExecutorSummary() - Constructor for class org.apache.spark.ui.jobs.UIData.ExecutorSummary
-
- UIData.JobUIData - Class in org.apache.spark.ui.jobs
-
- UIData.JobUIData(int, Option<Object>, Option<Object>, Seq<Object>, Option<String>, JobExecutionStatus, int, int, int, int, int, int, OpenHashSet<Object>, int, int) - Constructor for class org.apache.spark.ui.jobs.UIData.JobUIData
-
- UIData.JobUIData$ - Class in org.apache.spark.ui.jobs
-
- UIData.JobUIData$() - Constructor for class org.apache.spark.ui.jobs.UIData.JobUIData$
-
- UIData.StageUIData - Class in org.apache.spark.ui.jobs
-
- UIData.StageUIData() - Constructor for class org.apache.spark.ui.jobs.UIData.StageUIData
-
- UIData.TaskUIData - Class in org.apache.spark.ui.jobs
-
These are kept mutable and reused throughout a task's lifetime to avoid excessive reallocation.
- UIData.TaskUIData(TaskInfo, Option<TaskMetrics>, Option<String>) - Constructor for class org.apache.spark.ui.jobs.UIData.TaskUIData
-
- UIData.TaskUIData$ - Class in org.apache.spark.ui.jobs
-
- UIData.TaskUIData$() - Constructor for class org.apache.spark.ui.jobs.UIData.TaskUIData$
-
- uiRoot() - Static method in class org.apache.spark.ui.UIUtils
-
- uiTab() - Method in class org.apache.spark.streaming.StreamingContext
-
- UIUtils - Class in org.apache.spark.ui
-
Utility functions for generating XML pages with spark content.
- UIUtils() - Constructor for class org.apache.spark.ui.UIUtils
-
- UIWorkloadGenerator - Class in org.apache.spark.ui
-
Continuously generates jobs that expose various features of the WebUI (internal testing tool).
- UIWorkloadGenerator() - Constructor for class org.apache.spark.ui.UIWorkloadGenerator
-
- unapply(Object) - Method in class org.apache.spark.sql.hive.HiveQl.Token$
-
- unapply(String) - Static method in class org.apache.spark.util.IntParam
-
- unapply(String) - Static method in class org.apache.spark.util.MemoryParam
-
- UnaryNode - Interface in org.apache.spark.sql.execution
-
- UnaryTransformer<IN,OUT,T extends UnaryTransformer<IN,OUT,T>> - Class in org.apache.spark.ml
-
Abstract class for transformers that take one input column, apply transformation, and output the
result as a new column.
- UnaryTransformer() - Constructor for class org.apache.spark.ml.UnaryTransformer
-
- unBlockifyObject(ByteBuffer[], Serializer, Option<CompressionCodec>, ClassTag<T>) - Static method in class org.apache.spark.broadcast.TorrentBroadcast
-
- unbound() - Method in class org.apache.spark.sql.execution.Aggregate.ComputedAggregate
-
- unbroadcast(long, boolean, boolean) - Method in interface org.apache.spark.broadcast.BroadcastFactory
-
- unbroadcast(long, boolean, boolean) - Method in class org.apache.spark.broadcast.BroadcastManager
-
- unbroadcast(long, boolean, boolean) - Method in class org.apache.spark.broadcast.HttpBroadcastFactory
-
Remove all persisted state associated with the HTTP broadcast with the given ID.
- unbroadcast(long, boolean, boolean) - Method in class org.apache.spark.broadcast.TorrentBroadcastFactory
-
Remove all persisted state associated with the torrent broadcast with the given ID.
- uncacheQuery(SchemaRDD, boolean) - Method in interface org.apache.spark.sql.CacheManager
-
Removes the data for the given SchemaRDD from the cache
- uncacheTable(String) - Method in interface org.apache.spark.sql.CacheManager
-
Removes the specified table from the in-memory cache.
