VertexRDDImpl (Spark 2.4.0 JavaDoc)

Object
- org.apache.spark.rdd.RDD<scala.Tuple2<Object,VD>>
- - org.apache.spark.graphx.VertexRDD<VD>
  - - org.apache.spark.graphx.impl.VertexRDDImpl<VD>

All Implemented Interfaces:

java.io.Serializable, Logging
```
public class VertexRDDImpl<VD>
extends VertexRDD<VD>
```
See Also:

Serialized Form

Method Summary

All Methods Static Methods Instance Methods Concrete 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$30)`
`<VD2> VertexRDD<VD2>`	`aggregateUsingIndex(RDD<scala.Tuple2<Object,VD2>> messages, scala.Function2<VD2,VD2,VD2> reduceFunc, scala.reflect.ClassTag<VD2> evidence$12)` Aggregates vertices in `messages` that have the same ids using `reduceFunc`, returning a VertexRDD co-indexed with `this`.
`static RDDBarrier<T>`	`barrier()`
`VertexRDDImpl<VD>`	`cache()` Persists the vertex partitions at `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)`
`static Object`	`collect()`
`static <U> RDD<U>`	`collect(scala.PartialFunction<T,U> f, scala.reflect.ClassTag<U> evidence$29)`
`static scala.collection.Iterator<scala.Tuple2<Object,VD>>`	`compute(Partition part, TaskContext context)`
`static SparkContext`	`context()`
`long`	`count()` The number of vertices in the RDD.
`static PartialResult<BoundedDouble>`	`countApprox(long timeout, double confidence)`
`static double`	`countApprox$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$3(long timeout, double confidence)`
`static scala.collection.Seq<Dependency<?>>`	`dependencies()`
`VertexRDD<VD>`	`diff(RDD<scala.Tuple2<Object,VD>> other)` For each vertex present in both `this` and `other`, `diff` returns only those vertices with differing values; for values that are different, keeps the values from `other`.
`VertexRDD<VD>`	`diff(VertexRDD<VD> other)` For each vertex present in both `this` and `other`, `diff` returns only those vertices with differing values; for values that are different, keeps the values from `other`.
`static RDD<T>`	`distinct()`
`static RDD<T>`	`distinct(int numPartitions, scala.math.Ordering<T> ord)`
`static scala.math.Ordering<T>`	`distinct$default$2(int numPartitions)`
`static VertexRDD<VD>`	`filter(scala.Function1<scala.Tuple2<Object,VD>,Object> pred)`
`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()`
`<U,VD2> VertexRDD<VD2>`	`innerJoin(RDD<scala.Tuple2<Object,U>> other, scala.Function3<Object,VD,U,VD2> f, scala.reflect.ClassTag<U> evidence$10, scala.reflect.ClassTag<VD2> evidence$11)` Inner joins this VertexRDD with an RDD containing vertex attribute pairs.
`<U,VD2> VertexRDD<VD2>`	`innerZipJoin(VertexRDD<U> other, scala.Function3<Object,VD,U,VD2> f, scala.reflect.ClassTag<U> evidence$8, scala.reflect.ClassTag<VD2> evidence$9)` Efficiently inner joins this VertexRDD with another VertexRDD sharing the same index.
`static RDD<T>`	`intersection(RDD<T> other)`
`static RDD<T>`	`intersection(RDD<T> other, int numPartitions)`
`static RDD<T>`	`intersection(RDD<T> other, Partitioner partitioner, scala.math.Ordering<T> ord)`
`static scala.math.Ordering<T>`	`intersection$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)`
`<VD2,VD3> VertexRDD<VD3>`	`leftJoin(RDD<scala.Tuple2<Object,VD2>> other, scala.Function3<Object,VD,scala.Option<VD2>,VD3> f, scala.reflect.ClassTag<VD2> evidence$6, scala.reflect.ClassTag<VD3> evidence$7)` Left joins this VertexRDD with an RDD containing vertex attribute pairs.
`<VD2,VD3> VertexRDD<VD3>`	`leftZipJoin(VertexRDD<VD2> other, scala.Function3<Object,VD,scala.Option<VD2>,VD3> f, scala.reflect.ClassTag<VD2> evidence$4, scala.reflect.ClassTag<VD3> evidence$5)` Left joins this RDD with another VertexRDD with the same index.
