liufangqi commented on code in PR #5997:
URL: https://github.com/apache/hudi/pull/5997#discussion_r913748605
##########
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:
> Then why not try to promote the hash algorithm, say the murmur hash ?
The hash algorithm what flink use is the murmur hash.
The point is that the bucket num is small that equals to the downstream task
num.
See this example code:
_int bucketNum = 10;
int taskNum = 10;
int [] map = new int[taskNum];
for (int i = 0; i < bucketNum ; i++) {
map[Math.abs(murmurHash(UUID.randomUUID().hashCode()))
% taskNum] += 1;
}
for (int num:
map) {
System.out.println(num);
}_
if we just generate 10 buckets for 10 tasks, we can get like this:
if we generate more buckets for 10 tasks, it seems like more balance:
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