Обсуждение: [HACKERS] Parallel Plans and Cost of non-filter functions
I'm working on a custom aggregate, that generates a serialized data format. The preparation of the geometry before being formatted is pretty intense, so it is probably a good thing for that work to be done in parallel, in partial aggregates. Here's an example SQL call:
EXPLAIN analyze
SELECT length(ST_AsMVT(a)) FROM (
SELECT ST_AsMVTGeom(p.geom, ::geometry_literal, 4096, 0, true), gid, fed_num
FROM pts_10 p
WHERE p.geom && ::geometry_literal
AND p.geom IS NOT NULL
) a;
The ST_AsMVTGeom() function can be comically expensive, it's really good when it's in partial aggregates. But the cost of the function seems to be ignored.
(First note that, in order to consistently get parallel plans I have to brutally suppress parallel_tuple_cost, as described here http://blog.cleverelephant.ca/2017/10/parallel-postgis-2.html)
Whether I get a parallel aggregate seems entirely determined by the number of rows, not the cost of preparing those rows.
When changing the number of rows in the subquery, with a LIMIT, I can change from a seq scan to a paralllel seq scan and finally to a parallel aggregate, as the number of rows goes up.
An odd effect: when I have enough rows to get a paralllel seq scan, I get flip it back to a seq scan, by *increasing* the cost of ST_AsMVTGeom. That seems odd and backwards.
Is there anywhere a guide or rough description to how costs are used in determining parallel plans? The empirical approach starts to wear one down after a while :)
P.
Just clarifying myself a little, since I made a dumb error partway through.
On Thu, Nov 2, 2017 at 10:09 AM, Paul Ramsey <pramsey@cleverelephant.ca> wrote:
I'm working on a custom aggregate, that generates a serialized data format. The preparation of the geometry before being formatted is pretty intense, so it is probably a good thing for that work to be done in parallel, in partial aggregates. Here's an example SQL call:EXPLAIN analyzeSELECT length(ST_AsMVT(a)) FROM (SELECT ST_AsMVTGeom(p.geom, ::geometry_literal, 4096, 0, true), gid, fed_numFROM pts_10 pWHERE p.geom && ::geometry_literalAND p.geom IS NOT NULL) a;The ST_AsMVTGeom() function can be comically expensive, it's really good when it's in partial aggregates. But the cost of the function seems to be ignored.(First note that, in order to consistently get parallel plans I have to brutally suppress parallel_tuple_cost, as described here http://blog.cleverelephant.ca/2017/10/ parallel-postgis-2.html) Whether I get a parallel aggregate seems entirely determined by the number of rows, not the cost of preparing those rows.
This is true, as far as I can tell and unfortunate. Feeding tables with 100ks of rows, I get parallel plans, feeding 10ks of rows, never do, no matter how costly the work going on within. That's true of changing costs on the subquery select list, and on the aggregate transfn.
When changing the number of rows in the subquery, with a LIMIT, I can change from a seq scan to a paralllel seq scan and finally to a parallel aggregate, as the number of rows goes up.
I see now that as soon as I brought the LIMIT in, the plans had to go sequential, just due to the nature of a LIMIT in a subquery. Ignore the below, sorry.
Thanks!
P
P
An odd effect: when I have enough rows to get a paralllel seq scan, I get flip it back to a seq scan, by *increasing* the cost of ST_AsMVTGeom. That seems odd and backwards.Is there anywhere a guide or rough description to how costs are used in determining parallel plans? The empirical approach starts to wear one down after a while :)P.
Paul Ramsey <pramsey@cleverelephant.ca> writes: >> Whether I get a parallel aggregate seems entirely determined by the number >> of rows, not the cost of preparing those rows. > This is true, as far as I can tell and unfortunate. Feeding tables with > 100ks of rows, I get parallel plans, feeding 10ks of rows, never do, no > matter how costly the work going on within. That's true of changing costs > on the subquery select list, and on the aggregate transfn. This sounds like it might be the same issue being discussed in https://www.postgresql.org/message-id/flat/CAMkU=1ycXNipvhWuweUVpKuyu6SpNjF=yHWu4c4US5JgVGxtZQ@mail.gmail.com regards, tom lane -- Sent via pgsql-hackers mailing list (pgsql-hackers@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-hackers
Moin, On Fri, November 3, 2017 7:13 pm, Tom Lane wrote: > Paul Ramsey <pramsey@cleverelephant.ca> writes: >>> Whether I get a parallel aggregate seems entirely determined by the >>> number >>> of rows, not the cost of preparing those rows. > >> This is true, as far as I can tell and unfortunate. Feeding tables with >> 100ks of rows, I get parallel plans, feeding 10ks of rows, never do, no >> matter how costly the work going on within. That's true of changing >> costs >> on the subquery select list, and on the aggregate transfn. > > This sounds like it might be the same issue being discussed in > > https://www.postgresql.org/message-id/flat/CAMkU=1ycXNipvhWuweUVpKuyu6SpNjF=yHWu4c4US5JgVGxtZQ@mail.gmail.com When looking at the web archive, the link is broken, even though in the mail above it appears correct for me: https://www.postgresql.org/message-id/28621.1509750807%40sss.pgh.pa.us (shortened: http://bit.ly/2zetO5T) Seems the email-obfuskation breaks such links? Here is a short-link for people reading it via the archive on http: http://bit.ly/2hF4lIt Best regards, Tels -- Sent via pgsql-hackers mailing list (pgsql-hackers@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-hackers
On Sat, Nov 4, 2017 at 4:43 AM, Tom Lane <tgl@sss.pgh.pa.us> wrote: > Paul Ramsey <pramsey@cleverelephant.ca> writes: >>> Whether I get a parallel aggregate seems entirely determined by the number >>> of rows, not the cost of preparing those rows. > >> This is true, as far as I can tell and unfortunate. Feeding tables with >> 100ks of rows, I get parallel plans, feeding 10ks of rows, never do, no >> matter how costly the work going on within. That's true of changing costs >> on the subquery select list, and on the aggregate transfn. > > This sounds like it might be the same issue being discussed in > > https://www.postgresql.org/message-id/flat/CAMkU=1ycXNipvhWuweUVpKuyu6SpNjF=yHWu4c4US5JgVGxtZQ@mail.gmail.com > I have rebased the patch being discussed on that thread. Paul, you might want to once check with the recent patch [1] posted on the thread mentioned by Tom. [1] - https://www.postgresql.org/message-id/CAA4eK1%2B1H5Urm0_Wp-n5XszdLX1YXBqS_zW0f-vvWKwdh3eCJA%40mail.gmail.com -- With Regards, Amit Kapila. EnterpriseDB: http://www.enterprisedb.com -- Sent via pgsql-hackers mailing list (pgsql-hackers@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-hackers
On Sat, Nov 4, 2017 at 10:02 PM, Amit Kapila <amit.kapila16@gmail.com> wrote:
On Sat, Nov 4, 2017 at 4:43 AM, Tom Lane <tgl@sss.pgh.pa.us> wrote:
> Paul Ramsey <pramsey@cleverelephant.ca> writes:
>>> Whether I get a parallel aggregate seems entirely determined by the number
>>> of rows, not the cost of preparing those rows.
>
>> This is true, as far as I can tell and unfortunate. Feeding tables with
>> 100ks of rows, I get parallel plans, feeding 10ks of rows, never do, no
>> matter how costly the work going on within. That's true of changing costs
>> on the subquery select list, and on the aggregate transfn.
>
> This sounds like it might be the same issue being discussed in
>
> https://www.postgresql.org/message-id/flat/CAMkU= 1ycXNipvhWuweUVpKuyu6SpNjF= yHWu4c4US5JgVGxtZQ@mail.gmail. com
>
Thanks Tom, Amit; yes, this issue (expensive things in target lists not affecting plans) seems like what I'm talking about in this particular case and something that shows up a lot in PostGIS use cases: a function on a target list like ST_Buffer() or ST_Intersection() will be a couple orders of magnitude more expensive than anything in the filters.
I have rebased the patch being discussed on that thread.
Paul, you might want to once check with the recent patch [1] posted on
the thread mentioned by Tom.
[1] - https://www.postgresql.org/message-id/CAA4eK1%2B1H5Urm0_ Wp-n5XszdLX1YXBqS_zW0f- vvWKwdh3eCJA%40mail.gmail.com
Awesome! I will compare and report back,
Thanks much!
P
--
With Regards,
Amit Kapila.
EnterpriseDB: http://www.enterprisedb.com
From my perspective, this is much much better. For sufficiently large tables, I get parallel behaviour without jimmying with the defaults on parallel_setup_cost and parallel_tuple_cost. *And*, the parallel behaviour *is* sensitive to the costs of functions in target lists, so reasonably chosen costs will flip us into a parallel mode for expensive functions against smaller tables too.
Hopefully some variant of this finds it's way into core! Is there any way I can productively help?
P.
P.
On Sat, Nov 4, 2017 at 10:02 PM, Amit Kapila <amit.kapila16@gmail.com> wrote:
On Sat, Nov 4, 2017 at 4:43 AM, Tom Lane <tgl@sss.pgh.pa.us> wrote:
> Paul Ramsey <pramsey@cleverelephant.ca> writes:
>>> Whether I get a parallel aggregate seems entirely determined by the number
>>> of rows, not the cost of preparing those rows.
>
>> This is true, as far as I can tell and unfortunate. Feeding tables with
>> 100ks of rows, I get parallel plans, feeding 10ks of rows, never do, no
>> matter how costly the work going on within. That's true of changing costs
>> on the subquery select list, and on the aggregate transfn.
>
> This sounds like it might be the same issue being discussed in
>
> https://www.postgresql.org/message-id/flat/CAMkU= 1ycXNipvhWuweUVpKuyu6SpNjF= yHWu4c4US5JgVGxtZQ@mail.gmail. com
>
I have rebased the patch being discussed on that thread.
Paul, you might want to once check with the recent patch [1] posted on
the thread mentioned by Tom.
[1] - https://www.postgresql.org/message-id/CAA4eK1%2B1H5Urm0_ Wp-n5XszdLX1YXBqS_zW0f- vvWKwdh3eCJA%40mail.gmail.com
--
With Regards,
Amit Kapila.
EnterpriseDB: http://www.enterprisedb.com
On Mon, Nov 6, 2017 at 7:40 PM, Paul Ramsey <pramsey@cleverelephant.ca> wrote: > From my perspective, this is much much better. For sufficiently large > tables, I get parallel behaviour without jimmying with the defaults on > parallel_setup_cost and parallel_tuple_cost. *And*, the parallel behaviour > *is* sensitive to the costs of functions in target lists, so reasonably > chosen costs will flip us into a parallel mode for expensive functions > against smaller tables too. > Thanks for the confirmation. > Hopefully some variant of this finds it's way into core! Is there any way I > can productively help? You have already helped a lot by providing the use case, but feel free to ping on that thread if you find it is not moving. -- With Regards, Amit Kapila. EnterpriseDB: http://www.enterprisedb.com -- Sent via pgsql-hackers mailing list (pgsql-hackers@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-hackers