> On Sep 22, 2021, at 12:49 PM, Ryan Booz <r...@timescale.com> wrote: > > [Timescale Dev Advocate here] > I realize this might not be the most accepted answer (could be interpreted as > trying to "sell" something), but feels like an opportunity to talk about > DISTINCT queries and opportunities. Because you have that index, Timescale > 2.3 added a "Skip Scan" query planner node that works on regular BTree > indexes (it doesn't have to be time-series/TimescaleDB Hypertable data at > all). In this case, your distinct query would likely run in a few > milliseconds based on the counts you mention (170 stations, 3 channels per > station), and then the outer aggregation would do the GROUP BY. So, you > **could** add the TimescaleDB extension to your database (or a copy of) and > give it a try. You don't actually need to use any TimescaleDB features > otherwise.
I had actually already done that, as I was considering, in spite of past negative experiences with timescaledb, experimenting with it on this DB to see if it worked any better with this data. Out of curiosity, I tried removing the timescaledb extension, whereupon the query in question took roughly twice as long. So you are right that installing timescaledb speeds things up, even when not using any timescaledb specific functions. So that was a good call. Thanks! --- 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 > > A writeup of why this kind of DISTINCT query is slow in PostgreSQL (for now) > and what we did to overcome it: > https://blog.timescale.com/blog/how-we-made-distinct-queries-up-to-8000x-faster-on-postgresql/ > > <https://blog.timescale.com/blog/how-we-made-distinct-queries-up-to-8000x-faster-on-postgresql/> > Plans for a similar feature in PostgreSQL proper that we'd totally support > but hasn't made forward progress yet: > https://commitfest.postgresql.org/19/1741/ > <https://commitfest.postgresql.org/19/1741/> > Anyway, it might be worth a shot. HTH > > Ryan B > > On Wed, Sep 22, 2021 at 4:27 PM David G. Johnston <david.g.johns...@gmail.com > <mailto:david.g.johns...@gmail.com>> wrote: > On Wed, Sep 22, 2021 at 1:21 PM Michael Lewis <mle...@entrata.com > <mailto:mle...@entrata.com>> wrote: > In the future, please share the plan returned by explain analyze, and some > data about how many rows in the involved tables, > > I believe we consider it acceptable to link to an explain viewer, which is > what the OP did. Reading explain output in email has its own challenges, and > I'd rather have the website than a text attachment. > > > How does the below work? It should do a very simple index scan only, then > aggregate the relative few rows after the fact. > > select station, array_agg(distinct(channel)) as channels > FROM( > SELECT station,channel FROM data GROUP BY station,channel > ) AS sub > group by station; > > Yeah, am pondering this too, though seems like the queries should be > identical so the plan/execution should be the same either way. > > > If there is correlation between station & channel, then you might look at > creating a multivariate statistics object and analyzing the table so the > planner can make better choices > > There is no where clause so I'm doubtful there is much to be gained going > down this path. The Index-Only scan seems like an optimal way to obtain this > data and the existing query already does that. The aggregation path might > vary though it seems like that shouldn't be the case here. > > David J.
