EdgeRDDImpl (Spark 2.0.1 JavaDoc)

Object
- org.apache.spark.rdd.RDD<Edge<ED>>
- - org.apache.spark.graphx.EdgeRDD<ED>
  - - org.apache.spark.graphx.impl.EdgeRDDImpl<ED,VD>

All Implemented Interfaces:

java.io.Serializable
```
public class EdgeRDDImpl<ED,VD>
extends EdgeRDD<ED>
```
See Also:
Serialized Form

Method Summary

Methods
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$29)`
`EdgeRDDImpl<ED,VD>`	`cache()` Persists the edge partitions using `targetStorageLevel`, which defaults to MEMORY_ONLY.
`static <U> RDD<scala.Tuple2<T,U>>`	`cartesian(RDD<U> other, scala.reflect.ClassTag<U> evidence$5)`
`void`	`checkpoint()`
`static RDD<T>`	`coalesce(int numPartitions, boolean shuffle, scala.Option<PartitionCoalescer> partitionCoalescer, scala.math.Ordering<T> ord)`
`static boolean`	`coalesce$default$2()`
`static scala.Option<PartitionCoalescer>`	`coalesce$default$3()`
`static scala.math.Ordering<T>`	`coalesce$default$4(int numPartitions, boolean shuffle, scala.Option<PartitionCoalescer> partitionCoalescer)`
`Edge<ED>[]`	`collect()`
`static scala.collection.Iterator<Edge<ED>>`	`compute(Partition part, TaskContext context)`
`static SparkContext`	`context()`
`long`	`count()` The number of edges in the RDD.
`static PartialResult<BoundedDouble>`	`countApprox(long timeout, double confidence)`
`static double`	`countApprox$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$3(long timeout, double confidence)`
`static scala.collection.Seq<Dependency<?>>`	`dependencies()`
`static RDD<T>`	`distinct()`
`static RDD<T>`	`distinct(int numPartitions, scala.math.Ordering<T> ord)`
`static scala.math.Ordering<T>`	`distinct$default$2(int numPartitions)`
`EdgeRDDImpl<ED,VD>`	`filter(scala.Function1<EdgeTriplet<VD,ED>,Object> epred, scala.Function2<Object,VD,Object> vpred)`
`static T`	`first()`
`static <U> RDD<U>`	`flatMap(scala.Function1<T,scala.collection.TraversableOnce<U>> f, scala.reflect.ClassTag<U> evidence$4)`
`static T`	`fold(T zeroValue, scala.Function2<T,T,T> op)`
`static void`	`foreach(scala.Function1<T,scala.runtime.BoxedUnit> f)`
`static void`	`foreachPartition(scala.Function1<scala.collection.Iterator<T>,scala.runtime.BoxedUnit> f)`
`scala.Option<String>`	`getCheckpointFile()`
`static int`	`getNumPartitions()`
`StorageLevel`	`getStorageLevel()`
`static RDD<Object>`	`glom()`
`static <K> RDD<scala.Tuple2<K,scala.collection.Iterable<T>>>`	`groupBy(scala.Function1<T,K> f, scala.reflect.ClassTag<K> kt)`
`static <K> RDD<scala.Tuple2<K,scala.collection.Iterable<T>>>`	`groupBy(scala.Function1<T,K> f, int numPartitions, scala.reflect.ClassTag<K> kt)`
`static <K> RDD<scala.Tuple2<K,scala.collection.Iterable<T>>>`	`groupBy(scala.Function1<T,K> f, Partitioner p, scala.reflect.ClassTag<K> kt, scala.math.Ordering<K> ord)`
`static <K> scala.runtime.Null$`	`groupBy$default$4(scala.Function1<T,K> f, Partitioner p)`
`static int`	`id()`
`<ED2,ED3> EdgeRDDImpl<ED3,VD>`	`innerJoin(EdgeRDD<ED2> other, scala.Function4<Object,Object,ED,ED2,ED3> f, scala.reflect.ClassTag<ED2> evidence$4, scala.reflect.ClassTag<ED3> evidence$5)` Inner joins this EdgeRDD with another EdgeRDD, assuming both are partitioned using the same `PartitionStrategy`.
`static RDD<T>`	`intersection(RDD<T> other)`
`static RDD<T>`	`intersection(RDD<T> other, int numPartitions)`
`static RDD<T>`	`intersection(RDD<T> other, Partitioner partitioner, scala.math.Ordering<T> ord)`
`static scala.math.Ordering<T>`	`intersection$default$3(RDD<T> other, Partitioner partitioner)`
`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)`
`<ED2,VD2> EdgeRDDImpl<ED2,VD2>`	`mapEdgePartitions(scala.Function2<Object,org.apache.spark.graphx.impl.EdgePartition<ED,VD>,org.apache.spark.graphx.impl.EdgePartition<ED2,VD2>> f, scala.reflect.ClassTag<ED2> evidence$6, scala.reflect.ClassTag<VD2> evidence$7)`
