public class VertexRDDImpl<VD> extends VertexRDD<VD>
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) |
<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 . |
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$28) |
static scala.collection.Iterator<scala.Tuple2<Object,VD>> |
compute(Partition part,
TaskContext context) |
static SparkContext |
context() |
long |
count()
The number of vertices in the RDD.
|
static PartialResult<BoundedDouble> |
countApprox(long timeout,
double confidence) |
static double |
countApprox$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$8) |
static <U> boolean |
mapPartitionsWithIndex$default$2() |
<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$30) |
static <U> int |
treeAggregate$default$4(U zeroValue) |
static T |
treeReduce(scala.Function2<T,T,T> f,
int depth) |
static int |
treeReduce$default$2() |
static RDD<T> |
union(RDD<T> other) |
VertexRDDImpl<VD> |
unpersist(boolean blocking) |
static boolean |
unpersist$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$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$27) |
static RDD<scala.Tuple2<T,Object>> |
zipWithIndex() |
static RDD<scala.Tuple2<T,Object>> |
zipWithUniqueId() |
apply, apply, apply, compute, filter, fromEdges, persist
aggregate, cartesian, coalesce, collect, collect, context, countApprox, countApproxDistinct, countApproxDistinct, countByValue, countByValueApprox, dependencies, distinct, distinct, doubleRDDToDoubleRDDFunctions, first, flatMap, fold, foreach, foreachPartition, getNumPartitions, glom, groupBy, groupBy, groupBy, id, intersection, intersection, intersection, isEmpty, iterator, keyBy, localCheckpoint, map, mapPartitions, mapPartitionsWithIndex, max, min, name, numericRDDToDoubleRDDFunctions, partitions, persist, pipe, pipe, pipe, preferredLocations, randomSplit, rddToAsyncRDDActions, rddToOrderedRDDFunctions, rddToPairRDDFunctions, rddToSequenceFileRDDFunctions, reduce, repartition, sample, saveAsObjectFile, saveAsTextFile, saveAsTextFile, sortBy, sparkContext, subtract, subtract, subtract, take, takeOrdered, takeSample, toDebugString, toJavaRDD, toLocalIterator, top, toString, treeAggregate, treeReduce, union, zip, zipPartitions, zipPartitions, zipPartitions, zipPartitions, zipPartitions, zipPartitions, zipWithIndex, zipWithUniqueId
public static SparkContext sparkContext()
public static int id()
public static String name()
public static void name_$eq(String x$1)
public static final scala.collection.Seq<Dependency<?>> dependencies()
public static final Partition[] partitions()
public static final int getNumPartitions()
public static final scala.collection.Seq<String> preferredLocations(Partition split)
public static final scala.collection.Iterator<T> iterator(Partition split, TaskContext context)
public static <U> RDD<U> map(scala.Function1<T,U> f, scala.reflect.ClassTag<U> evidence$3)
public static <U> RDD<U> flatMap(scala.Function1<T,scala.collection.TraversableOnce<U>> f, scala.reflect.ClassTag<U> evidence$4)
public static RDD<T> distinct(int numPartitions, scala.math.Ordering<T> ord)
public static RDD<T> distinct()
public static RDD<T> repartition(int numPartitions, scala.math.Ordering<T> ord)
public static RDD<T> coalesce(int numPartitions, boolean shuffle, scala.Option<PartitionCoalescer> partitionCoalescer, scala.math.Ordering<T> ord)
public static RDD<T> sample(boolean withReplacement, double fraction, long seed)
public static RDD<T>[] randomSplit(double[] weights, long seed)
public static Object takeSample(boolean withReplacement, int num, long seed)
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)
public static RDD<T> intersection(RDD<T> other, Partitioner partitioner, scala.math.Ordering<T> ord)
public static RDD<Object> glom()
public static <U> RDD<scala.Tuple2<T,U>> cartesian(RDD<U> other, scala.reflect.ClassTag<U> evidence$5)
public static <K> RDD<scala.Tuple2<K,scala.collection.Iterable<T>>> groupBy(scala.Function1<T,K> f, scala.reflect.ClassTag<K> kt)
public static <K> RDD<scala.Tuple2<K,scala.collection.Iterable<T>>> groupBy(scala.Function1<T,K> f, int numPartitions, scala.reflect.ClassTag<K> kt)
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)
public static RDD<String> pipe(String command)
public static RDD<String> pipe(String command, scala.collection.Map<String,String> env)
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)
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)
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)
public static <U> RDD<scala.Tuple2<T,U>> zip(RDD<U> other, scala.reflect.ClassTag<U> evidence$9)
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)
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)
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)
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)
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)
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)
public static void foreach(scala.Function1<T,scala.runtime.BoxedUnit> f)
public static void foreachPartition(scala.Function1<scala.collection.Iterator<T>,scala.runtime.BoxedUnit> f)
public static Object collect()
public static scala.collection.Iterator<T> toLocalIterator()
public static <U> RDD<U> collect(scala.PartialFunction<T,U> f, scala.reflect.ClassTag<U> evidence$28)
public static RDD<T> subtract(RDD<T> other, Partitioner p, scala.math.Ordering<T> ord)
public static T reduce(scala.Function2<T,T,T> f)
public static T treeReduce(scala.Function2<T,T,T> f, int depth)
public static T fold(T zeroValue, scala.Function2<T,T,T> op)
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)
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$30)
public static PartialResult<BoundedDouble> countApprox(long timeout, double confidence)
public static scala.collection.Map<T,Object> countByValue(scala.math.Ordering<T> ord)
public static PartialResult<scala.collection.Map<T,BoundedDouble>> countByValueApprox(long timeout, double confidence, scala.math.Ordering<T> ord)
public static long countApproxDistinct(int p, int sp)
public static long countApproxDistinct(double relativeSD)
public static RDD<scala.Tuple2<T,Object>> zipWithIndex()
public static RDD<scala.Tuple2<T,Object>> zipWithUniqueId()
public static Object take(int num)
public static T first()
public static Object top(int num, scala.math.Ordering<T> ord)
public static Object takeOrdered(int num, scala.math.Ordering<T> ord)
public static T max(scala.math.Ordering<T> ord)
public static T min(scala.math.Ordering<T> ord)
public static boolean isEmpty()
public static void saveAsTextFile(String path)
public static void saveAsTextFile(String path, Class<? extends org.apache.hadoop.io.compress.CompressionCodec> codec)
public static void saveAsObjectFile(String path)
public static <K> RDD<scala.Tuple2<K,T>> keyBy(scala.Function1<T,K> f)
public static RDD<T> localCheckpoint()
public static SparkContext context()
public static String toDebugString()
public static String toString()
public static JavaRDD<T> toJavaRDD()
public static long sample$default$3()
public static <U> boolean mapPartitionsWithIndex$default$2()
public static boolean unpersist$default$1()
public static scala.math.Ordering<T> distinct$default$2(int numPartitions)
public static boolean coalesce$default$2()
public static scala.Option<PartitionCoalescer> coalesce$default$3()
public static scala.math.Ordering<T> coalesce$default$4(int numPartitions, boolean shuffle, scala.Option<PartitionCoalescer> partitionCoalescer)
public static scala.math.Ordering<T> repartition$default$2(int numPartitions)
public static scala.math.Ordering<T> subtract$default$3(RDD<T> other, Partitioner p)
public static scala.math.Ordering<T> intersection$default$3(RDD<T> other, Partitioner partitioner)
public static long randomSplit$default$2()
public static <K> boolean sortBy$default$2()
public static <K> int sortBy$default$3()
public static <U> boolean mapPartitions$default$2()
public static <K> scala.runtime.Null$ groupBy$default$4(scala.Function1<T,K> f, Partitioner p)
public static scala.collection.Map<String,String> pipe$default$2()
public static scala.Function1<scala.Function1<String,scala.runtime.BoxedUnit>,scala.runtime.BoxedUnit> pipe$default$3()
public static scala.Function2<T,scala.Function1<String,scala.runtime.BoxedUnit>,scala.runtime.BoxedUnit> pipe$default$4()
public static boolean pipe$default$5()
