spark.timeseries

RunRDD

class RunRDD [T] extends RDD[Run[T]]

A class that represents an RDD of Runs.

Splits up a parent RDD containing a series of measurement data into meaningful partitions such as measurement runs, activity peaks, etc. Accepts a RunDetector to detect Runs from data and partition the data into them.

Overlapping runs are currently not supported. To support them, store data in the RunDetector implementation.

Linear Supertypes
RDD[Run[T]], Serializable, Serializable, AnyRef, Any
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  1. RunRDD
  2. RDD
  3. Serializable
  4. Serializable
  5. AnyRef
  6. Any
Visibility
  1. Public
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Instance Constructors

  1. new RunRDD (prev: RDD[Array[T]], detector: RunDetector[T])(implicit arg0: ClassManifest[T])

Type Members

  1. type _$1

    Attributes
    abstract
    Definition Classes
    RDD

Value Members

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

    Attributes
    final
    Definition Classes
    AnyRef

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

    Attributes
    final
    Definition Classes
    Any

  3. def ## (): Int

    Attributes
    final
    Definition Classes
    AnyRef → Any

  4. def ++ (other: RDD[Run[T]]): RDD[Run[T]]

    Definition Classes
    RDD

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

    Attributes
    final
    Definition Classes
    AnyRef

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

    Attributes
    final
    Definition Classes
    Any

  7. def asInstanceOf [T0] : T0

    Attributes
    final
    Definition Classes
    Any

  8. def cache (): RDD[Run[T]]

    Definition Classes
    RDD

  9. def cartesian [U] (other: RDD[U])(implicit arg0: ClassManifest[U]): RDD[(Run[T], U)]

    Definition Classes
    RDD

  10. def clone (): AnyRef

    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws()

  11. def collect (): Array[Run[T]]

    Definition Classes
    RDD

  12. def compute (split: Split): Iterator[Run[T]]

    Computes the splits according to the spark.timeseries.RunDetector[T] given.

    Computes the splits according to the spark.timeseries.RunDetector[T] given.

    Definition Classes
    RunRDD → RDD

  13. def context : SparkContext

    Definition Classes
    RDD

  14. def count (): Long

    Definition Classes
    RDD

  15. val dependencies : List[OneToOneDependency[Array[T]]]

    Definition Classes
    RunRDD → RDD

  16. def eq (arg0: AnyRef): Boolean

    Attributes
    final
    Definition Classes
    AnyRef

  17. def equals (arg0: Any): Boolean

    Definition Classes
    AnyRef → Any

  18. def filter (f: (Run[T]) ⇒ Boolean): RDD[Run[T]]

    Definition Classes
    RDD

  19. def finalize (): Unit

    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws()

  20. def first (): Run[T]

    Definition Classes
    RDD

  21. def flatMap [U] (f: (Run[T]) ⇒ Traversable[U])(implicit arg0: ClassManifest[U]): RDD[U]

    Definition Classes
    RDD

  22. def foreach (f: (Run[T]) ⇒ Unit): Unit

    Definition Classes
    RDD

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

    Attributes
    final
    Definition Classes
    AnyRef → Any

  24. def glom (): RDD[Array[Run[T]]]

    Definition Classes
    RDD

  25. def groupBy [K] (f: (Run[T]) ⇒ K)(implicit arg0: ClassManifest[K]): RDD[(K, Seq[Run[T]])]

    Definition Classes
    RDD

  26. def groupBy [K] (f: (Run[T]) ⇒ K, numSplits: Int)(implicit arg0: ClassManifest[K]): RDD[(K, Seq[Run[T]])]

    Definition Classes
    RDD

  27. def hashCode (): Int

    Definition Classes
    AnyRef → Any

  28. val id : Int

    Definition Classes
    RDD

  29. def isInstanceOf [T0] : Boolean

    Attributes
    final
    Definition Classes
    Any

  30. def iterator (split: Split): Iterator[Run[T]]

    Attributes
    final
    Definition Classes
    RDD

  31. def map [U] (f: (Run[T]) ⇒ U)(implicit arg0: ClassManifest[U]): RDD[U]

    Definition Classes
    RDD

  32. def mapPartitions [U] (f: (Iterator[Run[T]]) ⇒ Iterator[U])(implicit arg0: ClassManifest[U]): RDD[U]

    Definition Classes
    RDD

  33. def ne (arg0: AnyRef): Boolean

    Attributes
    final
    Definition Classes
    AnyRef

  34. def notify (): Unit

    Attributes
    final
    Definition Classes
    AnyRef

  35. def notifyAll (): Unit

    Attributes
    final
    Definition Classes
    AnyRef

  36. val partitioner : Option[Partitioner]

    Definition Classes
    RDD

  37. def pipe (command: Seq[String]): RDD[String]

    Definition Classes
    RDD

  38. def pipe (command: String): RDD[String]

    Definition Classes
    RDD

  39. def preferredLocations (split: Split): Seq[String]

    Definition Classes
    RDD

  40. val prevSplits : Array[Split]

  41. def reduce (f: (Run[T], Run[T]) ⇒ Run[T]): Run[T]

    Definition Classes
    RDD

  42. def sample (withReplacement: Boolean, fraction: Double, seed: Int): RDD[Run[T]]

    Definition Classes
    RDD

  43. def saveAsObjectFile (path: String): Unit

    Definition Classes
    RDD

  44. def saveAsTextFile (path: String): Unit

    Definition Classes
    RDD

  45. def splits : Array[Split]

    Definition Classes
    RunRDD → RDD

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

    Attributes
    final
    Definition Classes
    AnyRef

  47. def take (num: Int): Array[Run[T]]

    Definition Classes
    RDD

  48. def toArray (): Array[Run[T]]

    Definition Classes
    RDD

  49. def toString (): String

    Definition Classes
    AnyRef → Any

  50. def union (other: RDD[Run[T]]): RDD[Run[T]]

    Definition Classes
    RDD

  51. def wait (): Unit

    Attributes
    final
    Definition Classes
    AnyRef
    Annotations
    @throws()

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

    Attributes
    final
    Definition Classes
    AnyRef
    Annotations
    @throws()

  53. def wait (arg0: Long): Unit

    Attributes
    final
    Definition Classes
    AnyRef
    Annotations
    @throws()

Inherited from RDD[Run[T]]

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any