public class EdgeRDDImpl<ED,VD> extends EdgeRDD<ED>
Modifier and Type | Method and Description |
---|---|
static RDD<T> |
$plus$plus(RDD<T> other) |
static <U> U |
aggregate(U zeroValue,
scala.Function2<U,T,U> seqOp,
scala.Function2<U,U,U> combOp,
scala.reflect.ClassTag<U> evidence$29) |
EdgeRDDImpl<ED,VD> |
cache()
Persists the edge partitions using `targetStorageLevel`, which defaults to MEMORY_ONLY.
|
static <U> RDD<scala.Tuple2<T,U>> |
cartesian(RDD<U> other,
scala.reflect.ClassTag<U> evidence$5) |
void |
checkpoint() |
protected static void |
clearDependencies() |
static RDD<T> |
coalesce(int numPartitions,
boolean shuffle,
scala.Option<PartitionCoalescer> partitionCoalescer,
scala.math.Ordering<T> ord) |
static boolean |
coalesce$default$2() |
static scala.Option<PartitionCoalescer> |
coalesce$default$3() |
static scala.math.Ordering<T> |
coalesce$default$4(int numPartitions,
boolean shuffle,
scala.Option<PartitionCoalescer> partitionCoalescer) |
Edge<ED>[] |
collect() |
static scala.collection.Iterator<Edge<ED>> |
compute(Partition part,
TaskContext context) |
static SparkContext |
context() |
long |
count()
The number of edges in the RDD.
|
static PartialResult<BoundedDouble> |
countApprox(long timeout,
double confidence) |
static double |
countApprox$default$2() |
static long |
countApproxDistinct(double relativeSD) |
static long |
countApproxDistinct(int p,
int sp) |
static double |
countApproxDistinct$default$1() |
static scala.collection.Map<T,java.lang.Object> |
countByValue(scala.math.Ordering<T> ord) |
static scala.math.Ordering<T> |
countByValue$default$1() |
static PartialResult<scala.collection.Map<T,BoundedDouble>> |
countByValueApprox(long timeout,
double confidence,
scala.math.Ordering<T> ord) |
static double |
countByValueApprox$default$2() |
static scala.math.Ordering<T> |
countByValueApprox$default$3(long timeout,
double confidence) |
static scala.collection.Seq<Dependency<?>> |
dependencies() |
static RDD<T> |
distinct() |
static RDD<T> |
distinct(int numPartitions,
scala.math.Ordering<T> ord) |
static scala.math.Ordering<T> |
distinct$default$2(int numPartitions) |
EdgeRDDImpl<ED,VD> |
filter(scala.Function1<EdgeTriplet<VD,ED>,java.lang.Object> epred,
scala.Function2<java.lang.Object,VD,java.lang.Object> vpred) |
static T |
first() |
protected static <U> RDD<U> |
firstParent(scala.reflect.ClassTag<U> evidence$31) |
static <U> RDD<U> |
flatMap(scala.Function1<T,scala.collection.TraversableOnce<U>> f,
scala.reflect.ClassTag<U> evidence$4) |
static T |
fold(T zeroValue,
scala.Function2<T,T,T> op) |
static void |
foreach(scala.Function1<T,scala.runtime.BoxedUnit> f) |
static void |
foreachPartition(scala.Function1<scala.collection.Iterator<T>,scala.runtime.BoxedUnit> f) |
scala.Option<java.lang.String> |
getCheckpointFile() |
protected static scala.collection.Seq<Dependency<?>> |
getDependencies() |
static int |
getNumPartitions() |
protected static Partition[] |
getPartitions() |
protected static scala.collection.Seq<java.lang.String> |
getPreferredLocations(Partition split) |
StorageLevel |
getStorageLevel() |
static RDD<java.lang.Object> |
glom() |
static <K> RDD<scala.Tuple2<K,scala.collection.Iterable<T>>> |
groupBy(scala.Function1<T,K> f,
scala.reflect.ClassTag<K> kt) |
static <K> RDD<scala.Tuple2<K,scala.collection.Iterable<T>>> |
groupBy(scala.Function1<T,K> f,
int numPartitions,
scala.reflect.ClassTag<K> kt) |
static <K> RDD<scala.Tuple2<K,scala.collection.Iterable<T>>> |
groupBy(scala.Function1<T,K> f,
Partitioner p,
scala.reflect.ClassTag<K> kt,
scala.math.Ordering<K> ord) |
static <K> scala.runtime.Null$ |
groupBy$default$4(scala.Function1<T,K> f,
Partitioner p) |
static int |
id() |
protected static void |
initializeLogIfNecessary(boolean isInterpreter) |
<ED2,ED3> EdgeRDDImpl<ED3,VD> |
innerJoin(EdgeRDD<ED2> other,
scala.Function4<java.lang.Object,java.lang.Object,ED,ED2,ED3> f,
scala.reflect.ClassTag<ED2> evidence$4,
scala.reflect.ClassTag<ED3> evidence$5)
Inner joins this EdgeRDD with another EdgeRDD, assuming both are partitioned using the same
PartitionStrategy . |
static RDD<T> |
intersection(RDD<T> other) |
static RDD<T> |
intersection(RDD<T> other,
int numPartitions) |
static RDD<T> |
intersection(RDD<T> other,
Partitioner partitioner,
scala.math.Ordering<T> ord) |
static scala.math.Ordering<T> |
intersection$default$3(RDD<T> other,
Partitioner partitioner) |
boolean |
isCheckpointed() |
static boolean |
isEmpty() |
protected static boolean |
isTraceEnabled() |
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() |
protected static org.slf4j.Logger |
log() |
protected static void |
logDebug(scala.Function0<java.lang.String> msg) |
protected static void |
logDebug(scala.Function0<java.lang.String> msg,
java.lang.Throwable throwable) |
protected static void |
logError(scala.Function0<java.lang.String> msg) |
protected static void |
logError(scala.Function0<java.lang.String> msg,
java.lang.Throwable throwable) |
protected static void |
logInfo(scala.Function0<java.lang.String> msg) |
protected static void |
logInfo(scala.Function0<java.lang.String> msg,
java.lang.Throwable throwable) |
protected static java.lang.String |
logName() |
protected static void |
logTrace(scala.Function0<java.lang.String> msg) |
protected static void |
logTrace(scala.Function0<java.lang.String> msg,
java.lang.Throwable throwable) |
protected static void |
logWarning(scala.Function0<java.lang.String> msg) |
protected static void |
logWarning(scala.Function0<java.lang.String> msg,
java.lang.Throwable throwable) |
static <U> RDD<U> |
map(scala.Function1<T,U> f,
scala.reflect.ClassTag<U> evidence$3) |
<ED2,VD2> EdgeRDDImpl<ED2,VD2> |
mapEdgePartitions(scala.Function2<java.lang.Object,org.apache.spark.graphx.impl.EdgePartition<ED,VD>,org.apache.spark.graphx.impl.EdgePartition<ED2,VD2>> f,
scala.reflect.ClassTag<ED2> evidence$6,
scala.reflect.ClassTag<VD2> evidence$7) |
static <U> RDD<U> |
mapPartitions(scala.Function1<scala.collection.Iterator<T>,scala.collection.Iterator<U>> f,
boolean preservesPartitioning,
scala.reflect.ClassTag<U> evidence$6) |
static <U> boolean |
mapPartitions$default$2() |
static <U> boolean |
mapPartitionsInternal$default$2() |
static <U> RDD<U> |
mapPartitionsWithIndex(scala.Function2<java.lang.Object,scala.collection.Iterator<T>,scala.collection.Iterator<U>> f,
boolean preservesPartitioning,
scala.reflect.ClassTag<U> evidence$8) |
static <U> boolean |
mapPartitionsWithIndex$default$2() |
<ED2> EdgeRDDImpl<ED2,VD> |
mapValues(scala.Function1<Edge<ED>,ED2> f,
scala.reflect.ClassTag<ED2> evidence$3)
Map the values in an edge partitioning preserving the structure but changing the values.
|
static T |
max(scala.math.Ordering<T> ord) |
static T |
min(scala.math.Ordering<T> ord) |
static void |
name_$eq(java.lang.String x$1) |
static java.lang.String |
name() |
protected static <U> RDD<U> |
parent(int j,
scala.reflect.ClassTag<U> evidence$32) |
scala.Option<Partitioner> |
partitioner()
If
partitionsRDD already has a partitioner, use it. |
static Partition[] |
partitions() |
RDD<scala.Tuple2<java.lang.Object,org.apache.spark.graphx.impl.EdgePartition<ED,VD>>> |
partitionsRDD() |
EdgeRDDImpl<ED,VD> |
persist(StorageLevel newLevel)
Persists the edge partitions at the specified storage level, ignoring any existing target
storage level.
