org.apache.spark.mllib.rdd

MLPairRDDFunctions

class MLPairRDDFunctions[K, V] extends Serializable

Machine learning specific Pair RDD functions.

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@DeveloperApi()
Source
MLPairRDDFunctions.scala
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Instance Constructors

  1. new MLPairRDDFunctions(self: RDD[(K, V)])(implicit arg0: ClassTag[K], arg1: ClassTag[V])

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

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  18. def toString(): String

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  19. def topByKey(num: Int)(implicit ord: Ordering[V]): RDD[(K, Array[V])]

    Returns the top k (largest) elements for each key from this RDD as defined by the specified implicit Ordering[T].

    Returns the top k (largest) elements for each key from this RDD as defined by the specified implicit Ordering[T]. If the number of elements for a certain key is less than k, all of them will be returned.

    num

    k, the number of top elements to return

    ord

    the implicit ordering for T

    returns

    an RDD that contains the top k values for each key

  20. final def wait(): Unit

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

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

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