ZippedPartitionsBaseRDD

abstract class ZippedPartitionsBaseRDD[V] extends RDD[V]

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RDD[V], Logging, Serializable, Serializable, AnyRef, Any
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1. ZippedPartitionsBaseRDD
2. RDD
3. Logging
4. Serializable
5. Serializable
6. AnyRef
7. Any
Visibility
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Abstract Value Members

1. abstract def compute(split: Partition, context: TaskContext): Iterator[V]

Implemented by subclasses to compute a given partition.

Implemented by subclasses to compute a given partition.

Definition Classes
RDD

Concrete 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[V]): RDD[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, 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[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[(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.

Definition Classes
ZippedPartitionsBaseRDDRDD
13. def clone(): AnyRef

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

Return a new RDD that is reduced into `numPartitions` partitions.

Return a new RDD that is reduced into `numPartitions` partitions.

This results in a narrow dependency, e.g. if you go from 1000 partitions to 100 partitions, there will not be a shuffle, instead each of the 100 new partitions will claim 10 of the current partitions.

However, if you're doing a drastic coalesce, e.g. to numPartitions = 1, this may result in your computation taking place on fewer nodes than you like (e.g. one node in the case of numPartitions = 1). To avoid this, you can pass shuffle = true. This will add a shuffle step, but means the current upstream partitions will be executed in parallel (per whatever the current partitioning is).

Note: With shuffle = true, you can actually coalesce to a larger number of partitions. This is useful if you have a small number of partitions, say 100, potentially with a few partitions being abnormally large. Calling coalesce(1000, shuffle = true) will result in 1000 partitions with the data distributed using a hash partitioner.

Definition Classes
RDD
15. def collect[U](f: PartialFunction[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[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 context: SparkContext

The SparkContext that this RDD was created on.

The SparkContext that this RDD was created on.

Definition Classes
RDD
18. def count(): Long

Return the number of elements in the RDD.

Return the number of elements in the RDD.

Definition Classes
RDD
19. 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
20. def countByValue(): Map[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
21. def countByValueApprox(timeout: Long, confidence: Double = 0.95): PartialResult[Map[V, BoundedDouble]]

(Experimental) Approximate version of countByValue().

(Experimental) Approximate version of countByValue().

Definition Classes
RDD
22. final def dependencies: Seq[org.apache.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
23. def distinct(): RDD[V]

Definition Classes
RDD
24. def distinct(numPartitions: Int): RDD[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
25. final def eq(arg0: AnyRef): Boolean

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

Definition Classes
AnyRef → Any
27. def filter(f: (V) ⇒ Boolean): RDD[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
28. def filterWith[A](constructA: (Int) ⇒ A)(p: (V, A) ⇒ Boolean)(implicit arg0: ClassManifest[A]): RDD[V]

Filters this RDD with p, where p takes an additional parameter of type A.

Filters this RDD with p, where p takes an additional parameter of type A. This additional parameter is produced by constructA, which is called in each partition with the index of that partition.

Definition Classes
RDD
29. def finalize(): Unit

Attributes
protected[lang]
Definition Classes
AnyRef
Annotations
@throws()
30. def first(): 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: (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 flatMapWith[A, U](constructA: (Int) ⇒ A, preservesPartitioning: Boolean)(f: (V, A) ⇒ Seq[U])(implicit arg0: ClassManifest[A], arg1: ClassManifest[U]): RDD[U]

FlatMaps f over this RDD, where f takes an additional parameter of type A.

FlatMaps f over this RDD, where f takes an additional parameter of type A. This additional parameter is produced by constructA, which is called in each partition with the index of that partition.

Definition Classes
RDD
34. def fold(zeroValue: V)(op: (V, V) ⇒ V): 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
35. def foreach(f: (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
36. def foreachPartition(f: (Iterator[V]) ⇒ Unit): Unit

Applies a function f to each partition of this RDD.

Applies a function f to each partition of this RDD.

Definition Classes
RDD
37. def foreachWith[A](constructA: (Int) ⇒ A)(f: (V, A) ⇒ Unit)(implicit arg0: ClassManifest[A]): Unit

Applies f to each element of this RDD, where f takes an additional parameter of type A.

Applies f to each element of this RDD, where f takes an additional parameter of type A. This additional parameter is produced by constructA, which is called in each partition with the index of that partition.

