nsivabalan commented on code in PR #14090:
URL: https://github.com/apache/hudi/pull/14090#discussion_r2452175074
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hudi-common/src/main/java/org/apache/hudi/metadata/HoodieTableMetadataUtil.java:
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@@ -1089,25 +1089,40 @@ public static Pair<Set<String>, Set<String>>
computeRevivedAndDeletedKeys(Set<St
}
/**
- * There are chances that same record key from data table has 2 entries (1
delete from older partition and 1 insert to newer partition)
- * So, this method performs reduce by key to ignore the deleted entry.
- * @param recordIndexRecords hoodie records after rli index lookup.
- * @param parallelism parallelism to use.
- * @return
+ * Reduces metadata table index records by their metadata record key to
ensure only a single
+ * update per metadata record key.
+ * <p>
+ * This is critical for handling scenarios where the same metadata record
key appears multiple times:
+ * - Partition movements: A data record moving from one partition to another
generates both
+ * a delete entry (from old partition) and an insert entry (to new partition)
+ * - File group movements: A record moving from one file group to another
+ * - When usePartitionInKey is true: Groups by (metadata record key,
partition path) tuple
+ * - When usePartitionInKey is false: Groups by metadata record key only
+ * <p>
+ * The reduce logic prefers non-deleted records over deleted ones to
properly handle movements.
+ * For Record Level Index: When both records are non-deleted (indicating
duplicate inserts for
+ * the same key), an exception is thrown since this represents an invalid
state.
+ * For Secondary Index: When both records are non-deleted, the later record
(record2) is preferred.
+ *
+ * @param metadataRecords {@link HoodieData} of metadata table index
records to be reduced by keys
+ * @param parallelism parallelism for the reduce-by operation
+ * @param usePartitionInKey whether to use partition path as part of the
grouping key
+ * (true for partitioned RLI, false for
non-partitioned RLI and SI)
+ * @return HoodieData of deduplicated metadata records with one record per
metadata record key
*/
@VisibleForTesting
- public static HoodieData<HoodieRecord> reduceByKeys(HoodieData<HoodieRecord>
recordIndexRecords, int parallelism, boolean isPartitionedRLI) {
- HoodiePairData<HoodieKey, HoodieRecord> recordIndexRecordsPair;
- if (isPartitionedRLI) {
- recordIndexRecordsPair = recordIndexRecords.mapToPair(r -> {
+ public static HoodieData<HoodieRecord> reduceByKeys(HoodieData<HoodieRecord>
metadataRecords, int parallelism, boolean usePartitionInKey) {
+ HoodiePairData<HoodieKey, HoodieRecord> metadataRecordsPair;
+ if (usePartitionInKey) {
+ metadataRecordsPair = metadataRecords.mapToPair(r -> {
String recordPartitionPath = r.isDelete(DELETE_CONTEXT,
CollectionUtils.emptyProps())
? ((EmptyHoodieRecordPayloadWithPartition)
r.getData()).getPartitionPath() : ((HoodieMetadataPayload)
r.getData()).getDataPartition();
return Pair.of(new HoodieKey(r.getRecordKey(), recordPartitionPath),
r);
});
} else {
- recordIndexRecordsPair = recordIndexRecords.mapToPair(r ->
Pair.of(r.getKey(), r));
+ metadataRecordsPair = metadataRecords.mapToPair(r -> Pair.of(r.getKey(),
r));
}
- return
recordIndexRecordsPair.reduceByKey((SerializableBiFunction<HoodieRecord,
HoodieRecord, HoodieRecord>) (record1, record2) -> {
+ return
metadataRecordsPair.reduceByKey((SerializableBiFunction<HoodieRecord,
HoodieRecord, HoodieRecord>) (record1, record2) -> {
Review Comment:
yes, if we have delete and update on the same key, we could remove it.
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