Packages

class FallbackSampler extends Sampler[AnyRef, AnyRef]

Sampler implementation for global sorting reducer splits.

The random sampler can fail to return any data if the input set is small, which then causes the TotalOrderPartitioner to fail.

This class tries to use the random sampler, but falls back to first n if needed.

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Sampler[AnyRef, AnyRef], AnyRef, Any
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Instance Constructors

  1. new FallbackSampler(frequency: Double, numSamples: Int, maxSplitsToSample: Int)

Value Members

  1. final def !=(arg0: Any): Boolean
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  2. final def ##(): Int
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  3. final def ==(arg0: Any): Boolean
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  4. final def asInstanceOf[T0]: T0
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  5. def clone(): AnyRef
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  6. final def eq(arg0: AnyRef): Boolean
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  7. def equals(arg0: Any): Boolean
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  8. def finalize(): Unit
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  9. final def getClass(): Class[_]
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    @native()
  10. def getSample(inf: InputFormat[AnyRef, AnyRef], job: Job): Array[AnyRef]
    Definition Classes
    FallbackSampler → Sampler
  11. def hashCode(): Int
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    @native()
  12. final def isInstanceOf[T0]: Boolean
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  13. final def ne(arg0: AnyRef): Boolean
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  14. final def notify(): Unit
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  15. final def notifyAll(): Unit
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  16. final def synchronized[T0](arg0: ⇒ T0): T0
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  17. def toString(): String
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  18. final def wait(): Unit
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  19. final def wait(arg0: Long, arg1: Int): Unit
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    @throws( ... )
  20. final def wait(arg0: Long): Unit
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Inherited from Sampler[AnyRef, AnyRef]

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