- UncacheTableCommand - Class in org.apache.spark.sql.execution
-
:: DeveloperApi ::
- UncacheTableCommand(String) - Constructor for class org.apache.spark.sql.execution.UncacheTableCommand
-
- UNCAUGHT_EXCEPTION() - Static method in class org.apache.spark.util.SparkExitCode
-
The default uncaught exception handler was reached.
- UNCAUGHT_EXCEPTION_TWICE() - Static method in class org.apache.spark.util.SparkExitCode
-
The default uncaught exception handler was called and an exception was encountered while
logging the exception.
- uncaughtException(Thread, Throwable) - Static method in class org.apache.spark.util.SparkUncaughtExceptionHandler
-
- uncaughtException(Throwable) - Static method in class org.apache.spark.util.SparkUncaughtExceptionHandler
-
- uncompressedSize() - Method in class org.apache.spark.sql.columnar.compression.BooleanBitSet.Encoder
-
- uncompressedSize() - Method in class org.apache.spark.sql.columnar.compression.DictionaryEncoding.Encoder
-
- uncompressedSize() - Method in interface org.apache.spark.sql.columnar.compression.Encoder
-
- uncompressedSize() - Method in class org.apache.spark.sql.columnar.compression.IntDelta.Encoder
-
- uncompressedSize() - Method in class org.apache.spark.sql.columnar.compression.LongDelta.Encoder
-
- uncompressedSize() - Method in class org.apache.spark.sql.columnar.compression.PassThrough.Encoder
-
- uncompressedSize() - Method in class org.apache.spark.sql.columnar.compression.RunLengthEncoding.Encoder
-
- underlyingBuffer() - Method in interface org.apache.spark.sql.columnar.ColumnAccessor
-
- underlyingSplit() - Method in class org.apache.spark.scheduler.SplitInfo
-
- UniformGenerator - Class in org.apache.spark.mllib.random
-
:: DeveloperApi ::
Generates i.i.d.
- UniformGenerator() - Constructor for class org.apache.spark.mllib.random.UniformGenerator
-
- uniformJavaRDD(JavaSparkContext, long, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- uniformJavaRDD(JavaSparkContext, long, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- uniformJavaRDD(JavaSparkContext, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- uniformJavaVectorRDD(JavaSparkContext, long, int, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- uniformJavaVectorRDD(JavaSparkContext, long, int, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- uniformJavaVectorRDD(JavaSparkContext, long, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- uniformRDD(SparkContext, long, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
Generates an RDD comprised of i.i.d.
- uniformVectorRDD(SparkContext, long, int, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
Generates an RDD[Vector] with vectors containing i.i.d.
- union(JavaDoubleRDD) - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Return the union of this RDD and another one.
- union(JavaPairRDD<K, V>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Return the union of this RDD and another one.
- union(JavaRDD<T>) - Method in class org.apache.spark.api.java.JavaRDD
-
Return the union of this RDD and another one.
- union(JavaRDD<T>, List<JavaRDD<T>>) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Build the union of two or more RDDs.
- union(JavaPairRDD<K, V>, List<JavaPairRDD<K, V>>) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Build the union of two or more RDDs.
- union(JavaDoubleRDD, List<JavaDoubleRDD>) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Build the union of two or more RDDs.
- union(RDD<T>) - Method in class org.apache.spark.rdd.RDD
-
Return the union of this RDD and another one.
- union(Seq<RDD<T>>, ClassTag<T>) - Method in class org.apache.spark.SparkContext
-
Build the union of a list of RDDs.
- union(RDD<T>, Seq<RDD<T>>, ClassTag<T>) - Method in class org.apache.spark.SparkContext
-
Build the union of a list of RDDs passed as variable-length arguments.
- Union - Class in org.apache.spark.sql.execution
-
:: DeveloperApi ::
- Union(Seq<SparkPlan>) - Constructor for class org.apache.spark.sql.execution.Union
-
- union(JavaDStream<T>) - Method in class org.apache.spark.streaming.api.java.JavaDStream
-
Return a new DStream by unifying data of another DStream with this DStream.
