spark

DoubleRDDFunctions

class DoubleRDDFunctions extends Logging with Serializable

Extra functions available on RDDs of Doubles through an implicit conversion. Import spark.SparkContext._ at the top of your program to use these functions.

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  1. DoubleRDDFunctions
  2. Serializable
  3. Serializable
  4. Logging
  5. AnyRef
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Instance Constructors

  1. new DoubleRDDFunctions(self: RDD[Double])

Value Members

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

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    AnyRef
  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. final def asInstanceOf[T0]: T0

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  7. def clone(): AnyRef

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    protected[lang]
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  8. final def eq(arg0: AnyRef): Boolean

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  9. def equals(arg0: Any): Boolean

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  10. def finalize(): Unit

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

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  12. def hashCode(): Int

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  13. def initLogging(): Unit

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    protected
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    Logging
  14. final def isInstanceOf[T0]: Boolean

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  15. def log: Logger

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    protected
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    Logging
  16. def logDebug(msg: ⇒ String, throwable: Throwable): Unit

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    Logging
  17. def logDebug(msg: ⇒ String): Unit

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  18. def logError(msg: ⇒ String, throwable: Throwable): Unit

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  19. def logError(msg: ⇒ String): Unit

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  20. def logInfo(msg: ⇒ String, throwable: Throwable): Unit

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  21. def logInfo(msg: ⇒ String): Unit

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  22. def logTrace(msg: ⇒ String, throwable: Throwable): Unit

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    protected
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  23. def logTrace(msg: ⇒ String): Unit

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  24. def logWarning(msg: ⇒ String, throwable: Throwable): Unit

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    protected
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    Logging
  25. def logWarning(msg: ⇒ String): Unit

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    protected
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  26. def mean(): Double

    Compute the mean of this RDD's elements.

  27. def meanApprox(timeout: Long, confidence: Double = 0.95): PartialResult[BoundedDouble]

    (Experimental) Approximate operation to return the mean within a timeout.

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

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  29. final def notify(): Unit

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  30. final def notifyAll(): Unit

    Definition Classes
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  31. def sampleStdev(): Double

    Compute the sample standard deviation of this RDD's elements (which corrects for bias in estimating the standard deviation by dividing by N-1 instead of N).

  32. def stats(): StatCounter

    Return a StatCounter object that captures the mean, variance and count of the RDD's elements in one operation.

  33. def stdev(): Double

    Compute the standard deviation of this RDD's elements.

  34. def sum(): Double

    Add up the elements in this RDD.

  35. def sumApprox(timeout: Long, confidence: Double = 0.95): PartialResult[BoundedDouble]

    (Experimental) Approximate operation to return the sum within a timeout.

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

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  37. def toString(): String

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  38. def variance(): Double

    Compute the variance of this RDD's elements.

  39. final def wait(): Unit

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

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    @throws()
  41. final def wait(arg0: Long): Unit

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Inherited from Serializable

Inherited from Serializable

Inherited from Logging

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