Packages

trait ShuffleSpec extends AnyRef

This is used in the scenario where an operator has multiple children (e.g., join) and one or more of which have their own requirement regarding whether its data can be considered as co-partitioned from others. This offers APIs for:

  • Comparing with specs from other children of the operator and check if they are compatible. When two specs are compatible, we can say their data are co-partitioned, and Spark will potentially be able to eliminate shuffle if necessary.
  • Creating a partitioning that can be used to re-partition another child, so that to make it having a compatible partitioning as this node.
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AnyRef, Any
Known Subclasses
HashShuffleSpec, KeyGroupedShuffleSpec, RangeShuffleSpec, ShuffleSpecCollection, SinglePartitionShuffleSpec
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Abstract Value Members

  1. abstract def canCreatePartitioning: Boolean

    Whether this shuffle spec can be used to create partitionings for the other children.

  2. abstract def isCompatibleWith(other: ShuffleSpec): Boolean

    Returns true iff this spec is compatible with the provided shuffle spec.

    Returns true iff this spec is compatible with the provided shuffle spec.

    A true return value means that the data partitioning from this spec can be seen as co-partitioned with the other, and therefore no shuffle is required when joining the two sides.

    Note that Spark assumes this to be reflexive, symmetric and transitive.

  3. abstract def numPartitions: Int

    Returns the number of partitions of this shuffle spec

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  6. def createPartitioning(clustering: Seq[Expression]): Partitioning

    Creates a partitioning that can be used to re-partition the other side with the given clustering expressions.

    Creates a partitioning that can be used to re-partition the other side with the given clustering expressions.

    This will only be called when:

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