SequenceAggregators

Value Members

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

   

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2. final def ##(): Int

   

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

   

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4. def MeanSeqMapDouble(size: Int): Aggregator[SeqMapDouble, SeqMapTuple, SeqMapDouble]

   

   Creates a TypedColumn that computes the means by key of a Dataset column of type Seq[Map[String, Double]].

   Creates a TypedColumn that computes the means by key of a Dataset column of type Seq[Map[String, Double]]. Each map has a separate mean by key computed. Because each map does not have to have all the possible keys, the element counts for each map's keys can all be different.

   size

   the size of the Sequence

   returns

   spark aggregator

5. def MeanSeqNullNum(size: Int): Aggregator[SeqOptD, SeqTupD, SeqD]

   

   Creates a TypedColumn that computes mean on a Dataset column of type Seq[Option[Double]]

   Creates a TypedColumn that computes mean on a Dataset column of type Seq[Option[Double]]

   size

   the size of the Sequence

   returns

   spark aggregator

6. def ModeSeqMapLong(size: Int): Aggregator[SeqMapLong, SeqMapMapLong, SeqMapLong]

   

   Creates a TypedColumn that computes the modes by key of a Dataset column of type Seq[Map[String, Long]].

   Creates a TypedColumn that computes the modes by key of a Dataset column of type Seq[Map[String, Long]]. Each map has a separate mode by key computed. Because each map does not have to have all the possible keys, the element counts for each map's keys can all be different.

   size

   the size of the Sequence

   returns

   spark aggregator

7. def ModeSeqNullInt(size: Int): Aggregator[SeqOptL, SeqMapLL, SeqL]

   

   Creates a TypedColumn that computes mode on a Dataset column of type Seq[Option[Long]]

   Creates a TypedColumn that computes mode on a Dataset column of type Seq[Option[Long]]

   size

   the size of the Sequence

   returns

   spark aggregator

8. def SumNumSeq[T](size: Int)(implicit arg0: Numeric[T], arg1: Encoder[T], enc: Encoder[Seq[T]]): Aggregator[Seq[T], Seq[T], Seq[T]]

   

   Creates a TypedColumn that sums a Dataset column of type Seq[T: Numeric]

   Creates a TypedColumn that sums a Dataset column of type Seq[T: Numeric]

   T

   numeric type

   size

   the size of the Sequence

   returns

   spark aggregator

9. def SumSeqMapMap(size: Int): Aggregator[SeqMapMap, SeqMapMap, SeqMapMap]

   

   Creates a TypedColumn that sums a Dataset column of type Seq[Map[String, Map[String, Long]]] such that the maps are summed with the keys preserved and the values resulting are the sum of the values for the two maps

   Creates a TypedColumn that sums a Dataset column of type Seq[Map[String, Map[String, Long]]] such that the maps are summed with the keys preserved and the values resulting are the sum of the values for the two maps

   size

   the size of the Sequence

   returns

   spark aggregator

10. def SumSeqSet(size: Int): Aggregator[SeqSet, SeqSet, SeqSet]

    

    Creates a TypedColumn that sums a Dataset column of type Seq[Set[String]]

    Creates a TypedColumn that sums a Dataset column of type Seq[Set[String]]

    size

    the size of the Sequence

    returns

    spark aggregator

11. final def asInstanceOf[T0]: T0

    

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12. def clone(): AnyRef

    

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

    

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14. def equals(arg0: Any): Boolean

    

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15. def finalize(): Unit

    

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

    

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17. def hashCode(): Int

    

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18. final def isInstanceOf[T0]: Boolean

    

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

    

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20. final def notify(): Unit

    

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21. final def notifyAll(): Unit

    

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

    

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23. def toString(): String

    

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24. final def wait(): Unit

    

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

    

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

    

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