Class/Object

org.apache.spark.sql

CachedDataFrame

Related Docs: object CachedDataFrame | package sql

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class CachedDataFrame extends Dataset[Row] with Logging

Linear Supertypes
Logging, Dataset[Row], Serializable, Serializable, AnyRef, Any
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Inherited
  1. CachedDataFrame
  2. Logging
  3. Dataset
  4. Serializable
  5. Serializable
  6. AnyRef
  7. Any
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Visibility
  1. Public
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Instance Constructors

  1. new CachedDataFrame(snappySession: SnappySession, queryExecution: QueryExecution, queryExecutionString: String, queryPlanInfo: SparkPlanInfo, currentQueryExecutionString: String, currentQueryPlanInfo: SparkPlanInfo, cachedRDD: RDD[InternalRow], shuffleDependencies: Array[Int], encoder: Encoder[Row], shuffleCleanups: Array[Future[Unit]], rddId: Int, noSideEffects: Boolean, queryHints: Map[String, String], currentExecutionId: Long, planStartTime: Long, planEndTime: Long, linkPart: Boolean = false)

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Value Members

  1. final def !=(arg0: Any): Boolean

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    AnyRef → Any

  2. final def ##(): Int

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    AnyRef → Any

  3. final def ==(arg0: Any): Boolean

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    AnyRef → Any

  4. def agg(expr: Column, exprs: Column*): DataFrame

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    Definition Classes
    Dataset
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    @varargs()

  5. def agg(exprs: Map[String, String]): DataFrame

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    Dataset

  6. def agg(exprs: Map[String, String]): DataFrame

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    Dataset

  7. def agg(aggExpr: (String, String), aggExprs: (String, String)*): DataFrame

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    Definition Classes
    Dataset

  8. def alias(alias: Symbol): Dataset[Row]

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    Dataset

  9. def alias(alias: String): Dataset[Row]

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    Dataset

  10. def apply(colName: String): Column

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    Dataset

  11. def as(alias: Symbol): Dataset[Row]

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    Dataset

  12. def as(alias: String): Dataset[Row]

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    Definition Classes
    Dataset

  13. def as[U](implicit arg0: Encoder[U]): Dataset[U]

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    Dataset
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    @Experimental() @Evolving()

  14. final def asInstanceOf[T0]: T0

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    Any

  15. def cache(): CachedDataFrame.this.type

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    Definition Classes
    Dataset

  16. def checkpoint(eager: Boolean): Dataset[Row]

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    Definition Classes
    Dataset
    Annotations
    @Experimental() @Evolving()

  17. def checkpoint(): Dataset[Row]

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    Definition Classes
    Dataset
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    @Experimental() @Evolving()

  18. def clone(): AnyRef

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    protected[java.lang]
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    @throws( ... )

  19. def coalesce(numPartitions: Int): Dataset[Row]

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    Definition Classes
    Dataset

  20. def col(colName: String): Column

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    Definition Classes
    Dataset

  21. def collect(): Array[Row]

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    Definition Classes
    CachedDataFrame → Dataset

  22. def collectAsList(): List[Row]

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    Definition Classes
    CachedDataFrame → Dataset

  23. def collectInternal(): Iterator[InternalRow]

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  24. def collectWithHandler[U, R](processPartition: (TaskContext, Iterator[InternalRow]) ⇒ (U, Int), resultHandler: (Int, U) ⇒ R, decodeResult: (R) ⇒ Iterator[InternalRow], skipUnpartitionedDataProcessing: Boolean = false, skipLocalCollectProcessing: Boolean = false)(implicit arg0: ClassTag[U], arg1: ClassTag[R]): Iterator[R]

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  25. def columns: Array[String]

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    Definition Classes
    Dataset

  26. def count(): Long

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    Definition Classes
    CachedDataFrame → Dataset

  27. def createGlobalTempView(viewName: String): Unit

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    Dataset
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    @throws( ... )

  28. def createOrReplaceTempView(viewName: String): Unit

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    Dataset

  29. def createTempView(viewName: String): Unit

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    Dataset
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    @throws( ... )

  30. def crossJoin(right: Dataset[_]): DataFrame

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    Definition Classes
    Dataset

  31. def cube(col1: String, cols: String*): RelationalGroupedDataset

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    Dataset
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    @varargs()

  32. def cube(cols: Column*): RelationalGroupedDataset

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    Dataset
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    @varargs()

  33. def describe(cols: String*): DataFrame

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    Dataset
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    @varargs()

  34. def distinct(): Dataset[Row]

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    Dataset

  35. def drop(col: Column): DataFrame

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    Dataset

  36. def drop(colNames: String*): DataFrame

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    Dataset
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    @varargs()

  37. def drop(colName: String): DataFrame

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    Dataset

  38. def dropDuplicates(col1: String, cols: String*): Dataset[Row]

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    Dataset
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    @varargs()

  39. def dropDuplicates(colNames: Array[String]): Dataset[Row]

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    Dataset

  40. def dropDuplicates(colNames: Seq[String]): Dataset[Row]

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    Dataset

  41. def dropDuplicates(): Dataset[Row]

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  42. def dtypes: Array[(String, String)]

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    Dataset

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

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  44. def equals(arg0: Any): Boolean

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    AnyRef → Any

  45. def except(other: Dataset[Row]): Dataset[Row]

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    Dataset

  46. def explain(): Unit

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    Dataset

  47. def explain(extended: Boolean): Unit

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    Dataset

  48. def filter(func: FilterFunction[Row]): Dataset[Row]

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    Dataset
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    @Experimental() @Evolving()

  49. def filter(func: (Row) ⇒ Boolean): Dataset[Row]

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    @Experimental() @Evolving()

  50. def filter(conditionExpr: String): Dataset[Row]

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  51. def filter(condition: Column): Dataset[Row]

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  52. def finalize(): Unit

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    @throws( classOf[java.lang.Throwable] )

  53. def first(): Row

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    Dataset

  54. def flatMap[U](f: FlatMapFunction[Row, U], encoder: Encoder[U]): Dataset[U]

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    Dataset
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    @Experimental() @Evolving()

  55. def flatMap[U](func: (Row) ⇒ TraversableOnce[U])(implicit arg0: Encoder[U]): Dataset[U]

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    @Experimental() @Evolving()

  56. def foreach(func: ForeachFunction[Row]): Unit

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  57. def foreach(f: (Row) ⇒ Unit): Unit

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  58. def foreachPartition(func: ForeachPartitionFunction[Row]): Unit

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  59. def foreachPartition(f: (Iterator[Row]) ⇒ Unit): Unit

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    Dataset

  60. final def getClass(): Class[_]

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  61. def groupBy(col1: String, cols: String*): RelationalGroupedDataset

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    Dataset
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    @varargs()

  62. def groupBy(cols: Column*): RelationalGroupedDataset

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    @varargs()

  63. def groupByKey[K](func: MapFunction[Row, K], encoder: Encoder[K]): KeyValueGroupedDataset[K, Row]

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    Dataset
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    @Experimental() @Evolving()

  64. def groupByKey[K](func: (Row) ⇒ K)(implicit arg0: Encoder[K]): KeyValueGroupedDataset[K, Row]

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    Dataset
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    @Experimental() @Evolving()

  65. def hashCode(): Int

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    AnyRef → Any

  66. def head(n: Int): Array[Row]

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    CachedDataFrame → Dataset

  67. def head(): Row

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    Dataset

  68. def initializeLogIfNecessary(): Unit

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    protected
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    Logging

  69. def inputFiles: Array[String]

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  70. def intersect(other: Dataset[Row]): Dataset[Row]

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  71. final def isDebugEnabled: Boolean

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  72. final def isInfoEnabled: Boolean

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  73. final def isInstanceOf[T0]: Boolean

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  74. def isLocal: Boolean

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  75. def isStreaming: Boolean

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    @Experimental() @Evolving()

  76. final def isTraceEnabled: Boolean

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  77. def javaRDD: JavaRDD[Row]

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  78. def join(right: Dataset[_], joinExprs: Column, joinType: String): DataFrame

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  79. def join(right: Dataset[_], joinExprs: Column): DataFrame

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  80. def join(right: Dataset[_], usingColumns: Seq[String], joinType: String): DataFrame

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  81. def join(right: Dataset[_], usingColumns: Seq[String]): DataFrame

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  82. def join(right: Dataset[_], usingColumn: String): DataFrame

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  83. def join(right: Dataset[_]): DataFrame

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  84. def joinWith[U](other: Dataset[U], condition: Column): Dataset[(Row, U)]

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    Dataset
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    @Experimental() @Evolving()

  85. def joinWith[U](other: Dataset[U], condition: Column, joinType: String): Dataset[(Row, U)]

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    @Experimental() @Evolving()

  86. final var levelFlags: Int

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  87. def limit(n: Int): Dataset[Row]

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  88. val linkPart: Boolean

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  89. def log: Logger

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  90. def logDebug(msg: ⇒ String, throwable: Throwable): Unit

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  91. def logDebug(msg: ⇒ String): Unit

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  92. def logError(msg: ⇒ String, throwable: Throwable): Unit

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  93. def logError(msg: ⇒ String): Unit

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  94. def logInfo(msg: ⇒ String, throwable: Throwable): Unit

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  95. def logInfo(msg: ⇒ String): Unit

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  96. def logName: String

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  97. def logTrace(msg: ⇒ String, throwable: Throwable): Unit

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  98. def logTrace(msg: ⇒ String): Unit

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  99. def logWarning(msg: ⇒ String, throwable: Throwable): Unit

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  100. def logWarning(msg: ⇒ String): Unit

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  101. final var log_: Logger

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    Logging

  102. def map[U](func: MapFunction[Row, U], encoder: Encoder[U]): Dataset[U]

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    @Experimental() @Evolving()

  103. def map[U](func: (Row) ⇒ U)(implicit arg0: Encoder[U]): Dataset[U]

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    Dataset
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    @Experimental() @Evolving()

  104. def mapPartitions[U](f: MapPartitionsFunction[Row, U], encoder: Encoder[U]): Dataset[U]

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    Dataset
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    @Experimental() @Evolving()

  105. def mapPartitions[U](func: (Iterator[Row]) ⇒ Iterator[U])(implicit arg0: Encoder[U]): Dataset[U]

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    @Experimental() @Evolving()

  106. def na: DataFrameNaFunctions

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  107. final def ne(arg0: AnyRef): Boolean

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  108. final def notify(): Unit

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  109. final def notifyAll(): Unit

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  110. def orderBy(sortExprs: Column*): Dataset[Row]

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    @varargs()

  111. def orderBy(sortCol: String, sortCols: String*): Dataset[Row]

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    @varargs()

  112. def persist(newLevel: StorageLevel): CachedDataFrame.this.type

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  113. def persist(): CachedDataFrame.this.type

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  114. def printSchema(): Unit

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  115. val queryExecution: QueryExecution

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    Dataset

  116. val queryHints: Map[String, String]

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  117. def randomSplit(weights: Array[Double]): Array[Dataset[Row]]

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  118. def randomSplit(weights: Array[Double], seed: Long): Array[Dataset[Row]]

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  119. def randomSplitAsList(weights: Array[Double], seed: Long): List[Dataset[Row]]

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  120. lazy val rdd: RDD[Row]

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  121. val rddId: Int

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  122. def reduce(func: ReduceFunction[Row]): Row

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    @Experimental() @Evolving()

  123. def reduce(func: (Row, Row) ⇒ Row): Row

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    Dataset
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    @Experimental() @Evolving()

  124. def repartition(partitionExprs: Column*): Dataset[Row]

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    Dataset
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    @varargs()

  125. def repartition(numPartitions: Int, partitionExprs: Column*): Dataset[Row]

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    @varargs()

  126. def repartition(numPartitions: Int): Dataset[Row]

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    Dataset

  127. def resetLogger(): Unit

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    protected
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    Logging

  128. def rollup(col1: String, cols: String*): RelationalGroupedDataset

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    @varargs()

  129. def rollup(cols: Column*): RelationalGroupedDataset

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    @varargs()

  130. def sample(withReplacement: Boolean, fraction: Double): Dataset[Row]

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  131. def sample(withReplacement: Boolean, fraction: Double, seed: Long): Dataset[Row]

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  132. def schema: StructType

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  133. def select[U1, U2, U3, U4, U5](c1: TypedColumn[Row, U1], c2: TypedColumn[Row, U2], c3: TypedColumn[Row, U3], c4: TypedColumn[Row, U4], c5: TypedColumn[Row, U5]): Dataset[(U1, U2, U3, U4, U5)]

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    @Experimental() @Evolving()

  134. def select[U1, U2, U3, U4](c1: TypedColumn[Row, U1], c2: TypedColumn[Row, U2], c3: TypedColumn[Row, U3], c4: TypedColumn[Row, U4]): Dataset[(U1, U2, U3, U4)]

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    @Experimental() @Evolving()

  135. def select[U1, U2, U3](c1: TypedColumn[Row, U1], c2: TypedColumn[Row, U2], c3: TypedColumn[Row, U3]): Dataset[(U1, U2, U3)]

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    @Experimental() @Evolving()

  136. def select[U1, U2](c1: TypedColumn[Row, U1], c2: TypedColumn[Row, U2]): Dataset[(U1, U2)]

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    @Experimental() @Evolving()

  137. def select[U1](c1: TypedColumn[Row, U1]): Dataset[U1]

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    @Experimental() @Evolving()

  138. def select(col: String, cols: String*): DataFrame

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    @varargs()

  139. def select(cols: Column*): DataFrame

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    @varargs()

  140. def selectExpr(exprs: String*): DataFrame

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    @varargs()

  141. def selectUntyped(columns: TypedColumn[_, _]*): Dataset[_]

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  142. def show(numRows: Int, truncate: Int): Unit

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  143. def show(numRows: Int, truncate: Boolean): Unit

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  144. def show(truncate: Boolean): Unit

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  145. def show(): Unit

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  146. def show(numRows: Int): Unit

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  147. def sort(sortExprs: Column*): Dataset[Row]

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    @varargs()

  148. def sort(sortCol: String, sortCols: String*): Dataset[Row]

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    @varargs()

  149. def sortWithinPartitions(sortExprs: Column*): Dataset[Row]

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    @varargs()

  150. def sortWithinPartitions(sortCol: String, sortCols: String*): Dataset[Row]

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    @varargs()

  151. val sparkSession: SparkSession

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    Dataset

  152. lazy val sqlContext: SQLContext

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  153. def stat: DataFrameStatFunctions

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  154. def storageLevel: StorageLevel

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

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  156. def take(n: Int): Array[Row]

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  157. def takeAsList(n: Int): List[Row]

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  158. def toDF(colNames: String*): DataFrame

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    @varargs()

  159. def toDF(): DataFrame

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  160. def toJSON: Dataset[String]

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  161. def toJavaRDD: JavaRDD[Row]

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    Dataset

  162. def toLocalIterator(): Iterator[Row]

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    CachedDataFrame → Dataset

  163. def toString(): String

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    Dataset → AnyRef → Any

  164. def transform[U](t: (Dataset[Row]) ⇒ Dataset[U]): Dataset[U]

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  165. def union(other: Dataset[Row]): Dataset[Row]

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  166. def unpersist(): CachedDataFrame.this.type

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  167. def unpersist(blocking: Boolean): CachedDataFrame.this.type

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  168. final def wait(): Unit

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  169. final def wait(arg0: Long, arg1: Int): Unit

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  170. final def wait(arg0: Long): Unit

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  171. def where(conditionExpr: String): Dataset[Row]

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  172. def where(condition: Column): Dataset[Row]

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  173. def withColumn(colName: String, col: Column): DataFrame

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  174. def withColumnRenamed(existingName: String, newName: String): DataFrame

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  175. def withNewExecutionId[T](body: ⇒ T): T

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    CachedDataFrame → Dataset

  176. def withWatermark(eventTime: String, delayThreshold: String): Dataset[Row]

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    Dataset
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    @Experimental() @Evolving()

  177. def write: DataFrameWriter[Row]

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  178. def writeStream: DataStreamWriter[Row]

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    Dataset
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    @Experimental() @Evolving()

Deprecated Value Members

  1. def explode[A, B](inputColumn: String, outputColumn: String)(f: (A) ⇒ TraversableOnce[B])(implicit arg0: scala.reflect.api.JavaUniverse.TypeTag[B]): DataFrame

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    Definition Classes
    Dataset
    Annotations
    @deprecated
    Deprecated

    (Since version 2.0.0) use flatMap() or select() with functions.explode() instead

  2. def explode[A <: Product](input: Column*)(f: (Row) ⇒ TraversableOnce[A])(implicit arg0: scala.reflect.api.JavaUniverse.TypeTag[A]): DataFrame

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    Definition Classes
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    Annotations
    @deprecated
    Deprecated

    (Since version 2.0.0) use flatMap() or select() with functions.explode() instead

  3. def registerTempTable(tableName: String): Unit

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    Definition Classes
    Dataset
    Annotations
    @deprecated
    Deprecated

    (Since version 2.0.0) Use createOrReplaceTempView(viewName) instead.

  4. def unionAll(other: Dataset[Row]): Dataset[Row]

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    Definition Classes
    Dataset
    Annotations
    @deprecated
    Deprecated

    (Since version 2.0.0) use union()

Inherited from Logging

Inherited from Dataset[Row]

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped