StatsCompute

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 addDerivedMetrics(df: DataFrame, aggregator: RowAggregator): DataFrame

   

   Given a summary Dataframe that computed the stats.

   Given a summary Dataframe that computed the stats. Add derived data (example: null rate, median, etc)

5. final def asInstanceOf[T0]: T0

   

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6. def clone(): AnyRef

   

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7. def dailySummary(aggregator: RowAggregator, sample: Double = 1.0, timeBucketMinutes: Long = 60): TimedKvRdd

   

   Navigate the dataframe and compute statistics partitioned by date stamp

   Navigate the dataframe and compute statistics partitioned by date stamp

   Partitioned by day version of the normalized summary. Useful for scheduling a job that computes daily stats. Returns a KvRdd to be able to be pushed into a KvStore for fetching and merging. As well as a dataframe for storing in hive.

   For entity on the left we use daily partition as the key. For events we bucket by timeBucketMinutes (def. 1 hr) Since the stats are mergeable coarser granularities can be obtained through fetcher merging.

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

   

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9. def equals(arg0: Any): Boolean

   

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10. def finalize(): Unit

    

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

    

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12. def hashCode(): Int

    

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13. final def isInstanceOf[T0]: Boolean

    

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14. val metrics: Seq[MetricTransform]

    

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

    

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16. final def notify(): Unit

    

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17. final def notifyAll(): Unit

    

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18. lazy val selectedDf: DataFrame

    

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

    

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20. implicit val tableUtils: TableUtils

    

21. val timeColumns: Seq[String]

    

22. def toString(): String

    

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23. final def wait(): Unit

    

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

    

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

    

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