org.apache.spark.sql.api.java

JavaSchemaRDD

class JavaSchemaRDD extends JavaRDDLike[Row, JavaRDD[Row]] with SchemaRDDLike

An RDD of Row objects that is returned as the result of a Spark SQL query. In addition to standard RDD operations, a JavaSchemaRDD can also be registered as a table in the JavaSQLContext that was used to create. Registering a JavaSchemaRDD allows its contents to be queried in future SQL statement.

Linear Supertypes
SchemaRDDLike, JavaRDDLike[Row, JavaRDD[Row]], Serializable, Serializable, AnyRef, Any
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  1. JavaSchemaRDD
  2. SchemaRDDLike
  3. JavaRDDLike
  4. Serializable
  5. Serializable
  6. AnyRef
  7. Any
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Instance Constructors

  1. new JavaSchemaRDD(sqlContext: SQLContext, baseLogicalPlan: LogicalPlan)

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, Row, 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. val baseLogicalPlan: LogicalPlan

    Definition Classes
    JavaSchemaRDD → SchemaRDDLike
  9. def cache(): JavaSchemaRDD

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

  10. def cartesian[U](other: JavaRDDLike[U, _]): JavaPairRDD[Row, 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
  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
    JavaRDDLike
  12. val classTag: ClassTag[Row]

    Definition Classes
    JavaSchemaRDDJavaRDDLike
  13. def clone(): AnyRef

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

    Return a new RDD that is reduced into numPartitions partitions.

  15. def collect(): List[Row]

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

    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
    Annotations
    @Experimental()
  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
    Annotations
    @Experimental()
  21. def countApproxDistinct(relativeSD: Double): Long

    Return approximate number of distinct elements in the RDD.

    Return approximate number of distinct elements in the RDD.

    The algorithm used is based on streamlib's implementation of "HyperLogLog in Practice: Algorithmic Engineering of a State of The Art Cardinality Estimation Algorithm", available here.

    relativeSD

    Relative accuracy. Smaller values create counters that require more space. It must be greater than 0.000017.

    Definition Classes
    JavaRDDLike
  22. def countByValue(): Map[Row, 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[Row, BoundedDouble]]

    (Experimental) Approximate version of countByValue().

    (Experimental) Approximate version of countByValue().

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

    (Experimental) Approximate version of countByValue().

    (Experimental) Approximate version of countByValue().

    Definition Classes
    JavaRDDLike
  25. def distinct(numPartitions: Int): JavaSchemaRDD

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

  26. def distinct(): JavaSchemaRDD

    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[Row, Boolean]): JavaSchemaRDD

    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(): Row

    Return the first element in this RDD.

    Return the first element in this RDD.

    Definition Classes
    JavaRDDLike
  32. def flatMap[U](f: FlatMapFunction[Row, 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
  33. def flatMapToDouble(f: DoubleFlatMapFunction[Row]): 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 flatMapToPair[K2, V2](f: PairFlatMapFunction[Row, 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
  35. def fold(zeroValue: Row)(f: Function2[Row, Row, Row]): Row

    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[Row]): 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 foreachPartition(f: VoidFunction[Iterator[Row]]): Unit

    Applies a function f to each partition of this RDD.

    Applies a function f to each partition of this RDD.

    Definition Classes
    JavaRDDLike
  38. 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
  39. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any
  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
    JavaRDDLike
  41. def glom(): JavaRDD[List[Row]]

    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
  42. def groupBy[K](f: Function[Row, K], numPartitions: Int): JavaPairRDD[K, Iterable[Row]]

    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 groupBy[K](f: Function[Row, K]): JavaPairRDD[K, Iterable[Row]]

    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
  44. def hashCode(): Int

    Definition Classes
    AnyRef → Any
  45. def id: Int

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

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

    Definition Classes
    JavaRDDLike
  46. def insertInto(tableName: String): Unit

    :: Experimental :: Appends the rows from this RDD to the specified table.

    :: Experimental :: Appends the rows from this RDD to the specified table.

    Definition Classes
    SchemaRDDLike
    Annotations
    @Experimental()
  47. def insertInto(tableName: String, overwrite: Boolean): Unit

    :: Experimental :: Adds the rows from this RDD to the specified table, optionally overwriting the existing data.

    :: Experimental :: Adds the rows from this RDD to the specified table, optionally overwriting the existing data.

    Definition Classes
    SchemaRDDLike
    Annotations
    @Experimental()
  48. def intersection(other: JavaSchemaRDD, numPartitions: Int): JavaSchemaRDD

    Return the intersection of this RDD and another one.

    Return the intersection of this RDD and another one. The output will not contain any duplicate elements, even if the input RDDs did. Performs a hash partition across the cluster

    Note that this method performs a shuffle internally.

    numPartitions

    How many partitions to use in the resulting RDD

  49. def intersection(other: JavaSchemaRDD, partitioner: Partitioner): JavaSchemaRDD

    Return the intersection of this RDD and another one.

