com.cloudera.sparkts.api.java

JavaTimeSeriesRDD

class JavaTimeSeriesRDD[K] extends JavaPairRDD[K, Vector]

A lazy distributed collection of univariate series with a conformed time dimension. Lazy in the sense that it is an RDD: it encapsulates all the information needed to generate its elements, but doesn't materialize them upon instantiation. Distributed in the sense that different univariate series within the collection can be stored and processed on different nodes. Within each univariate series, observations are not distributed. The time dimension is conformed in the sense that a single DateTimeIndex applies to all the univariate series. Each univariate series within the RDD has a String key to identify it.

Linear Supertypes
JavaPairRDD[K, Vector], AbstractJavaRDDLike[(K, Vector), JavaPairRDD[K, Vector]], JavaRDDLike[(K, Vector), JavaPairRDD[K, Vector]], Serializable, Serializable, AnyRef, Any
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Inherited
  1. JavaTimeSeriesRDD
  2. JavaPairRDD
  3. AbstractJavaRDDLike
  4. JavaRDDLike
  5. Serializable
  6. Serializable
  7. AnyRef
  8. Any
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  1. Public
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Instance Constructors

  1. new JavaTimeSeriesRDD(tsrdd: TimeSeriesRDD[K])(implicit kClassTag: ClassTag[K])

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, (K, Vector), U], combOp: Function2[U, U, U]): U

    Definition Classes
    JavaRDDLike
  7. def aggregateByKey[U](zeroValue: U, seqFunc: Function2[U, Vector, U], combFunc: Function2[U, U, U]): JavaPairRDD[K, U]

    Definition Classes
    JavaPairRDD
  8. def aggregateByKey[U](zeroValue: U, numPartitions: Int, seqFunc: Function2[U, Vector, U], combFunc: Function2[U, U, U]): JavaPairRDD[K, U]

    Definition Classes
    JavaPairRDD
  9. def aggregateByKey[U](zeroValue: U, partitioner: Partitioner, seqFunc: Function2[U, Vector, U], combFunc: Function2[U, U, U]): JavaPairRDD[K, U]

    Definition Classes
    JavaPairRDD
  10. final def asInstanceOf[T0]: T0

    Definition Classes
    Any
  11. def cache(): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
  12. def cartesian[U](other: JavaRDDLike[U, _]): JavaPairRDD[(K, Vector), U]

    Definition Classes
    JavaRDDLike
  13. def checkpoint(): Unit

    Definition Classes
    JavaRDDLike
  14. val classTag: ClassTag[(K, Vector)]

    Definition Classes
    JavaPairRDD → JavaRDDLike
  15. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  16. def coalesce(numPartitions: Int, shuffle: Boolean): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
  17. def coalesce(numPartitions: Int): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
  18. def cogroup[W1, W2, W3](other1: JavaPairRDD[K, W1], other2: JavaPairRDD[K, W2], other3: JavaPairRDD[K, W3], numPartitions: Int): JavaPairRDD[K, (Iterable[Vector], Iterable[W1], Iterable[W2], Iterable[W3])]

    Definition Classes
    JavaPairRDD
  19. def cogroup[W1, W2](other1: JavaPairRDD[K, W1], other2: JavaPairRDD[K, W2], numPartitions: Int): JavaPairRDD[K, (Iterable[Vector], Iterable[W1], Iterable[W2])]

    Definition Classes
    JavaPairRDD
  20. def cogroup[W](other: JavaPairRDD[K, W], numPartitions: Int): JavaPairRDD[K, (Iterable[Vector], Iterable[W])]

    Definition Classes
    JavaPairRDD
  21. def cogroup[W1, W2, W3](other1: JavaPairRDD[K, W1], other2: JavaPairRDD[K, W2], other3: JavaPairRDD[K, W3]): JavaPairRDD[K, (Iterable[Vector], Iterable[W1], Iterable[W2], Iterable[W3])]

    Definition Classes
    JavaPairRDD
  22. def cogroup[W1, W2](other1: JavaPairRDD[K, W1], other2: JavaPairRDD[K, W2]): JavaPairRDD[K, (Iterable[Vector], Iterable[W1], Iterable[W2])]

    Definition Classes
    JavaPairRDD
  23. def cogroup[W](other: JavaPairRDD[K, W]): JavaPairRDD[K, (Iterable[Vector], Iterable[W])]

