spark.streaming.util

RawTextHelper

object RawTextHelper extends AnyRef

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

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  6. def add(v1: Long, v2: Long): Long

  7. final def asInstanceOf[T0]: T0

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  8. def clone(): AnyRef

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

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  13. def hashCode(): Int

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  14. final def isInstanceOf[T0]: Boolean

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  15. def max(v1: Long, v2: Long): Long

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

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  17. final def notify(): Unit

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  18. final def notifyAll(): Unit

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  19. def splitAndCountPartitions(iter: Iterator[String]): Iterator[(String, Long)]

    Splits lines and counts the words in them using specialized object-to-long hashmap (to avoid boxing-unboxing overhead of Long in java/scala HashMap)

  20. def subtract(v1: Long, v2: Long): Long

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

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  22. def toString(): String

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  23. def topK(data: Iterator[(String, Long)], k: Int): Iterator[(String, Long)]

    Gets the top k words in terms of word counts.

    Gets the top k words in terms of word counts. Assumes that each word exists only once in the data iterator (that is, the counts have been reduced).

  24. final def wait(): Unit

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

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

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  27. def warmUp(sc: SparkContext): Unit

    Warms up the SparkContext in master and slave by running tasks to force JIT kick in before real workload starts.

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