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).

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

package feature

Definition Classes: mllib

package fpm

Definition Classes: mllib

package linalg

Definition Classes: mllib

package distributed

DenseMatrix

DenseVector

Matrices

Matrix

QRDecomposition

SingularValueDecomposition

SparseMatrix

SparseVector

Vector

VectorUDT

Vectors

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:

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

linalg

package linalg

Ordering

Alphabetic

Visibility

Public
All

Type Members

class DenseMatrix extends Matrix
Column-major dense matrix.
Column-major dense matrix. The entry values are stored in a single array of doubles with columns listed in sequence. For example, the following matrix
```
1.0 2.0
3.0 4.0
5.0 6.0
```
is stored as [1.0, 3.0, 5.0, 2.0, 4.0, 6.0].
Annotations
@Since( "1.0.0" ) @SQLUserDefinedType()
class DenseVector extends Vector
A dense vector represented by a value array.
A dense vector represented by a value array.

Annotations
@Since( "1.0.0" ) @SQLUserDefinedType()
sealed trait Matrix extends Serializable
Trait for a local matrix.
Trait for a local matrix.

Annotations
@SQLUserDefinedType() @Since( "1.0.0" )
case class QRDecomposition[QType, RType](Q: QType, R: RType) extends Product with Serializable
Represents QR factors.
Represents QR factors.

Annotations
@Since( "1.5.0" )
case class SingularValueDecomposition[UType, VType](U: UType, s: Vector, V: VType) extends Product with Serializable
Represents singular value decomposition (SVD) factors.
Represents singular value decomposition (SVD) factors.

Annotations
@Since( "1.0.0" )
class SparseMatrix extends Matrix
Column-major sparse matrix.
Column-major sparse matrix. The entry values are stored in Compressed Sparse Column (CSC) format. For example, the following matrix
```
1.0 0.0 4.0
0.0 3.0 5.0
2.0 0.0 6.0
```
is stored as values: [1.0, 2.0, 3.0, 4.0, 5.0, 6.0], rowIndices=[0, 2, 1, 0, 1, 2], colPointers=[0, 2, 3, 6].
Annotations
@Since( "1.2.0" ) @SQLUserDefinedType()
class SparseVector extends Vector
A sparse vector represented by an index array and a value array.
A sparse vector represented by an index array and a value array.

Annotations
@Since( "1.0.0" ) @SQLUserDefinedType()
sealed trait Vector extends Serializable
Represents a numeric vector, whose index type is Int and value type is Double.
Represents a numeric vector, whose index type is Int and value type is Double.

Annotations
@SQLUserDefinedType() @Since( "1.0.0" )
Note
Users should not implement this interface.
class VectorUDT extends UserDefinedType[Vector]
:: AlphaComponent ::
:: AlphaComponent ::
User-defined type for Vector which allows easy interaction with SQL via org.apache.spark.sql.Dataset.

Annotations
@AlphaComponent()

Value Members

object DenseMatrix extends Serializable
Factory methods for org.apache.spark.mllib.linalg.DenseMatrix.
Factory methods for org.apache.spark.mllib.linalg.DenseMatrix.

Annotations
@Since( "1.3.0" )
object DenseVector extends Serializable

Annotations
@Since( "1.3.0" )
object Matrices
Factory methods for org.apache.spark.mllib.linalg.Matrix.
Factory methods for org.apache.spark.mllib.linalg.Matrix.

Annotations
@Since( "1.0.0" )
object SparseMatrix extends Serializable
Factory methods for org.apache.spark.mllib.linalg.SparseMatrix.
Factory methods for org.apache.spark.mllib.linalg.SparseMatrix.

Annotations
@Since( "1.3.0" )
object SparseVector extends Serializable

Annotations
@Since( "1.3.0" )
object Vectors
Factory methods for org.apache.spark.mllib.linalg.Vector.
Factory methods for org.apache.spark.mllib.linalg.Vector. We don't use the name Vector because Scala imports scala.collection.immutable.Vector by default.

Annotations
@Since( "1.0.0" )

Packages

linalg 

package linalg

Type Members

Value Members

Ungrouped

linalg