SparseVector (Spark 3.5.4 JavaDoc)

Object
- org.apache.spark.mllib.linalg.SparseVector

All Implemented Interfaces:

java.io.Serializable, Vector
```
public class SparseVector
extends Object
implements Vector
```
A sparse vector represented by an index array and a value array.
param: size size of the vector. param: indices index array, assume to be strictly increasing. param: values value array, must have the same length as the index array.

See Also:

Serialized Form

Constructor Summary

Constructors
Constructor and Description

SparseVector(int size, int[] indices, double[] values)

Constructors
Constructor and Description
`SparseVector(int size, int[] indices, double[] values)`

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`double`	`apply(int i)` Gets the value of the ith element.
`int`	`argmax()` Find the index of a maximal element.
`SparseVector`	`asML()` Convert this vector to the new mllib-local representation.
`SparseVector`	`copy()` Makes a deep copy of this vector.
`boolean`	`equals(Object other)`
`static SparseVector`	`fromML(SparseVector v)` Convert new linalg type to spark.mllib type.
`int`	`hashCode()` Returns a hash code value for the vector.
`int[]`	`indices()`
`int`	`numActives()` Number of active entries.
`int`	`numNonzeros()` Number of nonzero elements.
`int`	`size()` Size of the vector.
`double[]`	`toArray()` Converts the instance to a double array.
`String`	`toJson()` Converts the vector to a JSON string.
`String`	`toString()`
`static scala.Option<scala.Tuple3<Object,int[],double[]>>`	`unapply(SparseVector sv)`
`double[]`	`values()`

Methods inherited from class Object
getClass, notify, notifyAll, wait, wait, wait

Methods inherited from interface org.apache.spark.mllib.linalg.Vector
compressed, dot, foreach, foreachActive, foreachNonZero, nonZeroIterator, sparsity, toDense, toSparse

- Constructor Detail
  - SparseVector
```
public SparseVector(int size,
                    int[] indices,
                    double[] values)
```
- Method Detail
  - unapply
```
public static scala.Option<scala.Tuple3<Object,int[],double[]>> unapply(SparseVector sv)
```
  - fromML
```
public static SparseVector fromML(SparseVector v)
```
    Convert new linalg type to spark.mllib type. Light copy; only copies references
    
    Parameters:
    
    v - (undocumented)
    
    Returns:
    
    (undocumented)
  - size
```
public int size()
```
    Description copied from interface: Vector
    
    Size of the vector.
    
    Specified by:
    
    size in interface Vector
    
    Returns:
    
    (undocumented)
  - indices
```
public int[] indices()
```
  - values
```
public double[] values()
```
  - toString
```
public String toString()
```
    Overrides:
    
    toString in class Object
  - toArray
```
public double[] toArray()
```
    Description copied from interface: Vector
    
    Converts the instance to a double array.
    
    Specified by:
    
    toArray in interface Vector
    
    Returns:
    
    (undocumented)
  - copy
```
public SparseVector copy()
```
    Description copied from interface: Vector
    
    Makes a deep copy of this vector.
    
    Specified by:
    
    copy in interface Vector
    
    Returns:
    
    (undocumented)
  - apply
```
public double apply(int i)
```
    Description copied from interface: Vector
    
    Gets the value of the ith element.
    
    Specified by:
    
    apply in interface Vector
    
    Parameters:
    
    i - index
    
    Returns:
    
    (undocumented)
  - equals
```
public boolean equals(Object other)
```
    Specified by:
    
    equals in interface Vector
    
    Overrides:
    
    equals in class Object
  - hashCode
```
public int hashCode()
```
    Description copied from interface: 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.
    
    Specified by:
    
    hashCode in interface Vector
    
    Overrides:
    
    hashCode in class Object
    
    Returns:
    
    (undocumented)
  - numActives
```
public int numActives()
```
    Description copied from interface: Vector
    
    Number of active entries. An "active entry" is an element which is explicitly stored, regardless of its value.
    
    Specified by:
    
    numActives in interface Vector
    
    Returns:
    
    (undocumented)
  - numNonzeros
```
public int numNonzeros()
```
    Description copied from interface: Vector
    
    Number of nonzero elements. This scans all active values and count nonzeros.
    
    Specified by:
    
    numNonzeros in interface Vector
    
    Returns:
    
    (undocumented)
  - argmax
```
public int argmax()
```
    Description copied from interface: Vector
    
    Find the index of a maximal element. Returns the first maximal element in case of a tie. Returns -1 if vector has length 0.
    
    Specified by:
    
    argmax in interface Vector
    
    Returns:
    
    (undocumented)
  - toJson
```
public String toJson()
```
    Description copied from interface: Vector
    
    Converts the vector to a JSON string.
    
    Specified by:
    
    toJson in interface Vector
    
    Returns:
    
    (undocumented)
  - asML
```
public SparseVector asML()
```
    Description copied from interface: Vector
    
    Convert this vector to the new mllib-local representation. This does NOT copy the data; it copies references.
    
    Specified by:
    
    asML in interface Vector
    
    Returns:
    
    (undocumented)

Class SparseVector

Constructor Summary

Method Summary

Methods inherited from class Object

Methods inherited from interface org.apache.spark.mllib.linalg.Vector

Constructor Detail

SparseVector

Method Detail

unapply

fromML

size

indices

values

toString

toArray

copy

apply

equals

hashCode

numActives

numNonzeros

argmax

toJson

asML