edu.stanford.nlp.tmt.data.concurrent

Concurrent

object Concurrent extends AnyRef

Concurrent operations.

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

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

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  3. def ## (): Int

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

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  5. def == (arg0: Any): Boolean

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  6. def asInstanceOf [T0] : T0

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  7. def clone (): AnyRef

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  8. def daemon (fn: ⇒ Unit): Thread

    Runs the given function in a daemon thread.

  9. def eq (arg0: AnyRef): Boolean

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  10. def equals (arg0: Any): Boolean

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  11. def finalize (): Unit

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  12. def getClass (): java.lang.Class[_]

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  13. def hashCode (): Int

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  14. def isInstanceOf [T0] : Boolean

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  15. def map [A, B] (iterator: Iterator[A], fn: (A) ⇒ B, queueSize: Int)(implicit pool: Executor = pool): Iterator[B]

    Maps the values of the given iterator in parallel using workers in the given thread pool.

    Maps the values of the given iterator in parallel using workers in the given thread pool. These workers are started in the order of the original iterator, but might not finish in that order. To keep the other cores busy, up to queueSize values can processed at at time, with results being queued up and returned in the original iteration order. By default, queueSize is four times the number of cores on the machine to keep things humming, but this number can be raised or lowered to change the relative preference of memory versus throughput.

  16. def mapreduce [T, V] (items: TraversableOnce[T], map: (T) ⇒ V, reduce: (V, V) ⇒ V, numCores: Int)(implicit arg0: ClassManifest[V]): V

  17. def ne (arg0: AnyRef): Boolean

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  18. def notify (): Unit

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  19. def notifyAll (): Unit

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  20. lazy val pool : Executor

    Shared thread pool for all concurrent ops.

  21. def reduce [C] (seq: Seq[C], reduce: (C, C) ⇒ C)(implicit pool: Executor = pool): C

    Parallel reduce on a set of values.

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

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  23. def toString (): String

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  24. def wait (): Unit

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

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  26. def wait (arg0: Long): Unit

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