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org.apache.spark.sql.execution.adaptive

ShufflePartitionsUtil

object ShufflePartitionsUtil extends Logging

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  4. final val MERGED_PARTITION_FACTOR: Double(1.2)
  5. final val SMALL_PARTITION_FACTOR: Double(0.2)
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  8. def coalescePartitions(mapOutputStatistics: Seq[Option[MapOutputStatistics]], inputPartitionSpecs: Seq[Option[Seq[ShufflePartitionSpec]]], advisoryTargetSize: Long, minNumPartitions: Int, minPartitionSize: Long): Seq[Seq[ShufflePartitionSpec]]

    Coalesce the partitions from multiple shuffles, either in their original states, or applied with skew handling partition specs.

    Coalesce the partitions from multiple shuffles, either in their original states, or applied with skew handling partition specs. If called on partitions containing skew partition specs, this method will keep the skew partition specs intact and only coalesce the partitions outside the skew sections.

    This method will return an empty result if the shuffles have been coalesced already, or if they do not have the same number of partitions, or if the coalesced result is the same as the input partition layout.

    returns

    A sequence of sequence of ShufflePartitionSpecs, which each inner sequence as the new partition specs for its corresponding shuffle after coalescing. If Nil is returned, then no coalescing is applied.

  9. def createSkewPartitionSpecs(shuffleId: Int, reducerId: Int, targetSize: Long): Option[Seq[PartialReducerPartitionSpec]]

    Splits the skewed partition based on the map size and the target partition size after split, and create a list of PartialMapperPartitionSpec.

    Splits the skewed partition based on the map size and the target partition size after split, and create a list of PartialMapperPartitionSpec. Returns None if can't split.

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