Thanks, Tom, for this quick answer.
Le 12/09/2016 à 16:41, Tom Lane a écrit :
phb07 <phb07@xxxxxxxxxxxx> writes:
The performance issue, encountered in very specific situations, is the
time needed to cancel a significant number of insertions.
I have build a simple test case that reproduces the problem without the
need of the extension. It just mimics the behaviour.
At least for this example, the problem is that the DELETE enormously
alters the statistics for the t1_log.tuple column (going from 100% "NEW"
to 50% "NEW" and 50% "OLD"), but the plan for your last command is
generated with stats saying there are no "OLD" entries. So you get a plan
that would be fast for small numbers of "OLD" entries, but it sucks when
there are lots of them. The fix I would recommend is to do a manual
"ANALYZE t1_log" after such a large data change. Auto-ANALYZE would fix
it for you after a minute or so, probably, but if your script doesn't want
to wait around then an extra ANALYZE is the ticket.
regards, tom lane
I understand the point (and I now realize that I should have found the
answer by myself...)
Adding an ANALYZE of the log table effectively changes the plan and
brings good performances for the INSERT statement.
The drawback is the overhead of this added ANALYZE statement. With a
heavy processing like in this test case, it is worth to be done. But for
common cases, it's a little bit expensive.
But I keep the idea and I will study the best solution to implement.
Regards. Philippe.
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