spark.api.java

JavaDoubleRDD

class JavaDoubleRDD extends JavaRDDLike[Double, JavaDoubleRDD]

Linear Supertypes
JavaRDDLike[Double, JavaDoubleRDD], Serializable, Serializable, AnyRef, Any
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  1. JavaDoubleRDD
  2. JavaRDDLike
  3. Serializable
  4. Serializable
  5. AnyRef
  6. Any
Visibility
  1. Public
  2. All

Instance Constructors

  1. new JavaDoubleRDD(srdd: RDD[Double])

Value Members

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

    Definition Classes
    AnyRef
  2. final def !=(arg0: Any): Boolean

    Definition Classes
    Any
  3. final def ##(): Int

    Definition Classes
    AnyRef → Any
  4. final def ==(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  5. final def ==(arg0: Any): Boolean

    Definition Classes
    Any
  6. def aggregate[U](zeroValue: U)(seqOp: Function2[U, Double, U], combOp: Function2[U, U, U]): U

    Aggregate the elements of each partition, and then the results for all the partitions, using given combine functions and a neutral "zero value".

    Aggregate the elements of each partition, and then the results for all the partitions, using given combine functions and a neutral "zero value". This function can return a different result type, U, than the type of this RDD, T. Thus, we need one operation for merging a T into an U and one operation for merging two U's, as in scala.TraversableOnce. Both of these functions are allowed to modify and return their first argument instead of creating a new U to avoid memory allocation.

    Definition Classes
    JavaRDDLike
  7. final def asInstanceOf[T0]: T0

    Definition Classes
    Any
  8. def cache(): JavaDoubleRDD

    Persist this RDD with the default storage level (MEMORY_ONLY).

  9. def cartesian[U](other: spark.api.java.JavaRDDLike[U, _]): JavaPairRDD[Double, U]

    Return the Cartesian product of this RDD and another one, that is, the RDD of all pairs of elements (a, b) where a is in this and b is in other.

    Return the Cartesian product of this RDD and another one, that is, the RDD of all pairs of elements (a, b) where a is in this and b is in other.

    Definition Classes
    JavaRDDLike
  10. val classManifest: ClassManifest[Double]

    Definition Classes
    JavaDoubleRDDJavaRDDLike
  11. def clone(): AnyRef

    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws()
  12. def collect(): List[Double]

    Return an array that contains all of the elements in this RDD.

    Return an array that contains all of the elements in this RDD.

    Definition Classes
    JavaRDDLike
  13. def context: SparkContext

    The SparkContext that this RDD was created on.

    The SparkContext that this RDD was created on.

    Definition Classes
    JavaRDDLike
  14. def count(): Long

    Return the number of elements in the RDD.

    Return the number of elements in the RDD.

    Definition Classes
    JavaRDDLike
  15. def countApprox(timeout: Long): PartialResult[BoundedDouble]

    (Experimental) Approximate version of count() that returns a potentially incomplete result within a timeout, even if not all tasks have finished.

    (Experimental) Approximate version of count() that returns a potentially incomplete result within a timeout, even if not all tasks have finished.

    Definition Classes
    JavaRDDLike
  16. def countApprox(timeout: Long, confidence: Double): PartialResult[BoundedDouble]

    (Experimental) Approximate version of count() that returns a potentially incomplete result within a timeout, even if not all tasks have finished.

    (Experimental) Approximate version of count() that returns a potentially incomplete result within a timeout, even if not all tasks have finished.

    Definition Classes
    JavaRDDLike
  17. def countByValue(): Map[Double, Long]

    Return the count of each unique value in this RDD as a map of (value, count) pairs.

    Return the count of each unique value in this RDD as a map of (value, count) pairs. The final combine step happens locally on the master, equivalent to running a single reduce task.

    Definition Classes
    JavaRDDLike
  18. def countByValueApprox(timeout: Long): PartialResult[Map[Double, BoundedDouble]]

    (Experimental) Approximate version of countByValue().

    (Experimental) Approximate version of countByValue().

    Definition Classes
    JavaRDDLike
  19. def countByValueApprox(timeout: Long, confidence: Double): PartialResult[Map[Double, BoundedDouble]]

    (Experimental) Approximate version of countByValue().

    (Experimental) Approximate version of countByValue().

    Definition Classes
    JavaRDDLike
  20. def distinct(numSplits: Int): JavaDoubleRDD

    Return a new RDD containing the distinct elements in this RDD.

  21. def distinct(): JavaDoubleRDD

    Return a new RDD containing the distinct elements in this RDD.

  22. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  23. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any
  24. def filter(f: Function[Double, Boolean]): JavaDoubleRDD

    Return a new RDD containing only the elements that satisfy a predicate.

  25. def finalize(): Unit

    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws()
  26. def first(): Double

    Return the first element in this RDD.

    Return the first element in this RDD.

    Definition Classes
    JavaDoubleRDDJavaRDDLike
  27. def flatMap[K, V](f: PairFlatMapFunction[Double, K, V]): JavaPairRDD[K, V]

    Return a new RDD by first applying a function to all elements of this RDD, and then flattening the results.

    Return a new RDD by first applying a function to all elements of this RDD, and then flattening the results.

    Definition Classes
    JavaRDDLike
  28. def flatMap(f: DoubleFlatMapFunction[Double]): JavaDoubleRDD

    Return a new RDD by first applying a function to all elements of this RDD, and then flattening the results.

    Return a new RDD by first applying a function to all elements of this RDD, and then flattening the results.

    Definition Classes
    JavaRDDLike
  29. def flatMap[U](f: FlatMapFunction[Double, U]): JavaRDD[U]

    Return a new RDD by first applying a function to all elements of this RDD, and then flattening the results.

    Return a new RDD by first applying a function to all elements of this RDD, and then flattening the results.

    Definition Classes
    JavaRDDLike
  30. def fold(zeroValue: Double)(f: Function2[Double, Double, Double]): Double

    Aggregate the elements of each partition, and then the results for all the partitions, using a given associative function and a neutral "zero value".

    Aggregate the elements of each partition, and then the results for all the partitions, using a given associative function and a neutral "zero value". The function op(t1, t2) is allowed to modify t1 and return it as its result value to avoid object allocation; however, it should not modify t2.

    Definition Classes
    JavaRDDLike
  31. def foreach(f: VoidFunction[Double]): Unit

    Applies a function f to all elements of this RDD.

    Applies a function f to all elements of this RDD.

    Definition Classes
    JavaRDDLike
  32. final def getClass(): java.lang.Class[_]

    Definition Classes
    AnyRef → Any
  33. def getStorageLevel: StorageLevel

    Get the RDD's current storage level, or StorageLevel.

    Get the RDD's current storage level, or StorageLevel.NONE if none is set.

    Definition Classes
    JavaRDDLike
  34. def glom(): JavaRDD[List[Double]]

    Return an RDD created by coalescing all elements within each partition into an array.

    Return an RDD created by coalescing all elements within each partition into an array.

    Definition Classes
    JavaRDDLike
  35. def groupBy[K](f: Function[Double, K], numSplits: Int): JavaPairRDD[K, List[Double]]

    Return an RDD of grouped elements.

    Return an RDD of grouped elements. Each group consists of a key and a sequence of elements mapping to that key.

    Definition Classes
    JavaRDDLike
  36. def groupBy[K](f: Function[Double, K]): JavaPairRDD[K, List[Double]]

    Return an RDD of grouped elements.

    Return an RDD of grouped elements. Each group consists of a key and a sequence of elements mapping to that key.

    Definition Classes
    JavaRDDLike
  37. def hashCode(): Int

    Definition Classes
    AnyRef → Any
  38. def id: Int

    A unique ID for this RDD (within its SparkContext).

    A unique ID for this RDD (within its SparkContext).

    Definition Classes
    JavaRDDLike
  39. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any
  40. def iterator(split: Split): Iterator[Double]

    Internal method to this RDD; will read from cache if applicable, or otherwise compute it.

    Internal method to this RDD; will read from cache if applicable, or otherwise compute it. This should not be called by users directly, but is available for implementors of custom subclasses of RDD.

    Definition Classes
    JavaRDDLike
  41. def map[K2, V2](f: PairFunction[Double, K2, V2]): JavaPairRDD[K2, V2]

    Return a new RDD by applying a function to all elements of this RDD.

    Return a new RDD by applying a function to all elements of this RDD.

    Definition Classes
    JavaRDDLike
  42. def map[R](f: DoubleFunction[Double]): JavaDoubleRDD

    Return a new RDD by applying a function to all elements of this RDD.

    Return a new RDD by applying a function to all elements of this RDD.

    Definition Classes
    JavaRDDLike
  43. def map[R](f: Function[Double, R]): JavaRDD[R]

    Return a new RDD by applying a function to all elements of this RDD.

    Return a new RDD by applying a function to all elements of this RDD.

    Definition Classes
    JavaRDDLike
  44. def mapPartitions[K, V](f: PairFlatMapFunction[Iterator[Double], K, V]): JavaPairRDD[K, V]

    Return a new RDD by applying a function to each partition of this RDD.

    Return a new RDD by applying a function to each partition of this RDD.

    Definition Classes
    JavaRDDLike
  45. def mapPartitions(f: DoubleFlatMapFunction[Iterator[Double]]): JavaDoubleRDD

    Return a new RDD by applying a function to each partition of this RDD.

    Return a new RDD by applying a function to each partition of this RDD.

    Definition Classes
    JavaRDDLike
  46. def mapPartitions[U](f: FlatMapFunction[Iterator[Double], U]): JavaRDD[U]

    Return a new RDD by applying a function to each partition of this RDD.

    Return a new RDD by applying a function to each partition of this RDD.

    Definition Classes
    JavaRDDLike
  47. def mean(): Double

    Return the mean of the elements in this RDD.

  48. def meanApprox(timeout: Long): PartialResult[BoundedDouble]

    Return the approximate mean of the elements in this RDD.

  49. def meanApprox(timeout: Long, confidence: Double): PartialResult[BoundedDouble]

    Return the approximate mean of the elements in this RDD.

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

    Definition Classes
    AnyRef
  51. final def notify(): Unit

    Definition Classes
    AnyRef
  52. final def notifyAll(): Unit

    Definition Classes
    AnyRef
  53. def persist(newLevel: StorageLevel): JavaDoubleRDD

    Set this RDD's storage level to persist its values across operations after the first time it is computed.

    Set this RDD's storage level to persist its values across operations after the first time it is computed. Can only be called once on each RDD.

  54. def pipe(command: List[String], env: Map[String, String]): JavaRDD[String]

    Return an RDD created by piping elements to a forked external process.

    Return an RDD created by piping elements to a forked external process.

    Definition Classes
    JavaRDDLike
  55. def pipe(command: List[String]): JavaRDD[String]

    Return an RDD created by piping elements to a forked external process.

    Return an RDD created by piping elements to a forked external process.

    Definition Classes
    JavaRDDLike
  56. def pipe(command: String): JavaRDD[String]

    Return an RDD created by piping elements to a forked external process.

    Return an RDD created by piping elements to a forked external process.

    Definition Classes
    JavaRDDLike
  57. val rdd: RDD[Double]

    Definition Classes
    JavaDoubleRDDJavaRDDLike
  58. def reduce(f: Function2[Double, Double, Double]): Double

    Reduces the elements of this RDD using the specified associative binary operator.

    Reduces the elements of this RDD using the specified associative binary operator.

    Definition Classes
    JavaRDDLike
  59. def sample(withReplacement: Boolean, fraction: Double, seed: Int): JavaDoubleRDD

    Return a sampled subset of this RDD.

  60. def saveAsObjectFile(path: String): Unit

    Save this RDD as a SequenceFile of serialized objects.

    Save this RDD as a SequenceFile of serialized objects.

    Definition Classes
    JavaRDDLike
  61. def saveAsTextFile(path: String): Unit

    Save this RDD as a text file, using string representations of elements.

    Save this RDD as a text file, using string representations of elements.

    Definition Classes
    JavaRDDLike
  62. def splits: List[Split]

    Set of partitions in this RDD.

    Set of partitions in this RDD.

    Definition Classes
    JavaRDDLike
  63. val srdd: RDD[Double]

  64. def stats(): StatCounter

    Return a spark.StatCounter describing the elements in this RDD.

  65. def stdev(): Double

    Return the standard deviation of the elements in this RDD.

  66. def sum(): Double

    Return the sum of the elements in this RDD.

  67. def sumApprox(timeout: Long): PartialResult[BoundedDouble]

    Return the approximate sum of the elements in this RDD.

  68. def sumApprox(timeout: Long, confidence: Double): PartialResult[BoundedDouble]

    Return the approximate sum of the elements in this RDD.

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

    Definition Classes
    AnyRef
  70. def take(num: Int): List[Double]

    Take the first num elements of the RDD.

    Take the first num elements of the RDD. This currently scans the partitions *one by one*, so it will be slow if a lot of partitions are required. In that case, use collect() to get the whole RDD instead.

    Definition Classes
    JavaRDDLike
  71. def takeSample(withReplacement: Boolean, num: Int, seed: Int): List[Double]

    Definition Classes
    JavaRDDLike
  72. def toString(): String

    Definition Classes
    AnyRef → Any
  73. def union(other: JavaDoubleRDD): JavaDoubleRDD

    Return the union of this RDD and another one.

    Return the union of this RDD and another one. Any identical elements will appear multiple times (use .distinct() to eliminate them).

  74. def variance(): Double

    Return the variance of the elements in this RDD.

  75. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws()
  76. final def wait(arg0: Long, arg1: Int): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws()
  77. final def wait(arg0: Long): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws()
  78. def wrapRDD(rdd: RDD[Double]): JavaDoubleRDD

    Definition Classes
    JavaDoubleRDDJavaRDDLike

Inherited from JavaRDDLike[Double, JavaDoubleRDD]

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any