spark.rdd

ShuffledRDD

class ShuffledRDD[K, V] extends RDD[(K, V)]

The resulting RDD from a shuffle (e.g. repartitioning of data).

K

the key class.

V

the value class.

Linear Supertypes
RDD[(K, V)], Logging, Serializable, Serializable, AnyRef, Any
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  1. ShuffledRDD
  2. RDD
  3. Logging
  4. Serializable
  5. Serializable
  6. AnyRef
  7. Any
Visibility
  1. Public
  2. All

Instance Constructors

  1. new ShuffledRDD(prev: RDD[(K, V)], part: Partitioner)

    prev

    the parent RDD.

    part

    the partitioner used to partition the RDD

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. def ++(other: RDD[(K, V)]): RDD[(K, V)]

    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).

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

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

    Definition Classes
    Any
  7. def aggregate[U](zeroValue: U)(seqOp: (U, (K, V)) ⇒ U, combOp: (U, U) ⇒ U)(implicit arg0: ClassManifest[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
    RDD
  8. final def asInstanceOf[T0]: T0

    Definition Classes
    Any
  9. def cache(): RDD[(K, V)]

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

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

    Definition Classes
    RDD
  10. def cartesian[U](other: RDD[U])(implicit arg0: ClassManifest[U]): RDD[((K, V), 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
    RDD
  11. def checkpoint(): Unit

    Mark this RDD for checkpointing.

    Mark this RDD for checkpointing. It will be saved to a file inside the checkpoint directory set with SparkContext.setCheckpointDir() and all references to its parent RDDs will be removed. This function must be called before any job has been executed on this RDD. It is strongly recommended that this RDD is persisted in memory, otherwise saving it on a file will require recomputation.

    Definition Classes
    RDD
  12. def clearDependencies(): Unit

    Clears the dependencies of this RDD.

    Clears the dependencies of this RDD. This method must ensure that all references to the original parent RDDs is removed to enable the parent RDDs to be garbage collected. Subclasses of RDD may override this method for implementing their own cleaning logic. See UnionRDD for an example.

    Attributes
    protected
    Definition Classes
    RDD
  13. def clone(): AnyRef

    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws()
  14. def coalesce(numPartitions: Int): RDD[(K, V)]

    Return a new RDD that is reduced into numPartitions partitions.

    Return a new RDD that is reduced into numPartitions partitions.

    Definition Classes
    RDD
  15. def collect[U](f: PartialFunction[(K, V), U])(implicit arg0: ClassManifest[U]): RDD[U]

    Return an RDD that contains all matching values by applying f.

    Return an RDD that contains all matching values by applying f.

    Definition Classes
    RDD
  16. def collect(): Array[(K, V)]

    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
    RDD
  17. def compute(split: Partition, context: TaskContext): Iterator[(K, V)]

    Implemented by subclasses to compute a given partition.

    Implemented by subclasses to compute a given partition.

    Definition Classes
    ShuffledRDDRDD
  18. def context: SparkContext

    The SparkContext that this RDD was created on.

    The SparkContext that this RDD was created on.

    Definition Classes
    RDD
  19. def count(): Long

    Return the number of elements in the RDD.

    Return the number of elements in the RDD.

    Definition Classes
    RDD
  20. def countApprox(timeout: Long, confidence: Double = 0.95): 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
    RDD
  21. def countByValue(): Map[(K, V), 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
    RDD
  22. def countByValueApprox(timeout: Long, confidence: Double = 0.95): PartialResult[Map[(K, V), BoundedDouble]]

    (Experimental) Approximate version of countByValue().

    (Experimental) Approximate version of countByValue().

    Definition Classes
    RDD
  23. final def dependencies: Seq[spark.Dependency[_]]

    Get the list of dependencies of this RDD, taking into account whether the RDD is checkpointed or not.

    Get the list of dependencies of this RDD, taking into account whether the RDD is checkpointed or not.

    Definition Classes
    RDD
  24. def distinct(): RDD[(K, V)]

    Definition Classes
    RDD
  25. def distinct(numPartitions: Int): RDD[(K, V)]

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

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

    Definition Classes
    RDD
  26. final def eq(arg0: AnyRef): Boolean

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

    Definition Classes
    AnyRef → Any
  28. def filter(f: ((K, V)) ⇒ Boolean): RDD[(K, V)]

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

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

    Definition Classes
    RDD
  29. def finalize(): Unit

    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws()
  30. def first(): (K, V)

    Return the first element in this RDD.

    Return the first element in this RDD.

