public abstract class EdgeRDD<ED> extends RDD<Edge<ED>>
EdgeRDD[ED, VD]
extends RDD[Edge[ED}
by storing the edges in columnar format on each
partition for performance. It may additionally store the vertex attributes associated with each
edge to provide the triplet view. Shipping of the vertex attributes is managed by
impl.ReplicatedVertexView
.Constructor and Description |
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EdgeRDD(SparkContext sc,
scala.collection.Seq<Dependency<?>> deps) |
Modifier and Type | Method and Description |
---|---|
static RDD<T> |
$plus$plus(RDD<T> other) |
static <U> U |
aggregate(U zeroValue,
scala.Function2<U,T,U> seqOp,
scala.Function2<U,U,U> combOp,
scala.reflect.ClassTag<U> evidence$30) |
static RDD<T> |
cache() |
static <U> RDD<scala.Tuple2<T,U>> |
cartesian(RDD<U> other,
scala.reflect.ClassTag<U> evidence$5) |
static void |
checkpoint() |
static RDD<T> |
coalesce(int numPartitions,
boolean shuffle,
scala.Option<PartitionCoalescer> partitionCoalescer,
scala.math.Ordering<T> ord) |
static boolean |
coalesce$default$2() |
static scala.Option<PartitionCoalescer> |
coalesce$default$3() |
static scala.math.Ordering<T> |
coalesce$default$4(int numPartitions,
boolean shuffle,
scala.Option<PartitionCoalescer> partitionCoalescer) |
static Object |
collect() |
static <U> RDD<U> |
collect(scala.PartialFunction<T,U> f,
scala.reflect.ClassTag<U> evidence$29) |
scala.collection.Iterator<Edge<ED>> |
compute(Partition part,
TaskContext context)
:: DeveloperApi ::
Implemented by subclasses to compute a given partition.
|
static SparkContext |
context() |
static long |
count() |
static PartialResult<BoundedDouble> |
countApprox(long timeout,
double confidence) |
static double |
countApprox$default$2() |
static long |
countApproxDistinct(double relativeSD) |
static long |
countApproxDistinct(int p,
int sp) |
static double |
countApproxDistinct$default$1() |
static scala.collection.Map<T,Object> |
countByValue(scala.math.Ordering<T> ord) |
static scala.math.Ordering<T> |
countByValue$default$1() |
static PartialResult<scala.collection.Map<T,BoundedDouble>> |
countByValueApprox(long timeout,
double confidence,
scala.math.Ordering<T> ord) |
static double |
countByValueApprox$default$2() |
static scala.math.Ordering<T> |
countByValueApprox$default$3(long timeout,
double confidence) |
static scala.collection.Seq<Dependency<?>> |
dependencies() |
static RDD<T> |
distinct() |
static RDD<T> |
distinct(int numPartitions,
scala.math.Ordering<T> ord) |
static scala.math.Ordering<T> |
distinct$default$2(int numPartitions) |
static RDD<T> |
filter(scala.Function1<T,Object> f) |
static T |
first() |
static <U> RDD<U> |
flatMap(scala.Function1<T,scala.collection.TraversableOnce<U>> f,
scala.reflect.ClassTag<U> evidence$4) |
static T |
fold(T zeroValue,
scala.Function2<T,T,T> op) |
static void |
foreach(scala.Function1<T,scala.runtime.BoxedUnit> f) |
static void |
foreachPartition(scala.Function1<scala.collection.Iterator<T>,scala.runtime.BoxedUnit> f) |
static <ED,VD> EdgeRDDImpl<ED,VD> |
fromEdges(RDD<Edge<ED>> edges,
scala.reflect.ClassTag<ED> evidence$4,
scala.reflect.ClassTag<VD> evidence$5)
Creates an EdgeRDD from a set of edges.