`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()`
`<VD2> VertexRDD<VD2>`	`mapValues(scala.Function1<VD,VD2> f, scala.reflect.ClassTag<VD2> evidence$2)` Maps each vertex attribute, preserving the index.
`<VD2> VertexRDD<VD2>`	`mapValues(scala.Function2<Object,VD,VD2> f, scala.reflect.ClassTag<VD2> evidence$3)` Maps each vertex attribute, additionally supplying the vertex ID.
`static T`	`max(scala.math.Ordering<T> ord)`
`static T`	`min(scala.math.Ordering<T> ord)`
`VertexRDD<VD>`	`minus(RDD<scala.Tuple2<Object,VD>> other)` For each VertexId present in both `this` and `other`, minus will act as a set difference operation returning only those unique VertexId's present in `this`.
`VertexRDD<VD>`	`minus(VertexRDD<VD> other)` For each VertexId present in both `this` and `other`, minus will act as a set difference operation returning only those unique VertexId's present in `this`.
`static void`	`name_$eq(String x$1)`
`static String`	`name()`
`scala.Option<Partitioner>`	`partitioner()`
`static Partition[]`	`partitions()`
`RDD<org.apache.spark.graphx.impl.ShippableVertexPartition<VD>>`	`partitionsRDD()`
`VertexRDDImpl<VD>`	`persist(StorageLevel newLevel)` Persists the vertex partitions at the specified storage level, ignoring any existing target storage level.
`static RDD<String>`	`pipe(scala.collection.Seq<String> command, scala.collection.Map<String,String> env, scala.Function1<scala.Function1<String,scala.runtime.BoxedUnit>,scala.runtime.BoxedUnit> printPipeContext, scala.Function2<T,scala.Function1<String,scala.runtime.BoxedUnit>,scala.runtime.BoxedUnit> printRDDElement, boolean separateWorkingDir, int bufferSize, String encoding)`
`static RDD<String>`	`pipe(String command)`
`static RDD<String>`	`pipe(String command, scala.collection.Map<String,String> env)`
`static scala.collection.Map<String,String>`	`pipe$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$2()`
`static T`	`reduce(scala.Function2<T,T,T> f)`
`VertexRDD<VD>`	`reindex()` Construct a new VertexRDD that is indexed by only the visible vertices.
`static RDD<T>`	`repartition(int numPartitions, scala.math.Ordering<T> ord)`
`static scala.math.Ordering<T>`	`repartition$default$2(int numPartitions)`
`VertexRDD<VD>`	`reverseRoutingTables()` Returns a new `VertexRDD` reflecting a reversal of all edge directions in the corresponding `EdgeRDD`.
`static RDD<T>`	`sample(boolean withReplacement, double fraction, long seed)`
`static long`	`sample$default$3()`
`static void`	`saveAsObjectFile(String path)`
`static void`	`saveAsTextFile(String path)`
`static void`	`saveAsTextFile(String path, Class<? extends org.apache.hadoop.io.compress.CompressionCodec> codec)`
`VertexRDDImpl<VD>`	`setName(String _name)`
`static <K> RDD<T>`	`sortBy(scala.Function1<T,K> f, boolean ascending, int numPartitions, scala.math.Ordering<K> ord, scala.reflect.ClassTag<K> ctag)`
`static <K> boolean`	`sortBy$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$31)`
`static <U> int`	`treeAggregate$default$4(U zeroValue)`
`static T`	`treeReduce(scala.Function2<T,T,T> f, int depth)`
`static int`	`treeReduce$default$2()`
`static RDD<T>`	`union(RDD<T> other)`
`VertexRDDImpl<VD>`	`unpersist(boolean blocking)`
`static boolean`	`unpersist$default$1()`
`VertexRDD<VD>`	`withEdges(EdgeRDD<?> edges)` Prepares this VertexRDD for efficient joins with the given EdgeRDD.
`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.graphx.VertexRDD
apply, apply, apply, compute, filter, fromEdges, persist

Methods inherited from class org.apache.spark.rdd.RDD
aggregate, barrier, cartesian, coalesce, collect, collect, context, countApprox, countApproxDistinct, countApproxDistinct, countByValue, countByValueApprox, dependencies, distinct, distinct, doubleRDDToDoubleRDDFunctions, 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

Methods inherited from interface org.apache.spark.internal.Logging
initializeLogging, initializeLogIfNecessary, initializeLogIfNecessary, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning

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$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)

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()

barrier
```
public static RDDBarrier<T> barrier()
```

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()

compute

public static scala.collection.Iterator<scala.Tuple2<Object,VD>> compute(Partition part,
                                                                         TaskContext context)

filter

public static VertexRDD<VD> filter(scala.Function1<scala.Tuple2<Object,VD>,Object> pred)

partitionsRDD

public RDD<org.apache.spark.graphx.impl.ShippableVertexPartition<VD>> partitionsRDD()

targetStorageLevel

public StorageLevel targetStorageLevel()

reindex
```
public VertexRDD<VD> reindex()
```
Description copied from class: VertexRDD

Construct a new VertexRDD that is indexed by only the visible vertices. The resulting VertexRDD will be based on a different index and can no longer be quickly joined with this RDD.

Specified by:

reindex in class VertexRDD<VD>

Returns:

(undocumented)

partitioner
```
public scala.Option<Partitioner> partitioner()
```
Overrides:

partitioner in class VertexRDD<VD>

setName

public VertexRDDImpl<VD> setName(String _name)

Overrides:: setName in class VertexRDD<VD>

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

Overrides:

persist in class VertexRDD<VD>

Parameters:

newLevel - (undocumented)

Returns:

(undocumented)

unpersist

public VertexRDDImpl<VD> unpersist(boolean blocking)

Overrides:: unpersist in class VertexRDD<VD>

cache
```
public VertexRDDImpl<VD> cache()
```
Persists the vertex partitions at targetStorageLevel, which defaults to MEMORY_ONLY.

Overrides:

cache in class VertexRDD<VD>

Returns:

(undocumented)

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

getStorageLevel in class VertexRDD<VD>

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

checkpoint in class VertexRDD<VD>

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

isCheckpointed in class VertexRDD<VD>

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

getCheckpointFile in class VertexRDD<VD>

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

Overrides:

count in class VertexRDD<VD>

mapValues
```
public <VD2> VertexRDD<VD2> mapValues(scala.Function1<VD,VD2> f,
                                      scala.reflect.ClassTag<VD2> evidence$2)
```
Description copied from class: VertexRDD

Maps each vertex attribute, preserving the index.

Specified by:

mapValues in class VertexRDD<VD>

Parameters:

f - the function applied to each value in the RDD

evidence$2 - (undocumented)

Returns:

a new VertexRDD with values obtained by applying f to each of the entries in the original VertexRDD

mapValues
```
public <VD2> VertexRDD<VD2> mapValues(scala.Function2<Object,VD,VD2> f,
                                      scala.reflect.ClassTag<VD2> evidence$3)
```
Description copied from class: VertexRDD

Maps each vertex attribute, additionally supplying the vertex ID.

Specified by:

mapValues in class VertexRDD<VD>

Parameters:

f - the function applied to each ID-value pair in the RDD

evidence$3 - (undocumented)

Returns:

a new VertexRDD with values obtained by applying f to each of the entries in the original VertexRDD. The resulting VertexRDD retains the same index.

minus
```
public VertexRDD<VD> minus(RDD<scala.Tuple2<Object,VD>> other)
```
Description copied from class: VertexRDD

For each VertexId present in both this and other, minus will act as a set difference operation returning only those unique VertexId's present in this.

Specified by:

minus in class VertexRDD<VD>

Parameters:

other - an RDD to run the set operation against

Returns:

(undocumented)

minus
```
public VertexRDD<VD> minus(VertexRDD<VD> other)
```
Description copied from class: VertexRDD

For each VertexId present in both this and other, minus will act as a set difference operation returning only those unique VertexId's present in this.

Specified by:

minus in class VertexRDD<VD>

Parameters:

other - a VertexRDD to run the set operation against

Returns:

(undocumented)

diff
```
public VertexRDD<VD> diff(RDD<scala.Tuple2<Object,VD>> other)
```
Description copied from class: VertexRDD

For each vertex present in both this and other, diff returns only those vertices with differing values; for values that are different, keeps the values from other. This is only guaranteed to work if the VertexRDDs share a common ancestor.

Specified by:

diff in class VertexRDD<VD>

Parameters:

other - the other RDD[(VertexId, VD)] with which to diff against.

Returns:

(undocumented)

diff
```
public VertexRDD<VD> diff(VertexRDD<VD> other)
```
Description copied from class: VertexRDD

For each vertex present in both this and other, diff returns only those vertices with differing values; for values that are different, keeps the values from other. This is only guaranteed to work if the VertexRDDs share a common ancestor.

Specified by:

diff in class VertexRDD<VD>

Parameters:

other - the other VertexRDD with which to diff against.

Returns:

(undocumented)

leftZipJoin
```
public <VD2,VD3> VertexRDD<VD3> leftZipJoin(VertexRDD<VD2> other,
                                            scala.Function3<Object,VD,scala.Option<VD2>,VD3> f,
                                            scala.reflect.ClassTag<VD2> evidence$4,
                                            scala.reflect.ClassTag<VD3> evidence$5)
```
Description copied from class: VertexRDD

Left joins this RDD with another VertexRDD with the same index. This function will fail if both VertexRDDs do not share the same index. The resulting vertex set contains an entry for each vertex in this. If other is missing any vertex in this VertexRDD, f is passed None.

Specified by:

leftZipJoin in class VertexRDD<VD>

Parameters:

other - the other VertexRDD with which to join.

f - the function mapping a vertex id and its attributes in this and the other vertex set to a new vertex attribute.

evidence$4 - (undocumented)

evidence$5 - (undocumented)

Returns:

a VertexRDD containing the results of f

leftJoin
```
public <VD2,VD3> VertexRDD<VD3> leftJoin(RDD<scala.Tuple2<Object,VD2>> other,
                                         scala.Function3<Object,VD,scala.Option<VD2>,VD3> f,
                                         scala.reflect.ClassTag<VD2> evidence$6,
                                         scala.reflect.ClassTag<VD3> evidence$7)
```
Description copied from class: VertexRDD

Left joins this VertexRDD with an RDD containing vertex attribute pairs. If the other RDD is backed by a VertexRDD with the same index then the efficient leftZipJoin implementation is used. The resulting VertexRDD contains an entry for each vertex in this. If other is missing any vertex in this VertexRDD, f is passed None. If there are duplicates, the vertex is picked arbitrarily.

Specified by:

leftJoin in class VertexRDD<VD>

Parameters:

other - the other VertexRDD with which to join

f - the function mapping a vertex id and its attributes in this and the other vertex set to a new vertex attribute.

evidence$6 - (undocumented)

evidence$7 - (undocumented)

Returns:

a VertexRDD containing all the vertices in this VertexRDD with the attributes emitted by f.

innerZipJoin
```
public <U,VD2> VertexRDD<VD2> innerZipJoin(VertexRDD<U> other,
                                           scala.Function3<Object,VD,U,VD2> f,
                                           scala.reflect.ClassTag<U> evidence$8,
                                           scala.reflect.ClassTag<VD2> evidence$9)
```
Description copied from class: VertexRDD

Efficiently inner joins this VertexRDD with another VertexRDD sharing the same index. See innerJoin for the behavior of the join.

Specified by:

innerZipJoin in class VertexRDD<VD>

Parameters:

other - (undocumented)

f - (undocumented)

evidence$8 - (undocumented)

evidence$9 - (undocumented)

Returns:

(undocumented)

innerJoin
```
public <U,VD2> VertexRDD<VD2> innerJoin(RDD<scala.Tuple2<Object,U>> other,
                                        scala.Function3<Object,VD,U,VD2> f,
                                        scala.reflect.ClassTag<U> evidence$10,
                                        scala.reflect.ClassTag<VD2> evidence$11)
```
Description copied from class: VertexRDD

Inner joins this VertexRDD with an RDD containing vertex attribute pairs. If the other RDD is backed by a VertexRDD with the same index then the efficient innerZipJoin implementation is used.

Specified by:

innerJoin in class VertexRDD<VD>

Parameters:

other - an RDD containing vertices to join. If there are multiple entries for the same vertex, one is picked arbitrarily. Use aggregateUsingIndex to merge multiple entries.

f - the join function applied to corresponding values of this and other

evidence$10 - (undocumented)

evidence$11 - (undocumented)

Returns:

a VertexRDD co-indexed with this, containing only vertices that appear in both this and other, with values supplied by f

aggregateUsingIndex
```
public <VD2> VertexRDD<VD2> aggregateUsingIndex(RDD<scala.Tuple2<Object,VD2>> messages,
                                                scala.Function2<VD2,VD2,VD2> reduceFunc,
                                                scala.reflect.ClassTag<VD2> evidence$12)
```
Description copied from class: VertexRDD

Aggregates vertices in messages that have the same ids using reduceFunc, returning a VertexRDD co-indexed with this.

Specified by:

aggregateUsingIndex in class VertexRDD<VD>

Parameters:

messages - an RDD containing messages to aggregate, where each message is a pair of its target vertex ID and the message data

reduceFunc - the associative aggregation function for merging messages to the same vertex

evidence$12 - (undocumented)

Returns:

a VertexRDD co-indexed with this, containing only vertices that received messages. For those vertices, their values are the result of applying reduceFunc to all received messages.

reverseRoutingTables
```
public VertexRDD<VD> reverseRoutingTables()
```
Description copied from class: VertexRDD

Returns a new VertexRDD reflecting a reversal of all edge directions in the corresponding EdgeRDD.

Specified by:

reverseRoutingTables in class VertexRDD<VD>

Returns:

(undocumented)

withEdges
```
public VertexRDD<VD> withEdges(EdgeRDD<?> edges)
```
Description copied from class: VertexRDD

Prepares this VertexRDD for efficient joins with the given EdgeRDD.

Specified by:

withEdges in class VertexRDD<VD>

Class VertexRDDImpl<VD>

Method Summary

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

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

Methods inherited from class Object

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

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

collect

toLocalIterator

collect

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