Package

org.apache.spark.util

random

Permalink

package random

Utilities for random number generation.

Source
package.scala
Linear Supertypes
AnyRef, Any
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. random
  2. AnyRef
  3. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. All

Type Members

  1. class BernoulliCellSampler[T] extends RandomSampler[T, T]

    Permalink

    :: DeveloperApi :: A sampler based on Bernoulli trials for partitioning a data sequence.

    :: DeveloperApi :: A sampler based on Bernoulli trials for partitioning a data sequence.

    T

    item type

    Annotations
    @DeveloperApi()
  2. class BernoulliSampler[T] extends RandomSampler[T, T]

    Permalink

    :: DeveloperApi :: A sampler based on Bernoulli trials.

    :: DeveloperApi :: A sampler based on Bernoulli trials.

    T

    item type

    Annotations
    @DeveloperApi()
  3. class PoissonSampler[T] extends RandomSampler[T, T]

    Permalink

    :: DeveloperApi :: A sampler for sampling with replacement, based on values drawn from Poisson distribution.

    :: DeveloperApi :: A sampler for sampling with replacement, based on values drawn from Poisson distribution.

    T

    item type

    Annotations
    @DeveloperApi()
  4. trait Pseudorandom extends AnyRef

    Permalink

    :: DeveloperApi :: A class with pseudorandom behavior.

    :: DeveloperApi :: A class with pseudorandom behavior.

    Annotations
    @DeveloperApi()
  5. trait RandomSampler[T, U] extends Pseudorandom with Cloneable with Serializable

    Permalink

    :: DeveloperApi :: A pseudorandom sampler.

    :: DeveloperApi :: A pseudorandom sampler. It is possible to change the sampled item type. For example, we might want to add weights for stratified sampling or importance sampling. Should only use transformations that are tied to the sampler and cannot be applied after sampling.

    T

    item type

    U

    sampled item type

    Annotations
    @DeveloperApi()

Inherited from AnyRef

Inherited from Any

Ungrouped