|
static scala.Option<String> |
getCheckpointFile() |
static int |
getNumPartitions() |
static StorageLevel |
getStorageLevel() |
static RDD<Object> |
glom() |
static <K> RDD<scala.Tuple2<K,scala.collection.Iterable<T>>> |
groupBy(scala.Function1<T,K> f,
scala.reflect.ClassTag<K> kt) |
static <K> RDD<scala.Tuple2<K,scala.collection.Iterable<T>>> |
groupBy(scala.Function1<T,K> f,
int numPartitions,
scala.reflect.ClassTag<K> kt) |
static <K> RDD<scala.Tuple2<K,scala.collection.Iterable<T>>> |
groupBy(scala.Function1<T,K> f,
Partitioner p,
scala.reflect.ClassTag<K> kt,
scala.math.Ordering<K> ord) |
static <K> scala.runtime.Null$ |
groupBy$default$4(scala.Function1<T,K> f,
Partitioner p) |
static int |
id() |
abstract <ED2,ED3> EdgeRDD<ED3> |
innerJoin(EdgeRDD<ED2> other,
scala.Function4<Object,Object,ED,ED2,ED3> f,
scala.reflect.ClassTag<ED2> evidence$2,
scala.reflect.ClassTag<ED3> evidence$3)
Inner joins this EdgeRDD with another EdgeRDD, assuming both are partitioned using the same
PartitionStrategy . |
static RDD<T> |
intersection(RDD<T> other) |
static RDD<T> |
intersection(RDD<T> other,
int numPartitions) |
static RDD<T> |
intersection(RDD<T> other,
Partitioner partitioner,
scala.math.Ordering<T> ord) |
static scala.math.Ordering<T> |
intersection$default$3(RDD<T> other,
Partitioner partitioner) |
static boolean |
isCheckpointed() |
static boolean |
isEmpty() |
static scala.collection.Iterator<T> |
iterator(Partition split,
TaskContext context) |
static <K> RDD<scala.Tuple2<K,T>> |
keyBy(scala.Function1<T,K> f) |
static RDD<T> |
localCheckpoint() |
static <U> RDD<U> |
map(scala.Function1<T,U> f,
scala.reflect.ClassTag<U> evidence$3) |
static <U> RDD<U> |
mapPartitions(scala.Function1<scala.collection.Iterator<T>,scala.collection.Iterator<U>> f,
boolean preservesPartitioning,
scala.reflect.ClassTag<U> evidence$6) |
static <U> boolean |
mapPartitions$default$2() |
static <U> boolean |
mapPartitionsInternal$default$2() |
static <U> RDD<U> |
mapPartitionsWithIndex(scala.Function2<Object,scala.collection.Iterator<T>,scala.collection.Iterator<U>> f,
boolean preservesPartitioning,
scala.reflect.ClassTag<U> evidence$9) |
static <U> boolean |
mapPartitionsWithIndex$default$2() |
static <U> boolean |
mapPartitionsWithIndexInternal$default$2() |
abstract <ED2> EdgeRDD<ED2> |
mapValues(scala.Function1<Edge<ED>,ED2> f,
scala.reflect.ClassTag<ED2> evidence$1)
Map the values in an edge partitioning preserving the structure but changing the values.