Definition Classes
RDD
38. var generator: String

User-defined generator of this RDD

User-defined generator of this RDD

Definition Classes
RDD
39. 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
40. final def getClass(): java.lang.Class[_]

Definition Classes
AnyRef → Any
41. def getDependencies: Seq[org.apache.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
42. 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
ZippedPartitionsBaseRDDRDD
43. def getPreferredLocations(s: Partition): Seq[String]

Optionally overridden by subclasses to specify placement preferences.

Optionally overridden by subclasses to specify placement preferences.

Definition Classes
ZippedPartitionsBaseRDDRDD
44. 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
45. def glom(): RDD[Array[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
46. def groupBy[K](f: (V) ⇒ K, p: Partitioner)(implicit arg0: ClassManifest[K]): RDD[(K, Seq[V])]

Return an RDD of grouped items.

Return an RDD of grouped items.

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

Return an RDD of grouped items.

Return an RDD of grouped items.

Definition Classes
RDD
49. def hashCode(): Int

Definition Classes
AnyRef → Any
50. val id: Int

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

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

Definition Classes
RDD
51. def initLogging(): Unit

Attributes
protected
Definition Classes
Logging
52. def isCheckpointed: Boolean

Return whether this RDD has been checkpointed or not

Return whether this RDD has been checkpointed or not

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

Definition Classes
Any
54. def isTraceEnabled(): Boolean

Attributes
protected
Definition Classes
Logging
55. final def iterator(split: Partition, context: TaskContext): Iterator[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
56. def keyBy[K](f: (V) ⇒ K): RDD[(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
57. def log: Logger

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

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

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

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

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

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

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

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

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

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

Attributes
protected
Definition Classes
Logging
68. def map[U](f: (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
69. def mapPartitions[U](f: (Iterator[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
70. def mapPartitionsWithContext[U](f: (TaskContext, Iterator[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. This is a variant of mapPartitions that also passes the TaskContext into the closure.

Definition Classes
RDD
71. def mapPartitionsWithIndex[U](f: (Int, Iterator[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
72. def mapWith[A, U](constructA: (Int) ⇒ A, preservesPartitioning: Boolean)(f: (V, A) ⇒ U)(implicit arg0: ClassManifest[A], arg1: ClassManifest[U]): RDD[U]

Maps f over this RDD, where f takes an additional parameter of type A.

Maps f over this RDD, where f takes an additional parameter of type A. This additional parameter is produced by constructA, which is called in each partition with the index of that partition.

Definition Classes
RDD
73. var name: String

A friendly name for this RDD

A friendly name for this RDD

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

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

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

Definition Classes
AnyRef
77. val partitioner: Option[Partitioner]

Optionally overridden by subclasses to specify how they are partitioned.

Optionally overridden by subclasses to specify how they are partitioned.

Definition Classes
RDD
78. 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
79. def persist(): RDD[V]

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

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

Definition Classes
RDD
80. def persist(newLevel: StorageLevel): RDD[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. This can only be used to assign a new storage level if the RDD does not have a storage level set yet..

Definition Classes
RDD
81. def pipe(command: Seq[String], env: Map[String, String] = Map(), printPipeContext: ((String) ⇒ Unit) ⇒ Unit = null, printRDDElement: (V, (String) ⇒ Unit) ⇒ Unit = null): 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. The print behavior can be customized by providing two functions.

command

command to run in forked process.

env

environment variables to set.

printPipeContext

Before piping elements, this function is called as an oppotunity to pipe context data. Print line function (like out.println) will be passed as printPipeContext's parameter.

printRDDElement

Use this function to customize how to pipe elements. This function will be called with each RDD element as the 1st parameter, and the print line function (like out.println()) as the 2nd parameter. An example of pipe the RDD data of groupBy() in a streaming way, instead of constructing a huge String to concat all the elements: def printRDDElement(record:(String, Seq[String]), f:String=>Unit) = for (e <- record._2){f(e)}

returns

the result RDD

Definition Classes
RDD
82. def pipe(command: 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
83. 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
84. final def preferredLocations(split: Partition): Seq[String]

Get the preferred locations of a partition (as hostnames), taking into account whether the RDD is checkpointed.

Get the preferred locations of a partition (as hostnames), taking into account whether the RDD is checkpointed.

Definition Classes
RDD

86. def reduce(f: (V, V) ⇒ V): 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
87. def repartition(numPartitions: Int): RDD[V]

Return a new RDD that has exactly numPartitions partitions.

Return a new RDD that has exactly numPartitions partitions.

