Class

ksb.csle.component.pipe.stream.operator

GroupByOperator

Related Doc: package operator

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class GroupByOperator extends BasePipeOperator[DataFrame, StreamPipeOperatorInfo, SparkSession]

:: ApplicationDeveloperApi ::

Operator that pipelines dataframe by aggregating records according to a given group condition.

Linear Supertypes
BasePipeOperator[DataFrame, StreamPipeOperatorInfo, SparkSession], BaseGenericPipeOperator[(Any) ⇒ DataFrame, DataFrame, DataFrame, StreamPipeOperatorInfo, SparkSession], BaseGenericMutantOperator[StreamPipeOperatorInfo, (Any) ⇒ DataFrame, (DataFrame) ⇒ DataFrame], BaseDoer, Logging, Serializable, Serializable, AnyRef, Any
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Inherited
  1. GroupByOperator
  2. BasePipeOperator
  3. BaseGenericPipeOperator
  4. BaseGenericMutantOperator
  5. BaseDoer
  6. Logging
  7. Serializable
  8. Serializable
  9. AnyRef
  10. Any
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Visibility
  1. Public
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Instance Constructors

  1. new GroupByOperator(o: StreamPipeOperatorInfo, session: SparkSession)

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    o

    Object that contains message ksb.csle.common.proto.StreamOperatorProto.GroupbyPipeInfo GroupbyPipeInfo contains attributes as follows:

    • timeColName: Column name containing time information (optional)
    • keyColName: A list of column names to be used as group by keys (required)
    • valColName: A list of column name to be used as a value columns (required)
    • groupby: Method for aggregation. (required)
    • window: Window information including key, time window length, and sliding interval.

    GroupbyPipeInfo

    message GroupbyPipeInfo {
     optional string timeColName = 3;
     repeated string keyColName = 4;
     repeated string valColName = 5;
     enum GroupbyOp {
       SUM = 0;
       COUNT = 1;
       AVG = 2;
       MIN = 3;
       MAX = 4;
     }
     required GroupbyOp groupby = 6;
     optional Window window = 7;
    }

    Window

     message Window {
     required string key = 1;
     required string windowLength = 2;
     required string slidingInterval = 3;
    }

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. final def asInstanceOf[T0]: T0

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  5. def clone(): AnyRef

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    Attributes
    protected[java.lang]
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    @throws( ... )
  6. final def eq(arg0: AnyRef): Boolean

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  7. def equals(arg0: Any): Boolean

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  8. def finalize(): Unit

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    protected[java.lang]
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    @throws( classOf[java.lang.Throwable] )
  9. final def getClass(): Class[_]

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  10. def hashCode(): Int

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  11. final def isInstanceOf[T0]: Boolean

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  12. val logger: Logger

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    Attributes
    protected
    Definition Classes
    Logging
  13. final def ne(arg0: AnyRef): Boolean

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  14. final def notify(): Unit

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  15. final def notifyAll(): Unit

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  16. def operate(df: (Any) ⇒ DataFrame): (DataFrame) ⇒ DataFrame

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    Operates groupby function for data integration

    Operates groupby function for data integration

    df

    Input dataframe

    returns

    DataFrame Output dataframe

    Definition Classes
    GroupByOperator → BasePipeOperator → BaseGenericPipeOperator → BaseGenericMutantOperator
  17. def stop: Unit

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    Definition Classes
    BasePipeOperator → BaseGenericPipeOperator → BaseGenericMutantOperator
    Annotations
    @DeveloperApi()
  18. final def synchronized[T0](arg0: ⇒ T0): T0

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  19. def toString(): String

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  20. final def wait(): Unit

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    @throws( ... )
  21. final def wait(arg0: Long, arg1: Int): Unit

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    @throws( ... )
  22. final def wait(arg0: Long): Unit

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Inherited from BasePipeOperator[DataFrame, StreamPipeOperatorInfo, SparkSession]

Inherited from BaseGenericPipeOperator[(Any) ⇒ DataFrame, DataFrame, DataFrame, StreamPipeOperatorInfo, SparkSession]

Inherited from BaseGenericMutantOperator[StreamPipeOperatorInfo, (Any) ⇒ DataFrame, (DataFrame) ⇒ DataFrame]

Inherited from BaseDoer

Inherited from Logging

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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