|
static T |
max(scala.math.Ordering<T> ord) |
static T |
min(scala.math.Ordering<T> ord) |
static void |
name_$eq(String x$1) |
static String |
name() |
static scala.Option<Partitioner> |
partitioner() |
static Partition[] |
partitions() |
static RDD<T> |
persist() |
static RDD<T> |
persist(StorageLevel newLevel) |
static RDD<String> |
pipe(scala.collection.Seq<String> command,
scala.collection.Map<String,String> env,
scala.Function1<scala.Function1<String,scala.runtime.BoxedUnit>,scala.runtime.BoxedUnit> printPipeContext,
scala.Function2<T,scala.Function1<String,scala.runtime.BoxedUnit>,scala.runtime.BoxedUnit> printRDDElement,
boolean separateWorkingDir,
int bufferSize,
String encoding) |
static RDD<String> |
pipe(String command) |
static RDD<String> |
pipe(String command,
scala.collection.Map<String,String> env) |
static scala.collection.Map<String,String> |
pipe$default$2() |
static scala.Function1<scala.Function1<String,scala.runtime.BoxedUnit>,scala.runtime.BoxedUnit> |
pipe$default$3() |
static scala.Function2<T,scala.Function1<String,scala.runtime.BoxedUnit>,scala.runtime.BoxedUnit> |
pipe$default$4() |
static boolean |
pipe$default$5() |
static int |
pipe$default$6() |
static String |
pipe$default$7() |
static scala.collection.Seq<String> |
preferredLocations(Partition split) |
static RDD<T>[] |
randomSplit(double[] weights,
long seed) |
static long |
randomSplit$default$2() |
static T |
reduce(scala.Function2<T,T,T> f) |
static RDD<T> |
repartition(int numPartitions,
scala.math.Ordering<T> ord) |
static scala.math.Ordering<T> |
repartition$default$2(int numPartitions) |
abstract EdgeRDD<ED> |
reverse()
Reverse all the edges in this RDD.
|
static RDD<T> |
sample(boolean withReplacement,
double fraction,
long seed) |
static long |
sample$default$3() |
static void |
saveAsObjectFile(String path) |
static void |
saveAsTextFile(String path) |
static void |
saveAsTextFile(String path,
Class<? extends org.apache.hadoop.io.compress.CompressionCodec> codec) |
static RDD<T> |
setName(String _name) |
static <K> RDD<T> |
sortBy(scala.Function1<T,K> f,
boolean ascending,
int numPartitions,
scala.math.Ordering<K> ord,
scala.reflect.ClassTag<K> ctag) |
static <K> boolean |
sortBy$default$2() |
static <K> int |
sortBy$default$3() |
static SparkContext |
sparkContext() |
static RDD<T> |
subtract(RDD<T> other) |
static RDD<T> |
subtract(RDD<T> other,
int numPartitions) |
static RDD<T> |
subtract(RDD<T> other,
Partitioner p,
scala.math.Ordering<T> ord) |
static scala.math.Ordering<T> |
subtract$default$3(RDD<T> other,
Partitioner p) |
static Object |
take(int num) |
static Object |
takeOrdered(int num,
scala.math.Ordering<T> ord) |
static Object |
takeSample(boolean withReplacement,
int num,
long seed) |
static long |
takeSample$default$3() |
static String |
toDebugString() |
static JavaRDD<T> |
toJavaRDD() |
static scala.collection.Iterator<T> |
toLocalIterator() |
static Object |
top(int num,
scala.math.Ordering<T> ord) |
static String |
toString() |
static <U> U |
treeAggregate(U zeroValue,
scala.Function2<U,T,U> seqOp,
scala.Function2<U,U,U> combOp,
int depth,
scala.reflect.ClassTag<U> evidence$31) |
static <U> int |
treeAggregate$default$4(U zeroValue) |
static T |
treeReduce(scala.Function2<T,T,T> f,
int depth) |
static int |
treeReduce$default$2() |
static RDD<T> |
union(RDD<T> other) |
static RDD<T> |
unpersist(boolean blocking) |
static boolean |
unpersist$default$1() |
static <U> RDD<scala.Tuple2<T,U>> |
zip(RDD<U> other,
scala.reflect.ClassTag<U> evidence$10) |
static <B,V> RDD<V> |
zipPartitions(RDD<B> rdd2,
boolean preservesPartitioning,