Can increase or decrease the level of parallelism in this RDD. Internally, this uses a shuffle to redistribute data.

If you are decreasing the number of partitions in this RDD, consider using `coalesce`, which can avoid performing a shuffle.

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

Return a sampled subset of this RDD.

Return a sampled subset of this RDD.

Definition Classes
RDD
89. 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
90. def saveAsTextFile(path: String, codec: Class[_ <: org.apache.hadoop.io.compress.CompressionCodec]): Unit

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

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

Definition Classes
RDD
91. 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
92. def setGenerator(_generator: String): Unit

Reset generator

Reset generator

Definition Classes
RDD
93. def setName(_name: String): RDD[V]

Assign a name to this RDD

Assign a name to this RDD

Definition Classes
RDD
94. def sparkContext: SparkContext

The SparkContext that created this RDD.

The SparkContext that created this RDD.

Definition Classes
RDD
95. def subtract(other: RDD[V], p: Partitioner): RDD[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
96. def subtract(other: RDD[V], numPartitions: Int): RDD[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
97. def subtract(other: RDD[V]): RDD[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
98. final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
99. def take(num: Int): Array[V]

Take the first num elements of the RDD.

Take the first num elements of the RDD. It works by first scanning one partition, and use the results from that partition to estimate the number of additional partitions needed to satisfy the limit.

Definition Classes
RDD
100. def takeOrdered(num: Int)(implicit ord: Ordering[V]): Array[V]

Returns the first K elements from this RDD as defined by the specified implicit Ordering[T] and maintains the ordering.

Returns the first K elements from this RDD as defined by the specified implicit Ordering[T] and maintains the ordering.

num

the number of top elements to return

ord

the implicit ordering for T

returns

an array of top elements

Definition Classes
RDD
101. def takeSample(withReplacement: Boolean, num: Int, seed: Int): Array[V]

Definition Classes
RDD
102. def toArray(): Array[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
103. 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
104. def toJavaRDD(): JavaRDD[V]

Definition Classes
RDD
105. def toString(): String

Definition Classes
RDD → AnyRef → Any
106. def top(num: Int)(implicit ord: Ordering[V]): Array[V]

Returns the top K elements from this RDD as defined by the specified implicit Ordering[T].

Returns the top K elements from this RDD as defined by the specified implicit Ordering[T].

num

the number of top elements to return

ord

the implicit ordering for T

returns

an array of top elements

Definition Classes
RDD
107. def union(other: RDD[V]): RDD[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
108. def unpersist(blocking: Boolean = true): RDD[V]

Mark the RDD as non-persistent, and remove all blocks for it from memory and disk.

Mark the RDD as non-persistent, and remove all blocks for it from memory and disk.

blocking

Whether to block until all blocks are deleted.

returns

This RDD.

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

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

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

Definition Classes
AnyRef
Annotations
@throws()
112. def zip[U](other: RDD[U])(implicit arg0: ClassManifest[U]): RDD[(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
113. def zipPartitions[B, C, D, V](rdd2: RDD[B], rdd3: RDD[C], rdd4: RDD[D])(f: (Iterator[V], Iterator[B], Iterator[C], Iterator[D]) ⇒ Iterator[V])(implicit arg0: ClassManifest[B], arg1: ClassManifest[C], arg2: ClassManifest[D], arg3: ClassManifest[V]): RDD[V]

Definition Classes
RDD
114. def zipPartitions[B, C, V](rdd2: RDD[B], rdd3: RDD[C])(f: (Iterator[V], Iterator[B], Iterator[C]) ⇒ Iterator[V])(implicit arg0: ClassManifest[B], arg1: ClassManifest[C], arg2: ClassManifest[V]): RDD[V]

Definition Classes
RDD
115. def zipPartitions[B, V](rdd2: RDD[B])(f: (Iterator[V], Iterator[B]) ⇒ Iterator[V])(implicit arg0: ClassManifest[B], arg1: ClassManifest[V]): RDD[V]

Zip this RDD's partitions with one (or more) RDD(s) and return a new RDD by applying a function to the zipped partitions.

Zip this RDD's partitions with one (or more) RDD(s) and return a new RDD by applying a function to the zipped partitions. Assumes that all the RDDs have the *same number of partitions*, but does *not* require them to have the same number of elements in each partition.

Definition Classes
RDD

Deprecated Value Members

1. def mapPartitionsWithSplit[U](f: (Int, Iterator[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 0.7.0) use mapPartitionsWithIndex