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.  lazy val aggPartWithSchema: Seq[(AggregationPart, DataType)]
5.  lazy val aggregationParts: Seq[AggregationPart]
6.  val aggregations: Seq[Aggregation]
7.  final def asInstanceOf[T0]: T0

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8.  def clone(): AnyRef

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9.  lazy val columnAggregators: Array[ColumnAggregator]
10.  final def eq(arg0: AnyRef): Boolean

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11.  def equals(arg0: Any): Boolean

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12.  def finalize(): Unit

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13.  final def getClass(): Class[_]

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    @native()

14.  def hashCode(): Int

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    @native()

15.  def hopsAggregate(minQueryTs: Long, resolution: Resolution): RDD[(KeyWithHash, OutputArrayType)]
16.  val inputDf: DataFrame
17.  final def isInstanceOf[T0]: Boolean

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18.  val keyColumns: Seq[String]
19.  val keySchema: StructType
20.  val mutationDf: DataFrame
21.  final def ne(arg0: AnyRef): Boolean

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22.  final def notify(): Unit

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23.  final def notifyAll(): Unit

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24.  lazy val outputSchema: StructType
25.  lazy val postAggSchema: StructType
26.  val preAggSchema: StructType
27.  val selectedSchema: Array[(String, DataType)]

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28.  def snapshotEntities: DataFrame
29.  def snapshotEntitiesBase: RDD[(Array[Any], Array[Any])]
30.  def snapshotEvents(partitionRange: PartitionRange): DataFrame
31.  def snapshotEventsBase(partitionRange: PartitionRange, resolution: Resolution = DailyResolution): RDD[(Array[Any], Array[Any])]
32.  implicit val sparkSession: SparkSession
33.  final def synchronized[T0](arg0: ⇒ T0): T0

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34.  def temporalEntities(queriesUnfilteredDf: DataFrame, resolution: Resolution = FiveMinuteResolution): DataFrame

    Support for entities with mutations.

    Support for entities with mutations. Three way join between: Queries: grouped by key and dsOf[ts] Snapshot[InputDf]: Grouped by key and ds providing a FinalBatchIR to be extended. Mutations[MutationDf]: Grouped by key and dsOf[MutationTs] providing an array of updates/deletes to be done With this process the components (end of day batchIr + day's mutations + day's queries -> output)

35.  def temporalEvents(queriesUnfilteredDf: DataFrame, queryTimeRange: Option[TimeRange] = None, resolution: Resolution = FiveMinuteResolution): DataFrame
36.  def toDf(aggregateRdd: RDD[(Array[Any], Array[Any])], additionalFields: Seq[(String, DataType)]): DataFrame

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    protected[spark]

37.  def toString(): String

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38.  val tsIndex: Int

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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.  lazy val windowAggregator: RowAggregator

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    protected[spark]

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    @transient()