Re: Very slow 101-feeling design/query..

PG 13.4. Can't quite run the EXPLAIN ANALYZE since it takes so long, but
EXPLAIN SELECT DISTINCT game_id FROM vw_joints shows (s = joints, p = plays)

----------------------------------------------------------------------------------------------------
HashAggregate (cost=63810150.11..63810168.40 rows=1829 width=4)
Group Key: p.game_id
-> Hash Left Join (cost=21647.78..60977838.19 rows=1132924766 width=4)
Hash Cond: (s.play_uuid = p.play_uuid)
-> Append (cost=0.00..57982241.49 rows=1132924766 width=16)
-> Seq Scan on joints_2021_01 s_1 (cost=0.00..13.00
rows=300 width=16)
-> Seq Scan on joints_2021_02 s_2 (cost=0.00..13.00
rows=300 width=16)
-> Seq Scan on joints_2021_03 s_3 (cost=0.00..13.00
rows=300 width=16)
-> Seq Scan on joints_2021_04 s_4 (cost=0.00..2217902.16
rows=49859816 width=16)
-> Seq Scan on joints_2021_05 s_5 (cost=0.00..2965019.35
rows=63440735 width=16)
-> Seq Scan on joints_2021_06 s_6 (cost=0.00..3797848.89
rows=85688889 width=16)
-> Seq Scan on joints_2021_07 s_7 (cost=0.00..5867829.24
rows=115975424 width=16)
-> Seq Scan on joints_2021_08 s_8 (cost=0.00..17274328.41
rows=380175741 width=16)
-> Seq Scan on joints_2021_09 s_9 (cost=0.00..18226427.88
rows=393209088 width=16)
-> Seq Scan on joints_2021_10 s_10 (cost=0.00..1942824.01
rows=44003201 width=16)
-> Seq Scan on joints_2021_11 s_11 (cost=0.00..25385.72
rows=570672 width=16)
-> Seq Scan on joints_2021_12 s_12 (cost=0.00..13.00
rows=300 width=16)
-> Hash (cost=14292.90..14292.90 rows=588390 width=20)
-> Seq Scan on plays p (cost=0.00..14292.90 rows=588390
width=20)
JIT:
Functions: 34
Options: Inlining true, Optimization true, Expressions true, Deforming
true
(22 rows)

On Fri, Dec 10, 2021 at 3:17 PM Ron <ronljohnsonjr(at)gmail(dot)com> wrote:

> On 12/10/21 4:53 PM, Wells Oliver wrote:
> > This feels very 101 but I feel like it should be much faster:
> >
> > A table "joints" with a PK of play_uuid, target_id, joint_seq,
> > joint_timestamp.
> >
> > "joints" is partitioned using RANGE on joint_timestamp for monthly
> > partitions 1/1 - 2/1, 2-1 - 3/1, etc.
> >
> > "joints" has an FK where play_uuid refers to table "plays" and
> > column "play_uuid" where "play_uuid" is the PK.
> >
> > "plays" additionally has an indexed column game_id.
> >
> > "joints" has 1133,932,391 rows across 12 monthly partitions for 2021,
> and
> > "plays has 585,627 rows. We made a view called "vw_joints" which just
> does:
> >
> > SELECT * FROM joints JOIN plays USING (play_id);
> >
> > Then doing:
> >
> > SELECT DISTINCT game_id FROM vw_joints
> >
> > Takes 35-45 minutes. Which seems nuts. We do this kind of design in a
> few
> > different plays to normalize things, but it comes at the cost of these
> > agonizingly slow (and seemingly dead simple) qeuries.
> >
> > Is there any optimization to do here beyond flattening table and
> > de-normalizing data? Is the partitioning causing a slowness here? I feel
> > like partitioning is creating some difficulty...
>
> What Postgresql version?
>
> What does the query plan look like?
>
> --
> Angular momentum makes the world go 'round.
>
>
>

--
Wells Oliver
wells(dot)oliver(at)gmail(dot)com <wellsoliver(at)gmail(dot)com>