org.hammerlab.magic.rdd.scan

ScanRightRDD

class ScanRightRDD[T] extends Serializable

RDD wrapper supporting methods that compute partial-sums (from right to left) across the RDD.

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Instance Constructors

  1. new ScanRightRDD(rdd: RDD[T])(implicit arg0: ClassTag[T])

Value Members

  1. final def !=(arg0: AnyRef): Boolean

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  2. final def !=(arg0: Any): Boolean

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  3. final def ##(): Int

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  4. final def ==(arg0: AnyRef): Boolean

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  6. final def asInstanceOf[T0]: T0

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  7. def clone(): AnyRef

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  8. final def eq(arg0: AnyRef): Boolean

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  9. def equals(arg0: Any): Boolean

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  10. def finalize(): Unit

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  11. final def getClass(): Class[_]

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  12. def hashCode(): Int

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  13. final def isInstanceOf[T0]: Boolean

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  14. final def ne(arg0: AnyRef): Boolean

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  15. final def notify(): Unit

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  16. final def notifyAll(): Unit

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  17. val rdd: RDD[T]

  18. def scanRight(identity: T, useRDDReversal: Boolean = false)(combine: (T, T) ⇒ T): RDD[T]

  19. def scanRight[U](identity: U, aggregate: (T, U) ⇒ U, combine: (U, U) ⇒ U)(implicit arg0: ClassTag[U]): RDD[U]

  20. def scanRight[U](identity: U, aggregate: (T, U) ⇒ U, combine: (U, U) ⇒ U, useRDDReversal: Boolean)(implicit arg0: ClassTag[U]): RDD[U]

    identity

    used to initialize per-partition "sums"

    aggregate

    aggregate an RDD element into a running "sum"

    combine

    combine two "sums"

    useRDDReversal

    when set, reverse the RDD, do a scanLeft (see ScanLeftRDD, and then reverse it back. Usually this will be more work than the default implementation, but the latter materializes whole partitions into memory as part of calling Iterator.scanRight, which may be prohibitively memory-expensive in some cases.

    returns

  21. final def synchronized[T0](arg0: ⇒ T0): T0

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  22. def toString(): String

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  23. final def wait(): Unit

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  24. final def wait(arg0: Long, arg1: Int): Unit

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  25. final def wait(arg0: Long): Unit

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