bart-samwel commented on pull request #29181:
URL: https://github.com/apache/spark/pull/29181#issuecomment-662483694


   Can you double check that the ordering is correct if there are NULLs 
involved, or outer join conditions? The tricky cases I see:
   
   - RIGHT / FULL SHJ. If the streaming / "probe" input is ordered by (some of) 
the join keys. After consuming the streaming input, the hash join will emit 
rows for build side rows that didn't have matches. Those rows may actually have 
values for the join keys, and those will end up in the output. Those will be 
out of order.
   
   - RIGHT / FULL SHJ. If the streaming / "prob" input is ordered by some 
non-join keys. After consuming the streaming input, the hash join will emit 
rows with NULL values for the streaming input's columns, which include the 
ordering keys. This may be correct if Spark's ordering property has "nulls 
last", but it may not be correct even then. For instance, if the input is 
ordered by (JOINKEY1, NONJOINKEY1) with NULLS LAST, then a final output 
ordering may look like:
   
   (1, 'a')
   (2, 'c')
   (3, 'b')
   (1,  NULL)
   
   But the correct ordering for NULLS LAST is
   
   (1, 'a')
   (1,  NULL)
   (2, 'c')
   (3, 'b')


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