    Definition Classes
    RDD
  31. def firstParent[U](implicit arg0: ClassManifest[U]): RDD[U]

    Returns the first parent RDD

    Returns the first parent RDD

    Attributes
    protected[spark]
    Definition Classes
    RDD
  32. def flatMap[U](f: ((K, V)) ⇒ TraversableOnce[U])(implicit arg0: ClassManifest[U]): RDD[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
    RDD
  33. def fold(zeroValue: (K, V))(op: ((K, V), (K, V)) ⇒ (K, V)): (K, V)

    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
    RDD
  34. def foreach(f: ((K, V)) ⇒ Unit): Unit

    Applies a function f to all elements of this RDD.

    Applies a function f to all elements of this RDD.

    Definition Classes
    RDD
  35. def getCheckpointFile: Option[String]

    Gets the name of the file to which this RDD was checkpointed

    Gets the name of the file to which this RDD was checkpointed

    Definition Classes
    RDD
  36. final def getClass(): java.lang.Class[_]

    Definition Classes
    AnyRef → Any
  37. def getDependencies: Seq[spark.Dependency[_]]

    Implemented by subclasses to return how this RDD depends on parent RDDs.

    Implemented by subclasses to return how this RDD depends on parent RDDs. This method will only be called once, so it is safe to implement a time-consuming computation in it.

    Attributes
    protected
    Definition Classes
    RDD
  38. def getPartitions: Array[Partition]

    Implemented by subclasses to return the set of partitions in this RDD.

    Implemented by subclasses to return the set of partitions in this RDD. This method will only be called once, so it is safe to implement a time-consuming computation in it.

    Definition Classes
    ShuffledRDDRDD
  39. def getPreferredLocations(split: Partition): Seq[String]

    Optionally overridden by subclasses to specify placement preferences.

    Optionally overridden by subclasses to specify placement preferences.

    Attributes
    protected
    Definition Classes
    RDD
  40. 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
    RDD
  41. def glom(): RDD[Array[(K, V)]]

    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
    RDD
  42. def groupBy[K](f: ((K, V)) ⇒ K, p: Partitioner)(implicit arg0: ClassManifest[K]): RDD[(K, Seq[(K, V)])]

    Return an RDD of grouped items.

    Return an RDD of grouped items.

    Definition Classes
    RDD
  43. def groupBy[K](f: ((K, V)) ⇒ K, numPartitions: Int)(implicit arg0: ClassManifest[K]): RDD[(K, Seq[(K, V)])]

    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
    RDD
  44. def groupBy[K](f: ((K, V)) ⇒ K)(implicit arg0: ClassManifest[K]): RDD[(K, Seq[(K, V)])]

    Return an RDD of grouped items.

    Return an RDD of grouped items.

    Definition Classes
    RDD
  45. def hashCode(): Int

    Definition Classes
    AnyRef → Any
  46. val id: Int

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

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

    Definition Classes
    RDD
  47. def initLogging(): Unit

    Attributes
    protected
    Definition Classes
    Logging
  48. def isCheckpointed: Boolean

    Return whether this RDD has been checkpointed or not

    Return whether this RDD has been checkpointed or not

    Definition Classes
    RDD
  49. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any
  50. final def iterator(split: Partition, context: TaskContext): Iterator[(K, V)]

    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
    RDD
  51. def keyBy[K](f: ((K, V)) ⇒ K): RDD[(K, (K, V))]

    Creates tuples of the elements in this RDD by applying f.

    Creates tuples of the elements in this RDD by applying f.

    Definition Classes
    RDD
  52. def log: Logger

    Attributes
    protected
    Definition Classes
    Logging
  53. def logDebug(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging
  54. def logDebug(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging
  55. def logError(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging
  56. def logError(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging
  57. def logInfo(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging
  58. def logInfo(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging
  59. def logTrace(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging
  60. def logTrace(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging
  61. def logWarning(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging
  62. def logWarning(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging
  63. def map[U](f: ((K, V)) ⇒ U)(implicit arg0: ClassManifest[U]): RDD[U]

    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
    RDD
  64. def mapPartitions[U](f: (Iterator[(K, V)]) ⇒ Iterator[U], preservesPartitioning: Boolean)(implicit arg0: ClassManifest[U]): RDD[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
    RDD
  65. def mapPartitionsWithIndex[U](f: (Int, Iterator[(K, V)]) ⇒ Iterator[U], preservesPartitioning: Boolean)(implicit arg0: ClassManifest[U]): RDD[U]

    Return a new RDD by applying a function to each partition of this RDD, while tracking the index of the original partition.

    Return a new RDD by applying a function to each partition of this RDD, while tracking the index of the original partition.

