JingsongLi commented on a change in pull request #17939:
URL: https://github.com/apache/flink/pull/17939#discussion_r765481583
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File path:
flink-table/flink-table-planner/src/main/java/org/apache/flink/table/planner/plan/nodes/exec/common/CommonExecSink.java
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@@ -280,26 +297,29 @@ private int deriveSinkParallelism(
* messages.
*/
private Transformation<RowData> applyKeyBy(
- ChangelogMode changelogMode,
+ TableConfig config,
Transformation<RowData> inputTransform,
int[] primaryKeys,
int sinkParallelism,
- boolean upsertMaterialize) {
- final int inputParallelism = inputTransform.getParallelism();
- if ((inputParallelism == sinkParallelism ||
changelogMode.containsOnly(RowKind.INSERT))
- && !upsertMaterialize) {
- return inputTransform;
+ int inputParallelism,
+ boolean inputInsertOnly,
+ boolean needMaterialize) {
+ final ExecutionConfigOptions.SinkKeyedShuffle sinkShuffleByPk =
+
config.getConfiguration().get(ExecutionConfigOptions.TABLE_EXEC_SINK_KEYED_SHUFFLE);
+ boolean sinkKeyBy = false;
+ switch (sinkShuffleByPk) {
+ case NONE:
+ break;
+ case AUTO:
+ sinkKeyBy = inputInsertOnly && sinkParallelism !=
inputParallelism;
+ break;
+ case FORCE:
+ // single parallelism has no problem
+ sinkKeyBy = sinkParallelism != 1 || inputParallelism != 1;
Review comment:
I was torn about this condition because I originally thought we
shouldn't specialize the single parallelism case. But considering that there
are a lot of single parallelism jobs in stream computing, it is worth
optimizing to remove keyBy for single parallelism.
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