> On Jan 13, 2020, at 6:34 PM, Dilip Kumar <dilipbal...@gmail.com> wrote: > > On Tue, Jan 14, 2020 at 5:29 AM Israel Brewster <ijbrews...@alaska.edu > <mailto:ijbrews...@alaska.edu>> wrote: >> >> I was working on diagnosing a “slow” (about 6 second run time) query: >> >> SELECT >> to_char(bucket,'YYYY-MM-DD"T"HH24:MI:SS') as dates, >> x_tilt, >> y_tilt, >> rot_x, >> rot_y, >> date_part('epoch', bucket) as timestamps, >> temp >> FROM >> (SELECT >> time_bucket('1 week', read_time) as bucket, >> avg(tilt_x::float) as x_tilt, >> avg(tilt_y::float) as y_tilt, >> avg(rot_x::float) as rot_x, >> avg(rot_y::float) as rot_y, >> avg(temperature::float) as temp >> FROM tilt_data >> WHERE station='c08883c0-fbe5-11e9-bd6e-aec49259cebb' >> AND read_time::date<='2020-01-13'::date >> GROUP BY bucket) s1 >> ORDER BY bucket; >> >> 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). 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), most of which was in a HashAggregate. >> >> I am running PostgreSQL 11.6 on a machine with 128GB of ram (so, like I >> said, plenty of RAM) >> >> How can I fix this? Thanks. > > I have noticed that after increasing the work_mem your plan has > switched from a parallel plan to a non-parallel plan. Basically, > earlier it was getting executed with 3 workers. And, after it becomes > non-parallel plan execution time is 3x. For the analysis can we just > reduce the value of parallel_tuple_cost and parallel_setup_cost and > see how it behaves?
That was it. Setting the parallel_tuple_cost parameter to .05 and the parallel_setup_cost parameter to 500 (so, both to half their default values) caused this query to run in parallel again with the higher work_mem setting (and do the sorts in memory, as was the original goal). New explain output at https://explain.depesz.com/s/rX3m <https://explain.depesz.com/s/rX3m> Granted, doing the sorts in memory didn’t speed things up as much as I would have hoped - 5.58 seconds vs 5.9 - but at least the higher work_mem setting isn’t slowing down the query any more. Would be nice if the query could run a little faster - even six seconds is a relatively long time to wait - but I can live with that at least. So thanks! Hmmm… now I wonder how things would change if I increased the max_parallel_workers value? Might be something to play around with. Maybe grab a few more cores for the VM. --- Israel Brewster Software Engineer Alaska Volcano Observatory Geophysical Institute - UAF 2156 Koyukuk Drive Fairbanks AK 99775-7320 Work: 907-474-5172 cell: 907-328-9145 > > -- > Regards, > Dilip Kumar > EnterpriseDB: http://www.enterprisedb.com <http://www.enterprisedb.com/>