    Definition Classes
    RDD
  66. var name: String

    A friendly name for this RDD

    A friendly name for this RDD

    Definition Classes
    RDD
  67. final def ne(arg0: AnyRef): Boolean

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

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

    Definition Classes
    AnyRef
  70. val partitioner: Some[Partitioner]

    Optionally overridden by subclasses to specify how they are partitioned.

    Optionally overridden by subclasses to specify how they are partitioned.

    Definition Classes
    ShuffledRDDRDD
  71. final def partitions: Array[Partition]

    Get the array of partitions of this RDD, taking into account whether the RDD is checkpointed or not.

    Get the array of partitions of this RDD, taking into account whether the RDD is checkpointed or not.

    Definition Classes
    RDD
  72. def persist(): RDD[(K, V)]

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

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

    Definition Classes
    RDD
  73. def persist(newLevel: StorageLevel): RDD[(K, V)]

    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.

    Definition Classes
    RDD
  74. def pipe(command: Seq[String], env: Map[String, String]): RDD[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
    RDD
  75. def pipe(command: Seq[String]): RDD[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
    RDD
  76. def pipe(command: String): RDD[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
    RDD
  77. final def preferredLocations(split: Partition): Seq[String]

    Get the preferred location of a split, taking into account whether the RDD is checkpointed or not.

    Get the preferred location of a split, taking into account whether the RDD is checkpointed or not.

    Definition Classes
    RDD
  78. def reduce(f: ((K, V), (K, V)) ⇒ (K, V)): (K, V)

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

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

    Definition Classes
    RDD
  79. def sample(withReplacement: Boolean, fraction: Double, seed: Int): RDD[(K, V)]

    Return a sampled subset of this RDD.

    Return a sampled subset of this RDD.

    Definition Classes
    RDD
  80. 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
    RDD
  81. 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
    RDD
  82. def setName(_name: String): RDD[(K, V)]

    Assign a name to this RDD

    Assign a name to this RDD

    Definition Classes
    RDD
  83. def subtract(other: RDD[(K, V)], p: Partitioner): RDD[(K, V)]

    Return an RDD with the elements from this that are not in other.

    Return an RDD with the elements from this that are not in other.

    Definition Classes
    RDD
  84. def subtract(other: RDD[(K, V)], numPartitions: Int): RDD[(K, V)]

    Return an RDD with the elements from this that are not in other.

    Return an RDD with the elements from this that are not in other.

    Definition Classes
    RDD
  85. def subtract(other: RDD[(K, V)]): RDD[(K, V)]

    Return an RDD with the elements from this that are not in other.

    Return an RDD with the elements from this that are not in other.

    Uses this partitioner/partition size, because even if other is huge, the resulting RDD will be <= us.

    Definition Classes
    RDD
  86. final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes
    AnyRef
  87. def take(num: Int): Array[(K, V)]

    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
    RDD
  88. def takeSample(withReplacement: Boolean, num: Int, seed: Int): Array[(K, V)]

    Definition Classes
    RDD
  89. def toArray(): Array[(K, V)]

    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
    RDD
  90. def toDebugString: String

    A description of this RDD and its recursive dependencies for debugging.

    A description of this RDD and its recursive dependencies for debugging.

    Definition Classes
    RDD
  91. def toString(): String

    Definition Classes
    RDD → AnyRef → Any
  92. def union(other: RDD[(K, V)]): RDD[(K, V)]

    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).

    Definition Classes
    RDD
  93. final def wait(): Unit

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

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

    Definition Classes
    AnyRef
    Annotations
    @throws()
  96. def zip[U](other: RDD[U])(implicit arg0: ClassManifest[U]): RDD[((K, V), U)]

    Zips this RDD with another one, returning key-value pairs with the first element in each RDD, second element in each RDD, etc.

    Zips this RDD with another one, returning key-value pairs with the first element in each RDD, second element in each RDD, etc. Assumes that the two RDDs have the *same number of partitions* and the *same number of elements in each partition* (e.g. one was made through a map on the other).

    Definition Classes
    RDD

Deprecated Value Members

  1. def mapPartitionsWithSplit[U](f: (Int, Iterator[(K, V)]) ⇒ Iterator[U], preservesPartitioning: Boolean)(implicit arg0: ClassManifest[U]): RDD[U]

    Return a new RDD by applying a function to each partition of this RDD, while tracking the index of the original partition.

    Return a new RDD by applying a function to each partition of this RDD, while tracking the index of the original partition.

    Definition Classes
    RDD
    Annotations
    @deprecated
    Deprecated

    (Since version scala.this.deprecated.init$default$2) use mapPartitionsWithIndex

Inherited from RDD[(K, V)]

Inherited from Logging

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any