    Definition Classes
    JavaPairRDD
  24. def cogroup[W1, W2, W3](other1: JavaPairRDD[K, W1], other2: JavaPairRDD[K, W2], other3: JavaPairRDD[K, W3], partitioner: Partitioner): JavaPairRDD[K, (Iterable[Vector], Iterable[W1], Iterable[W2], Iterable[W3])]

    Definition Classes
    JavaPairRDD
  25. def cogroup[W1, W2](other1: JavaPairRDD[K, W1], other2: JavaPairRDD[K, W2], partitioner: Partitioner): JavaPairRDD[K, (Iterable[Vector], Iterable[W1], Iterable[W2])]

    Definition Classes
    JavaPairRDD
  26. def cogroup[W](other: JavaPairRDD[K, W], partitioner: Partitioner): JavaPairRDD[K, (Iterable[Vector], Iterable[W])]

    Definition Classes
    JavaPairRDD
  27. def collect(): List[(K, Vector)]

    Definition Classes
    JavaRDDLike
  28. def collectAsMap(): Map[K, Vector]

    Definition Classes
    JavaPairRDD
  29. def collectAsTimeSeries(): JavaTimeSeries[K]

    Collects the RDD as a local JavaTimeSeries

  30. def collectAsync(): JavaFutureAction[List[(K, Vector)]]

    Definition Classes
    JavaRDDLike
  31. def collectPartitions(partitionIds: Array[Int]): Array[List[(K, Vector)]]

    Definition Classes
    JavaRDDLike
  32. def combineByKey[C](createCombiner: Function[Vector, C], mergeValue: Function2[C, Vector, C], mergeCombiners: Function2[C, C, C]): JavaPairRDD[K, C]

    Definition Classes
    JavaPairRDD
  33. def combineByKey[C](createCombiner: Function[Vector, C], mergeValue: Function2[C, Vector, C], mergeCombiners: Function2[C, C, C], numPartitions: Int): JavaPairRDD[K, C]

    Definition Classes
    JavaPairRDD
  34. def combineByKey[C](createCombiner: Function[Vector, C], mergeValue: Function2[C, Vector, C], mergeCombiners: Function2[C, C, C], partitioner: Partitioner): JavaPairRDD[K, C]

    Definition Classes
    JavaPairRDD
  35. def compute(split: Partition, context: TaskContext): Iterator[(K, Vector)]

  36. def context: SparkContext

    Definition Classes
    JavaRDDLike
  37. def count(): Long

    Definition Classes
    JavaRDDLike
  38. def countApprox(timeout: Long): PartialResult[BoundedDouble]

    Definition Classes
    JavaRDDLike
    Annotations
    @Experimental()
  39. def countApprox(timeout: Long, confidence: Double): PartialResult[BoundedDouble]

    Definition Classes
    JavaRDDLike
    Annotations
    @Experimental()
  40. def countApproxDistinct(relativeSD: Double): Long

    Definition Classes
    JavaRDDLike
  41. def countApproxDistinctByKey(relativeSD: Double): JavaPairRDD[K, Long]

    Definition Classes
    JavaPairRDD
  42. def countApproxDistinctByKey(relativeSD: Double, numPartitions: Int): JavaPairRDD[K, Long]

    Definition Classes
    JavaPairRDD
  43. def countApproxDistinctByKey(relativeSD: Double, partitioner: Partitioner): JavaPairRDD[K, Long]

    Definition Classes
    JavaPairRDD
  44. def countAsync(): JavaFutureAction[Long]

    Definition Classes
    JavaRDDLike
  45. def countByKey(): Map[K, Long]

    Definition Classes
    JavaPairRDD
  46. def countByKeyApprox(timeout: Long, confidence: Double): PartialResult[Map[K, BoundedDouble]]

    Definition Classes
    JavaPairRDD
    Annotations
    @Experimental()
  47. def countByKeyApprox(timeout: Long): PartialResult[Map[K, BoundedDouble]]

    Definition Classes
    JavaPairRDD
    Annotations
    @Experimental()
  48. def countByValue(): Map[(K, Vector), Long]

    Definition Classes
    JavaRDDLike
  49. def countByValueApprox(timeout: Long): PartialResult[Map[(K, Vector), BoundedDouble]]

    Definition Classes
    JavaRDDLike
  50. def countByValueApprox(timeout: Long, confidence: Double): PartialResult[Map[(K, Vector), BoundedDouble]]

    Definition Classes
    JavaRDDLike
  51. def differences(n: Int): JavaTimeSeriesRDD[K]

    Returns a JavaTimeSeriesRDD where each time series is differenced with the given order.

