org.apache.spark.sql.catalyst.expressions

HiveHashFunction

object HiveHashFunction extends InterpretedHashFunction

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

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

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  3. final def ##(): Int

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  4. final def ==(arg0: AnyRef): Boolean

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

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  6. final def asInstanceOf[T0]: T0

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  7. def clone(): AnyRef

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  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 hash(value: Any, dataType: DataType, seed: Long): Long

    Computes hash of a given value of type dataType.

    Computes hash of a given value of type dataType. The caller needs to check the validity of input value.

    Definition Classes
    HiveHashFunctionInterpretedHashFunction
  13. def hashCalendarInterval(calendarInterval: CalendarInterval): Long

    Hive allows input intervals to be defined using units below but the intervals have to be from the same category: - year, month (stored as HiveIntervalYearMonth) - day, hour, minute, second, nanosecond (stored as HiveIntervalDayTime)

    Hive allows input intervals to be defined using units below but the intervals have to be from the same category: - year, month (stored as HiveIntervalYearMonth) - day, hour, minute, second, nanosecond (stored as HiveIntervalDayTime)

    eg. (INTERVAL '30' YEAR + INTERVAL '-23' DAY) fails in Hive

    This method mimics HiveIntervalDayTime.hashCode() in Hive.

    Two differences wrt Hive due to how intervals are stored in Spark vs Hive:

    - If the INTERVAL is backed as HiveIntervalYearMonth in Hive, then this method will not produce Hive compatible result. The reason being Spark's representation of calendar does not have such categories based on the interval and is unified.

    - Spark's CalendarInterval has precision upto microseconds but Hive's HiveIntervalDayTime can store data with precision upto nanoseconds. So, any input intervals with nanosecond values will lead to wrong output hashes (ie. non adherent with Hive output)

  14. def hashCode(): Int

    Definition Classes
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  15. def hashInt(i: Int, seed: Long): Long

    Attributes
    protected
    Definition Classes
    HiveHashFunctionInterpretedHashFunction
  16. def hashLong(l: Long, seed: Long): Long

    Attributes
    protected
    Definition Classes
    HiveHashFunctionInterpretedHashFunction
  17. def hashTimestamp(timestamp: Long): Long

    Mimics TimestampWritable.

    Mimics TimestampWritable.hashCode() in Hive

  18. def hashUnsafeBytes(base: AnyRef, offset: Long, len: Int, seed: Long): Long

    Attributes
    protected
    Definition Classes
    HiveHashFunctionInterpretedHashFunction
  19. final def isInstanceOf[T0]: Boolean

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

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  21. def normalizeDecimal(input: BigDecimal): BigDecimal

  22. final def notify(): Unit

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  23. final def notifyAll(): Unit

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

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  25. def toString(): String

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  26. final def wait(): Unit

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

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

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Inherited from InterpretedHashFunction

Inherited from AnyRef

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