Packages

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 api

Definition Classes: spark

package broadcast

Spark's broadcast variables, used to broadcast immutable datasets to all nodes.

Definition Classes: spark

package deploy

Definition Classes: spark

package executor

Executor components used with various cluster managers.

Executor components used with various cluster managers. See org.apache.spark.executor.Executor.

Definition Classes: spark

DataReadMethod

DataWriteMethod

ExecutorMetrics

InputMetrics

OutputMetrics

ShuffleReadMetrics

ShuffleWriteMetrics

TaskMetrics

package input

Definition Classes: spark

package internal

Definition Classes: spark

package io

IO codecs used for compression.

IO codecs used for compression. See org.apache.spark.io.CompressionCodec.

Definition Classes: spark

package mapred

Definition Classes: spark

package memory

This package implements Spark's memory management system.

This package implements Spark's memory management system. This system consists of two main components, a JVM-wide memory manager and a per-task manager:

org.apache.spark.memory.MemoryManager manages Spark's overall memory usage within a JVM. This component implements the policies for dividing the available memory across tasks and for allocating memory between storage (memory used caching and data transfer) and execution (memory used by computations, such as shuffles, joins, sorts, and aggregations).
org.apache.spark.memory.TaskMemoryManager manages the memory allocated by individual tasks. Tasks interact with TaskMemoryManager and never directly interact with the JVM-wide MemoryManager.

Internally, each of these components have additional abstractions for memory bookkeeping:

org.apache.spark.memory.MemoryConsumers are clients of the TaskMemoryManager and correspond to individual operators and data structures within a task. The TaskMemoryManager receives memory allocation requests from MemoryConsumers and issues callbacks to consumers in order to trigger spilling when running low on memory.
org.apache.spark.memory.MemoryPools are a bookkeeping abstraction used by the MemoryManager to track the division of memory between storage and execution.

Diagrammatically:

                                                       +---------------------------+
+-------------+                                        |       MemoryManager       |
| MemConsumer |----+                                   |                           |
+-------------+    |    +-------------------+          |  +---------------------+  |
                   +--->| TaskMemoryManager |----+     |  |OnHeapStorageMemPool |  |
+-------------+    |    +-------------------+    |     |  +---------------------+  |
| MemConsumer |----+                             |     |                           |
+-------------+         +-------------------+    |     |  +---------------------+  |
                        | TaskMemoryManager |----+     |  |OffHeapStorageMemPool|  |
                        +-------------------+    |     |  +---------------------+  |
                                                 +---->|                           |
                                 *               |     |  +---------------------+  |
                                 *               |     |  |OnHeapExecMemPool    |  |
+-------------+                  *               |     |  +---------------------+  |
| MemConsumer |----+                             |     |                           |
+-------------+    |    +-------------------+    |     |  +---------------------+  |
                   +--->| TaskMemoryManager |----+     |  |OffHeapExecMemPool   |  |
                        +-------------------+          |  +---------------------+  |
                                                       |                           |
                                                       +---------------------------+

There is one implementation of org.apache.spark.memory.MemoryManager:

org.apache.spark.memory.UnifiedMemoryManager enforces soft boundaries between storage and execution memory, allowing requests for memory in one region to be fulfilled by borrowing memory from the other.

Definition Classes: spark

package metrics

Definition Classes: spark

package network

Definition Classes: spark

package partial

Support for approximate results.

Support for approximate results. This provides convenient api and also implementation for approximate calculation.

Definition Classes: spark
See also: org.apache.spark.rdd.RDD.countApprox

package rdd

Provides several RDD implementations.

Provides several RDD implementations. See org.apache.spark.rdd.RDD.

Definition Classes: spark

package resource

Definition Classes: spark

package scheduler

Spark's scheduling components.

Spark's scheduling components. This includes the org.apache.spark.scheduler.DAGScheduler and lower level org.apache.spark.scheduler.TaskScheduler.

Definition Classes: spark

package security

Definition Classes: spark

package serializer

Pluggable serializers for RDD and shuffle data.

Definition Classes: spark
See also: org.apache.spark.serializer.Serializer

package shuffle

Definition Classes: spark

package status

Definition Classes: spark

package storage

Definition Classes: spark

package unsafe

Definition Classes: spark

package util

Spark utilities.

Definition Classes: spark

org.apache.spark

executor

package executor

Executor components used with various cluster managers. See org.apache.spark.executor.Executor.

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Type Members

class ExecutorMetrics extends Serializable
:: DeveloperApi :: Metrics tracked for executors and the driver.
:: DeveloperApi :: Metrics tracked for executors and the driver.
Executor-level metrics are sent from each executor to the driver as part of the Heartbeat.

Annotations
@DeveloperApi()
class InputMetrics extends Serializable
:: DeveloperApi :: A collection of accumulators that represents metrics about reading data from external systems.
:: DeveloperApi :: A collection of accumulators that represents metrics about reading data from external systems.

Annotations
@DeveloperApi()
class OutputMetrics extends Serializable
:: DeveloperApi :: A collection of accumulators that represents metrics about writing data to external systems.
:: DeveloperApi :: A collection of accumulators that represents metrics about writing data to external systems.

Annotations
@DeveloperApi()
class ShuffleReadMetrics extends Serializable
:: DeveloperApi :: A collection of accumulators that represent metrics about reading shuffle data.
:: DeveloperApi :: A collection of accumulators that represent metrics about reading shuffle data. Operations are not thread-safe.

Annotations
@DeveloperApi()
class ShuffleWriteMetrics extends ShuffleWriteMetricsReporter with Serializable
:: DeveloperApi :: A collection of accumulators that represent metrics about writing shuffle data.
:: DeveloperApi :: A collection of accumulators that represent metrics about writing shuffle data. Operations are not thread-safe.

Annotations
@DeveloperApi()
class TaskMetrics extends Serializable
:: DeveloperApi :: Metrics tracked during the execution of a task.
:: DeveloperApi :: Metrics tracked during the execution of a task.
This class is wrapper around a collection of internal accumulators that represent metrics associated with a task. The local values of these accumulators are sent from the executor to the driver when the task completes. These values are then merged into the corresponding accumulator previously registered on the driver.
The accumulator updates are also sent to the driver periodically (on executor heartbeat) and when the task failed with an exception. The TaskMetrics object itself should never be sent to the driver.

Annotations
@DeveloperApi()

Value Members

object DataReadMethod extends Enumeration with Serializable
:: DeveloperApi :: Method by which input data was read.
:: DeveloperApi :: Method by which input data was read. Network means that the data was read over the network from a remote block manager (which may have stored the data on-disk or in-memory). Operations are not thread-safe.

Annotations
@DeveloperApi()
object DataWriteMethod extends Enumeration with Serializable
:: DeveloperApi :: Method by which output data was written.
:: DeveloperApi :: Method by which output data was written. Operations are not thread-safe.

Annotations
@DeveloperApi()

Packages

executor

package executor

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executor 

package executor

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executor