    Return the intersection of this RDD and another one. The output will not contain any duplicate elements, even if the input RDDs did.

    Note that this method performs a shuffle internally.

    partitioner

    Partitioner to use for the resulting RDD

  50. def intersection(other: JavaSchemaRDD): JavaSchemaRDD

    Return the intersection of this RDD and another one.

    Return the intersection of this RDD and another one. The output will not contain any duplicate elements, even if the input RDDs did.

    Note that this method performs a shuffle internally.

  51. def isCheckpointed: Boolean

    Return whether this RDD has been checkpointed or not

    Return whether this RDD has been checkpointed or not

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

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

    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
  54. def keyBy[K](f: Function[Row, K]): JavaPairRDD[K, Row]

    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
  55. val logicalPlan: LogicalPlan

    Attributes
    protected[org.apache.spark]
    Definition Classes
    SchemaRDDLike
  56. def map[R](f: Function[Row, 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
  57. def mapPartitions[U](f: FlatMapFunction[Iterator[Row], U], preservesPartitioning: Boolean): 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
  58. def mapPartitions[U](f: FlatMapFunction[Iterator[Row], 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
  59. def mapPartitionsToDouble(f: DoubleFlatMapFunction[Iterator[Row]], preservesPartitioning: Boolean): 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
  60. def mapPartitionsToDouble(f: DoubleFlatMapFunction[Iterator[Row]]): 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
  61. def mapPartitionsToPair[K2, V2](f: PairFlatMapFunction[Iterator[Row], K2, V2], preservesPartitioning: Boolean): 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
  62. def mapPartitionsToPair[K2, V2](f: PairFlatMapFunction[Iterator[Row], 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
  63. def mapPartitionsWithIndex[R](f: Function2[Integer, Iterator[Row], Iterator[R]], preservesPartitioning: Boolean = false): 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
  64. def mapToDouble[R](f: DoubleFunction[Row]): 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
  65. def mapToPair[K2, V2](f: PairFunction[Row, 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
  66. def max(comp: Comparator[Row]): Row

    Returns the maximum element from this RDD as defined by the specified Comparator[T].

    Returns the maximum element from this RDD as defined by the specified Comparator[T].

    comp

    the comparator that defines ordering

    returns

    the maximum of the RDD

    Definition Classes
    JavaRDDLike
  67. def min(comp: Comparator[Row]): Row

    Returns the minimum element from this RDD as defined by the specified Comparator[T].

    Returns the minimum element from this RDD as defined by the specified Comparator[T].

    comp

    the comparator that defines ordering

    returns

    the minimum of the RDD

    Definition Classes
    JavaRDDLike
  68. def name(): String

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

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

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

    Definition Classes
    AnyRef
  72. def partitions: List[Partition]

    Set of partitions in this RDD.

    Set of partitions in this RDD.

    Definition Classes
    JavaRDDLike
  73. def persist(newLevel: StorageLevel): JavaSchemaRDD

    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..

  74. def persist(): JavaSchemaRDD

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

  75. 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
  76. 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
  77. 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
  78. def printSchema(): Unit

    Prints out the schema.

    Prints out the schema.

    Definition Classes
    SchemaRDDLike
  79. lazy val queryExecution: QueryExecution

    :: DeveloperApi :: A lazily computed query execution workflow.

    :: DeveloperApi :: A lazily computed query execution workflow. All other RDD operations are passed through to the RDD that is produced by this workflow. This workflow is produced lazily because invoking the whole query optimization pipeline can be expensive.

    The query execution is considered a Developer API as phases may be added or removed in future releases. This execution is only exposed to provide an interface for inspecting the various phases for debugging purposes. Applications should not depend on particular phases existing or producing any specific output, even for exactly the same query.

    Additionally, the RDD exposed by this execution is not designed for consumption by end users. In particular, it does not contain any schema information, and it reuses Row objects internally. This object reuse improves performance, but can make programming against the RDD more difficult. Instead end users should perform RDD operations on a SchemaRDD directly.

    Definition Classes
    SchemaRDDLike
  80. val rdd: RDD[Row]

    Definition Classes
    JavaSchemaRDDJavaRDDLike
  81. def reduce(f: Function2[Row, Row, Row]): Row

    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
  82. def registerTempTable(tableName: String): Unit

    Registers this RDD as a temporary table using the given name.

    Registers this RDD as a temporary table using the given name. The lifetime of this temporary table is tied to the SQLContext that was used to create this SchemaRDD.

    Definition Classes
    SchemaRDDLike
  83. def repartition(numPartitions: Int): JavaSchemaRDD

    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.