    Returns a JavaTimeSeriesRDD where each time series is differenced with the given order. The new RDD will be missing the first n date-times.

  52. def distinct(numPartitions: Int): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
  53. def distinct(): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
  54. final def eq(arg0: AnyRef): Boolean

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

    Definition Classes
    AnyRef → Any
  56. def fill(method: String): JavaTimeSeriesRDD[K]

    Fills in missing data (NaNs) in each series according to a given imputation method.

    Fills in missing data (NaNs) in each series according to a given imputation method.

    method

    "linear", "nearest", "next", or "previous"

    returns

    A JavaTimeSeriesRDD with missing observations filled in.

  57. def filter(f: Function[(K, Vector), Boolean]): JavaTimeSeriesRDD[K]

    Definition Classes
    JavaTimeSeriesRDD → JavaPairRDD
  58. def filterEndingAfter(dt: ZonedDateTime): JavaTimeSeriesRDD[K]

    Keep only time series whose last observation is after or equal to the given end date.

  59. def filterStartingBefore(dt: ZonedDateTime): JavaTimeSeriesRDD[K]

    Keep only time series whose first observation is before or equal to the given start date.

  60. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  61. def findSeries(key: K): Vector

    Finds a series in the JavaTimeSeriesRDD with the given key.

  62. def first(): (K, Vector)

    Definition Classes
    JavaPairRDD → JavaRDDLike
  63. def flatMap[U](f: FlatMapFunction[(K, Vector), U]): JavaRDD[U]

    Definition Classes
    JavaRDDLike
  64. def flatMapToDouble(f: DoubleFlatMapFunction[(K, Vector)]): JavaDoubleRDD

    Definition Classes
    JavaRDDLike
  65. def flatMapToPair[K2, V2](f: PairFlatMapFunction[(K, Vector), K2, V2]): JavaPairRDD[K2, V2]

    Definition Classes
    JavaRDDLike
  66. def flatMapValues[U](f: Function[Vector, Iterable[U]]): JavaPairRDD[K, U]

    Definition Classes
    JavaPairRDD
  67. def fold(zeroValue: (K, Vector))(f: Function2[(K, Vector), (K, Vector), (K, Vector)]): (K, Vector)

    Definition Classes
    JavaRDDLike
  68. def foldByKey(zeroValue: Vector, func: Function2[Vector, Vector, Vector]): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
  69. def foldByKey(zeroValue: Vector, numPartitions: Int, func: Function2[Vector, Vector, Vector]): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
  70. def foldByKey(zeroValue: Vector, partitioner: Partitioner, func: Function2[Vector, Vector, Vector]): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
  71. def foreach(f: VoidFunction[(K, Vector)]): Unit

    Definition Classes
    JavaRDDLike
  72. def foreachAsync(f: VoidFunction[(K, Vector)]): JavaFutureAction[Void]

    Definition Classes
    JavaRDDLike
  73. def foreachPartition(f: VoidFunction[Iterator[(K, Vector)]]): Unit

    Definition Classes
    JavaRDDLike
  74. def foreachPartitionAsync(f: VoidFunction[Iterator[(K, Vector)]]): JavaFutureAction[Void]

    Definition Classes
    JavaRDDLike
  75. def fullOuterJoin[W](other: JavaPairRDD[K, W], numPartitions: Int): JavaPairRDD[K, (Optional[Vector], Optional[W])]

    Definition Classes
    JavaPairRDD
  76. def fullOuterJoin[W](other: JavaPairRDD[K, W]): JavaPairRDD[K, (Optional[Vector], Optional[W])]

    Definition Classes
    JavaPairRDD
  77. def fullOuterJoin[W](other: JavaPairRDD[K, W], partitioner: Partitioner): JavaPairRDD[K, (Optional[Vector], Optional[W])]

    Definition Classes
    JavaPairRDD
  78. def getCheckpointFile(): Optional[String]

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

    Definition Classes
    AnyRef → Any
  80. def getStorageLevel: StorageLevel

    Definition Classes
    JavaRDDLike
  81. def glom(): JavaRDD[List[(K, Vector)]]

    Definition Classes
    JavaRDDLike
  82. def groupBy[U](f: Function[(K, Vector), U], numPartitions: Int): JavaPairRDD[U, Iterable[(K, Vector)]]

    Definition Classes
    JavaRDDLike
  83. def groupBy[U](f: Function[(K, Vector), U]): JavaPairRDD[U, Iterable[(K, Vector)]]

    Definition Classes
    JavaRDDLike
  84. def groupByKey(): JavaPairRDD[K, Iterable[Vector]]

    Definition Classes
    JavaPairRDD
  85. def groupByKey(numPartitions: Int): JavaPairRDD[K, Iterable[Vector]]

    Definition Classes
    JavaPairRDD
  86. def groupByKey(partitioner: Partitioner): JavaPairRDD[K, Iterable[Vector]]

    Definition Classes
    JavaPairRDD
  87. def groupWith[W1, W2, W3](other1: JavaPairRDD[K, W1], other2: JavaPairRDD[K, W2], other3: JavaPairRDD[K, W3]): JavaPairRDD[K, (Iterable[Vector], Iterable[W1], Iterable[W2], Iterable[W3])]

    Definition Classes
    JavaPairRDD
  88. def groupWith[W1, W2](other1: JavaPairRDD[K, W1], other2: JavaPairRDD[K, W2]): JavaPairRDD[K, (Iterable[Vector], Iterable[W1], Iterable[W2])]

    Definition Classes
    JavaPairRDD
  89. def groupWith[W](other: JavaPairRDD[K, W]): JavaPairRDD[K, (Iterable[Vector], Iterable[W])]

    Definition Classes
    JavaPairRDD
  90. def hashCode(): Int

    Definition Classes
    AnyRef → Any
  91. def id: Int

    Definition Classes
    JavaRDDLike
  92. def index: DateTimeIndex

  93. def intersection(other: JavaPairRDD[K, Vector]): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
  94. def isCheckpointed: Boolean

    Definition Classes
    JavaRDDLike
  95. def isEmpty(): Boolean

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

    Definition Classes
    Any
  97. def iterator(split: Partition, taskContext: TaskContext): Iterator[(K, Vector)]

    Definition Classes
    JavaRDDLike
  98. def join[W](other: JavaPairRDD[K, W], numPartitions: Int): JavaPairRDD[K, (Vector, W)]

    Definition Classes
    JavaPairRDD
  99. def join[W](other: JavaPairRDD[K, W]): JavaPairRDD[K, (Vector, W)]

    Definition Classes
    JavaPairRDD
  100. def join[W](other: JavaPairRDD[K, W], partitioner: Partitioner): JavaPairRDD[K, (Vector, W)]

    Definition Classes
    JavaPairRDD
  101. implicit val kClassTag: ClassTag[K]

    Definition Classes
    JavaTimeSeriesRDD → JavaPairRDD
  102. def keyBy[U](f: Function[(K, Vector), U]): JavaPairRDD[U, (K, Vector)]

    Definition Classes
    JavaRDDLike
  103. def keys(): JavaRDD[K]

    Definition Classes
    JavaPairRDD
  104. def leftOuterJoin[W](other: JavaPairRDD[K, W], numPartitions: Int): JavaPairRDD[K, (Vector, Optional[W])]

    Definition Classes
    JavaPairRDD
  105. def leftOuterJoin[W](other: JavaPairRDD[K, W]): JavaPairRDD[K, (Vector, Optional[W])]

    Definition Classes
    JavaPairRDD
  106. def leftOuterJoin[W](other: JavaPairRDD[K, W], partitioner: Partitioner): JavaPairRDD[K, (Vector, Optional[W])]

    Definition Classes
    JavaPairRDD
  107. def lookup(key: K): List[Vector]

    Definition Classes
    JavaPairRDD
  108. def map[R](f: Function[(K, Vector), R]): JavaRDD[R]

    Definition Classes
    JavaRDDLike
  109. def mapPartitions[U](f: FlatMapFunction[Iterator[(K, Vector)], U], preservesPartitioning: Boolean): JavaRDD[U]

