org.apache.spark.rdd

Class JdbcRDD<T>

Object

org.apache.spark.rdd.RDD<T>

org.apache.spark.rdd.JdbcRDD<T>

All Implemented Interfaces:

java.io.Serializable, Logging

public class JdbcRDD<T>
extends RDD<T>
implements Logging

An RDD that executes a SQL query on a JDBC connection and reads results. For usage example, see test case JdbcRDDSuite.

param: getConnection a function that returns an open Connection. The RDD takes care of closing the connection. param: sql the text of the query. The query must contain two ? placeholders for parameters used to partition the results. For example,

   select title, author from books where ? <= id and id <= ?
   

param: lowerBound the minimum value of the first placeholder param: upperBound the maximum value of the second placeholder The lower and upper bounds are inclusive. param: numPartitions the number of partitions. Given a lowerBound of 1, an upperBound of 20, and a numPartitions of 2, the query would be executed twice, once with (1, 10) and once with (11, 20) param: mapRow a function from a ResultSet to a single row of the desired result type(s). This should only call getInt, getString, etc; the RDD takes care of calling next. The default maps a ResultSet to an array of Object.

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static interface	JdbcRDD.ConnectionFactory

Constructor Summary

Constructors

Constructor and Description
JdbcRDD(SparkContext sc, scala.Function0<java.sql.Connection> getConnection, String sql, long lowerBound, long upperBound, int numPartitions, scala.Function1<java.sql.ResultSet,T> mapRow, scala.reflect.ClassTag<T> evidence$1)

Method Summary

Modifier and Type	Method and Description
static RDD<T>	$plus$plus(RDD<T> other)
static <U> U	aggregate(U zeroValue, scala.Function2<U,T,U> seqOp, scala.Function2<U,U,U> combOp, scala.reflect.ClassTag<U> evidence$30)
static RDD<T>	cache()
static <U> RDD<scala.Tuple2<T,U>>	cartesian(RDD<U> other, scala.reflect.ClassTag<U> evidence$5)
static void	checkpoint()
static RDD<T>	coalesce(int numPartitions, boolean shuffle, scala.Option<PartitionCoalescer> partitionCoalescer, scala.math.Ordering<T> ord)
static boolean	coalesce$default$2()
static scala.Option<PartitionCoalescer>	coalesce$default$3()
static scala.math.Ordering<T>	coalesce$default$4(int numPartitions, boolean shuffle, scala.Option<PartitionCoalescer> partitionCoalescer)
static Object	collect()
static <U> RDD<U>	collect(scala.PartialFunction<T,U> f, scala.reflect.ClassTag<U> evidence$29)
scala.collection.Iterator<T>	compute(Partition thePart, TaskContext context) :: DeveloperApi :: Implemented by subclasses to compute a given partition.
static SparkContext	context()
static long	count()
static PartialResult<BoundedDouble>	countApprox(long timeout, double confidence)
static double	countApprox$default$2()
static long	countApproxDistinct(double relativeSD)
static long	countApproxDistinct(int p, int sp)
static double	countApproxDistinct$default$1()
static scala.collection.Map<T,Object>	countByValue(scala.math.Ordering<T> ord)
static scala.math.Ordering<T>	countByValue$default$1()
static PartialResult<scala.collection.Map<T,BoundedDouble>>	countByValueApprox(long timeout, double confidence, scala.math.Ordering<T> ord)
static double	countByValueApprox$default$2()
static scala.math.Ordering<T>	countByValueApprox$default$3(long timeout, double confidence)
static JavaRDD<Object[]>	create(JavaSparkContext sc, JdbcRDD.ConnectionFactory connectionFactory, String sql, long lowerBound, long upperBound, int numPartitions) Create an RDD that executes a SQL query on a JDBC connection and reads results.
static <T> JavaRDD<T>	create(JavaSparkContext sc, JdbcRDD.ConnectionFactory connectionFactory, String sql, long lowerBound, long upperBound, int numPartitions, Function<java.sql.ResultSet,T> mapRow) Create an RDD that executes a SQL query on a JDBC connection and reads results.
static scala.collection.Seq<Dependency<?>>	dependencies()
static RDD<T>	distinct()
static RDD<T>	distinct(int numPartitions, scala.math.Ordering<T> ord)
static scala.math.Ordering<T>	distinct$default$2(int numPartitions)
static RDD<T>	filter(scala.Function1<T,Object> f)
static T	first()
static <U> RDD<U>	flatMap(scala.Function1<T,scala.collection.TraversableOnce<U>> f, scala.reflect.ClassTag<U> evidence$4)
static T	fold(T zeroValue, scala.Function2<T,T,T> op)
static void	foreach(scala.Function1<T,scala.runtime.BoxedUnit> f)
static void	foreachPartition(scala.Function1<scala.collection.Iterator<T>,scala.runtime.BoxedUnit> f)
static scala.Option<String>	getCheckpointFile()
static int	getNumPartitions()
Partition[]	getPartitions() Implemented by subclasses to return the set of partitions in this RDD.
static StorageLevel	getStorageLevel()
static RDD<Object>	glom()
static <K> RDD<scala.Tuple2<K,scala.collection.Iterable<T>>>	groupBy(scala.Function1<T,K> f, scala.reflect.ClassTag<K> kt)
static <K> RDD<scala.Tuple2<K,scala.collection.Iterable<T>>>	groupBy(scala.Function1<T,K> f, int numPartitions, scala.reflect.ClassTag<K> kt)
static <K> RDD<scala.Tuple2<K,scala.collection.Iterable<T>>>	groupBy(scala.Function1<T,K> f, Partitioner p, scala.reflect.ClassTag<K> kt, scala.math.Ordering<K> ord)
static <K> scala.runtime.Null$	groupBy$default$4(scala.Function1<T,K> f, Partitioner p)
static int	id()
static RDD<T>	intersection(RDD<T> other)
static RDD<T>	intersection(RDD<T> other, int numPartitions)
static RDD<T>	intersection(RDD<T> other, Partitioner partitioner, scala.math.Ordering<T> ord)
static scala.math.Ordering<T>	intersection$default$3(RDD<T> other, Partitioner partitioner)
static boolean	isCheckpointed()
static boolean	isEmpty()
static scala.collection.Iterator<T>	iterator(Partition split, TaskContext context)
static <K> RDD<scala.Tuple2<K,T>>	keyBy(scala.Function1<T,K> f)
static RDD<T>	localCheckpoint()
static <U> RDD<U>	map(scala.Function1<T,U> f, scala.reflect.ClassTag<U> evidence$3)
static <U> RDD<U>	mapPartitions(scala.Function1<scala.collection.Iterator<T>,scala.collection.Iterator<U>> f, boolean preservesPartitioning, scala.reflect.ClassTag<U> evidence$6)
static <U> boolean	mapPartitions$default$2()
static <U> boolean	mapPartitionsInternal$default$2()
static <U> RDD<U>	mapPartitionsWithIndex(scala.Function2<Object,scala.collection.Iterator<T>,scala.collection.Iterator<U>> f, boolean preservesPartitioning, scala.reflect.ClassTag<U> evidence$9)
static <U> boolean	mapPartitionsWithIndex$default$2()
static <U> boolean	mapPartitionsWithIndexInternal$default$2()
static <U> boolean	mapPartitionsWithIndexInternal$default$3()
static T	max(scala.math.Ordering<T> ord)
static T	min(scala.math.Ordering<T> ord)
static void	name_$eq(String x$1)
static String	name()
static scala.Option<Partitioner>	partitioner()
static Partition[]	partitions()
static RDD<T>	persist()
static RDD<T>	persist(StorageLevel newLevel)
static RDD<String>	pipe(scala.collection.Seq<String> command, scala.collection.Map<String,String> env, scala.Function1<scala.Function1<String,scala.runtime.BoxedUnit>,scala.runtime.BoxedUnit> printPipeContext, scala.Function2<T,scala.Function1<String,scala.runtime.BoxedUnit>,scala.runtime.BoxedUnit> printRDDElement, boolean separateWorkingDir, int bufferSize, String encoding)
static RDD<String>	pipe(String command)
static RDD<String>	pipe(String command, scala.collection.Map<String,String> env)
static scala.collection.Map<String,String>	pipe$default$2()
static scala.Function1<scala.Function1<String,scala.runtime.BoxedUnit>,scala.runtime.BoxedUnit>	pipe$default$3()
static scala.Function2<T,scala.Function1<String,scala.runtime.BoxedUnit>,scala.runtime.BoxedUnit>	pipe$default$4()
static boolean	pipe$default$5()
static int	pipe$default$6()
static String	pipe$default$7()
static scala.collection.Seq<String>	preferredLocations(Partition split)
static RDD<T>[]	randomSplit(double[] weights, long seed)
static long	randomSplit$default$2()
static T	reduce(scala.Function2<T,T,T> f)
static RDD<T>	repartition(int numPartitions, scala.math.Ordering<T> ord)
static scala.math.Ordering<T>	repartition$default$2(int numPartitions)
static Object[]	resultSetToObjectArray(java.sql.ResultSet rs)
static RDD<T>	sample(boolean withReplacement, double fraction, long seed)
static long	sample$default$3()
static void	saveAsObjectFile(String path)
static void	saveAsTextFile(String path)
static void	saveAsTextFile(String path, Class<? extends org.apache.hadoop.io.compress.CompressionCodec> codec)
static RDD<T>	setName(String _name)
static <K> RDD<T>	sortBy(scala.Function1<T,K> f, boolean ascending, int numPartitions, scala.math.Ordering<K> ord, scala.reflect.ClassTag<K> ctag)
static <K> boolean	sortBy$default$2()
static <K> int	sortBy$default$3()
static SparkContext	sparkContext()
static RDD<T>	subtract(RDD<T> other)
static RDD<T>	subtract(RDD<T> other, int numPartitions)
static RDD<T>	subtract(RDD<T> other, Partitioner p, scala.math.Ordering<T> ord)
static scala.math.Ordering<T>	subtract$default$3(RDD<T> other, Partitioner p)
static Object	take(int num)
static Object	takeOrdered(int num, scala.math.Ordering<T> ord)
static Object	takeSample(boolean withReplacement, int num, long seed)
static long	takeSample$default$3()
static String	toDebugString()
static JavaRDD<T>	toJavaRDD()
static scala.collection.Iterator<T>	toLocalIterator()
static Object	top(int num, scala.math.Ordering<T> ord)
static String	toString()
static <U> U	treeAggregate(U zeroValue, scala.Function2<U,T,U> seqOp, scala.Function2<U,U,U> combOp, int depth, scala.reflect.ClassTag<U> evidence$31)
static <U> int	treeAggregate$default$4(U zeroValue)
static T	treeReduce(scala.Function2<T,T,T> f, int depth)
static int	treeReduce$default$2()
static RDD<T>	union(RDD<T> other)
static RDD<T>	unpersist(boolean blocking)
static boolean	unpersist$default$1()
static <U> RDD<scala.Tuple2<T,U>>	zip(RDD<U> other, scala.reflect.ClassTag<U> evidence$10)
static <B,V> RDD<V>	zipPartitions(RDD<B> rdd2, boolean preservesPartitioning, scala.Function2<scala.collection.Iterator<T>,scala.collection.Iterator<B>,scala.collection.Iterator<V>> f, scala.reflect.ClassTag<B> evidence$11, scala.reflect.ClassTag<V> evidence$12)
static <B,V> RDD<V>	zipPartitions(RDD<B> rdd2, scala.Function2<scala.collection.Iterator<T>,scala.collection.Iterator<B>,scala.collection.Iterator<V>> f, scala.reflect.ClassTag<B> evidence$13, scala.reflect.ClassTag<V> evidence$14)
static <B,C,V> RDD<V>	zipPartitions(RDD<B> rdd2, RDD<C> rdd3, boolean preservesPartitioning, scala.Function3<scala.collection.Iterator<T>,scala.collection.Iterator<B>,scala.collection.Iterator<C>,scala.collection.Iterator<V>> f, scala.reflect.ClassTag<B> evidence$15, scala.reflect.ClassTag<C> evidence$16, scala.reflect.ClassTag<V> evidence$17)
static <B,C,V> RDD<V>	zipPartitions(RDD<B> rdd2, RDD<C> rdd3, scala.Function3<scala.collection.Iterator<T>,scala.collection.Iterator<B>,scala.collection.Iterator<C>,scala.collection.Iterator<V>> f, scala.reflect.ClassTag<B> evidence$18, scala.reflect.ClassTag<C> evidence$19, scala.reflect.ClassTag<V> evidence$20)
static <B,C,D,V> RDD<V>	zipPartitions(RDD<B> rdd2, RDD<C> rdd3, RDD<D> rdd4, boolean preservesPartitioning, scala.Function4<scala.collection.Iterator<T>,scala.collection.Iterator<B>,scala.collection.Iterator<C>,scala.collection.Iterator<D>,scala.collection.Iterator<V>> f, scala.reflect.ClassTag<B> evidence$21, scala.reflect.ClassTag<C> evidence$22, scala.reflect.ClassTag<D> evidence$23, scala.reflect.ClassTag<V> evidence$24)
static <B,C,D,V> RDD<V>	zipPartitions(RDD<B> rdd2, RDD<C> rdd3, RDD<D> rdd4, scala.Function4<scala.collection.Iterator<T>,scala.collection.Iterator<B>,scala.collection.Iterator<C>,scala.collection.Iterator<D>,scala.collection.Iterator<V>> f, scala.reflect.ClassTag<B> evidence$25, scala.reflect.ClassTag<C> evidence$26, scala.reflect.ClassTag<D> evidence$27, scala.reflect.ClassTag<V> evidence$28)
static RDD<scala.Tuple2<T,Object>>	zipWithIndex()
static RDD<scala.Tuple2<T,Object>>	zipWithUniqueId()