scala.Function2<scala.collection.Iterator<T>,scala.collection.Iterator<B>,scala.collection.Iterator<V>> f,
scala.reflect.ClassTag<B> evidence$11,
scala.reflect.ClassTag<V> evidence$12) |
static <B,V> RDD<V> |
zipPartitions(RDD<B> rdd2,
scala.Function2<scala.collection.Iterator<T>,scala.collection.Iterator<B>,scala.collection.Iterator<V>> f,
scala.reflect.ClassTag<B> evidence$13,
scala.reflect.ClassTag<V> evidence$14) |
static <B,C,V> RDD<V> |
zipPartitions(RDD<B> rdd2,
RDD<C> rdd3,
boolean preservesPartitioning,
scala.Function3<scala.collection.Iterator<T>,scala.collection.Iterator<B>,scala.collection.Iterator<C>,scala.collection.Iterator<V>> f,
scala.reflect.ClassTag<B> evidence$15,
scala.reflect.ClassTag<C> evidence$16,
scala.reflect.ClassTag<V> evidence$17) |
static <B,C,V> RDD<V> |
zipPartitions(RDD<B> rdd2,
RDD<C> rdd3,
scala.Function3<scala.collection.Iterator<T>,scala.collection.Iterator<B>,scala.collection.Iterator<C>,scala.collection.Iterator<V>> f,
scala.reflect.ClassTag<B> evidence$18,
scala.reflect.ClassTag<C> evidence$19,
scala.reflect.ClassTag<V> evidence$20) |
static <B,C,D,V> RDD<V> |
zipPartitions(RDD<B> rdd2,
RDD<C> rdd3,
RDD<D> rdd4,
boolean preservesPartitioning,
scala.Function4<scala.collection.Iterator<T>,scala.collection.Iterator<B>,scala.collection.Iterator<C>,scala.collection.Iterator<D>,scala.collection.Iterator<V>> f,
scala.reflect.ClassTag<B> evidence$21,
scala.reflect.ClassTag<C> evidence$22,
scala.reflect.ClassTag<D> evidence$23,
scala.reflect.ClassTag<V> evidence$24) |
static <B,C,D,V> RDD<V> |
zipPartitions(RDD<B> rdd2,
RDD<C> rdd3,
RDD<D> rdd4,
scala.Function4<scala.collection.Iterator<T>,scala.collection.Iterator<B>,scala.collection.Iterator<C>,scala.collection.Iterator<D>,scala.collection.Iterator<V>> f,
scala.reflect.ClassTag<B> evidence$25,
scala.reflect.ClassTag<C> evidence$26,
scala.reflect.ClassTag<D> evidence$27,
scala.reflect.ClassTag<V> evidence$28) |
static RDD<scala.Tuple2<T,Object>> |
zipWithIndex() |
static RDD<scala.Tuple2<T,Object>> |
zipWithUniqueId() |
aggregate, cache, cartesian, checkpoint, coalesce, collect, collect, context, count, countApprox, countApproxDistinct, countApproxDistinct, countByValue, countByValueApprox, dependencies, distinct, distinct, doubleRDDToDoubleRDDFunctions, filter, first, flatMap, fold, foreach, foreachPartition, getCheckpointFile, getNumPartitions, getStorageLevel, glom, groupBy, groupBy, groupBy, id, intersection, intersection, intersection, isCheckpointed, isEmpty, iterator, keyBy, localCheckpoint, map, mapPartitions, mapPartitionsWithIndex, max, min, name, numericRDDToDoubleRDDFunctions, partitioner, partitions, persist, persist, pipe, pipe, pipe, preferredLocations, randomSplit, rddToAsyncRDDActions, rddToOrderedRDDFunctions, rddToPairRDDFunctions, rddToSequenceFileRDDFunctions, reduce, repartition, sample, saveAsObjectFile, saveAsTextFile, saveAsTextFile, setName, sortBy, sparkContext, subtract, subtract, subtract, take, takeOrdered, takeSample, toDebugString, toJavaRDD, toLocalIterator, top, toString, treeAggregate, treeReduce, union, unpersist, zip, zipPartitions, zipPartitions, zipPartitions, zipPartitions, zipPartitions, zipPartitions, zipWithIndex, zipWithUniqueId
initializeLogging, initializeLogIfNecessary, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning
public EdgeRDD(SparkContext sc, scala.collection.Seq<Dependency<?>> deps)
public static <ED,VD> EdgeRDDImpl<ED,VD> fromEdges(RDD<Edge<ED>> edges, scala.reflect.ClassTag<ED> evidence$4, scala.reflect.ClassTag<VD> evidence$5)
edges
- (undocumented)evidence$4
- (undocumented)evidence$5
