> On Jan 13, 2020, at 5:41 PM, Israel Brewster <ijbrews...@alaska.edu> wrote: > >> On Jan 13, 2020, at 3:19 PM, Tom Lane <t...@sss.pgh.pa.us >> <mailto:t...@sss.pgh.pa.us>> wrote: >> >> Israel Brewster <ijbrews...@alaska.edu <mailto:ijbrews...@alaska.edu>> >> writes: >>> In looking at the explain analyze output, I noticed that it had an >>> “external merge Disk” sort going on, accounting for about 1 second of the >>> runtime (explain analyze output here: https://explain.depesz.com/s/jx0q >>> <https://explain.depesz.com/s/jx0q> <https://explain.depesz.com/s/jx0q >>> <https://explain.depesz.com/s/jx0q>>). Since the machine has plenty of RAM >>> available, I went ahead and increased the work_mem parameter. Whereupon the >>> query plan got much simpler, and performance of said query completely >>> tanked, increasing to about 15.5 seconds runtime >>> (https://explain.depesz.com/s/Kl0S <https://explain.depesz.com/s/Kl0S> >>> <https://explain.depesz.com/s/Kl0S <https://explain.depesz.com/s/Kl0S>>), >>> most of which was in a HashAggregate. >>> How can I fix this? Thanks. >> >> Well, the brute-force way not to get that plan is "set enable_hashagg = >> false". But it'd likely be a better idea to try to improve the planner's >> rowcount estimates. The problem here seems to be lack of stats for >> either "time_bucket('1 week', read_time)" or "read_time::date". >> In the case of the latter, do you really need a coercion to date? >> If it's a timestamp column, I'd think not. As for the former, >> if the table doesn't get a lot of updates then creating an expression >> index on that expression might be useful. >> > > Thanks for the suggestions. Disabling hash aggregates actually made things > even worse: (https://explain.depesz.com/s/cjDg > <https://explain.depesz.com/s/cjDg>), so even if that wasn’t a brute-force > option, it doesn’t appear to be a good one. Creating an index on the > time_bucket expression didn’t seem to make any difference, and my data does > get a lot of additions (though virtually no changes) anyway (about 1 > additional record per second). As far as coercion to date, that’s so I can do > queries bounded by date, and actually have all results from said date > included. That said, I could of course simply make sure that when I get a > query parameter of, say, 2020-1-13, I expand that into a full date-time for > the end of the day. However, doing so for a test query didn’t seem to make > much of a difference either: https://explain.depesz.com/s/X5VT > <https://explain.depesz.com/s/X5VT> > > So, to summarise: > > Set enable_hasagg=off: worse > Index on time_bucket expression: no change in execution time or query plan > that I can see > Get rid of coercion to date: *slight* improvement. 14.692 seconds instead of > 15.5 seconds. And it looks like the row count estimates were actually worse. > Lower work_mem, forcing a disk sort and completely different query plan: Way, > way better (around 6 seconds) > > …so so far, it looks like the best option is to lower the work_mem, run the > query, then set it back? > ---
I don’t see that you’ve updated the statistics?
