Class

odkl.analysis.spark.util.RDDOperations

PairRDDDecorator

Related Doc: package RDDOperations

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implicit class PairRDDDecorator[K, A] extends AnyRef

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Instance Constructors

  1. new PairRDDDecorator(rdd: RDD[(K, A)])(implicit arg0: ClassTag[K], arg1: ClassTag[A])

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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. def distributeToPartitions[B, D](mapping: RDD[(K, D)], partitioner: Partitioner)(f: (A) ⇒ B)(implicit arg0: ClassTag[D]): RDD[(D, (K, B))]

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    Creates an RDD having each of required objects distributed to all required destinations

    Creates an RDD having each of required objects distributed to all required destinations

    If the data and/or mapping are partitioned with the same partitioner, no shuffle is required.

    mapping

    Mapping of keys to destinations. Duplicate destinations from different partitions are coalesced.

    partitioner

    Partitioner to use. Operation is more efficient if data is partitioned with the same partitioner

    f

    Function to apply to values. It's called exactly once for each value in data

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

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  8. def equals(arg0: Any): Boolean

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  9. def finalize(): Unit

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

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  11. def groupWithinPartitionsByKey: RDD[(K, Iterator[A])]

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    Utility used to group data by key within RDD partitions by a key, assuming that RDD is already partitioned and sorted by key.

    Utility used to group data by key within RDD partitions by a key, assuming that RDD is already partitioned and sorted by key. The RDD data are processed sequentialy without shuffling and materializing them in memory.

    returns

    RDD with key -> values.

  12. def hashCode(): Int

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  13. final def isInstanceOf[T0]: Boolean

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  14. def joinUnique[B](other: RDD[(K, B)], partitioner: Partitioner)(implicit arg0: ClassTag[B]): RDD[(K, (A, B))]

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    Similar to org.apache.spark.rdd.PairRDDFunctions.join, but ensures that all keys are unique in both RDDs.

    Similar to org.apache.spark.rdd.PairRDDFunctions.join, but ensures that all keys are unique in both RDDs.

    Throws java.lang.IllegalArgumentException if encounters duplicate

  15. def joinUnique[B](other: RDD[(K, B)], numPartitions: Int)(implicit arg0: ClassTag[B]): RDD[(K, (A, B))]

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    Similar to org.apache.spark.rdd.PairRDDFunctions.join, but ensures that all keys are unique in both RDDs.

    Similar to org.apache.spark.rdd.PairRDDFunctions.join, but ensures that all keys are unique in both RDDs.

    Throws java.lang.IllegalArgumentException if encounters duplicate

  16. def joinUnique[B](other: RDD[(K, B)])(implicit arg0: ClassTag[B]): RDD[(K, (A, B))]

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    Similar to org.apache.spark.rdd.PairRDDFunctions.join, but ensures that all keys are unique in both RDDs.

    Similar to org.apache.spark.rdd.PairRDDFunctions.join, but ensures that all keys are unique in both RDDs.

    Throws java.lang.IllegalArgumentException if encounters duplicate

  17. def leftJoinUnique[B](other: RDD[(K, B)], partitioner: Partitioner)(implicit arg0: ClassTag[B]): RDD[(K, (A, Option[B]))]

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    Similar to org.apache.spark.rdd.PairRDDFunctions.leftOuterJoin, but ensures that all keys are unique in both RDDs.

    Similar to org.apache.spark.rdd.PairRDDFunctions.leftOuterJoin, but ensures that all keys are unique in both RDDs.

    Throws java.lang.IllegalArgumentException if encounters duplicate

  18. def leftJoinUnique[B](other: RDD[(K, B)], numPartitions: Int)(implicit arg0: ClassTag[B]): RDD[(K, (A, Option[B]))]

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    Similar to org.apache.spark.rdd.PairRDDFunctions.leftOuterJoin, but ensures that all keys are unique in both RDDs.

    Similar to org.apache.spark.rdd.PairRDDFunctions.leftOuterJoin, but ensures that all keys are unique in both RDDs.

    Throws java.lang.IllegalArgumentException if encounters duplicate

  19. def leftJoinUnique[B](other: RDD[(K, B)])(implicit arg0: ClassTag[B]): RDD[(K, (A, Option[B]))]

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    Similar to org.apache.spark.rdd.PairRDDFunctions.leftOuterJoin, but ensures that all keys are unique in both RDDs.

    Similar to org.apache.spark.rdd.PairRDDFunctions.leftOuterJoin, but ensures that all keys are unique in both RDDs.

    Throws java.lang.IllegalArgumentException if encounters duplicate

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

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  21. final def notify(): Unit

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  22. final def notifyAll(): Unit

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

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  24. def toString(): String

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  25. final def wait(): Unit

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

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

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