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object GpuOrcScan extends Serializable

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  1. final def !=(arg0: Any): Boolean
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  2. final def ##(): Int
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  4. final def asInstanceOf[T0]: T0
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  5. def canCast(from: TypeDescription, to: TypeDescription, isOrcFloatTypesToStringEnable: Boolean): Boolean

    Whether the type casting is supported by GPU ORC reading.

    Whether the type casting is supported by GPU ORC reading.

    No need to support the whole list that CPU does in "ConvertTreeReaderFactory.canConvert", but the ones between GPU supported types. Each supported casting is implemented in "castColumnTo".

  6. def castColumnTo(col: ColumnView, targetType: DataType, originalFromDt: DataType): ColumnView

    Cast the column to the target type for ORC schema evolution.

    Cast the column to the target type for ORC schema evolution. It is designed to support all the cases that canCast returns true. Both of the column type and target type should be primitive.

    The returned column may be either the input or a new one, users should check and close it when needed.

  7. def castIntegersToTimestamp(col: ColumnView, colType: DType, timeUnit: DType): ColumnVector

    Convert the integer vector into timestamp(microseconds) vector.

    Convert the integer vector into timestamp(microseconds) vector.

    col

    The integer columnar vector.

    colType

    Specific integer type, it should be BOOL/INT8/INT16/INT32/INT64.

    timeUnit

    It should be one of {DType.TIMESTAMP_SECONDS, DType.TIMESTAMP_MILLISECONDS}. If timeUnit == SECONDS, then we consider the integers as seconds. If timeUnit == MILLISECONDS, then we consider the integers as milliseconds. This parameter is determined by the shims.

    returns

    A timestamp vector.

  8. def clone(): AnyRef
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  18. final def synchronized[T0](arg0: ⇒ T0): T0
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  19. def tagSupport(sparkSession: SparkSession, schema: StructType, meta: RapidsMeta[_, _, _]): Unit
  20. def tagSupport(scanMeta: ScanMeta[OrcScan]): Unit
  21. def toString(): String
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  22. final def wait(): Unit
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