    Definition Classes
    JavaRDDLike
  110. def mapPartitions[U](f: FlatMapFunction[Iterator[(K, Vector)], U]): JavaRDD[U]

    Definition Classes
    JavaRDDLike
  111. def mapPartitionsToDouble(f: DoubleFlatMapFunction[Iterator[(K, Vector)]], preservesPartitioning: Boolean): JavaDoubleRDD

    Definition Classes
    JavaRDDLike
  112. def mapPartitionsToDouble(f: DoubleFlatMapFunction[Iterator[(K, Vector)]]): JavaDoubleRDD

    Definition Classes
    JavaRDDLike
  113. def mapPartitionsToPair[K2, V2](f: PairFlatMapFunction[Iterator[(K, Vector)], K2, V2], preservesPartitioning: Boolean): JavaPairRDD[K2, V2]

    Definition Classes
    JavaRDDLike
  114. def mapPartitionsToPair[K2, V2](f: PairFlatMapFunction[Iterator[(K, Vector)], K2, V2]): JavaPairRDD[K2, V2]

    Definition Classes
    JavaRDDLike
  115. def mapPartitionsWithIndex[R](f: Function2[Integer, Iterator[(K, Vector)], Iterator[R]], preservesPartitioning: Boolean): JavaRDD[R]

    Definition Classes
    JavaRDDLike
  116. def mapSeries(f: Function[Vector, Vector], index: DateTimeIndex): JavaTimeSeriesRDD[K]

    Applies a transformation to each time series and returns a JavaTimeSeriesRDD with the given index.

    Applies a transformation to each time series and returns a JavaTimeSeriesRDD with the given index. The caller is expected to ensure that the time series produced line up with the given index.

  117. def mapSeries(f: Function[Vector, Vector]): JavaTimeSeriesRDD[K]

    Applies a transformation to each time series that preserves the time index of this JavaTimeSeriesRDD.

  118. def mapToDouble[R](f: DoubleFunction[(K, Vector)]): JavaDoubleRDD

    Definition Classes
    JavaRDDLike
  119. def mapToPair[K2, V2](f: PairFunction[(K, Vector), K2, V2]): JavaPairRDD[K2, V2]

    Definition Classes
    JavaRDDLike
  120. def mapValues[U](f: Function[Vector, U]): JavaPairRDD[K, U]

    Definition Classes
    JavaPairRDD
  121. def max(comp: Comparator[(K, Vector)]): (K, Vector)

    Definition Classes
    JavaRDDLike
  122. def min(comp: Comparator[(K, Vector)]): (K, Vector)

    Definition Classes
    JavaRDDLike
  123. def name(): String

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

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

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

    Definition Classes
    AnyRef
  127. def partitionBy(partitioner: Partitioner): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
  128. def partitions: List[Partition]

    Definition Classes
    JavaRDDLike
  129. def persist(newLevel: StorageLevel): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
  130. def pipe(command: List[String], env: Map[String, String]): JavaRDD[String]

    Definition Classes
    JavaRDDLike
  131. def pipe(command: List[String]): JavaRDD[String]

    Definition Classes
    JavaRDDLike
  132. def pipe(command: String): JavaRDD[String]

    Definition Classes
    JavaRDDLike
  133. def quotients(n: Int): JavaTimeSeriesRDD[K]

    Returns a JavaTimeSeriesRDD where each time series is quotiented with the given order.

    Returns a JavaTimeSeriesRDD where each time series is quotiented with the given order. The new RDD will be missing the first n date-times.

  134. val rdd: RDD[(K, Vector)]

    Definition Classes
    JavaPairRDD → JavaRDDLike
  135. def reduce(f: Function2[(K, Vector), (K, Vector), (K, Vector)]): (K, Vector)

    Definition Classes
    JavaRDDLike
  136. def reduceByKey(func: Function2[Vector, Vector, Vector]): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
  137. def reduceByKey(func: Function2[Vector, Vector, Vector], numPartitions: Int): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
  138. def reduceByKey(partitioner: Partitioner, func: Function2[Vector, Vector, Vector]): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
  139. def reduceByKeyLocally(func: Function2[Vector, Vector, Vector]): Map[K, Vector]

    Definition Classes
    JavaPairRDD
  140. def removeInstantsWithNaNs(): JavaTimeSeriesRDD[K]

    Return a JavaTimeSeriesRDD with all instants removed that have a NaN in one of the series.

  141. def repartition(numPartitions: Int): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
  142. def repartitionAndSortWithinPartitions(partitioner: Partitioner, comp: Comparator[K]): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
  143. def repartitionAndSortWithinPartitions(partitioner: Partitioner): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
  144. def returnRates(): JavaTimeSeriesRDD[K]

    Returns a return rate series for each time series.

    Returns a return rate series for each time series. Assumes periodic (as opposed to continuously compounded) returns.

  145. def rightOuterJoin[W](other: JavaPairRDD[K, W], numPartitions: Int): JavaPairRDD[K, (Optional[Vector], W)]

    Definition Classes
    JavaPairRDD
  146. def rightOuterJoin[W](other: JavaPairRDD[K, W]): JavaPairRDD[K, (Optional[Vector], W)]

    Definition Classes
    JavaPairRDD
  147. def rightOuterJoin[W](other: JavaPairRDD[K, W], partitioner: Partitioner): JavaPairRDD[K, (Optional[Vector], W)]

    Definition Classes
    JavaPairRDD
  148. def sample(withReplacement: Boolean, fraction: Double, seed: Long): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
  149. def sample(withReplacement: Boolean, fraction: Double): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
  150. def sampleByKey(withReplacement: Boolean, fractions: Map[K, Double]): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
  151. def sampleByKey(withReplacement: Boolean, fractions: Map[K, Double], seed: Long): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
  152. def sampleByKeyExact(withReplacement: Boolean, fractions: Map[K, Double]): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
    Annotations
    @Experimental()
  153. def sampleByKeyExact(withReplacement: Boolean, fractions: Map[K, Double], seed: Long): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
    Annotations
    @Experimental()
  154. def saveAsCsv(path: String): Unit

    Writes out the contents of this JavaTimeSeriesRDD to a set of CSV files in the given directory, with an accompanying file in the same directory including the time index.

  155. def saveAsHadoopDataset(conf: JobConf): Unit

    Definition Classes
    JavaPairRDD
  156. def saveAsHadoopFile[F <: OutputFormat[_, _]](path: String, keyClass: Class[_], valueClass: Class[_], outputFormatClass: Class[F], codec: Class[_ <: CompressionCodec]): Unit

    Definition Classes
    JavaPairRDD
  157. def saveAsHadoopFile[F <: OutputFormat[_, _]](path: String, keyClass: Class[_], valueClass: Class[_], outputFormatClass: Class[F]): Unit

    Definition Classes
    JavaPairRDD
  158. def saveAsHadoopFile[F <: OutputFormat[_, _]](path: String, keyClass: Class[_], valueClass: Class[_], outputFormatClass: Class[F], conf: JobConf): Unit

    Definition Classes
    JavaPairRDD
  159. def saveAsNewAPIHadoopDataset(conf: Configuration): Unit

    Definition Classes
    JavaPairRDD
  160. def saveAsNewAPIHadoopFile[F <: OutputFormat[_, _]](path: String, keyClass: Class[_], valueClass: Class[_], outputFormatClass: Class[F]): Unit

    Definition Classes
    JavaPairRDD
  161. def saveAsNewAPIHadoopFile[F <: OutputFormat[_, _]](path: String, keyClass: Class[_], valueClass: Class[_], outputFormatClass: Class[F], conf: Configuration): Unit

    Definition Classes
    JavaPairRDD
  162. def saveAsObjectFile(path: String): Unit

    Definition Classes
    JavaRDDLike
  163. def saveAsTextFile(path: String, codec: Class[_ <: CompressionCodec]): Unit

    Definition Classes
    JavaRDDLike
  164. def saveAsTextFile(path: String): Unit

    Definition Classes
    JavaRDDLike
  165. def seriesStats(): JavaRDD[StatCounter]

    Gets stats like min, max, mean, and standard deviation for each time series.

  166. def setName(name: String): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
  167. def slice(start: Long, end: Long): JavaTimeSeriesRDD[K]

    Returns a JavaTimeSeriesRDD that's a sub-slice of the given series.

    Returns a JavaTimeSeriesRDD that's a sub-slice of the given series.

    start

    The start date the for slice.

    end

    The end date for the slice (inclusive).

  168. def slice(start: ZonedDateTime, end: ZonedDateTime): JavaTimeSeriesRDD[K]

    Returns a JavaTimeSeriesRDD that's a sub-slice of the given series.

    Returns a JavaTimeSeriesRDD that's a sub-slice of the given series.

    start

    The start date the for slice.

    end

    The end date for the slice (inclusive).

  169. def sortByKey(comp: Comparator[K], ascending: Boolean, numPartitions: Int): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
  170. def sortByKey(comp: Comparator[K], ascending: Boolean): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
  171. def sortByKey(comp: Comparator[K]): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
  172. def sortByKey(ascending: Boolean, numPartitions: Int): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
  173. def sortByKey(ascending: Boolean): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
  174. def sortByKey(): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
  175. def subtract(other: JavaPairRDD[K, Vector], p: Partitioner): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
  176. def subtract(other: JavaPairRDD[K, Vector], numPartitions: Int): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
  177. def subtract(other: JavaPairRDD[K, Vector]): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
  178. def subtractByKey[W](other: JavaPairRDD[K, W], p: Partitioner): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
  179. def subtractByKey[W](other: JavaPairRDD[K, W], numPartitions: Int): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
  180. def subtractByKey[W](other: JavaPairRDD[K, W]): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
  181. final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes
    AnyRef
  182. def take(num: Int): List[(K, Vector)]

    Definition Classes
    JavaRDDLike
  183. def takeAsync(num: Int): JavaFutureAction[List[(K, Vector)]]

    Definition Classes
    JavaRDDLike
  184. def takeOrdered(num: Int): List[(K, Vector)]

    Definition Classes
    JavaRDDLike
  185. def takeOrdered(num: Int, comp: Comparator[(K, Vector)]): List[(K, Vector)]

    Definition Classes
    JavaRDDLike
  186. def takeSample(withReplacement: Boolean, num: Int, seed: Long): List[(K, Vector)]

    Definition Classes
    JavaRDDLike
  187. def takeSample(withReplacement: Boolean, num: Int): List[(K, Vector)]

    Definition Classes
    JavaRDDLike
  188. def toArray(): List[(K, Vector)]

    Definition Classes
    JavaRDDLike
    Annotations
    @Deprecated
  189. def toDebugString(): String

    Definition Classes
    JavaRDDLike
  190. def toIndexedRowMatrix(): IndexedRowMatrix

    Equivalent to toIndexedRowMatrix(-1)

  191. def toIndexedRowMatrix(nPartitions: Int): IndexedRowMatrix

    Converts a JavaTimeSeriesRDD into a distributed IndexedRowMatrix, useful to take advantage of Spark MLlib's statistic functions on matrices in a distributed fashion.

    Converts a JavaTimeSeriesRDD into a distributed IndexedRowMatrix, useful to take advantage of Spark MLlib's statistic functions on matrices in a distributed fashion. This is only supported for cases with a uniform time series index. See http://spark.apache.org/docs/latest/mllib-data-types.html for more information on the matrix data structure

    nPartitions

    number of partitions, default to -1, which represents the same number as currently used for the TimeSeriesRDD

    returns

    an equivalent IndexedRowMatrix

  192. def toInstants(): JavaPairRDD[ZonedDateTime, Vector]

    Equivalent to toInstants(-1)

  193. def toInstants(nPartitions: Int): JavaPairRDD[ZonedDateTime, Vector]

    Essentially transposes the time series matrix to create a JavaPairRDD where each record contains a single instant in time as the key and all the values that correspond to it as the value.

    Essentially transposes the time series matrix to create a JavaPairRDD where each record contains a single instant in time as the key and all the values that correspond to it as the value. Involves a shuffle operation.

    In the returned JavaPairRDD, the ordering of values within each record corresponds to the ordering of the time series records in the original RDD. The records are ordered by time.

  194. def toInstantsDataFrame(sqlContext: SQLContext): DataFrame

    Equivalent to toInstantsDataFrame(sqlContext, -1)

  195. def toInstantsDataFrame(sqlContext: SQLContext, nPartitions: Int): DataFrame

    Performs the same operations as toInstants but returns a DataFrame instead.

    Performs the same operations as toInstants but returns a DataFrame instead.

