Spark 3.4.2 ScalaDoc < Back

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package root

Definition Classes
root
package org

Definition Classes
root
package apache

Definition Classes
org
package spark
Core Spark functionality.
Core Spark functionality. org.apache.spark.SparkContext serves as the main entry point to Spark, while org.apache.spark.rdd.RDD is the data type representing a distributed collection, and provides most parallel operations.
In addition, org.apache.spark.rdd.PairRDDFunctions contains operations available only on RDDs of key-value pairs, such as groupByKey and join; org.apache.spark.rdd.DoubleRDDFunctions contains operations available only on RDDs of Doubles; and org.apache.spark.rdd.SequenceFileRDDFunctions contains operations available on RDDs that can be saved as SequenceFiles. These operations are automatically available on any RDD of the right type (e.g. RDD[(Int, Int)] through implicit conversions.
Java programmers should reference the org.apache.spark.api.java package for Spark programming APIs in Java.
Classes and methods marked with Experimental are user-facing features which have not been officially adopted by the Spark project. These are subject to change or removal in minor releases.
Classes and methods marked with Developer API are intended for advanced users want to extend Spark through lower level interfaces. These are subject to changes or removal in minor releases.

Definition Classes
apache
package graphx
ALPHA COMPONENT GraphX is a graph processing framework built on top of Spark.
ALPHA COMPONENT GraphX is a graph processing framework built on top of Spark.

Definition Classes
spark
object PartitionStrategy extends Serializable
Collection of built-in PartitionStrategy implementations.
Collection of built-in PartitionStrategy implementations.

Definition Classes
graphx
CanonicalRandomVertexCut
EdgePartition1D
EdgePartition2D
RandomVertexCut

org.apache.spark.graphx.PartitionStrategy

CanonicalRandomVertexCut

object CanonicalRandomVertexCut extends PartitionStrategy with Product with Serializable

Assigns edges to partitions by hashing the source and destination vertex IDs in a canonical direction, resulting in a random vertex cut that colocates all edges between two vertices, regardless of direction.

Source: PartitionStrategy.scala

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Product, Equals, PartitionStrategy, Serializable, Serializable, AnyRef, Any

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@native()
def getPartition(src: VertexId, dst: VertexId, numParts: PartitionID): PartitionID
Returns the partition number for a given edge.
Returns the partition number for a given edge.

Definition Classes
CanonicalRandomVertexCut → PartitionStrategy
final def isInstanceOf[T0]: Boolean

Definition Classes
Any
final def ne(arg0: AnyRef): Boolean

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final def notify(): Unit

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final def notifyAll(): Unit

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Packages

CanonicalRandomVertexCut

object CanonicalRandomVertexCut extends PartitionStrategy with Product with Serializable

Value Members

Inherited from Product

Inherited from Equals

Inherited from PartitionStrategy

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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Packages

CanonicalRandomVertexCut 

object CanonicalRandomVertexCut extends PartitionStrategy with Product with Serializable

Value Members

Inherited from Product

Inherited from Equals

Inherited from PartitionStrategy

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped

CanonicalRandomVertexCut