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Databricks Scala Spark API - org.apache.spark.sql.KeyValueGroupedDataset

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1. KeyValueGroupedDataset
2. Serializable
3. Serializable
4. AnyRef
5. Any

1.  final def !=(arg0: Any): Boolean
2.  final def ##(): Int
3.  final def ==(arg0: Any): Boolean
4.  def agg[U1, U2, U3, U4, U5, U6, U7, U8](col1: TypedColumn[V, U1], col2: TypedColumn[V, U2], col3: TypedColumn[V, U3], col4: TypedColumn[V, U4], col5: TypedColumn[V, U5], col6: TypedColumn[V, U6], col7: TypedColumn[V, U7], col8: TypedColumn[V, U8]): Dataset[(K, U1, U2, U3, U4, U5, U6, U7, U8)]
5.  def agg[U1, U2, U3, U4, U5, U6, U7](col1: TypedColumn[V, U1], col2: TypedColumn[V, U2], col3: TypedColumn[V, U3], col4: TypedColumn[V, U4], col5: TypedColumn[V, U5], col6: TypedColumn[V, U6], col7: TypedColumn[V, U7]): Dataset[(K, U1, U2, U3, U4, U5, U6, U7)]
6.  def agg[U1, U2, U3, U4, U5, U6](col1: TypedColumn[V, U1], col2: TypedColumn[V, U2], col3: TypedColumn[V, U3], col4: TypedColumn[V, U4], col5: TypedColumn[V, U5], col6: TypedColumn[V, U6]): Dataset[(K, U1, U2, U3, U4, U5, U6)]
7.  def agg[U1, U2, U3, U4, U5](col1: TypedColumn[V, U1], col2: TypedColumn[V, U2], col3: TypedColumn[V, U3], col4: TypedColumn[V, U4], col5: TypedColumn[V, U5]): Dataset[(K, U1, U2, U3, U4, U5)]
8.  def agg[U1, U2, U3, U4](col1: TypedColumn[V, U1], col2: TypedColumn[V, U2], col3: TypedColumn[V, U3], col4: TypedColumn[V, U4]): Dataset[(K, U1, U2, U3, U4)]
9.  def agg[U1, U2, U3](col1: TypedColumn[V, U1], col2: TypedColumn[V, U2], col3: TypedColumn[V, U3]): Dataset[(K, U1, U2, U3)]
10.  def agg[U1, U2](col1: TypedColumn[V, U1], col2: TypedColumn[V, U2]): Dataset[(K, U1, U2)]
11.  def agg[U1](col1: TypedColumn[V, U1]): Dataset[(K, U1)]
12.  def aggUntyped(columns: TypedColumn[_, _]*): Dataset[_]
13.  final def asInstanceOf[T0]: T0
14.  def clone(): AnyRef
15.  def cogroup[U, R](other: KeyValueGroupedDataset[K, U], f: CoGroupFunction[K, V, U, R], encoder: Encoder[R]): Dataset[R]
16.  def cogroup[U, R](other: KeyValueGroupedDataset[K, U])(f: (K, Iterator[V], Iterator[U]) ⇒ TraversableOnce[R])(implicit arg0: Encoder[R]): Dataset[R]
17.  def count(): Dataset[(K, Long)]
18.  final def eq(arg0: AnyRef): Boolean
19.  def equals(arg0: Any): Boolean
20.  def finalize(): Unit
21.  def flatMapGroups[U](f: FlatMapGroupsFunction[K, V, U], encoder: Encoder[U]): Dataset[U]
22.  def flatMapGroups[U](f: (K, Iterator[V]) ⇒ TraversableOnce[U])(implicit arg0: Encoder[U]): Dataset[U]
23.  def flatMapGroupsWithState[S, U](func: FlatMapGroupsWithStateFunction[K, V, S, U], outputMode: OutputMode, stateEncoder: Encoder[S], outputEncoder: Encoder[U], timeoutConf: GroupStateTimeout, initialState: KeyValueGroupedDataset[K, S]): Dataset[U]
