org.apache.spark.api.java

JavaRDD

class JavaRDD[T] extends JavaRDDLike[T, JavaRDD[T]]

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JavaRDDLike[T, JavaRDD[T]], Serializable, Serializable, AnyRef, Any
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  2. JavaRDDLike
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Instance Constructors

  1. new JavaRDD(rdd: RDD[T])(implicit classTag: ClassTag[T])

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, T, 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(): JavaRDD[T]

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

  9. def cartesian[U](other: JavaRDDLike[U, _]): JavaPairRDD[T, 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. 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
    JavaRDDLike
  11. implicit val classTag: ClassTag[T]

    Definition Classes
    JavaRDDJavaRDDLike
  12. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  13. def coalesce(numPartitions: Int, shuffle: Boolean): JavaRDD[T]

    Return a new RDD that is reduced into numPartitions partitions.

  14. def coalesce(numPartitions: Int): JavaRDD[T]

    Return a new RDD that is reduced into numPartitions partitions.

  15. def collect(): List[T]

    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
  16. def collectPartitions(partitionIds: Array[Int]): Array[List[T]]

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

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

    Definition Classes
    JavaRDDLike
  17. def context: SparkContext

    The org.apache.spark.SparkContext that this RDD was created on.

    The org.apache.spark.SparkContext that this RDD was created on.

    Definition Classes
    JavaRDDLike
  18. def count(): Long

    Return the number of elements in the RDD.

    Return the number of elements in the RDD.

    Definition Classes
    JavaRDDLike
  19. 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
  20. 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
  21. def countApproxDistinct(relativeSD: Double = 0.05): Long

    Return approximate number of distinct elements in the RDD.

    Return approximate number of distinct elements in the RDD.

    The accuracy of approximation can be controlled through the relative standard deviation (relativeSD) parameter, which also controls the amount of memory used. Lower values result in more accurate counts but increase the memory footprint and vise versa. The default value of relativeSD is 0.05.

    Definition Classes
    JavaRDDLike
  22. def countByValue(): Map[T, 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
  23. def countByValueApprox(timeout: Long): PartialResult[Map[T, BoundedDouble]]

    (Experimental) Approximate version of countByValue().

    (Experimental) Approximate version of countByValue().

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

    (Experimental) Approximate version of countByValue().

    (Experimental) Approximate version of countByValue().

    Definition Classes
    JavaRDDLike
  25. def distinct(numPartitions: Int): JavaRDD[T]

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

  26. def distinct(): JavaRDD[T]

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

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

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

    Definition Classes
    AnyRef → Any
  29. def filter(f: Function[T, Boolean]): JavaRDD[T]

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

  30. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  31. def first(): T

    Return the first element in this RDD.

    Return the first element in this RDD.

    Definition Classes
    JavaRDDLike
  32. def flatMap[K2, V2](f: PairFlatMapFunction[T, K2, V2]): JavaPairRDD[K2, V2]

    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
  33. def flatMap(f: DoubleFlatMapFunction[T]): 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
  34. def flatMap[U](f: FlatMapFunction[T, 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
  35. def fold(zeroValue: T)(f: Function2[T, T, T]): T

    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
  36. def foreach(f: VoidFunction[T]): Unit

    Applies a function f to all elements of this RDD.

    Applies a function f to all elements of this RDD.

    Definition Classes
    JavaRDDLike
  37. def getCheckpointFile(): Optional[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
    JavaRDDLike
  38. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any
  39. 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
  40. def glom(): JavaRDD[List[T]]

    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
  41. def groupBy[K](f: Function[T, K], numPartitions: Int): JavaPairRDD[K, List[T]]

    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
  42. def groupBy[K](f: Function[T, K]): JavaPairRDD[K, List[T]]

    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
  43. def hashCode(): Int

    Definition Classes
    AnyRef → Any
  44. def id: Int

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

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

    Definition Classes
    JavaRDDLike
  45. def isCheckpointed: Boolean

    Return whether this RDD has been checkpointed or not

    Return whether this RDD has been checkpointed or not

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

    Definition Classes
    Any
  47. def iterator(split: Partition, taskContext: TaskContext): Iterator[T]

    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
  48. def keyBy[K](f: Function[T, K]): JavaPairRDD[K, T]

