cloud-fan commented on a change in pull request #32875:
URL: https://github.com/apache/spark/pull/32875#discussion_r769688143
##########
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/physical/partitioning.scala
##########
@@ -352,3 +350,142 @@ case class BroadcastPartitioning(mode: BroadcastMode)
extends Partitioning {
case _ => false
}
}
+
+/**
+ * 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:
+ *
+ * 1. 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 able to eliminate shuffle if necessary.
+ * 1. Creating a partitioning that can be used to re-partition another
child, so that to make it
+ * having a compatible partitioning as this node.
+ */
+trait ShuffleSpec {
+ /**
+ * Returns the number of partitions of this shuffle spec
+ */
+ def numPartitions: Int
+
+ /**
+ * 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.
+ */
+ def isCompatibleWith(other: ShuffleSpec): Boolean
+
+ /**
+ * Whether this shuffle spec can be used to create partitionings for the
other children.
+ */
+ def canCreatePartitioning: Boolean = false
+
+ /**
+ * Creates a partitioning that can be used to re-partitioned the other side
with the given
Review comment:
```suggestion
* Creates a partitioning that can be used to re-partition the other side
with the given
```
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