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 mllib

  RDD-based machine learning APIs (in maintenance mode).

  RDD-based machine learning APIs (in maintenance mode).

  The spark.mllib package is in maintenance mode as of the Spark 2.0.0 release to encourage migration to the DataFrame-based APIs under the org.apache.spark.ml package. While in maintenance mode,

  • no new features in the RDD-based spark.mllib package will be accepted, unless they block implementing new features in the DataFrame-based spark.ml package;
  • bug fixes in the RDD-based APIs will still be accepted.

  The developers will continue adding more features to the DataFrame-based APIs in the 2.x series to reach feature parity with the RDD-based APIs. And once we reach feature parity, this package will be deprecated.

  Definition Classes

  spark

  See also

  SPARK-4591 to track the progress of feature parity

•  package classification

  Definition Classes

  mllib

•  package clustering

  Definition Classes

  mllib

•  package evaluation

  Definition Classes

  mllib

• BinaryClassificationMetrics
• MulticlassMetrics
• MultilabelMetrics
• RankingMetrics
• RegressionMetrics
•  package feature

  Definition Classes

  mllib

•  package fpm

  Definition Classes

  mllib

•  package linalg

  Definition Classes

  mllib

•  package optimization

  Definition Classes

  mllib

•  package pmml

  Definition Classes

  mllib

•  package random

  Definition Classes

  mllib

•  package rdd

  Definition Classes

  mllib

•  package recommendation

  Definition Classes

  mllib

•  package regression

  Definition Classes

  mllib

•  package stat

  Definition Classes

  mllib

•  package tree

  This package contains the default implementation of the decision tree algorithm, which supports:

  This package contains the default implementation of the decision tree algorithm, which supports:

  • binary classification,
  • regression,
  • information loss calculation with entropy and Gini for classification and variance for regression,
  • both continuous and categorical features.

  Definition Classes

  mllib

•  package util

  Definition Classes

  mllib

org.apache.spark.mllib

evaluation 