GroupedDataSet

Value Members

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

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

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3. final def ##(): Int

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4. final def ==(arg0: AnyRef): Boolean

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

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6. def aggregate(agg: Aggregations, field: Int): AggregateDataSet[T]

   Creates a new DataSet by aggregating the specified field using the given aggregation function.

   Creates a new DataSet by aggregating the specified field using the given aggregation function. Since this is a keyed DataSet the aggregation will be performed on groups of elements with the same key.

   This only works on CaseClass DataSets.

7. def aggregate(agg: Aggregations, field: String): AggregateDataSet[T]

   Creates a new DataSet by aggregating the specified tuple field using the given aggregation function.

   Creates a new DataSet by aggregating the specified tuple field using the given aggregation function. Since this is a keyed DataSet the aggregation will be performed on groups of tuples with the same key.

   This only works on Tuple DataSets.

8. final def asInstanceOf[T0]: T0

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9. def clone(): AnyRef

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   protected[java.lang]

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   @throws( ... )

10. def combineGroup[R](combiner: GroupCombineFunction[T, R])(implicit arg0: TypeInformation[R], arg1: ClassTag[R]): DataSet[R]

    Applies a CombineFunction on a grouped DataSet.

    Applies a CombineFunction on a grouped DataSet. A CombineFunction is similar to a GroupReduceFunction but does not perform a full data exchange. Instead, the CombineFunction calls the combine method once per partition for combining a group of results. This operator is suitable for combining values into an intermediate format before doing a proper groupReduce where the data is shuffled across the node for further reduction. The GroupReduce operator can also be supplied with a combiner by implementing the RichGroupReduce function. The combine method of the RichGroupReduce function demands input and output type to be the same. The CombineFunction, on the other side, can have an arbitrary output type.

11. def combineGroup[R](fun: (Iterator[T], Collector[R]) ⇒ Unit)(implicit arg0: TypeInformation[R], arg1: ClassTag[R]): DataSet[R]

    Applies a CombineFunction on a grouped DataSet.

    Applies a CombineFunction on a grouped DataSet. A CombineFunction is similar to a GroupReduceFunction but does not perform a full data exchange. Instead, the CombineFunction calls the combine method once per partition for combining a group of results. This operator is suitable for combining values into an intermediate format before doing a proper groupReduce where the data is shuffled across the node for further reduction. The GroupReduce operator can also be supplied with a combiner by implementing the RichGroupReduce function. The combine method of the RichGroupReduce function demands input and output type to be the same. The CombineFunction, on the other side, can have an arbitrary output type.

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

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13. def equals(arg0: Any): Boolean

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14. def finalize(): Unit

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    protected[java.lang]

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

15. def first(n: Int): DataSet[T]

    Creates a new DataSet containing the first n elements of each group of this DataSet.

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

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17. def getCustomPartitioner[K](): Partitioner[K]

    Gets the custom partitioner to be used for this grouping, or null, if none was defined.

    Gets the custom partitioner to be used for this grouping, or null, if none was defined.

    Annotations

    @Internal()

18. def hashCode(): Int

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19. final def isInstanceOf[T0]: Boolean

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20. def max(field: String): AggregateDataSet[T]

    Syntactic sugar for aggregate with MAX

21. def max(field: Int): AggregateDataSet[T]

    Syntactic sugar for aggregate with MAX

22. def min(field: String): AggregateDataSet[T]

    Syntactic sugar for aggregate with MIN

23. def min(field: Int): AggregateDataSet[T]

    Syntactic sugar for aggregate with MIN

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

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25. final def notify(): Unit

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26. final def notifyAll(): Unit

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27. def reduce(reducer: ReduceFunction[T]): DataSet[T]

    Creates a new DataSet by merging the elements of each group (elements with the same key) using an associative reduce function.

28. def reduce(fun: (T, T) ⇒ T): DataSet[T]

    Creates a new DataSet by merging the elements of each group (elements with the same key) using an associative reduce function.

29. def reduceGroup[R](reducer: GroupReduceFunction[T, R])(implicit arg0: TypeInformation[R], arg1: ClassTag[R]): DataSet[R]

    Creates a new DataSet by passing for each group (elements with the same key) the list of elements to the GroupReduceFunction.

    Creates a new DataSet by passing for each group (elements with the same key) the list of elements to the GroupReduceFunction. The function can output zero or more elements. The concatenation of the emitted values will form the resulting DataSet.

30. def reduceGroup[R](fun: (Iterator[T], Collector[R]) ⇒ Unit)(implicit arg0: TypeInformation[R], arg1: ClassTag[R]): DataSet[R]

    Creates a new DataSet by passing for each group (elements with the same key) the list of elements to the group reduce function.

    Creates a new DataSet by passing for each group (elements with the same key) the list of elements to the group reduce function. The function can output zero or more elements using the Collector. The concatenation of the emitted values will form the resulting DataSet.

31. def reduceGroup[R](fun: (Iterator[T]) ⇒ R)(implicit arg0: TypeInformation[R], arg1: ClassTag[R]): DataSet[R]

    Creates a new DataSet by passing for each group (elements with the same key) the list of elements to the group reduce function.

    Creates a new DataSet by passing for each group (elements with the same key) the list of elements to the group reduce function. The function must output one element. The concatenation of those will form the resulting DataSet.

32. def sortGroup[K](fun: (T) ⇒ K, order: Order)(implicit arg0: TypeInformation[K]): GroupedDataSet[T]

    Adds a secondary sort key to this GroupedDataSet.

    Adds a secondary sort key to this GroupedDataSet. This will only have an effect if you use one of the group-at-a-time, i.e. reduceGroup.

    This works on any data type.

33. def sortGroup(field: String, order: Order): GroupedDataSet[T]

    Adds a secondary sort key to this GroupedDataSet.

    Adds a secondary sort key to this GroupedDataSet. This will only have an effect if you use one of the group-at-a-time, i.e. reduceGroup.

    This only works on CaseClass DataSets.

34. def sortGroup(field: Int, order: Order): GroupedDataSet[T]

    Adds a secondary sort key to this GroupedDataSet.

    Adds a secondary sort key to this GroupedDataSet. This will only have an effect if you use one of the group-at-a-time, i.e. reduceGroup.

    This only works on Tuple DataSets.

35. def sum(field: String): AggregateDataSet[T]

    Syntactic sugar for aggregate with SUM

36. def sum(field: Int): AggregateDataSet[T]

    Syntactic sugar for aggregate with SUM

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

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38. def toString(): String

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39. final def wait(): Unit

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

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

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42. def withPartitioner[K](partitioner: Partitioner[K])(implicit arg0: TypeInformation[K]): GroupedDataSet[T]

    Sets a custom partitioner for the grouping.