  84. 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
  85. def saveAsParquetFile(path: String): Unit

    Saves the contents of this SchemaRDD as a parquet file, preserving the schema.

    Saves the contents of this SchemaRDD as a parquet file, preserving the schema. Files that are written out using this method can be read back in as a SchemaRDD using the parquetFile function.

    Definition Classes
    SchemaRDDLike
  86. def saveAsTable(tableName: String): Unit

    :: Experimental :: Creates a table from the the contents of this SchemaRDD.

    :: Experimental :: Creates a table from the the contents of this SchemaRDD. This will fail if the table already exists.

    Note that this currently only works with SchemaRDDs that are created from a HiveContext as there is no notion of a persisted catalog in a standard SQL context. Instead you can write an RDD out to a parquet file, and then register that file as a table. This "table" can then be the target of an insertInto.

    Definition Classes
    SchemaRDDLike
    Annotations
    @Experimental()
  87. 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
  88. 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
  89. def schema: StructType

    Returns the schema of this JavaSchemaRDD (represented by a StructType).

  90. def schemaString: String

    Returns the schema as a string in the tree format.

    Returns the schema as a string in the tree format.

    Definition Classes
    SchemaRDDLike
  91. def setName(name: String): JavaSchemaRDD

    Assign a name to this RDD

  92. val sqlContext: SQLContext

    Definition Classes
    JavaSchemaRDD → SchemaRDDLike
  93. def subtract(other: JavaSchemaRDD, p: Partitioner): JavaSchemaRDD

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

  94. def subtract(other: JavaSchemaRDD, numPartitions: Int): JavaSchemaRDD

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

  95. def subtract(other: JavaSchemaRDD): JavaSchemaRDD

    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.

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

    Definition Classes
    AnyRef
  97. def take(num: Int): List[Row]

    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
    JavaSchemaRDDJavaRDDLike
  98. def takeOrdered(num: Int): List[Row]

    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
  99. def takeOrdered(num: Int, comp: Comparator[Row]): List[Row]

    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
  100. def takeSample(withReplacement: Boolean, num: Int, seed: Long): List[Row]

    Definition Classes
    JavaRDDLike
  101. def takeSample(withReplacement: Boolean, num: Int): List[Row]

    Definition Classes
    JavaRDDLike
  102. 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
  103. def toLocalIterator(): Iterator[Row]

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

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

    The iterator will consume as much memory as the largest partition in this RDD.

    Definition Classes
    JavaRDDLike
  104. def toString(): String

    Definition Classes
    JavaSchemaRDD → SchemaRDDLike → AnyRef → Any
  105. def top(num: Int): List[Row]

    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
  106. def top(num: Int, comp: Comparator[Row]): List[Row]

    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
  107. def unpersist(blocking: Boolean = true): JavaSchemaRDD

    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.

  108. final def wait(): Unit

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

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

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

    Definition Classes
    JavaSchemaRDDJavaRDDLike
  112. def zip[U](other: JavaRDDLike[U, _]): JavaPairRDD[Row, 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
  113. def zipPartitions[U, V](other: JavaRDDLike[U, _], f: FlatMapFunction2[Iterator[Row], 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
  114. def zipWithIndex(): JavaPairRDD[Row, Long]

    Zips this RDD with its element indices.

    Zips this RDD with its element indices. The ordering is first based on the partition index and then the ordering of items within each partition. So the first item in the first partition gets index 0, and the last item in the last partition receives the largest index. This is similar to Scala's zipWithIndex but it uses Long instead of Int as the index type. This method needs to trigger a spark job when this RDD contains more than one partitions.

    Definition Classes
    JavaRDDLike
  115. def zipWithUniqueId(): JavaPairRDD[Row, Long]

    Zips this RDD with generated unique Long ids.

    Zips this RDD with generated unique Long ids. Items in the kth partition will get ids k, n+k, 2*n+k, ..., where n is the number of partitions. So there may exist gaps, but this method won't trigger a spark job, which is different from org.apache.spark.rdd.RDD#zipWithIndex.

    Definition Classes
    JavaRDDLike

Deprecated Value Members

  1. def registerAsTable(tableName: String): Unit

    Definition Classes
    SchemaRDDLike
    Annotations
    @deprecated
    Deprecated

    (Since version 1.1) Use registerTempTable instead of registerAsTable.

  2. def splits: List[Partition]

    Definition Classes
    JavaRDDLike
    Annotations
    @deprecated
    Deprecated

    (Since version 1.1.0) Use partitions() instead.

  3. def toArray(): List[Row]

    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
    Annotations
    @Deprecated
    Deprecated

    As of Spark 1.0.0, toArray() is deprecated, use #collect() instead

Inherited from SchemaRDDLike

Inherited from JavaRDDLike[Row, JavaRDD[Row]]

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

SchemaRDD Functions

Base RDD Functions