- union(JavaPairDStream<K, V>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by unifying data of another DStream with this DStream.
- union(JavaDStream<T>, List<JavaDStream<T>>) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
Create a unified DStream from multiple DStreams of the same type and same slide duration.
- union(JavaPairDStream<K, V>, List<JavaPairDStream<K, V>>) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
Create a unified DStream from multiple DStreams of the same type and same slide duration.
- union(DStream<T>) - Method in class org.apache.spark.streaming.dstream.DStream
-
Return a new DStream by unifying data of another DStream with this DStream.
- union(Seq<DStream<T>>, ClassTag<T>) - Method in class org.apache.spark.streaming.StreamingContext
-
Create a unified DStream from multiple DStreams of the same type and same slide duration.
- unionAll(SchemaRDD) - Method in class org.apache.spark.sql.SchemaRDD
-
Combines the tuples of two RDDs with the same schema, keeping duplicates.
- UnionDStream<T> - Class in org.apache.spark.streaming.dstream
-
- UnionDStream(DStream<T>[], ClassTag<T>) - Constructor for class org.apache.spark.streaming.dstream.UnionDStream
-
- UnionPartition<T> - Class in org.apache.spark.rdd
-
Partition for UnionRDD.
- UnionPartition(int, RDD<T>, int, int, ClassTag<T>) - Constructor for class org.apache.spark.rdd.UnionPartition
-
- UnionRDD<T> - Class in org.apache.spark.rdd
-
- UnionRDD(SparkContext, Seq<RDD<T>>, ClassTag<T>) - Constructor for class org.apache.spark.rdd.UnionRDD
-
- uniqueId() - Method in class org.apache.spark.storage.StreamBlockId
-
- UniqueKeyHashedRelation - Class in org.apache.spark.sql.execution.joins
-
- UniqueKeyHashedRelation(HashMap<Row, Row>) - Constructor for class org.apache.spark.sql.execution.joins.UniqueKeyHashedRelation
-
- UnknownReason - Class in org.apache.spark
-
:: DeveloperApi ::
We don't know why the task ended -- for example, because of a ClassNotFound exception when
deserializing the task result.
- UnknownReason() - Constructor for class org.apache.spark.UnknownReason
-
- unorderedFeatures() - Method in class org.apache.spark.mllib.tree.impl.DecisionTreeMetadata
-
- unpersist() - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Mark the RDD as non-persistent, and remove all blocks for it from memory and disk.
- unpersist(boolean) - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Mark the RDD as non-persistent, and remove all blocks for it from memory and disk.
- unpersist() - Method in class org.apache.spark.api.java.JavaPairRDD
-
Mark the RDD as non-persistent, and remove all blocks for it from memory and disk.
- unpersist(boolean) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Mark the RDD as non-persistent, and remove all blocks for it from memory and disk.
- unpersist() - Method in class org.apache.spark.api.java.JavaRDD
-
Mark the RDD as non-persistent, and remove all blocks for it from memory and disk.
- unpersist(boolean) - Method in class org.apache.spark.api.java.JavaRDD
-
Mark the RDD as non-persistent, and remove all blocks for it from memory and disk.
- unpersist() - Method in class org.apache.spark.broadcast.Broadcast
-
Asynchronously delete cached copies of this broadcast on the executors.
- unpersist(boolean) - Method in class org.apache.spark.broadcast.Broadcast
-
Delete cached copies of this broadcast on the executors.
- unpersist(long, boolean, boolean) - Static method in class org.apache.spark.broadcast.HttpBroadcast
-
Remove all persisted blocks associated with this HTTP broadcast on the executors.
- unpersist(long, boolean, boolean) - Static method in class org.apache.spark.broadcast.TorrentBroadcast
-
Remove all persisted blocks associated with this torrent broadcast on the executors.
- unpersist(boolean) - Method in class org.apache.spark.graphx.Graph
-
Uncaches both vertices and edges of this graph.
- unpersist(boolean) - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- unpersist(boolean) - Method in class org.apache.spark.graphx.impl.GraphImpl
-
- unpersist(boolean) - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- unpersist() - Method in class org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
-
Unpersist intermediate RDDs used in the computation.
- unpersist(boolean) - Method in class org.apache.spark.rdd.RDD
-
Mark the RDD as non-persistent, and remove all blocks for it from memory and disk.
- unpersist(boolean) - Method in class org.apache.spark.sql.api.java.JavaSchemaRDD
-
Mark the RDD as non-persistent, and remove all blocks for it from memory and disk.
- unpersist(boolean) - Method in class org.apache.spark.sql.SchemaRDD
-
- unpersistRDD(int, boolean) - Method in class org.apache.spark.SparkContext
-
Unpersist an RDD from memory and/or disk storage
- unpersistRDDFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
-
- unpersistRDDToJson(SparkListenerUnpersistRDD) - Static method in class org.apache.spark.util.JsonProtocol
-
- unpersistVertices(boolean) - Method in class org.apache.spark.graphx.Graph
-
Uncaches only the vertices of this graph, leaving the edges alone.
- unpersistVertices(boolean) - Method in class org.apache.spark.graphx.impl.GraphImpl
-
- unregisterAllTables() - Method in class org.apache.spark.sql.hive.HiveMetastoreCatalog
-
- unregisterMapOutput(int, int, BlockManagerId) - Method in class org.apache.spark.MapOutputTrackerMaster
-
Unregister map output information of the given shuffle, mapper and block manager
- unregisterShuffle(int) - Method in class org.apache.spark.MapOutputTracker
-
Unregister shuffle data.
- unregisterShuffle(int) - Method in class org.apache.spark.MapOutputTrackerMaster
-
Unregister shuffle data
- unregisterTable(Seq<String>) - Method in class org.apache.spark.sql.hive.HiveMetastoreCatalog
-
UNIMPLEMENTED: It needs to be decided how we will persist in-memory tables to the metastore.
- unrollSafely(BlockId, Iterator<Object>, ArrayBuffer<Tuple2<BlockId, BlockStatus>>) - Method in class org.apache.spark.storage.MemoryStore
-
Unroll the given block in memory safely.
- unset() - Static method in class org.apache.spark.TaskContextHelper
-
- until(Time, Duration) - Method in class org.apache.spark.streaming.Time
-
- unwrap(Object, ObjectInspector) - Method in interface org.apache.spark.sql.hive.HiveInspectors
-
Converts hive types to native catalyst types.
- update(RDD<Vector>, double, String) - Method in class org.apache.spark.mllib.clustering.StreamingKMeansModel
-
Perform a k-means update on a batch of data.
- update(int, int, double) - Method in class org.apache.spark.mllib.linalg.DenseMatrix
-
- update(int, int, double) - Method in interface org.apache.spark.mllib.linalg.Matrix
-
Update element at (i, j)
- update(int, int, double) - Method in class org.apache.spark.mllib.linalg.SparseMatrix
-
- update(int, int, double, double) - Method in class org.apache.spark.mllib.tree.impl.DTStatsAggregator
-
Update the stats for a given (feature, bin) for ordered features, using the given label.
- update(double[], int, double, double) - Method in class org.apache.spark.mllib.tree.impurity.EntropyAggregator
-
Update stats for one (node, feature, bin) with the given label.
- update(double[], int, double, double) - Method in class org.apache.spark.mllib.tree.impurity.GiniAggregator
-
Update stats for one (node, feature, bin) with the given label.
- update(double[], int, double, double) - Method in class org.apache.spark.mllib.tree.impurity.ImpurityAggregator
-
Update stats for one (node, feature, bin) with the given label.
- update(double[], int, double, double) - Method in class org.apache.spark.mllib.tree.impurity.VarianceAggregator
-
Update stats for one (node, feature, bin) with the given label.
- update() - Method in class org.apache.spark.scheduler.AccumulableInfo
-
- update() - Method in class org.apache.spark.sql.execution.AggregateEvaluation
-
- update(Row) - Method in class org.apache.spark.sql.hive.HiveUdafFunction
-
- update(Time) - Method in class org.apache.spark.streaming.dstream.DStreamCheckpointData
-
Updates the checkpoint data of the DStream.
- update(Time) - Method in class org.apache.spark.streaming.dstream.FileInputDStream.FileInputDStreamCheckpointData
-
- update(T1, T2) - Method in class org.apache.spark.util.MutablePair
-
Updates this pair with new values and returns itself
- update(A, B) - Method in class org.apache.spark.util.TimeStampedHashMap
-
- update(A, B) - Method in class org.apache.spark.util.TimeStampedWeakValueHashMap
-
- UPDATE_PERIOD() - Method in class org.apache.spark.ui.ConsoleProgressBar
-
- updateAggregateMetrics(UIData.StageUIData, String, TaskMetrics, Option<TaskMetrics>) - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
Upon receiving new metrics for a task, updates the per-stage and per-executor-per-stage
aggregate metrics by calculating deltas between the currently recorded metrics and the new
metrics.
- updateBlock(BlockId, BlockStatus) - Method in class org.apache.spark.storage.StorageStatus
-
Update the given block in this storage status.
- updateBlockInfo(BlockId, StorageLevel, long, long, long) - Method in class org.apache.spark.storage.BlockManagerInfo
-
- updateBlockInfo(BlockManagerId, BlockId, StorageLevel, long, long, long) - Method in class org.apache.spark.storage.BlockManagerMaster
-
- updateCheckpointData(Time) - Method in class org.apache.spark.streaming.dstream.DStream
-
Refresh the list of checkpointed RDDs that will be saved along with checkpoint of
this stream.
- updateCheckpointData(Time) - Method in class org.apache.spark.streaming.DStreamGraph
-
- updatedConf(SparkConf, String, String, String, Seq<String>, Map<String, String>) - Static method in class org.apache.spark.SparkContext
-
Creates a modified version of a SparkConf with the parameters that can be passed separately
to SparkContext, to make it easier to write SparkContext's constructors.
- updateEpoch(long) - Method in class org.apache.spark.MapOutputTracker
-
Called from executors to update the epoch number, potentially clearing old outputs
because of a fetch failure.
- updateLastSeenMs() - Method in class org.apache.spark.storage.BlockManagerInfo
-
- updateNodeIndex(int[], Bin[][]) - Method in class org.apache.spark.mllib.tree.impl.NodeIndexUpdater
-
Determine a child node index based on the feature value and the split.
- updateNodeIndices(RDD<BaggedPoint<TreePoint>>, Map<Object, NodeIndexUpdater>[], Bin[][]) - Method in class org.apache.spark.mllib.tree.impl.NodeIdCache
-
Update the node index values in the cache.
- Updater - Class in org.apache.spark.mllib.optimization
-
:: DeveloperApi ::
Class used to perform steps (weight update) using Gradient Descent methods.
- Updater() - Constructor for class org.apache.spark.mllib.optimization.Updater
-
- updateRddInfo(Seq<RDDInfo>, Seq<StorageStatus>) - Static method in class org.apache.spark.storage.StorageUtils
-
Update the given list of RDDInfo with the given list of storage statuses.
- updateStateByKey(Function2<List<V>, Optional<S>, Optional<S>>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new "state" DStream where the state for each key is updated by applying
the given function on the previous state of the key and the new values of each key.
- updateStateByKey(Function2<List<V>, Optional<S>, Optional<S>>, int) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new "state" DStream where the state for each key is updated by applying
the given function on the previous state of the key and the new values of each key.
- updateStateByKey(Function2<List<V>, Optional<S>, Optional<S>>, Partitioner) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new "state" DStream where the state for each key is updated by applying
the given function on the previous state of the key and the new values of the key.
- updateStateByKey(Function2<Seq<V>, Option<S>, Option<S>>, ClassTag<S>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new "state" DStream where the state for each key is updated by applying
the given function on the previous state of the key and the new values of each key.
- updateStateByKey(Function2<Seq<V>, Option<S>, Option<S>>, int, ClassTag<S>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new "state" DStream where the state for each key is updated by applying
the given function on the previous state of the key and the new values of each key.
- updateStateByKey(Function2<Seq<V>, Option<S>, Option<S>>, Partitioner, ClassTag<S>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new "state" DStream where the state for each key is updated by applying
the given function on the previous state of the key and the new values of the key.
- updateStateByKey(Function1<Iterator<Tuple3<K, Seq<V>, Option<S>>>, Iterator<Tuple2<K, S>>>, Partitioner, boolean, ClassTag<S>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new "state" DStream where the state for each key is updated by applying
the given function on the previous state of the key and the new values of each key.
- updateVertices(Iterator<Tuple2<Object, VD>>) - Method in class org.apache.spark.graphx.impl.EdgePartition
-
Return a new `EdgePartition` with updates to vertex attributes specified in `iter`.
- updateVertices(VertexRDD<VD>) - Method in class org.apache.spark.graphx.impl.ReplicatedVertexView
-
Return a new ReplicatedVertexView
where vertex attributes in edge partition are updated using
updates
.
- upgrade(VertexRDD<VD>, boolean, boolean) - Method in class org.apache.spark.graphx.impl.ReplicatedVertexView
-
Upgrade the shipping level in-place to the specified levels by shipping vertex attributes from
vertices
.
- upper() - Method in class org.apache.spark.rdd.JdbcPartition
-
- UPPER() - Static method in class org.apache.spark.sql.hive.HiveQl
-
- upperBound() - Method in class org.apache.spark.sql.columnar.ColumnStatisticsSchema
-
- uri() - Method in class org.apache.spark.HttpServer
-
Get the URI of this HTTP server (http://host:port)
- useCachedData(LogicalPlan) - Method in interface org.apache.spark.sql.CacheManager
-
Replaces segments of the given logical plan with cached versions where possible.
- useCompression() - Method in class org.apache.spark.sql.columnar.InMemoryRelation
-
- useCompression() - Method in interface org.apache.spark.sql.SQLConf
-
When true tables cached using the in-memory columnar caching will be compressed.
- useDisk() - Method in class org.apache.spark.storage.StorageLevel
-
- useDst - Variable in class org.apache.spark.graphx.TripletFields
-
Indicates whether the destination vertex attribute is included.
- useEdge - Variable in class org.apache.spark.graphx.TripletFields
-
Indicates whether the edge attribute is included.
- useMemory() - Method in class org.apache.spark.storage.StorageLevel
-
- useNodeIdCache() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- useOffHeap() - Method in class org.apache.spark.storage.StorageLevel
-
- user() - Method in class org.apache.spark.mllib.recommendation.Rating
-
- user() - Method in class org.apache.spark.scheduler.JobLogger
-
- userClass() - Method in class org.apache.spark.mllib.linalg.VectorUDT
-
- userClass() - Method in class org.apache.spark.sql.api.java.JavaToScalaUDTWrapper
-
- userClass() - Method in class org.apache.spark.sql.api.java.ScalaToJavaUDTWrapper
-
- userClass() - Method in class org.apache.spark.sql.api.java.UserDefinedType
-
Class object for the UserType
- userClass() - Method in class org.apache.spark.sql.test.ExamplePointUDT
-
- UserDefinedType<UserType> - Class in org.apache.spark.sql.api.java
-
::DeveloperApi::
The data type representing User-Defined Types (UDTs).
- userFeatures() - Method in class org.apache.spark.mllib.recommendation.MatrixFactorizationModel
-
- useSrc - Variable in class org.apache.spark.graphx.TripletFields
-
Indicates whether the source vertex attribute is included.
- Utils - Class in org.apache.spark.util
-
Various utility methods used by Spark.
- Utils() - Constructor for class org.apache.spark.util.Utils
-
- UUIDFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
-
- UUIDToJson(UUID) - Static method in class org.apache.spark.util.JsonProtocol
-