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 ml

    DataFrame-based machine learning APIs to let users quickly assemble and configure practical machine learning pipelines.

    DataFrame-based machine learning APIs to let users quickly assemble and configure practical machine learning pipelines.

    Definition Classes
    spark
  • package linalg
    Definition Classes
    ml
  • DenseMatrix
  • DenseVector
  • Matrices
  • Matrix
  • SQLDataTypes
  • SparseMatrix
  • SparseVector
  • Vector
  • Vectors

sealed trait Vector extends Serializable

Represents a numeric vector, whose index type is Int and value type is Double.

Annotations
@Since("2.0.0")
Source
Vectors.scala
Note

Users should not implement this interface.

Linear Supertypes
Serializable, AnyRef, Any
Known Subclasses
DenseVector, SparseVector
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. Vector
  2. Serializable
  3. AnyRef
  4. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. Protected

Abstract Value Members

  1. abstract def argmax: Int

    Find the index of a maximal element.

    Find the index of a maximal element. Returns the first maximal element in case of a tie. Returns -1 if vector has length 0.

    Annotations
    @Since("2.0.0")
  2. abstract def numActives: Int

    Number of active entries.

    Number of active entries. An "active entry" is an element which is explicitly stored, regardless of its value. Note that inactive entries have value 0.

    Annotations
    @Since("2.0.0")
  3. abstract def numNonzeros: Int

    Number of nonzero elements.

    Number of nonzero elements. This scans all active values and count nonzeros.

    Annotations
    @Since("2.0.0")
  4. abstract def size: Int

    Size of the vector.

    Size of the vector.

    Annotations
    @Since("2.0.0")
  5. abstract def toArray: Array[Double]

    Converts the instance to a double array.

    Converts the instance to a double array.

    Annotations
    @Since("2.0.0")

Concrete Value Members

  1. def apply(i: Int): Double

    Gets the value of the ith element.

    Gets the value of the ith element.

    i

    index

    Annotations
    @Since("2.0.0")
  2. def compressed: Vector

    Returns a vector in either dense or sparse format, whichever uses less storage.

    Returns a vector in either dense or sparse format, whichever uses less storage.

    Annotations
    @Since("2.0.0")
  3. def copy: Vector

    Makes a deep copy of this vector.

    Makes a deep copy of this vector.

    Annotations
    @Since("2.0.0")
  4. def dot(v: Vector): Double

    Calculate the dot product of this vector with another.

    Calculate the dot product of this vector with another.

    If size does not match an IllegalArgumentException is thrown.

    Annotations
    @Since("3.0.0")
  5. def equals(other: Any): Boolean
    Definition Classes
    Vector → AnyRef → Any
  6. def foreachActive(f: (Int, Double) => Unit): Unit

    Applies a function f to all the active elements of dense and sparse vector.

    Applies a function f to all the active elements of dense and sparse vector.

    f

    the function takes two parameters where the first parameter is the index of the vector with type Int, and the second parameter is the corresponding value with type Double.

    Annotations
    @Since("2.0.0")
  7. def hashCode(): Int

    Returns a hash code value for the vector.

    Returns a hash code value for the vector. The hash code is based on its size and its first 128 nonzero entries, using a hash algorithm similar to java.util.Arrays.hashCode.

    Definition Classes
    Vector → AnyRef → Any
  8. def toDense: DenseVector

    Converts this vector to a dense vector.

    Converts this vector to a dense vector.

    Annotations
    @Since("2.0.0")
  9. def toSparse: SparseVector

    Converts this vector to a sparse vector with all explicit zeros removed.

    Converts this vector to a sparse vector with all explicit zeros removed.

    Annotations
    @Since("2.0.0")