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com.nvidia.spark.rapids

GpuBatchUtils

object GpuBatchUtils

Utility class with methods for calculating various metrics about GPU memory usage prior to allocation.

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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. val OFFSET_BYTES: Int

    Number of bytes per offset (32 bit)

  5. val VALIDITY_BUFFER_BOUNDARY_BYTES: Int

    Validity buffers are 64 byte aligned

  6. val VALIDITY_BUFFER_BOUNDARY_ROWS: Int

    Validity buffers are 64 byte aligned and each byte represents 8 rows

  7. final def asInstanceOf[T0]: T0
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  8. def calculateOffsetBufferSize(rows: Long): Long
  9. def calculateValidityBufferSize(rows: Long): Long
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  13. def estimateGpuMemory(dataType: DataType, nullable: Boolean, rowCount: Long): Long
  14. def estimateGpuMemory(schema: StructType, columnIndex: Int, rowCount: Long): Long

    Estimate the amount of GPU memory a batch of rows will occupy once converted

  15. def estimateGpuMemory(schema: StructType, rowCount: Long): Long

    Estimate the amount of GPU memory a batch of rows will occupy once converted

  16. def estimateRowCount(desiredBatchSizeBytes: Long, currentBatchSize: Long, currentBatchRowCount: Long): Int

    Estimate the number of rows required to meet a batch size limit

  17. def finalize(): Unit
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  18. def generateSplitIndices(rows: Long, numSplits: Int): Array[Int]

    Generate indices which evenly splitting input batch

    Generate indices which evenly splitting input batch

    rows

    number of rows of input batch

    numSplits

    desired number of splits

    returns

    splitting indices

  19. final def getClass(): Class[_]
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  21. def isFixedWidth(dt: DataType): Boolean
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  23. def isVariableWidth(dt: DataType): Boolean
  24. def minGpuMemory(dataType: DataType, nullable: Boolean, rowCount: Long): Long

    Get the minimum size a column could be that matches these conditions.

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