CTTY commented on code in PR #7359:
URL: https://github.com/apache/hudi/pull/7359#discussion_r1382290995
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hudi-client/hudi-flink-client/src/main/java/org/apache/hudi/table/action/commit/FlinkWriteHelper.java:
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@@ -99,24 +100,34 @@ public List<HoodieRecord<T>> deduplicateRecords(
// caution that the avro schema is not serializable
final Schema schema = new Schema.Parser().parse(schemaStr);
- return keyedRecords.values().stream().map(x -> x.stream().reduce((rec1,
rec2) -> {
- HoodieRecord<T> reducedRecord;
- try {
- // Precombine do not need schema and do not return null
- reducedRecord = merger.merge(rec1, schema, rec2, schema,
props).get().getLeft();
- } catch (IOException e) {
- throw new HoodieException(String.format("Error to merge two records,
%s, %s", rec1, rec2), e);
+ boolean sortBeforePrecombine = merger.useSortedMerge(props);
+ return keyedRecords.values().stream().map(hoodieRecords -> {
+ Stream<HoodieRecord<T>> recordStream;
+ if (sortBeforePrecombine) {
+ recordStream = hoodieRecords.stream().sorted(new
SortedPrecombineComparator(schema, props));
Review Comment:
The merging order matters and it can affect correctness. Here is an example:
Suppose we have record like below and the ordering key for each record is
its timestamp
|ts|city|data|changed_cols|
|--|----|----|---|
1|Seattle|0| |
---
2nd record:
|ts|city|data|changed_cols|
|--|----|----|---|
5|San Francisco|0|city|
---
3rd record:
|ts|city|data|changed_cols|
|--|----|----|---|
3|San Jose|0|city|
---
The ideal state is the record reflects newer updates and ends up storing
`San Francisco`. If we don't sort them then the `city` would be overwritten by
the 3rd record. The "sorted merge" logic can't be implemented within `merger`
because it's only aware of 2 records that it's merging
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