- (undocumented)public static scala.Option<Partitioner> partitioner()
public static SparkContext sparkContext()
public static int id()
public static String name()
public static void name_$eq(String x$1)
public static RDD<T> setName(String _name)
public static RDD<T> persist(StorageLevel newLevel)
public static RDD<T> persist()
public static RDD<T> cache()
public static RDD<T> unpersist(boolean blocking)
public static StorageLevel getStorageLevel()
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> filter(scala.Function1<T,Object> f)
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$9)
public static <U> RDD<scala.Tuple2<T,U>> zip(RDD<U> other, scala.reflect.ClassTag<U> evidence$10)
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)
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)
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)
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)
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)
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)
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$29)
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$30)
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$31)
public static long count()
public static PartialResult<BoundedDouble> countApprox(long timeout, double confidence)
public static scala.collection.Map<T,Object> countByValue(scala.math.Ordering<T> ord)
public static PartialResult<scala.collection.Map<T,BoundedDouble>> countByValueApprox(long timeout, double confidence, scala.math.Ordering<T> ord)
public static long countApproxDistinct(int p, int sp)
public static long countApproxDistinct(double relativeSD)
public static RDD<scala.Tuple2<T,Object>> zipWithIndex()
public static RDD<scala.Tuple2<T,Object>> zipWithUniqueId()
public static Object take(int num)
public static T first()
public static Object top(int num, scala.math.Ordering<T> ord)
public static Object takeOrdered(int num, scala.math.Ordering<T> ord)
public static T max(scala.math.Ordering<T> ord)
public static T min(scala.math.Ordering<T> ord)
public static boolean isEmpty()
public static void saveAsTextFile(String path)
public static void saveAsTextFile(String path, Class<? extends org.apache.hadoop.io.compress.CompressionCodec> codec)
public static void saveAsObjectFile(String path)
public static <K> RDD<scala.Tuple2<K,T>> keyBy(scala.Function1<T,K> f)
public static void checkpoint()
public static RDD<T> localCheckpoint()
public static boolean isCheckpointed()
public static scala.Option<String> getCheckpointFile()
public static SparkContext context()
public static String toDebugString()
public static String toString()
public static JavaRDD<T> toJavaRDD()
public static long sample$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$1()
public static <U> boolean mapPartitionsWithIndexInternal$default$2()
public static <U> boolean mapPartitionsInternal$default$2()
public scala.collection.Iterator<Edge<ED>> compute(Partition part, TaskContext context)
RDD
public abstract <ED2> EdgeRDD<ED2> mapValues(scala.Function1<Edge<ED>,ED2> f, scala.reflect.ClassTag<ED2> evidence$1)
f
- the function from an edge to a new edge valueevidence$1
- (undocumented)public abstract EdgeRDD<ED> reverse()
public abstract <ED2,ED3> EdgeRDD<ED3> innerJoin(EdgeRDD<ED2> other, scala.Function4<Object,Object,ED,ED2,ED3> f, scala.reflect.ClassTag<ED2> evidence$2, scala.reflect.ClassTag<ED3> evidence$3)
PartitionStrategy
.
other
- the EdgeRDD to join withf
- the join function applied to corresponding values of this
and other
evidence$2
- (undocumented)evidence$3
- (undocumented)this
and other
,
with values supplied by f