|
static RDD<java.lang.String> |
pipe(scala.collection.Seq<java.lang.String> command,
scala.collection.Map<java.lang.String,java.lang.String> env,
scala.Function1<scala.Function1<java.lang.String,scala.runtime.BoxedUnit>,scala.runtime.BoxedUnit> printPipeContext,
scala.Function2<T,scala.Function1<java.lang.String,scala.runtime.BoxedUnit>,scala.runtime.BoxedUnit> printRDDElement,
boolean separateWorkingDir,
int bufferSize) |
static RDD<java.lang.String> |
pipe(java.lang.String command) |
static RDD<java.lang.String> |
pipe(java.lang.String command,
scala.collection.Map<java.lang.String,java.lang.String> env) |
static scala.collection.Map<java.lang.String,java.lang.String> |
pipe$default$2() |
static scala.Function1<scala.Function1<java.lang.String,scala.runtime.BoxedUnit>,scala.runtime.BoxedUnit> |
pipe$default$3() |
static scala.Function2<T,scala.Function1<java.lang.String,scala.runtime.BoxedUnit>,scala.runtime.BoxedUnit> |
pipe$default$4() |
static boolean |
pipe$default$5() |
static int |
pipe$default$6() |
static scala.collection.Seq<java.lang.String> |
preferredLocations(Partition split) |
static RDD<T>[] |
randomSplit(double[] weights,
long seed) |
static long |
randomSplit$default$2() |
static T |
reduce(scala.Function2<T,T,T> f) |
static RDD<T> |
repartition(int numPartitions,
scala.math.Ordering<T> ord) |
static scala.math.Ordering<T> |
repartition$default$2(int numPartitions) |
EdgeRDDImpl<ED,VD> |
reverse()
Reverse all the edges in this RDD.
|
static RDD<T> |
sample(boolean withReplacement,
double fraction,
long seed) |
static long |
sample$default$3() |
static void |
saveAsObjectFile(java.lang.String path) |
static void |
saveAsTextFile(java.lang.String path) |
static void |
saveAsTextFile(java.lang.String path,
java.lang.Class<? extends org.apache.hadoop.io.compress.CompressionCodec> codec) |
EdgeRDDImpl<ED,VD> |
setName(java.lang.String _name) |
static <K> RDD<T> |
sortBy(scala.Function1<T,K> f,
boolean ascending,
int numPartitions,
scala.math.Ordering<K> ord,
scala.reflect.ClassTag<K> ctag) |
static <K> boolean |
sortBy$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$3(RDD<T> other,
Partitioner p) |
static java.lang.Object |
take(int num) |
static java.lang.Object |
takeOrdered(int num,
scala.math.Ordering<T> ord) |
static java.lang.Object |
takeSample(boolean withReplacement,
int num,
long seed) |
static long |
takeSample$default$3() |
StorageLevel |
targetStorageLevel() |
static java.lang.String |
toDebugString() |
static JavaRDD<T> |
toJavaRDD() |
static scala.collection.Iterator<T> |
toLocalIterator() |
static java.lang.Object |
top(int num,
scala.math.Ordering<T> ord) |
static java.lang.String |
toString() |
static <U> U |
treeAggregate(U zeroValue,
scala.Function2<U,T,U> seqOp,
scala.Function2<U,U,U> combOp,
int depth,
scala.reflect.ClassTag<U> evidence$30) |
static <U> int |
treeAggregate$default$4(U zeroValue) |
static T |
treeReduce(scala.Function2<T,T,T> f,
int depth) |
static int |
treeReduce$default$2() |
static RDD<T> |
union(RDD<T> other) |
EdgeRDDImpl<ED,VD> |
unpersist(boolean blocking) |
static boolean |
unpersist$default$1() |
static <U> RDD<scala.Tuple2<T,U>> |
zip(RDD<U> other,
scala.reflect.ClassTag<U> evidence$9) |
static <B,V> RDD<V> |
zipPartitions(RDD<B> rdd2,
boolean preservesPartitioning,
scala.Function2<scala.collection.Iterator<T>,scala.collection.Iterator<B>,scala.collection.Iterator<V>> f,
scala.reflect.ClassTag<B> evidence$10,
scala.reflect.ClassTag<V> evidence$11) |
static <B,V> RDD<V> |
zipPartitions(RDD<B> rdd2,
scala.Function2<scala.collection.Iterator<T>,scala.collection.Iterator<B>,scala.collection.Iterator<V>> f,
scala.reflect.ClassTag<B> evidence$12,
scala.reflect.ClassTag<V> evidence$13) |
static <B,C,V> RDD<V> |
zipPartitions(RDD<B> rdd2,
RDD<C> rdd3,
boolean preservesPartitioning,
scala.Function3<scala.collection.Iterator<T>,scala.collection.Iterator<B>,scala.collection.Iterator<C>,scala.collection.Iterator<V>> f,
scala.reflect.ClassTag<B> evidence$14,
scala.reflect.ClassTag<C> evidence$15,
scala.reflect.ClassTag<V> evidence$16) |
static <B,C,V> RDD<V> |
zipPartitions(RDD<B> rdd2,
