# ShuffledSortedRDD

#### class ShuffledSortedRDD[K, V] extends RepartitionShuffledRDD[K, V]

A sort-based shuffle (that doesn't apply aggregation). It does so by first repartitioning the RDD by range, and then sort within each range.

Linear Supertypes
RepartitionShuffledRDD[K, V], ShuffledRDD[K, V, V], RDD[(K, V)], Serializable, Serializable, AnyRef, Any
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1. ShuffledSortedRDD
2. RepartitionShuffledRDD
3. ShuffledRDD
4. RDD
5. Serializable
6. Serializable
7. AnyRef
8. Any
Visibility
1. Public
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### 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 clone(): AnyRef

Attributes
protected[lang]
Definition Classes
AnyRef
Annotations
@throws()
12. #### 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
13. #### def compute(split: Split): Iterator[(K, V)]

Function for computing a given partition.

Function for computing a given partition.

Definition Classes
ShuffledSortedRDDRepartitionShuffledRDDRDD
14. #### def context: SparkContext

The SparkContext that this RDD was created on.

The SparkContext that this RDD was created on.

Definition Classes
RDD
15. #### def count(): Long

Return the number of elements in the RDD.

Return the number of elements in the RDD.

Definition Classes
RDD
16. #### 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
17. #### 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
18. #### 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
19. #### val dep: ShuffleDependency[K, V, V]

Definition Classes
ShuffledRDD
20. #### val dependencies: List[ShuffleDependency[K, V, V]]

How this RDD depends on any parent RDDs.

How this RDD depends on any parent RDDs.

Definition Classes
ShuffledRDDRDD
21. #### def distinct(numSplits: Int = splits.size): 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
22. #### final def eq(arg0: AnyRef): Boolean

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

Definition Classes
AnyRef → Any
24. #### 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
25. #### def finalize(): Unit

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

Return the first element in this RDD.

Return the first element in this RDD.

Definition Classes
RDD
27. #### 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
28. #### 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
29. #### 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
30. #### final def getClass(): java.lang.Class[_]

Definition Classes
AnyRef → Any
31. #### 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
32. #### 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
33. #### 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
34. #### def groupBy[K](f: ((K, V)) ⇒ K, numSplits: 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
35. #### def hashCode(): Int

Definition Classes
AnyRef → Any
36. #### val id: Int

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

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

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

Definition Classes
Any
38. #### final def iterator(split: Split): 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
39. #### 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
40. #### def mapPartitions[U](f: (Iterator[(K, V)]) ⇒ Iterator[U])(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
41. #### def mapPartitionsWithSplit[U](f: (Int, Iterator[(K, V)]) ⇒ Iterator[U])(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
42. #### final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
43. #### final def notify(): Unit

Definition Classes
AnyRef
44. #### final def notifyAll(): Unit

Definition Classes
AnyRef
45. #### 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
46. #### 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
47. #### 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
48. #### 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
49. #### 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
50. #### 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
51. #### def preferredLocations(split: Split): scala.collection.immutable.Nil.type

Optionally overridden by subclasses to specify placement preferences.

Optionally overridden by subclasses to specify placement preferences.

Definition Classes
ShuffledRDDRDD
52. #### def reduce(f: ((K, V), (K, V)) ⇒ (K, V)): (K, V)

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
RDD
53. #### 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
54. #### 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
55. #### 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
56. #### def splits: Array[Split]

Set of partitions in this RDD.

Set of partitions in this RDD.

Definition Classes
ShuffledRDDRDD
57. #### val splits_: Array[Split]

Definition Classes
ShuffledRDD
58. #### final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
59. #### 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
60. #### def takeSample(withReplacement: Boolean, num: Int, seed: Int): Array[(K, V)]

Definition Classes
RDD
61. #### 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
62. #### def toString(): String

Definition Classes
AnyRef → Any
63. #### 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
64. #### final def wait(): Unit

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

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

Definition Classes
AnyRef
Annotations
@throws()