Package org.apache.spark

Class RangePartitioner<K,V>

Object

org.apache.spark.Partitioner

org.apache.spark.RangePartitioner<K,V>

All Implemented Interfaces:

Serializable

public class RangePartitioner<K,V>
extends Partitioner

A Partitioner that partitions sortable records by range into roughly equal ranges. The ranges are determined by sampling the content of the RDD passed in.

See Also:

• Serialized Form

Note:

The actual number of partitions created by the RangePartitioner might not be the same as the partitions parameter, in the case where the number of sampled records is less than the value of partitions.

Constructor Summary

Constructors

Constructor	Description
RangePartitioner(int partitions, RDD<? extends scala.Product2<K,V>> rdd, boolean ascending, int samplePointsPerPartitionHint, scala.math.Ordering<K> evidence$1, scala.reflect.ClassTag<K> evidence$2)
RangePartitioner(int partitions, RDD<? extends scala.Product2<K,V>> rdd, boolean ascending, scala.math.Ordering<K> evidence$3, scala.reflect.ClassTag<K> evidence$4)

Method Summary

Modifier and Type	Method	Description
static <K> Object	determineBounds(scala.collection.mutable.ArrayBuffer<scala.Tuple2<K,Object>> candidates, int partitions, scala.math.Ordering<K> evidence$6, scala.reflect.ClassTag<K> evidence$7)	Determines the bounds for range partitioning from candidates with weights indicating how many items each represents.
boolean	equals(Object other)
int	getPartition(Object key)
int	hashCode()
int	numPartitions()
int	samplePointsPerPartitionHint()
static <K> scala.Tuple2<Object,scala.Tuple3<Object,Object,Object>[]>	sketch(RDD<K> rdd, int sampleSizePerPartition, scala.reflect.ClassTag<K> evidence$5)	Sketches the input RDD via reservoir sampling on each partition.

Methods inherited from class org.apache.spark.Partitioner

defaultPartitioner

Methods inherited from class java.lang.Object

getClass, notify, notifyAll, toString, wait, wait, wait

Constructor Details

RangePartitioner

public RangePartitioner(int partitions,
 RDD<? extends scala.Product2<K,V>> rdd,
 boolean ascending,
 int samplePointsPerPartitionHint,
 scala.math.Ordering<K> evidence$1,
 scala.reflect.ClassTag<K> evidence$2)

RangePartitioner

public RangePartitioner(int partitions,
 RDD<? extends scala.Product2<K,V>> rdd,
 boolean ascending,
 scala.math.Ordering<K> evidence$3,
 scala.reflect.ClassTag<K> evidence$4)

Method Details

sketch

public static <K>
scala.Tuple2<Object,scala.Tuple3<Object,Object,Object>[]> sketch(RDD<K> rdd,
 int sampleSizePerPartition,
 scala.reflect.ClassTag<K> evidence$5)

Sketches the input RDD via reservoir sampling on each partition.

Parameters:

rdd - the input RDD to sketch

sampleSizePerPartition - max sample size per partition

evidence$5 - (undocumented)

Returns:

(total number of items, an array of (partitionId, number of items, sample))

determineBounds

public static <K> Object determineBounds(scala.collection.mutable.ArrayBuffer<scala.Tuple2<K,Object>> candidates,
 int partitions,
 scala.math.Ordering<K> evidence$6,
 scala.reflect.ClassTag<K> evidence$7)

Determines the bounds for range partitioning from candidates with weights indicating how many items each represents. Usually this is 1 over the probability used to sample this candidate.

Parameters:

candidates - unordered candidates with weights

partitions - number of partitions

evidence$6 - (undocumented)

evidence$7 - (undocumented)

Returns:

selected bounds

samplePointsPerPartitionHint

public int samplePointsPerPartitionHint()

numPartitions

public int numPartitions()

Specified by:

numPartitions in class Partitioner

getPartition

public int getPartition(Object key)

Specified by:

getPartition in class Partitioner

equals

public boolean equals(Object other)

Overrides:

equals in class Object

hashCode

public int hashCode()

Overrides:

hashCode in class Object