implicit final class FlatMapPartitionWrapper[V] extends AnyVal
Applies flatMap to partitions of RDDs in parallel.
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- new FlatMapPartitionWrapper(rdd: RDD[V])
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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
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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
-
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
-
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
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getClass(): Class[_ <: AnyVal]
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