WhyProfileSession

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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 aggProfiles(timestamp: Instant = Instant.now()): DataFrame

   

   Run aggregation and build profile based on the specification of this session

   Run aggregation and build profile based on the specification of this session

   timestamp

   the timestamp for the whole run (often the current time, or the start of the batch run

   returns

   a DataFrame with aggregated profiles under 'why_profile' column

5. final def asInstanceOf[T0]: T0

   

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6. def clone(): AnyRef

   

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

   

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8. def finalize(): Unit

   

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

   

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10. def groupBy(col1: String, cols: String*): WhyProfileSession

    

11. final def isInstanceOf[T0]: Boolean

    

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

    

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13. final def notify(): Unit

    

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14. final def notifyAll(): Unit

    

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

    

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16. final def wait(): Unit

    

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

    

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

    

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19. def withTimeColumn(timeColumn: String): WhyProfileSession

    

    Set the column for grouping by time.

    Set the column for grouping by time. This column must be of Timestamp type in Spark SQL.

    Note that WhyLogs uses this column to group data together, so please make sure you truncate the data to the appropriate level of precision (i.e. daily, hourly) before calling this. We only accept a column name at the moment. You can alias raw Column into a column name with String, col: Column)

    timeColumn

    the column that contains the timestamp.