public static int pipe$default$6()
public static String pipe$default$7()
public static int treeReduce$default$2()
public static <U> int treeAggregate$default$4(U zeroValue)
public static double countApprox$default$2()
public static scala.math.Ordering<T> countByValue$default$1()
public static double countByValueApprox$default$2()
public static scala.math.Ordering<T> countByValueApprox$default$3(long timeout, double confidence)
public static long takeSample$default$3()
public static double countApproxDistinct$default$1()
public static <U> boolean mapPartitionsInternal$default$2()
public static scala.collection.Iterator<scala.Tuple2<Object,VD>> compute(Partition part, TaskContext context)
public static VertexRDD<VD> filter(scala.Function1<scala.Tuple2<Object,VD>,Object> pred)
public StorageLevel targetStorageLevel()
public VertexRDD<VD> reindex()
VertexRDD
public scala.Option<Partitioner> partitioner()
partitioner
in class VertexRDD<VD>
public VertexRDDImpl<VD> setName(String _name)
public VertexRDDImpl<VD> persist(StorageLevel newLevel)
public VertexRDDImpl<VD> unpersist(boolean blocking)
public VertexRDDImpl<VD> cache()
public StorageLevel getStorageLevel()
getStorageLevel
in class VertexRDD<VD>
public void checkpoint()
checkpoint
in class VertexRDD<VD>
public boolean isCheckpointed()
isCheckpointed
in class VertexRDD<VD>
public scala.Option<String> getCheckpointFile()
getCheckpointFile
in class VertexRDD<VD>
public long count()
public <VD2> VertexRDD<VD2> mapValues(scala.Function1<VD,VD2> f, scala.reflect.ClassTag<VD2> evidence$2)
VertexRDD
public <VD2> VertexRDD<VD2> mapValues(scala.Function2<Object,VD,VD2> f, scala.reflect.ClassTag<VD2> evidence$3)
VertexRDD
public VertexRDD<VD> minus(RDD<scala.Tuple2<Object,VD>> other)
VertexRDD
this
and other
, minus will act as a set difference
operation returning only those unique VertexId's present in this
.
public VertexRDD<VD> minus(VertexRDD<VD> other)
VertexRDD
this
and other
, minus will act as a set difference
operation returning only those unique VertexId's present in this
.
public VertexRDD<VD> diff(RDD<scala.Tuple2<Object,VD>> other)
VertexRDD
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.
public VertexRDD<VD> diff(VertexRDD<VD> other)
VertexRDD
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.
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)
VertexRDD
this
.
If other
is missing any vertex in this VertexRDD, f
is passed None
.
leftZipJoin
in class VertexRDD<VD>
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)f
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)
VertexRDD
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.
leftJoin
in class VertexRDD<VD>
other
- the other VertexRDD with which to joinf
- 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)f
.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)
VertexRDD
innerJoin
for the behavior of the join.innerZipJoin
in class VertexRDD<VD>
other
- (undocumented)f
- (undocumented)evidence$8
- (undocumented)evidence$9
- (undocumented)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)
VertexRDD
innerZipJoin
implementation
is used.
innerJoin
in class VertexRDD<VD>
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)this
, containing only vertices that appear in both
this
and other
, with values supplied by f
public <VD2> VertexRDD<VD2> aggregateUsingIndex(RDD<scala.Tuple2<Object,VD2>> messages, scala.Function2<VD2,VD2,VD2> reduceFunc, scala.reflect.ClassTag<VD2> evidence$12)
VertexRDD
messages
that have the same ids using reduceFunc
, returning a
VertexRDD co-indexed with this
.
aggregateUsingIndex
in class VertexRDD<VD>
messages
- an RDD containing messages to aggregate, where each message is a pair of its
target vertex ID and the message datareduceFunc
- the associative aggregation function for merging messages to the same vertexevidence$12
- (undocumented)this
, containing only vertices that received messages.
For those vertices, their values are the result of applying reduceFunc
to all received
messages.public VertexRDD<VD> reverseRoutingTables()
VertexRDD
VertexRDD
reflecting a reversal of all edge directions in the corresponding
EdgeRDD
.reverseRoutingTables
in class VertexRDD<VD>