RDD<C> rdd3,
scala.Function3<scala.collection.Iterator<T>,scala.collection.Iterator<B>,scala.collection.Iterator<C>,scala.collection.Iterator<V>> f,
scala.reflect.ClassTag<B> evidence$17,
scala.reflect.ClassTag<C> evidence$18,
scala.reflect.ClassTag<V> evidence$19) |
static <B,C,D,V> RDD<V> |
zipPartitions(RDD<B> rdd2,
RDD<C> rdd3,
RDD<D> rdd4,
boolean preservesPartitioning,
scala.Function4<scala.collection.Iterator<T>,scala.collection.Iterator<B>,scala.collection.Iterator<C>,scala.collection.Iterator<D>,scala.collection.Iterator<V>> f,
scala.reflect.ClassTag<B> evidence$20,
scala.reflect.ClassTag<C> evidence$21,
scala.reflect.ClassTag<D> evidence$22,
scala.reflect.ClassTag<V> evidence$23) |
static <B,C,D,V> RDD<V> |
zipPartitions(RDD<B> rdd2,
RDD<C> rdd3,
RDD<D> rdd4,
scala.Function4<scala.collection.Iterator<T>,scala.collection.Iterator<B>,scala.collection.Iterator<C>,scala.collection.Iterator<D>,scala.collection.Iterator<V>> f,
scala.reflect.ClassTag<B> evidence$24,
scala.reflect.ClassTag<C> evidence$25,
scala.reflect.ClassTag<D> evidence$26,
scala.reflect.ClassTag<V> evidence$27) |
static RDD<scala.Tuple2<T,java.lang.Object>> |
zipWithIndex() |
static RDD<scala.Tuple2<T,java.lang.Object>> |
zipWithUniqueId() |
collect, compute, filter, fromEdges, getPartitions, persist
aggregate, cartesian, clearDependencies, coalesce, collect, context, countApprox, countApproxDistinct, countApproxDistinct, countByValue, countByValueApprox, dependencies, distinct, distinct, doubleRDDToDoubleRDDFunctions, filter, first, firstParent, flatMap, fold, foreach, foreachPartition, getDependencies, getNumPartitions, getPreferredLocations, glom, groupBy, groupBy, groupBy, id, intersection, intersection, intersection, isEmpty, iterator, keyBy, localCheckpoint, map, mapPartitions, mapPartitionsWithIndex, max, min, name, numericRDDToDoubleRDDFunctions, parent, 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
protected static java.lang.String logName()
protected static org.slf4j.Logger log()
protected static void logInfo(scala.Function0<java.lang.String> msg)
protected static void logDebug(scala.Function0<java.lang.String> msg)
protected static void logTrace(scala.Function0<java.lang.String> msg)
protected static void logWarning(scala.Function0<java.lang.String> msg)
protected static void logError(scala.Function0<java.lang.String> msg)
protected static void logInfo(scala.Function0<java.lang.String> msg, java.lang.Throwable throwable)
protected static void logDebug(scala.Function0<java.lang.String> msg, java.lang.Throwable throwable)
protected static void logTrace(scala.Function0<java.lang.String> msg, java.lang.Throwable throwable)
protected static void logWarning(scala.Function0<java.lang.String> msg, java.lang.Throwable throwable)
protected static void logError(scala.Function0<java.lang.String> msg, java.lang.Throwable throwable)
protected static boolean isTraceEnabled()
protected static void initializeLogIfNecessary(boolean isInterpreter)
protected static scala.collection.Seq<Dependency<?>> getDependencies()
protected static scala.collection.Seq<java.lang.String> getPreferredLocations(Partition split)
public static SparkContext sparkContext()
public static int id()
public static java.lang.String name()
public static void name_$eq(java.lang.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<java.lang.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 java.lang.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<java.lang.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<java.lang.String> pipe(java.lang.String command)
public static RDD<java.lang.String> pipe(java.lang.String command, scala.collection.Map<java.lang.String,java.lang.String> env)
public static RDD<java.lang.String> pipe(scala.collection.Seq<java.lang.String> command, scala.collection.Map<java.lang.String,java.lang.String> env, scala.Function1<scala.Function1<java.lang.String,scala.runtime.BoxedUnit>,scala.runtime.BoxedUnit> printPipeContext, scala.Function2<T,scala.Function1<java.lang.String,scala.runtime.BoxedUnit>,scala.runtime.BoxedUnit> printRDDElement, boolean separateWorkingDir, int bufferSize)
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<java.lang.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 scala.collection.Iterator<T> toLocalIterator()
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,java.lang.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,java.lang.Object>> zipWithIndex()
public static RDD<scala.Tuple2<T,java.lang.Object>> zipWithUniqueId()
public static java.lang.Object take(int num)
public static T first()
public static java.lang.Object top(int num, scala.math.Ordering<T> ord)
public static java.lang.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(java.lang.String path)
public static void saveAsTextFile(java.lang.String path, java.lang.Class<? extends org.apache.hadoop.io.compress.CompressionCodec> codec)
public static void saveAsObjectFile(java.lang.String path)
public static <K> RDD<scala.Tuple2<K,T>> keyBy(scala.Function1<T,K> f)
public static RDD<T> localCheckpoint()
protected static <U> RDD<U> firstParent(scala.reflect.ClassTag<U> evidence$31)
protected static <U> RDD<U> parent(int j, scala.reflect.ClassTag<U> evidence$32)
public static SparkContext context()
protected static void clearDependencies()
public static java.lang.String toDebugString()
public static java.lang.String toString()
public static JavaRDD<T> toJavaRDD()
public static long sample$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$4(scala.Function1<T,K> f, Partitioner p)
public static scala.collection.Map<java.lang.String,java.lang.String> pipe$default$2()
public static scala.Function1<scala.Function1<java.lang.String,scala.runtime.BoxedUnit>,scala.runtime.BoxedUnit> pipe$default$3()
public static scala.Function2<T,scala.Function1<java.lang.String,scala.runtime.BoxedUnit>,scala.runtime.BoxedUnit> pipe$default$4()
public static boolean pipe$default$5()
public static int pipe$default$6()
public static int treeReduce$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()
protected static Partition[] getPartitions()
public static scala.collection.Iterator<Edge<ED>> compute(Partition part, TaskContext context)
public RDD<scala.Tuple2<java.lang.Object,org.apache.spark.graphx.impl.EdgePartition<ED,VD>>> partitionsRDD()
public StorageLevel targetStorageLevel()
public EdgeRDDImpl<ED,VD> setName(java.lang.String _name)
public scala.Option<Partitioner> partitioner()
partitionsRDD
already has a partitioner, use it. Otherwise assume that the
PartitionID
s in partitionsRDD
correspond to the actual partitions and create a new
partitioner that allows co-partitioning with partitionsRDD
.partitioner
in class EdgeRDD<ED>
public EdgeRDDImpl<ED,VD> persist(StorageLevel newLevel)
public EdgeRDDImpl<ED,VD> unpersist(boolean blocking)
public EdgeRDDImpl<ED,VD> cache()
public StorageLevel getStorageLevel()
getStorageLevel
in class EdgeRDD<ED>
public void checkpoint()
checkpoint
in class EdgeRDD<ED>
public boolean isCheckpointed()
isCheckpointed
in class EdgeRDD<ED>
public scala.Option<java.lang.String> getCheckpointFile()
getCheckpointFile
in class EdgeRDD<ED>
public <ED2> EdgeRDDImpl<ED2,VD> mapValues(scala.Function1<Edge<ED>,ED2> f, scala.reflect.ClassTag<ED2> evidence$3)
EdgeRDD
public EdgeRDDImpl<ED,VD> reverse()
EdgeRDD
public EdgeRDDImpl<ED,VD> filter(scala.Function1<EdgeTriplet<VD,ED>,java.lang.Object> epred, scala.Function2<java.lang.Object,VD,java.lang.Object> vpred)
public <ED2,ED3> EdgeRDDImpl<ED3,VD> innerJoin(EdgeRDD<ED2> other, scala.Function4<java.lang.Object,java.lang.Object,ED,ED2,ED3> f, scala.reflect.ClassTag<ED2> evidence$4, scala.reflect.ClassTag<ED3> evidence$5)
EdgeRDD
PartitionStrategy
.
innerJoin
in class EdgeRDD<ED>
other
- the EdgeRDD to join withf
- the join function applied to corresponding values of this
and other
evidence$4
- (undocumented)evidence$5
- (undocumented)this
and other
,
with values supplied by f
public <ED2,VD2> EdgeRDDImpl<ED2,VD2> mapEdgePartitions(scala.Function2<java.lang.Object,org.apache.spark.graphx.impl.EdgePartition<ED,VD>,org.apache.spark.graphx.impl.EdgePartition<ED2,VD2>> f, scala.reflect.ClassTag<ED2> evidence$6, scala.reflect.ClassTag<VD2> evidence$7)