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com.nvidia.spark.rapids

AggregateUtils

object AggregateUtils

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  6. def computeTargetBatchSize(confTargetSize: Long, inputTypes: Seq[DataType], outputTypes: Seq[DataType], isReductionOnly: Boolean): Long

    Computes a target input batch size based on the assumption that computation can consume up to 4X the configured batch size.

    Computes a target input batch size based on the assumption that computation can consume up to 4X the configured batch size.

    confTargetSize

    user-configured maximum desired batch size

    inputTypes

    input batch schema

    outputTypes

    output batch schema

    isReductionOnly

    true if this is a reduction-only aggregation without grouping

    returns

    maximum target batch size to keep computation under the 4X configured batch limit

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  15. def shouldFallbackMultiDistinct(aggExprs: Seq[AggregateExpression]): Boolean

    Return true if there are multiple distinct functions along with non-distinct functions.

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  18. def validateAggregate(attributes: AttributeSet): Boolean

    Return true if the Attribute passed is one of aggregates in the aggs list.

    Return true if the Attribute passed is one of aggregates in the aggs list. Use it with caution. We are comparing the name of a column looking for anything that matches with the values in aggs.

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