`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$8)`
`static <U> boolean`	`mapPartitionsWithIndex$default$2()`
`<ED2> EdgeRDDImpl<ED2,VD>`	`mapValues(scala.Function1<Edge<ED>,ED2> f, scala.reflect.ClassTag<ED2> evidence$3)` Map the values in an edge partitioning preserving the structure but changing the values.
`static T`	`max(scala.math.Ordering<T> ord)`
`static T`	`min(scala.math.Ordering<T> ord)`
`static void`	`name_$eq(String x$1)`
`static String`	`name()`
`scala.Option<Partitioner>`	`partitioner()` If `partitionsRDD` already has a partitioner, use it.
`static Partition[]`	`partitions()`
`RDD<scala.Tuple2<Object,org.apache.spark.graphx.impl.EdgePartition<ED,VD>>>`	`partitionsRDD()`
`EdgeRDDImpl<ED,VD>`	`persist(StorageLevel newLevel)` Persists the edge partitions at the specified storage level, ignoring any existing target storage level.
`static RDD<String>`	`pipe(scala.collection.Seq<String> command, scala.collection.Map<String,String> env, scala.Function1<scala.Function1<String,scala.runtime.BoxedUnit>,scala.runtime.BoxedUnit> printPipeContext, scala.Function2<T,scala.Function1<String,scala.runtime.BoxedUnit>,scala.runtime.BoxedUnit> printRDDElement, boolean separateWorkingDir, int bufferSize, String encoding)`
`static RDD<String>`	`pipe(String command)`
`static RDD<String>`	`pipe(String command, scala.collection.Map<String,String> env)`
`static scala.collection.Map<String,String>`	`pipe$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$2(int numPartitions)`
`EdgeRDDImpl<ED,VD>`	`reverse()` Reverse all the edges in this RDD.
`static RDD<T>`	`sample(boolean withReplacement, double fraction, long seed)`
`static long`	`sample$default$3()`
`static void`	`saveAsObjectFile(String path)`
`static void`	`saveAsTextFile(String path)`
`static void`	`saveAsTextFile(String path, Class<? extends org.apache.hadoop.io.compress.CompressionCodec> codec)`
`EdgeRDDImpl<ED,VD>`	`setName(String _name)`
`static <K> RDD<T>`	`sortBy(scala.Function1<T,K> f, boolean ascending, int numPartitions, scala.math.Ordering<K> ord, scala.reflect.ClassTag<K> ctag)`
`static <K> boolean`	`sortBy$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()`
`StorageLevel`	`targetStorageLevel()`
`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$30)`
`static <U> int`	`treeAggregate$default$4(U zeroValue)`
`static T`	`treeReduce(scala.Function2<T,T,T> f, int depth)`
`static int`	`treeReduce$default$2()`
`static RDD<T>`	`union(RDD<T> other)`
`EdgeRDDImpl<ED,VD>`	`unpersist(boolean blocking)`
`static boolean`	`unpersist$default$1()`
`static <U> RDD<scala.Tuple2<T,U>>`	`zip(RDD<U> other, scala.reflect.ClassTag<U> evidence$9)`
`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$10, scala.reflect.ClassTag<V> evidence$11)`
`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$12, scala.reflect.ClassTag<V> evidence$13)`
`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$14, scala.reflect.ClassTag<C> evidence$15, scala.reflect.ClassTag<V> evidence$16)`
`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$17, scala.reflect.ClassTag<C> evidence$18, scala.reflect.ClassTag<V> evidence$19)`
`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$20, scala.reflect.ClassTag<C> evidence$21, scala.reflect.ClassTag<D> evidence$22, scala.reflect.ClassTag<V> evidence$23)`
`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$24, scala.reflect.ClassTag<C> evidence$25, scala.reflect.ClassTag<D> evidence$26, scala.reflect.ClassTag<V> evidence$27)`
`static RDD<scala.Tuple2<T,Object>>`	`zipWithIndex()`
`static RDD<scala.Tuple2<T,Object>>`	`zipWithUniqueId()`

Methods inherited from class org.apache.spark.graphx.EdgeRDD
collect, compute, filter, fromEdges, persist

Methods inherited from class org.apache.spark.rdd.RDD
aggregate, cartesian, coalesce, collect, context, countApprox, countApproxDistinct, countApproxDistinct, countByValue, countByValueApprox, dependencies, distinct, distinct, doubleRDDToDoubleRDDFunctions, filter, first, flatMap, fold, foreach, foreachPartition, getNumPartitions, glom, groupBy, groupBy, groupBy, id, intersection, intersection, intersection, isEmpty, iterator, keyBy, localCheckpoint, map, mapPartitions, mapPartitionsWithIndex, max, min, name, numericRDDToDoubleRDDFunctions, partitions, persist, pipe, pipe, pipe, preferredLocations, randomSplit, rddToAsyncRDDActions, rddToOrderedRDDFunctions, rddToPairRDDFunctions, rddToSequenceFileRDDFunctions, reduce, repartition, sample, saveAsObjectFile, saveAsTextFile, saveAsTextFile, sortBy, sparkContext, subtract, subtract, subtract, take, takeOrdered, takeSample, toDebugString, toJavaRDD, toLocalIterator, top, toString, treeAggregate, treeReduce, union, zip, zipPartitions, zipPartitions, zipPartitions, zipPartitions, zipPartitions, zipPartitions, zipWithIndex, zipWithUniqueId

Methods inherited from class Object
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Method Detail

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)

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)

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$8)

zip

public static <U> RDD<scala.Tuple2<T,U>> zip(RDD<U> other,
                             scala.reflect.ClassTag<U> evidence$9)

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$10,
                         scala.reflect.ClassTag<V> evidence$11)

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$12,
                         scala.reflect.ClassTag<V> evidence$13)

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$14,
                           scala.reflect.ClassTag<C> evidence$15,
                           scala.reflect.ClassTag<V> evidence$16)

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$17,
                           scala.reflect.ClassTag<C> evidence$18,
                           scala.reflect.ClassTag<V> evidence$19)

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$20,
                             scala.reflect.ClassTag<C> evidence$21,
                             scala.reflect.ClassTag<D> evidence$22,
                             scala.reflect.ClassTag<V> evidence$23)

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$24,
                             scala.reflect.ClassTag<C> evidence$25,
                             scala.reflect.ClassTag<D> evidence$26,
                             scala.reflect.ClassTag<V> evidence$27)

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)

toLocalIterator

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

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$29)

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$30)

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)

localCheckpoint

public static RDD<T> localCheckpoint()

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()

mapPartitionsInternal$default$2

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

compute

public static scala.collection.Iterator<Edge<ED>> compute(Partition part,
                                          TaskContext context)

partitionsRDD

public RDD<scala.Tuple2<Object,org.apache.spark.graphx.impl.EdgePartition<ED,VD>>> partitionsRDD()

targetStorageLevel

public StorageLevel targetStorageLevel()

setName

public EdgeRDDImpl<ED,VD> setName(String _name)

Overrides:: setName in class EdgeRDD<ED>

partitioner
```
public scala.Option<Partitioner> partitioner()
```
If partitionsRDD already has a partitioner, use it. Otherwise assume that the PartitionIDs in partitionsRDD correspond to the actual partitions and create a new partitioner that allows co-partitioning with partitionsRDD.

Overrides:

partitioner in class EdgeRDD<ED>

Returns:
(undocumented)

collect
```
public Edge<ED>[] collect()
```
Overrides:

collect in class EdgeRDD<ED>

persist
```
public EdgeRDDImpl<ED,VD> persist(StorageLevel newLevel)
```
Persists the edge partitions at the specified storage level, ignoring any existing target storage level.

Overrides:

persist in class EdgeRDD<ED>

Parameters:
newLevel - (undocumented)

Returns:
(undocumented)

unpersist

public EdgeRDDImpl<ED,VD> unpersist(boolean blocking)

Overrides:: unpersist in class EdgeRDD<ED>

cache
```
public EdgeRDDImpl<ED,VD> cache()
```
Persists the edge partitions using `targetStorageLevel`, which defaults to MEMORY_ONLY.

Overrides:

cache in class EdgeRDD<ED>

getStorageLevel
```
public StorageLevel getStorageLevel()
```
Overrides:

getStorageLevel in class EdgeRDD<ED>

checkpoint
```
public void checkpoint()
```
Overrides:

checkpoint in class EdgeRDD<ED>

isCheckpointed
```
public boolean isCheckpointed()
```
Overrides:

isCheckpointed in class EdgeRDD<ED>

getCheckpointFile
```
public scala.Option<String> getCheckpointFile()
```
Overrides:

getCheckpointFile in class EdgeRDD<ED>

count
```
public long count()
```
The number of edges in the RDD.

Overrides:

count in class EdgeRDD<ED>

mapValues
```
public <ED2> EdgeRDDImpl<ED2,VD> mapValues(scala.Function1<Edge<ED>,ED2> f,
                                  scala.reflect.ClassTag<ED2> evidence$3)
```
Description copied from class: EdgeRDD

Map the values in an edge partitioning preserving the structure but changing the values.

Specified by:

mapValues in class EdgeRDD<ED>

Parameters:
f - the function from an edge to a new edge value
evidence$3 - (undocumented)

Returns:
a new EdgeRDD containing the new edge values

reverse
```
public EdgeRDDImpl<ED,VD> reverse()
```
Description copied from class: EdgeRDD

Reverse all the edges in this RDD.

Specified by:

reverse in class EdgeRDD<ED>

Returns:
a new EdgeRDD containing all the edges reversed

filter

public EdgeRDDImpl<ED,VD> filter(scala.Function1<EdgeTriplet<VD,ED>,Object> epred,
                        scala.Function2<Object,VD,Object> vpred)

innerJoin
```
public <ED2,ED3> EdgeRDDImpl<ED3,VD> innerJoin(EdgeRDD<ED2> other,
                                      scala.Function4<Object,Object,ED,ED2,ED3> f,
                                      scala.reflect.ClassTag<ED2> evidence$4,
                                      scala.reflect.ClassTag<ED3> evidence$5)
```
Description copied from class: EdgeRDD

Inner joins this EdgeRDD with another EdgeRDD, assuming both are partitioned using the same PartitionStrategy.

Specified by:

innerJoin in class EdgeRDD<ED>

Parameters:
other - the EdgeRDD to join with
f - the join function applied to corresponding values of this and other
evidence$4 - (undocumented)
evidence$5 - (undocumented)

Returns:
a new EdgeRDD containing only edges that appear in both this and other, with values supplied by f

mapEdgePartitions

public <ED2,VD2> EdgeRDDImpl<ED2,VD2> mapEdgePartitions(scala.Function2<Object,org.apache.spark.graphx.impl.EdgePartition<ED,VD>,org.apache.spark.graphx.impl.EdgePartition<ED2,VD2>> f,
                                               scala.reflect.ClassTag<ED2> evidence$6,
                                               scala.reflect.ClassTag<VD2> evidence$7)

Class EdgeRDDImpl<ED,VD>

Method Summary

Methods inherited from class org.apache.spark.graphx.EdgeRDD

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

Methods inherited from class Object

Method Detail

sparkContext

id

name

name_$eq

dependencies

partitions

getNumPartitions

preferredLocations

iterator

map

flatMap

distinct

distinct

repartition

coalesce

sample

randomSplit

takeSample

union

$plus$plus

sortBy

intersection

intersection

intersection

glom

cartesian

groupBy

groupBy

groupBy

pipe

pipe

pipe

mapPartitions

mapPartitionsWithIndex

zip

zipPartitions

zipPartitions

zipPartitions

zipPartitions

zipPartitions

zipPartitions

foreach

foreachPartition

toLocalIterator

subtract

subtract

subtract

reduce

treeReduce

fold

aggregate

treeAggregate

countApprox

countByValue

countByValueApprox

countApproxDistinct

countApproxDistinct

zipWithIndex

zipWithUniqueId

take

first

top

takeOrdered

max

min

isEmpty

saveAsTextFile

saveAsTextFile

saveAsObjectFile

keyBy

localCheckpoint

context

toDebugString

toString