liufangqi commented on code in PR #5997:
URL: https://github.com/apache/hudi/pull/5997#discussion_r913452301
##########
hudi-flink-datasource/hudi-flink/src/main/java/org/apache/hudi/sink/utils/Pipelines.java:
##########
@@ -330,17 +330,23 @@ public static DataStream<Object>
hoodieStreamWrite(Configuration conf, int defau
.setParallelism(conf.getInteger(FlinkOptions.WRITE_TASKS));
} else {
WriteOperatorFactory<HoodieRecord> operatorFactory =
StreamWriteOperator.getFactory(conf);
- return dataStream
- // Key-by record key, to avoid multiple subtasks write to a bucket
at the same time
- .keyBy(HoodieRecord::getRecordKey)
- .transform(
- "bucket_assigner",
- TypeInformation.of(HoodieRecord.class),
- new KeyedProcessOperator<>(new BucketAssignFunction<>(conf)))
- .uid("uid_bucket_assigner_" +
conf.getString(FlinkOptions.TABLE_NAME))
-
.setParallelism(conf.getOptional(FlinkOptions.BUCKET_ASSIGN_TASKS).orElse(defaultParallelism))
- // shuffle by fileId(bucket id)
- .keyBy(record -> record.getCurrentLocation().getFileId())
+
+ DataStream<HoodieRecord> bucketDataStream = dataStream
+ // Key-by record key, to avoid multiple subtasks write to a
bucket at the same time
+ .keyBy(HoodieRecord::getRecordKey)
+ .transform(
+ "bucket_assigner",
+ TypeInformation.of(HoodieRecord.class),
+ new KeyedProcessOperator<>(new
BucketAssignFunction<>(conf)))
+ .uid("uid_bucket_assigner_" +
conf.getString(FlinkOptions.TABLE_NAME))
+
.setParallelism(conf.getOptional(FlinkOptions.BUCKET_ASSIGN_TASKS).orElse(defaultParallelism));
+
+ bucketDataStream =
conf.getOptional(FlinkOptions.BUCKET_ASSIGN_TASKS).orElse(defaultParallelism) ==
+ conf.getInteger(FlinkOptions.WRITE_TASKS) ? bucketDataStream :
bucketDataStream
+ // shuffle by fileId(bucket id)
+ .keyBy(record -> record.getCurrentLocation().getFileId());
Review Comment:
> I think it is a valid change but how much gains can we get here ?
As the result of our test, we can simply resolve the data skew problem.
Also, we can reduce the network overhead if we chain the opeators. Above all,
we can gain more resource usage and throughput.
Moreover, there is no loss when we apccept this change, cause we can switch
this flow autolly.
@danny0405 How do you look
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