Methods inherited from class org.apache.spark.rdd.RDD

aggregate, cache, cartesian, checkpoint, coalesce, collect, collect, context, count, countApprox, countApproxDistinct, countApproxDistinct, countByValue, countByValueApprox, dependencies, distinct, distinct, doubleRDDToDoubleRDDFunctions, filter, first, flatMap, fold, foreach, foreachPartition, getCheckpointFile, getNumPartitions, getStorageLevel, glom, groupBy, groupBy, groupBy, id, intersection, intersection, intersection, isCheckpointed, isEmpty, iterator, keyBy, localCheckpoint, map, mapPartitions, mapPartitionsWithIndex, max, min, name, numericRDDToDoubleRDDFunctions, partitioner, partitions, persist, persist, pipe, pipe, pipe, preferredLocations, randomSplit, rddToAsyncRDDActions, rddToOrderedRDDFunctions, rddToPairRDDFunctions, rddToSequenceFileRDDFunctions, reduce, repartition, sample, saveAsObjectFile, saveAsTextFile, saveAsTextFile, setName, sortBy, sparkContext, subtract, subtract, subtract, take, takeOrdered, takeSample, toDebugString, toJavaRDD, toLocalIterator, top, toString, treeAggregate, treeReduce, union, unpersist, zip, zipPartitions, zipPartitions, zipPartitions, zipPartitions, zipPartitions, zipPartitions, zipWithIndex, zipWithUniqueId

Methods inherited from class Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface org.apache.spark.internal.Logging

initializeLogging, initializeLogIfNecessary, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning

Constructor Detail

JdbcRDD

public JdbcRDD(SparkContext sc,
               scala.Function0<java.sql.Connection> getConnection,
               String sql,
               long lowerBound,
               long upperBound,
               int numPartitions,
               scala.Function1<java.sql.ResultSet,T> mapRow,
               scala.reflect.ClassTag<T> evidence$1)

Method Detail

resultSetToObjectArray

public static Object[] resultSetToObjectArray(java.sql.ResultSet rs)

create

public static <T> JavaRDD<T> create(JavaSparkContext sc,
                                    JdbcRDD.ConnectionFactory connectionFactory,
                                    String sql,
                                    long lowerBound,
                                    long upperBound,
                                    int numPartitions,
                                    Function<java.sql.ResultSet,T> mapRow)

Create an RDD that executes a SQL query on a JDBC connection and reads results. For usage example, see test case JavaAPISuite.testJavaJdbcRDD.

Parameters:

connectionFactory - a factory that returns an open Connection. The RDD takes care of closing the connection.

sql - the text of the query. The query must contain two ? placeholders for parameters used to partition the results. For example,

   select title, author from books where ? <= id and id <= ?
   

lowerBound - the minimum value of the first placeholder

upperBound - the maximum value of the second placeholder The lower and upper bounds are inclusive.

numPartitions - the number of partitions. Given a lowerBound of 1, an upperBound of 20, and a numPartitions of 2, the query would be executed twice, once with (1, 10) and once with (11, 20)

mapRow - a function from a ResultSet to a single row of the desired result type(s). This should only call getInt, getString, etc; the RDD takes care of calling next. The default maps a ResultSet to an array of Object.

sc - (undocumented)

Returns:

(undocumented)

create

public static JavaRDD<Object[]> create(JavaSparkContext sc,
                                       JdbcRDD.ConnectionFactory connectionFactory,
                                       String sql,
                                       long lowerBound,
                                       long upperBound,
                                       int numPartitions)

Create an RDD that executes a SQL query on a JDBC connection and reads results. Each row is converted into a Object array. For usage example, see test case JavaAPISuite.testJavaJdbcRDD.

Parameters:

connectionFactory - a factory that returns an open Connection. The RDD takes care of closing the connection.

sql - the text of the query. The query must contain two ? placeholders for parameters used to partition the results. For example,

   select title, author from books where ? <= id and id <= ?
   

lowerBound - the minimum value of the first placeholder

upperBound - the maximum value of the second placeholder The lower and upper bounds are inclusive.

numPartitions - the number of partitions. Given a lowerBound of 1, an upperBound of 20, and a numPartitions of 2, the query would be executed twice, once with (1, 10) and once with (11, 20)

sc - (undocumented)

Returns:

(undocumented)

partitioner

public static scala.Option<Partitioner> partitioner()

sparkContext

public static SparkContext sparkContext()

id

public static int id()

name

public static String name()

name_$eq

public static void name_$eq(String x$1)

setName

public static RDD<T> setName(String _name)

persist

public static RDD<T> persist(StorageLevel newLevel)

persist

public static RDD<T> persist()

cache

public static RDD<T> cache()

unpersist

public static RDD<T> unpersist(boolean blocking)

getStorageLevel

public static StorageLevel getStorageLevel()

dependencies

public static final scala.collection.Seq<Dependency<?>> dependencies()

partitions

public static final Partition[] partitions()

getNumPartitions

public static final int getNumPartitions()

preferredLocations

public static final scala.collection.Seq<String> preferredLocations(Partition split)

iterator

public static final scala.collection.Iterator<T> iterator(Partition split,
                                                          TaskContext context)

map

public static <U> RDD<U> map(scala.Function1<T,U> f,
                             scala.reflect.ClassTag<U> evidence$3)

flatMap

public static <U> RDD<U> flatMap(scala.Function1<T,scala.collection.TraversableOnce<U>> f,
                                 scala.reflect.ClassTag<U> evidence$4)

filter

public static RDD<T> filter(scala.Function1<T,Object> f)

distinct

public static RDD<T> distinct(int numPartitions,
                              scala.math.Ordering<T> ord)

distinct

public static RDD<T> distinct()

repartition

public static RDD<T> repartition(int numPartitions,
                                 scala.math.Ordering<T> ord)

coalesce

public static RDD<T> coalesce(int numPartitions,
                              boolean shuffle,
                              scala.Option<PartitionCoalescer> partitionCoalescer,
                              scala.math.Ordering<T> ord)

sample

public static RDD<T> sample(boolean withReplacement,
                            double fraction,
                            long seed)

randomSplit

public static RDD<T>[] randomSplit(double[] weights,
                                   long seed)

takeSample

public static Object takeSample(boolean withReplacement,
                                int num,
                                long seed)

union

public static RDD<T> union(RDD<T> other)

$plus$plus

public static RDD<T> $plus$plus(RDD<T> other)

sortBy

public static <K> RDD<T> sortBy(scala.Function1<T,K> f,
                                boolean ascending,
                                int numPartitions,
                                scala.math.Ordering<K> ord,
                                scala.reflect.ClassTag<K> ctag)

intersection

public static RDD<T> intersection(RDD<T> other)

intersection

public static RDD<T> intersection(RDD<T> other,
                                  Partitioner partitioner,
                                  scala.math.Ordering<T> ord)

intersection

public static RDD<T> intersection(RDD<T> other,
                                  int numPartitions)

glom

public static RDD<Object> glom()

cartesian

public static <U> RDD<scala.Tuple2<T,U>> cartesian(RDD<U> other,
                                                   scala.reflect.ClassTag<U> evidence$5)

groupBy

public static <K> RDD<scala.Tuple2<K,scala.collection.Iterable<T>>> groupBy(scala.Function1<T,K> f,
                                                                            scala.reflect.ClassTag<K> kt)

groupBy

public static <K> RDD<scala.Tuple2<K,scala.collection.Iterable<T>>> groupBy(scala.Function1<T,K> f,
                                                                            int numPartitions,
                                                                            scala.reflect.ClassTag<K> kt)

groupBy

public static <K> RDD<scala.Tuple2<K,scala.collection.Iterable<T>>> groupBy(scala.Function1<T,K> f,
                                                                            Partitioner p,
                                                                            scala.reflect.ClassTag<K> kt,
                                                                            scala.math.Ordering<K> ord)

pipe

public static RDD<String> pipe(String command)

pipe

public static RDD<String> pipe(String command,
                               scala.collection.Map<String,String> env)

pipe

public static RDD<String> pipe(scala.collection.Seq<String> command,
                               scala.collection.Map<String,String> env,
                               scala.Function1<scala.Function1<String,scala.runtime.BoxedUnit>,scala.runtime.BoxedUnit> printPipeContext,
                               scala.Function2<T,scala.Function1<String,scala.runtime.BoxedUnit>,scala.runtime.BoxedUnit> printRDDElement,
                               boolean separateWorkingDir,
                               int bufferSize,
                               String encoding)

mapPartitions

public static <U> RDD<U> mapPartitions(scala.Function1<scala.collection.Iterator<T>,scala.collection.Iterator<U>> f,
                                       boolean preservesPartitioning,
                                       scala.reflect.ClassTag<U> evidence$6)

mapPartitionsWithIndex

public static <U> RDD<U> mapPartitionsWithIndex(scala.Function2<Object,scala.collection.Iterator<T>,scala.collection.Iterator<U>> f,
                                                boolean preservesPartitioning,
                                                scala.reflect.ClassTag<U> evidence$9)

zip

public static <U> RDD<scala.Tuple2<T,U>> zip(RDD<U> other,
                                             scala.reflect.ClassTag<U> evidence$10)

zipPartitions

public static <B,V> RDD<V> zipPartitions(RDD<B> rdd2,
                                         boolean preservesPartitioning,
                                         scala.Function2<scala.collection.Iterator<T>,scala.collection.Iterator<B>,scala.collection.Iterator<V>> f,
                                         scala.reflect.ClassTag<B> evidence$11,
                                         scala.reflect.ClassTag<V> evidence$12)

zipPartitions

public static <B,V> RDD<V> zipPartitions(RDD<B> rdd2,
                                         scala.Function2<scala.collection.Iterator<T>,scala.collection.Iterator<B>,scala.collection.Iterator<V>> f,
                                         scala.reflect.ClassTag<B> evidence$13,
                                         scala.reflect.ClassTag<V> evidence$14)

zipPartitions

public static <B,C,V> RDD<V> zipPartitions(RDD<B> rdd2,
                                           RDD<C> rdd3,
                                           boolean preservesPartitioning,
                                           scala.Function3<scala.collection.Iterator<T>,scala.collection.Iterator<B>,scala.collection.Iterator<C>,scala.collection.Iterator<V>> f,
                                           scala.reflect.ClassTag<B> evidence$15,
                                           scala.reflect.ClassTag<C> evidence$16,
                                           scala.reflect.ClassTag<V> evidence$17)

zipPartitions

public static <B,C,V> RDD<V> zipPartitions(RDD<B> rdd2,
                                           RDD<C> rdd3,
                                           scala.Function3<scala.collection.Iterator<T>,scala.collection.Iterator<B>,scala.collection.Iterator<C>,scala.collection.Iterator<V>> f,
                                           scala.reflect.ClassTag<B> evidence$18,
                                           scala.reflect.ClassTag<C> evidence$19,
                                           scala.reflect.ClassTag<V> evidence$20)

zipPartitions

public static <B,C,D,V> RDD<V> zipPartitions(RDD<B> rdd2,
                                             RDD<C> rdd3,
                                             RDD<D> rdd4,
                                             boolean preservesPartitioning,
                                             scala.Function4<scala.collection.Iterator<T>,scala.collection.Iterator<B>,scala.collection.Iterator<C>,scala.collection.Iterator<D>,scala.collection.Iterator<V>> f,
                                             scala.reflect.ClassTag<B> evidence$21,
                                             scala.reflect.ClassTag<C> evidence$22,
                                             scala.reflect.ClassTag<D> evidence$23,
                                             scala.reflect.ClassTag<V> evidence$24)

zipPartitions

public static <B,C,D,V> RDD<V> zipPartitions(RDD<B> rdd2,
                                             RDD<C> rdd3,
                                             RDD<D> rdd4,
                                             scala.Function4<scala.collection.Iterator<T>,scala.collection.Iterator<B>,scala.collection.Iterator<C>,scala.collection.Iterator<D>,scala.collection.Iterator<V>> f,
                                             scala.reflect.ClassTag<B> evidence$25,
                                             scala.reflect.ClassTag<C> evidence$26,
                                             scala.reflect.ClassTag<D> evidence$27,
                                             scala.reflect.ClassTag<V> evidence$28)

foreach

public static void foreach(scala.Function1<T,scala.runtime.BoxedUnit> f)

foreachPartition

public static void foreachPartition(scala.Function1<scala.collection.Iterator<T>,scala.runtime.BoxedUnit> f)

collect

public static Object collect()

toLocalIterator

public static scala.collection.Iterator<T> toLocalIterator()

collect

public static <U> RDD<U> collect(scala.PartialFunction<T,U> f,
                                 scala.reflect.ClassTag<U> evidence$29)

subtract

public static RDD<T> subtract(RDD<T> other)

subtract

public static RDD<T> subtract(RDD<T> other,
                              int numPartitions)

subtract

public static RDD<T> subtract(RDD<T> other,
                              Partitioner p,
                              scala.math.Ordering<T> ord)

reduce

public static T reduce(scala.Function2<T,T,T> f)

treeReduce

public static T treeReduce(scala.Function2<T,T,T> f,
                           int depth)

fold

public static T fold(T zeroValue,
                     scala.Function2<T,T,T> op)

aggregate

public static <U> U aggregate(U zeroValue,
                              scala.Function2<U,T,U> seqOp,
                              scala.Function2<U,U,U> combOp,
                              scala.reflect.ClassTag<U> evidence$30)

treeAggregate

public static <U> U treeAggregate(U zeroValue,
                                  scala.Function2<U,T,U> seqOp,
                                  scala.Function2<U,U,U> combOp,
                                  int depth,
                                  scala.reflect.ClassTag<U> evidence$31)

count

public static long count()

countApprox

public static PartialResult<BoundedDouble> countApprox(long timeout,
                                                       double confidence)

countByValue

public static scala.collection.Map<T,Object> countByValue(scala.math.Ordering<T> ord)

countByValueApprox

public static PartialResult<scala.collection.Map<T,BoundedDouble>> countByValueApprox(long timeout,
                                                                                      double confidence,
                                                                                      scala.math.Ordering<T> ord)

countApproxDistinct

public static long countApproxDistinct(int p,
                                       int sp)

countApproxDistinct

public static long countApproxDistinct(double relativeSD)

zipWithIndex

public static RDD<scala.Tuple2<T,Object>> zipWithIndex()

zipWithUniqueId

public static RDD<scala.Tuple2<T,Object>> zipWithUniqueId()

take

public static Object take(int num)

first

public static T first()

top

public static Object top(int num,
                         scala.math.Ordering<T> ord)

takeOrdered

public static Object takeOrdered(int num,
                                 scala.math.Ordering<T> ord)

max

public static T max(scala.math.Ordering<T> ord)

min

public static T min(scala.math.Ordering<T> ord)

isEmpty

public static boolean isEmpty()

saveAsTextFile

public static void saveAsTextFile(String path)

saveAsTextFile

public static void saveAsTextFile(String path,
                                  Class<? extends org.apache.hadoop.io.compress.CompressionCodec> codec)

saveAsObjectFile

public static void saveAsObjectFile(String path)

