rdblue commented on a change in pull request #4047:
URL: https://github.com/apache/iceberg/pull/4047#discussion_r805432750
##########
File path:
spark/v3.2/spark/src/test/java/org/apache/iceberg/spark/TestSparkDistributionAndOrderingUtil.java
##########
@@ -1567,6 +1567,370 @@ public void
testRangePositionDeltaUpdatePartitionedTable() {
table, UPDATE, expectedDistribution,
SPEC_ID_PARTITION_FILE_POSITION_ORDERING);
}
+ //
==================================================================================
+ // Distribution and ordering for merge-on-read MERGE operations with
position deletes
+ //
==================================================================================
+ //
+ // UNPARTITIONED UNORDERED
+ // -------------------------------------------------------------------------
+ // merge mode is NOT SET -> rely on write distribution and ordering as a
basis
+ // merge mode is NONE -> unspecified distribution + LOCALLY ORDER BY
_spec_id, _partition, _file, _pos
+ // merge mode is HASH -> unspecified distribution + LOCALLY ORDER BY
_spec_id, _partition, _file, _pos
+ // merge mode is RANGE -> unspecified distribution + LOCALLY ORDER BY
_spec_id, _partition, _file, _pos
+ //
+ // UNPARTITIONED ORDERED BY id, data
+ // -------------------------------------------------------------------------
+ // merge mode is NOT SET -> rely on write distribution and ordering as a
basis
+ // merge mode is NONE -> unspecified distribution +
+ // LOCALLY ORDER BY _spec_id, _partition, _file, _pos,
id, data
+ // merge mode is HASH -> unspecified distribution +
Review comment:
Oh, I think I see. I was thinking about the `PARTITIONED BY, UNORDERED`
case that is actually below. I concluded what you did for that case, so that's
good validation!
Here, it still seems bad to me not to distribute. That's going to result in
a lot of small delete files, which is really expensive and possibly worse than
having a single writer for all the inserted data. It would be nice to be able
to round-robin the new data... what about using something like `HASH DISTRIBUTE
BY _spec, _partition, bucket(id, data, numShufflePartitions)`?
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