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com.here.platform.data.processing.spark.rdd.Implicits

FlatMapPartitionWrapper

implicit final class FlatMapPartitionWrapper[V] extends AnyVal

Applies flatMap to partitions of RDDs in parallel.

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  1. FlatMapPartitionWrapper
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Instance Constructors

  1. new FlatMapPartitionWrapper(rdd: RDD[V])

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 flatMapParallel[U](numThreads: Int)(f: (V) ⇒ TraversableOnce[U])(implicit arg0: ClassTag[U], vt: ClassTag[V]): RDD[U]

    Applies flatMap to an RDD, but it can use a thread pool if numThreads is >1, in that case partitions are computed in parallel.

    Applies flatMap to an RDD, but it can use a thread pool if numThreads is >1, in that case partitions are computed in parallel.

    U

    the type of the new values

    numThreads

    the number of threads to use for parallel invocations of f(). Can only be set to a value larger than 1 if the operations include IO operations, or if multiple cores are available per executor

    f

    the mapping function, providing the new value for the element

    returns

    an RDD with mapping function applied to each element

    Note

    calling this function loses partitioning for key-value pair RDD

  6. def flatMapParallel[U](f: (V) ⇒ TraversableOnce[U], numThreads: Int)(implicit arg0: ClassTag[U], vt: ClassTag[V]): RDD[U]

    Applies flatMap to an RDD, but it can use a thread pool if numThreads is >1, in that case partitions are computed in parallel.

    Applies flatMap to an RDD, but it can use a thread pool if numThreads is >1, in that case partitions are computed in parallel.

    U

    the type of the new values

    f

    the mapping function, providing the new value for the element

    numThreads

    the number of threads to use for parallel invocations of f(). Can only be set to a value larger than 1 if the operations include IO operations, or if multiple cores are available per executor

    returns

    an RDD with mapping function applied to each element

    Note

    calling this function loses partitioning for key-value pair RDD

  7. def flatMapParallelUnordered[U](numThreads: Int)(f: (V) ⇒ TraversableOnce[U])(implicit arg0: ClassTag[U], vt: ClassTag[V]): RDD[U]

    Applies flatMap to an RDD, but it can use a thread pool if numThreads is >1, in that case partitions are computed in parallel.

    Applies flatMap to an RDD, but it can use a thread pool if numThreads is >1, in that case partitions are computed in parallel. Elements are emitted as soon as they are ready, therefore it is possible that the transformed elements in each Spark partition are not in the same order as in the upstream RDD.

    U

    the type of the new values

    numThreads

    the number of threads to use for parallel invocations of f(). Can only be set to a value larger than 1 if the operations include IO operations, or if multiple cores are available per executor

    f

    the mapping function, providing the new value for the element

    returns

    an RDD with mapping function applied to each element

    Note

    calling this function loses partitioning for key-value pair RDD

  8. def flatMapParallelUnordered[U](f: (V) ⇒ TraversableOnce[U], numThreads: Int)(implicit arg0: ClassTag[U], vt: ClassTag[V]): RDD[U]

    Applies flatMap to an RDD, but it can use a thread pool if numThreads is >1, in that case partitions are computed in parallel.

    Applies flatMap to an RDD, but it can use a thread pool if numThreads is >1, in that case partitions are computed in parallel. Elements are emitted as soon as they are ready, therefore it is possible that the transformed elements in each Spark partition are not in the same order as in the upstream RDD.

    U

    the type of the new values

    f

    the mapping function, providing the new value for the element

    numThreads

    the number of threads to use for parallel invocations of f(). Can only be set to a value larger than 1 if the operations include IO operations, or if multiple cores are available per executor

    returns

    an RDD with mapping function applied to each element

    Note

    calling this function loses partitioning for key-value pair RDD

  9. def getClass(): Class[_ <: AnyVal]
    Definition Classes
    AnyVal → Any
  10. final def isInstanceOf[T0]: Boolean
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  11. def toString(): String
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