keyBy

public static <K> RDD<scala.Tuple2<K,T>> keyBy(scala.Function1<T,K> f)

checkpoint

public static void checkpoint()

localCheckpoint

public static RDD<T> localCheckpoint()

isCheckpointed

public static boolean isCheckpointed()

getCheckpointFile

public static scala.Option<String> getCheckpointFile()

context

public static SparkContext context()

toDebugString

public static String toDebugString()

toString

public static String toString()

toJavaRDD

public static JavaRDD<T> toJavaRDD()

sample$default$3

public static long sample$default$3()

mapPartitionsWithIndex$default$2

public static <U> boolean mapPartitionsWithIndex$default$2()

unpersist$default$1

public static boolean unpersist$default$1()

distinct$default$2

public static scala.math.Ordering<T> distinct$default$2(int numPartitions)

coalesce$default$2

public static boolean coalesce$default$2()

coalesce$default$3

public static scala.Option<PartitionCoalescer> coalesce$default$3()

coalesce$default$4

public static scala.math.Ordering<T> coalesce$default$4(int numPartitions,
                                                        boolean shuffle,
                                                        scala.Option<PartitionCoalescer> partitionCoalescer)

repartition$default$2

public static scala.math.Ordering<T> repartition$default$2(int numPartitions)

subtract$default$3

public static scala.math.Ordering<T> subtract$default$3(RDD<T> other,
                                                        Partitioner p)

intersection$default$3

public static scala.math.Ordering<T> intersection$default$3(RDD<T> other,
                                                            Partitioner partitioner)

randomSplit$default$2

public static long randomSplit$default$2()

sortBy$default$2

public static <K> boolean sortBy$default$2()

sortBy$default$3

public static <K> int sortBy$default$3()

mapPartitions$default$2

public static <U> boolean mapPartitions$default$2()

groupBy$default$4

public static <K> scala.runtime.Null$ groupBy$default$4(scala.Function1<T,K> f,
                                                        Partitioner p)

pipe$default$2

public static scala.collection.Map<String,String> pipe$default$2()

pipe$default$3

public static scala.Function1<scala.Function1<String,scala.runtime.BoxedUnit>,scala.runtime.BoxedUnit> pipe$default$3()

pipe$default$4

public static scala.Function2<T,scala.Function1<String,scala.runtime.BoxedUnit>,scala.runtime.BoxedUnit> pipe$default$4()

pipe$default$5

public static boolean pipe$default$5()

pipe$default$6

public static int pipe$default$6()

pipe$default$7

public static String pipe$default$7()

treeReduce$default$2

public static int treeReduce$default$2()

treeAggregate$default$4

public static <U> int treeAggregate$default$4(U zeroValue)

countApprox$default$2

public static double countApprox$default$2()

countByValue$default$1

public static scala.math.Ordering<T> countByValue$default$1()

countByValueApprox$default$2

public static double countByValueApprox$default$2()

countByValueApprox$default$3

public static scala.math.Ordering<T> countByValueApprox$default$3(long timeout,
                                                                  double confidence)

takeSample$default$3

public static long takeSample$default$3()

countApproxDistinct$default$1

public static double countApproxDistinct$default$1()

mapPartitionsWithIndexInternal$default$2

public static <U> boolean mapPartitionsWithIndexInternal$default$2()

mapPartitionsWithIndexInternal$default$3

public static <U> boolean mapPartitionsWithIndexInternal$default$3()

mapPartitionsInternal$default$2

public static <U> boolean mapPartitionsInternal$default$2()

getPartitions

public Partition[] getPartitions()

Description copied from class: RDD

Implemented by subclasses to return the set of partitions in this RDD. This method will only be called once, so it is safe to implement a time-consuming computation in it.

The partitions in this array must satisfy the following property: rdd.partitions.zipWithIndex.forall { case (partition, index) => partition.index == index }

Returns:

(undocumented)

compute

public scala.collection.Iterator<T> compute(Partition thePart,
                                            TaskContext context)

Description copied from class: RDD

:: DeveloperApi :: Implemented by subclasses to compute a given partition.

Specified by:

compute in class RDD<T>

Parameters:

thePart - (undocumented)

context - (undocumented)

Returns:

(undocumented)