    The schema of the DataFrame returned will be a java.sql.Timestamp column named "instant" and Double columns named identically to their keys in the JavaTimeSeriesRDD

  196. def toLocalIterator(): Iterator[(K, Vector)]

    Definition Classes
    JavaRDDLike
  197. def toObservationsDataFrame(sqlContext: SQLContext, tsCol: String = "timestamp", keyCol: String = "key", valueCol: String = "value"): DataFrame

    Returns a DataFrame where each row is an observation containing a timestamp, a key, and a value.

  198. def toRowMatrix(): RowMatrix

    Equivalent to toRowMatrix(-1)

  199. def toRowMatrix(nPartitions: Int): RowMatrix

    Converts a JavaTimeSeriesRDD into a distributed RowMatrix, note that indices in a RowMatrix are not significant, and thus this is a valid operation regardless of the type of time index.

    Converts a JavaTimeSeriesRDD into a distributed RowMatrix, note that indices in a RowMatrix are not significant, and thus this is a valid operation regardless of the type of time index. See http://spark.apache.org/docs/latest/mllib-data-types.html for more information on the matrix data structure

    returns

    an equivalent RowMatrix

  200. def toString(): String

    Definition Classes
    AnyRef → Any
  201. def top(num: Int): List[(K, Vector)]

    Definition Classes
    JavaRDDLike
  202. def top(num: Int, comp: Comparator[(K, Vector)]): List[(K, Vector)]

    Definition Classes
    JavaRDDLike
  203. def treeAggregate[U](zeroValue: U, seqOp: Function2[U, (K, Vector), U], combOp: Function2[U, U, U]): U

    Definition Classes
    JavaRDDLike
  204. def treeAggregate[U](zeroValue: U, seqOp: Function2[U, (K, Vector), U], combOp: Function2[U, U, U], depth: Int): U

    Definition Classes
    JavaRDDLike
  205. def treeReduce(f: Function2[(K, Vector), (K, Vector), (K, Vector)]): (K, Vector)

    Definition Classes
    JavaRDDLike
  206. def treeReduce(f: Function2[(K, Vector), (K, Vector), (K, Vector)], depth: Int): (K, Vector)

    Definition Classes
    JavaRDDLike
  207. def union(other: JavaPairRDD[K, Vector]): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
  208. def unpersist(blocking: Boolean): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
  209. def unpersist(): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD
  210. implicit val vClassTag: ClassTag[Vector]

    Definition Classes
    JavaPairRDD
  211. def values(): JavaRDD[Vector]

    Definition Classes
    JavaPairRDD
  212. final def wait(): Unit

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

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  215. def withIndex(newIndex: DateTimeIndex): JavaTimeSeriesRDD[K]

    Returns a JavaTimeSeriesRDD rebased on top of a new index.

    Returns a JavaTimeSeriesRDD rebased on top of a new index. Any timestamps that exist in the new index but not in the existing index will be filled in with NaNs.

    newIndex

    The DateTimeIndex for the new RDD

  216. def wrapRDD(rdd: RDD[(K, Vector)]): JavaPairRDD[K, Vector]

    Definition Classes
    JavaPairRDD → JavaRDDLike
  217. def zip[U](other: JavaRDDLike[U, _]): JavaPairRDD[(K, Vector), U]

    Definition Classes
    JavaRDDLike
  218. def zipPartitions[U, V](other: JavaRDDLike[U, _], f: FlatMapFunction2[Iterator[(K, Vector)], Iterator[U], V]): JavaRDD[V]

    Definition Classes
    JavaRDDLike
  219. def zipWithIndex(): JavaPairRDD[(K, Vector), Long]

    Definition Classes
    JavaRDDLike
  220. def zipWithUniqueId(): JavaPairRDD[(K, Vector), Long]

    Definition Classes
    JavaRDDLike

Deprecated Value Members

  1. def splits: List[Partition]

    Definition Classes
    JavaRDDLike
    Annotations
    @deprecated
    Deprecated

    (Since version 1.1.0) Use partitions() instead.

Inherited from JavaPairRDD[K, Vector]

Inherited from AbstractJavaRDDLike[(K, Vector), JavaPairRDD[K, Vector]]

Inherited from JavaRDDLike[(K, Vector), JavaPairRDD[K, Vector]]

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped