Class

org.apache.spark.sql

AQPDataFrame

Related Doc: package sql

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case class AQPDataFrame(snappySession: SnappySession, qe: QueryExecution) extends DataFrame with Product with Serializable

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Product, Equals, Dataset[Row], Serializable, Serializable, AnyRef, Any
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Inherited
  1. AQPDataFrame
  2. Product
  3. Equals
  4. Dataset
  5. Serializable
  6. Serializable
  7. AnyRef
  8. Any
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Visibility
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Instance Constructors

  1. new AQPDataFrame(snappySession: SnappySession, qe: QueryExecution)

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Value Members

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

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    Definition Classes
    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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    Definition Classes
    Dataset

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

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    Definition Classes
    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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    Definition Classes
    Dataset

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

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    Definition Classes
    Dataset

  10. def apply(colName: String): Column

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    Definition Classes
    Dataset

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

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

  14. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

  15. def cache(): AQPDataFrame.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]
    Definition Classes
    AnyRef
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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
    Dataset

  22. def collectAsList(): List[Row]

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    Definition Classes
    Dataset

  23. def columns: Array[String]

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    Definition Classes
    Dataset

  24. def count(): Long

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    Definition Classes
    Dataset

  25. def createGlobalTempView(viewName: String): Unit

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    Dataset
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    @throws( ... )

  26. def createOrReplaceTempView(viewName: String): Unit

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    Dataset

  27. def createTempView(viewName: String): Unit

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    Dataset
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    @throws( ... )

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

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    Dataset

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

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    Dataset
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    @varargs()

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

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    Dataset
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    @varargs()

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

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    Dataset
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    @varargs()

  32. def distinct(): Dataset[Row]

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    Dataset

  33. def drop(col: Column): DataFrame

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    Dataset

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

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    Dataset
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    @varargs()

  35. def drop(colName: String): DataFrame

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    Definition Classes
    Dataset

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

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    Dataset
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    @varargs()

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

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    Dataset

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

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    Dataset

  39. def dropDuplicates(): Dataset[Row]

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    Definition Classes
    Dataset

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

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    Definition Classes
    Dataset

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

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

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    Definition Classes
    Dataset

  43. def explain(): Unit

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    Definition Classes
    Dataset

  44. def explain(extended: Boolean): Unit

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    Definition Classes
    Dataset

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

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

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

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    Definition Classes
    Dataset
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    @Experimental() @Evolving()

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

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    Dataset

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

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    Definition Classes
    Dataset

  49. def finalize(): Unit

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

  50. def first(): Row

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    Definition Classes
    Dataset

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

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    Definition Classes
    Dataset
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    @Experimental() @Evolving()

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

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    Dataset
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    @Experimental() @Evolving()

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

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    Dataset

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

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    Dataset

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

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    Dataset

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

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    Dataset

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

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

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    Dataset
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    @varargs()

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

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    @varargs()

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

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    Definition Classes
    Dataset
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    @Experimental() @Evolving()

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

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    Definition Classes
    Dataset
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    @Experimental() @Evolving()

  62. def head(): Row

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    Dataset

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

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  64. def inputFiles: Array[String]

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

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    Dataset

  66. final def isInstanceOf[T0]: Boolean

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  67. def isLocal: Boolean

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  68. def isStreaming: Boolean

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    Dataset
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    @Experimental() @Evolving()

  69. def javaRDD: JavaRDD[Row]

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    Dataset

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

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    Dataset

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

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    Dataset

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

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

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

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    Dataset

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

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    Dataset

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

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    Definition Classes
    Dataset
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    @Experimental() @Evolving()

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

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    Definition Classes
    Dataset
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    @Experimental() @Evolving()

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

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    Dataset

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

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    Dataset
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    @Experimental() @Evolving()

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

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    Definition Classes
    Dataset
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    @Experimental() @Evolving()

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

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    Definition Classes
    Dataset
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    @Experimental() @Evolving()

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

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    Definition Classes
    Dataset
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    @Experimental() @Evolving()

  83. def na: DataFrameNaFunctions

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    Dataset

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

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  85. final def notify(): Unit

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  86. final def notifyAll(): Unit

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

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    Dataset
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    @varargs()

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

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    Definition Classes
    Dataset
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    @varargs()

  89. def persist(newLevel: StorageLevel): AQPDataFrame.this.type

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    Dataset

  90. def persist(): AQPDataFrame.this.type

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    Dataset

  91. def printSchema(): Unit

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    Definition Classes
    Dataset

  92. val qe: QueryExecution

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  93. val queryExecution: QueryExecution

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    Definition Classes
    Dataset

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

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    Dataset

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

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    Definition Classes
    Dataset

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

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    Dataset

  97. lazy val rdd: RDD[Row]

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    Definition Classes
    Dataset

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

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    Dataset
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    @Experimental() @Evolving()

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

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    Dataset
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    @Experimental() @Evolving()

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

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    Dataset
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    @varargs()

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

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    @varargs()

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

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    Dataset

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

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    Dataset
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    @varargs()

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

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    @varargs()

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

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

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    Dataset

  107. def schema: StructType

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    Dataset

  108. 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()

  109. 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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    Definition Classes
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    @Experimental() @Evolving()

  110. 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()

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

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    @Experimental() @Evolving()

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

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    @Experimental() @Evolving()

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

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    @varargs()

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

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    @varargs()

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

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    @varargs()

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

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    Attributes
    protected
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    Dataset

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

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    Dataset

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

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  119. def show(truncate: Boolean): Unit

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  120. def show(): Unit

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    Dataset

  121. def show(numRows: Int): Unit

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    Dataset

  122. val snappySession: SnappySession

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

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    Dataset
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    @varargs()

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

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    @varargs()

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

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    @varargs()

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

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    @varargs()

  127. val sparkSession: SparkSession

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  128. lazy val sqlContext: SQLContext

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  129. def stat: DataFrameStatFunctions

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  130. def storageLevel: StorageLevel

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

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

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

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    Dataset

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

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    @varargs()

  135. def toDF(): DataFrame

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  136. def toJSON: Dataset[String]

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  137. def toJavaRDD: JavaRDD[Row]

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  138. def toLocalIterator(): Iterator[Row]

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  139. def toString(): String

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    Dataset → AnyRef → Any

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

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

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  142. def unpersist(): AQPDataFrame.this.type

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  143. def unpersist(blocking: Boolean): AQPDataFrame.this.type

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  144. final def wait(): Unit

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

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

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

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

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    Dataset

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

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    Dataset

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

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  151. def withError(error: Double, confidence: Double = Constant.DEFAULT_CONFIDENCE, behavior: String = Constant.DEFAULT_BEHAVIOR): DataFrame

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

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    @Experimental() @Evolving()

  153. def write: DataFrameWriter[Row]

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  154. def writeStream: DataStreamWriter[Row]

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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
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    @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
    Dataset
    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 Product

Inherited from Equals

Inherited from Dataset[Row]

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped