Github user yhuai commented on the pull request:
https://github.com/apache/spark/pull/5208#issuecomment-91339237
Actually, instead of introducing new `Distribution` and `Partitioning`, how
about we add the following two concepts to a `SparkPlan`.
* `requiredPartitionOrdering: Seq[Seq[SortOrder]]` defines the required
ordering of rows in a partition for the children of a `SparkPlan`. For every
child, `Seq[SortOrder]` defines the required ordering of rows generated by this
child.
* `outputPartitionOrdering: Seq[SortOrder]` defines the ordering of rows
generated by a `SparkPlan`.
With these concepts, we can mix the requirements on the data distribution
in a partition with our existing requirements on the data distribution of the
entire dataset. For example, for `SortMergeJoin`, we need
`ClusteredDistribution` (or `OrderedDistribution`) and a non-empty list of
columns for `RequiredPartitionOrdering`s of its children.
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at [email protected] or file a JIRA ticket
with INFRA.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