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

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

    Definition Classes
    JavaRDDLike
  49. def map[K2, V2](f: PairFunction[T, 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
  50. def map[R](f: DoubleFunction[T]): 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
  51. def map[R](f: Function[T, 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
  52. def mapPartitions[K2, V2](f: PairFlatMapFunction[Iterator[T], K2, V2]): JavaPairRDD[K2, V2]

    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
  53. def mapPartitions(f: DoubleFlatMapFunction[Iterator[T]]): 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
  54. def mapPartitions[U](f: FlatMapFunction[Iterator[T], 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
  55. def mapPartitionsWithIndex[R](f: Function2[Int, Iterator[T], Iterator[R]], preservesPartitioning: Boolean = false)(implicit arg0: ClassTag[R]): JavaRDD[R]

    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
    JavaRDDLike
  56. def name(): String

    Definition Classes
    JavaRDDLike
  57. final def ne(arg0: AnyRef): Boolean

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

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

    Definition Classes
    AnyRef
  60. def persist(newLevel: StorageLevel): JavaRDD[T]

    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..

  61. 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
  62. 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
  63. 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
  64. val rdd: RDD[T]

    Definition Classes
    JavaRDDJavaRDDLike
  65. def reduce(f: Function2[T, T, T]): T

    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
    JavaRDDLike
  66. def repartition(numPartitions: Int): JavaRDD[T]

    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.

  67. def sample(withReplacement: Boolean, fraction: Double, seed: Int): JavaRDD[T]

    Return a sampled subset of this RDD.

  68. 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
  69. def saveAsTextFile(path: String, codec: Class[_ <: 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
    JavaRDDLike
  70. 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
  71. def setName(name: String): JavaRDD[T]

    Assign a name to this RDD

  72. def splits: List[Partition]

    Set of partitions in this RDD.

    Set of partitions in this RDD.

    Definition Classes
    JavaRDDLike
  73. def subtract(other: JavaRDD[T], p: Partitioner): JavaRDD[T]

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

  74. def subtract(other: JavaRDD[T], numPartitions: Int): JavaRDD[T]

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

  75. def subtract(other: JavaRDD[T]): JavaRDD[T]

    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.

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

    Definition Classes
    AnyRef
  77. def take(num: Int): List[T]

    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
  78. def takeOrdered(num: Int): List[T]

    Returns the first K elements from this RDD using the natural ordering for T while maintain the order.

    Returns the first K elements from this RDD using the natural ordering for T while maintain the order.

    num

    the number of top elements to return

    returns

    an array of top elements

    Definition Classes
    JavaRDDLike
  79. def takeOrdered(num: Int, comp: Comparator[T]): List[T]

    Returns the first K elements from this RDD as defined by the specified Comparator[T] and maintains the order.

    Returns the first K elements from this RDD as defined by the specified Comparator[T] and maintains the order.

    num

    the number of top elements to return

    comp

    the comparator that defines the order

    returns

    an array of top elements

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

    Definition Classes
    JavaRDDLike
  81. def toArray(): List[T]

    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
  82. 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
    JavaRDDLike
  83. def toString(): String

    Definition Classes
    JavaRDD → AnyRef → Any
  84. def top(num: Int): List[T]

    Returns the top K elements from this RDD using the natural ordering for T.

    Returns the top K elements from this RDD using the natural ordering for T.

    num

    the number of top elements to return

    returns

    an array of top elements

    Definition Classes
    JavaRDDLike
  85. def top(num: Int, comp: Comparator[T]): List[T]

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

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

    num

    the number of top elements to return

    comp

    the comparator that defines the order

    returns

    an array of top elements

    Definition Classes
    JavaRDDLike
  86. def union(other: JavaRDD[T]): JavaRDD[T]

    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).

  87. def unpersist(blocking: Boolean): JavaRDD[T]

    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.

  88. def unpersist(): JavaRDD[T]

    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. This method blocks until all blocks are deleted.

  89. final def wait(): Unit

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

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  92. def wrapRDD(rdd: RDD[T]): JavaRDD[T]

    Definition Classes
    JavaRDDJavaRDDLike
  93. def zip[U](other: JavaRDDLike[U, _]): JavaPairRDD[T, 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
    JavaRDDLike
  94. def zipPartitions[U, V](other: JavaRDDLike[U, _], f: FlatMapFunction2[Iterator[T], Iterator[U], V]): JavaRDD[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
    JavaRDDLike

Inherited from JavaRDDLike[T, JavaRDD[T]]

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped