> On Jun 4, 2020, at 3:03 PM, Sebastian Dressler <sebastian@xxxxxxxxxxx> wrote: > > Hi Philip, > >> On 4. Jun 2020, at 20:37, Philip Semanchuk <philip@xxxxxxxxxxxxxxxxxxxxx> wrote: >> >> [...] >>> >>>> This brings up a couple of questions — >>>> 1) I’ve read that this is Postgres’ formula for the max # of workers it will consider for a table — >>>> >>>> max_workers = log3(table size / min_parallel_table_scan_size) >>>> >>>> Does that use the raw table size, or does the planner use statistics to estimate the size of the subset of the table that will be read before allocating workers? >>> >>> "table size" is the number of PSQL pages, i.e. relation-size / 8 kB. This comes from statistics. >> >> OK, so it sounds like the planner does *not* use the values in pg_stats when planning workers, true? > > Full disclosure: I am not too deep into these internals, likely others on the list know much more about it. But with respect to the relation size, I think this is tracked elsewhere, it might be affected by other parameters though like vacuuming and probably, the estimated amount of how much of the table is scanned also plays a role. I’m not too familiar with the internals either, but if I interpret this line of code correctly, it’s seems that pg_stats is not involved, and the worker allocation is based strictly on pages in the relation -- https://github.com/postgres/postgres/blob/master/src/backend/optimizer/path/allpaths.c#L800 That means I still don’t have a reason for why this query gets a different number of workers depending on the WHERE clause, but I can experiment with that more on my own. >> I’m still trying to understand one thing I’ve observed. I can run the query that produced the plan in the gist I linked to above with max_parallel_workers_per_gather=6 and the year param = 2018, and I get 6 workers. When I set the year param=2022 I get only one worker. Same tables, same query, different parameter. That suggests to me that the planner is using pg_stats when allocating workers, but I can imagine there might be other things going on that I don’t understand. (I haven’t ruled out that this might be an AWS-specific quirk, either.) > > I think it would be helpful, if you could post again both plans. The ideal would be to use https://explain.dalibo.com/ and share the links. You will have to generate them with JSON format, but still can anonymize them. I really appreciate all the help you and others have already given. I think I’m good for now. Thank you so much, Philip