24.  def flatMapGroupsWithState[S, U](func: FlatMapGroupsWithStateFunction[K, V, S, U], outputMode: OutputMode, stateEncoder: Encoder[S], outputEncoder: Encoder[U], timeoutConf: GroupStateTimeout): Dataset[U]
25.  def flatMapGroupsWithState[S, U](outputMode: OutputMode, timeoutConf: GroupStateTimeout, initialState: KeyValueGroupedDataset[K, S])(func: (K, Iterator[V], GroupState[S]) ⇒ Iterator[U])(implicit arg0: Encoder[S], arg1: Encoder[U]): Dataset[U]
26.  def flatMapGroupsWithState[S, U](outputMode: OutputMode, timeoutConf: GroupStateTimeout)(func: (K, Iterator[V], GroupState[S]) ⇒ Iterator[U])(implicit arg0: Encoder[S], arg1: Encoder[U]): Dataset[U]
27.  final def getClass(): Class[_]
28.  def hashCode(): Int
29.  final def isInstanceOf[T0]: Boolean
30.  def keyAs[L](implicit arg0: Encoder[L]): KeyValueGroupedDataset[L, V]
31.  def keys: Dataset[K]
32.  def mapGroups[U](f: MapGroupsFunction[K, V, U], encoder: Encoder[U]): Dataset[U]
33.  def mapGroups[U](f: (K, Iterator[V]) ⇒ U)(implicit arg0: Encoder[U]): Dataset[U]
34.  def mapGroupsWithState[S, U](func: MapGroupsWithStateFunction[K, V, S, U], stateEncoder: Encoder[S], outputEncoder: Encoder[U], timeoutConf: GroupStateTimeout, initialState: KeyValueGroupedDataset[K, S]): Dataset[U]
35.  def mapGroupsWithState[S, U](func: MapGroupsWithStateFunction[K, V, S, U], stateEncoder: Encoder[S], outputEncoder: Encoder[U], timeoutConf: GroupStateTimeout): Dataset[U]
36.  def mapGroupsWithState[S, U](func: MapGroupsWithStateFunction[K, V, S, U], stateEncoder: Encoder[S], outputEncoder: Encoder[U]): Dataset[U]
37.  def mapGroupsWithState[S, U](timeoutConf: GroupStateTimeout, initialState: KeyValueGroupedDataset[K, S])(func: (K, Iterator[V], GroupState[S]) ⇒ U)(implicit arg0: Encoder[S], arg1: Encoder[U]): Dataset[U]
38.  def mapGroupsWithState[S, U](timeoutConf: GroupStateTimeout)(func: (K, Iterator[V], GroupState[S]) ⇒ U)(implicit arg0: Encoder[S], arg1: Encoder[U]): Dataset[U]
39.  def mapGroupsWithState[S, U](func: (K, Iterator[V], GroupState[S]) ⇒ U)(implicit arg0: Encoder[S], arg1: Encoder[U]): Dataset[U]
40.  def mapValues[W](func: MapFunction[V, W], encoder: Encoder[W]): KeyValueGroupedDataset[K, W]
41.  def mapValues[W](func: (V) ⇒ W)(implicit arg0: Encoder[W]): KeyValueGroupedDataset[K, W]
42.  final def ne(arg0: AnyRef): Boolean
43.  final def notify(): Unit
44.  final def notifyAll(): Unit
45.  val queryExecution: QueryExecution
46.  def reduceGroups(f: ReduceFunction[V]): Dataset[(K, V)]
47.  def reduceGroups(f: (V, V) ⇒ V): Dataset[(K, V)]
48.  final def synchronized[T0](arg0: ⇒ T0): T0
49.  def toString(): String
50.  final def wait(): Unit
51.  final def wait(arg0: Long, arg1: Int): Unit
52.  final def wait(arg0: Long): Unit

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