Στις 27/6/24 17:58, ο/η Laura Hausmann
έγραψε:
I'm sadly not sure how I could generate a test dataset that more closely resembles the production workload. In case that would be helpful in debugging this further, any tips on that would be greatly appreciated.I also tried rewriting it as a join (https://explain.depesz.com/s/36Ve), but that also didn't seem to have an effect.Heya & thank you for the response!That makes a lot of sense. I'm glad to hear it's on the radar of the team, but I understand that this is a complex task and won't happen anytime soon.
For the meantime, I've tried a couple ways of rewriting the query, sadly none of which seem to translate to the production database:
Simply dropping the or/union clause (and adding a relationship to the user themselves) fixes the problem in the test database (both user 1 (https://explain.depesz.com/s/ZY8l) and user 4 (https://explain.depesz.com/s/Q2Wk) run in 1~15ms, which isn't perfect but good enough), but not the production one (still fast for high frequency (https://explain.depesz.com/s/DixF) and slow for low frequency (https://explain.depesz.com/s/fIKm) users).
It's very possible I missed one or multiple ways the query could be rewritten in.
I am not sure my message made it through to you, I dont know if you are subscribed to the list, here is an idea :
select o.* from objects o where o."userId" = :userid UNION select o.* from objects o where o."userId" IN
(SELECT r."followeeId" FROM relationships r WHERE r."followerId"=:userid)
ORDER BY id DESC ;
With your test data I get <= 1ms answers with all inputs.
Thanks in advance,
Laura Hausmann
On Thu, Jun 27, 2024 at 12:31 PM Andrei Lepikhov <lepihov@xxxxxxxxx> wrote:
On 6/27/24 07:50, Laura Hausmann wrote:
> I'd appreciate any and all input on the situation. If I've left out any
> information that would be useful in figuring this out, please tell me.
Thanks for this curious case, I like it!
At first, you can try to avoid "OR" expressions - PostgreSQL has quite
limited set of optimisation/prediction tricks on such expressions.
Second - I see, postgres predicts wrong number of tuples. But using my
typical tool [1] and getting more precise estimations i don't see
significant profit:
Limit (cost=10832.85..10838.69 rows=50 width=21)
-> Gather Merge (cost=10832.85..10838.92 rows=52 width=21)
Workers Planned: 2
Workers Launched: 2
-> Sort (cost=9832.83..9832.90 rows=26 width=21)
Sort Key: objects.id DESC
Sort Method: top-N heapsort Memory: 32kB
Worker 0: Sort Method: quicksort Memory: 32kB
Worker 1: Sort Method: quicksort Memory: 32kB
-> Parallel Seq Scan on objects
Filter: ((hashed SubPlan 1) OR ("userId" = 1))
Rows Removed by Filter: 183372
SubPlan 1
-> Nested Loop
-> Index Only Scan using users_pkey on
Index Cond: (id = 1)
Heap Fetches: 0
-> Index Only Scan using
"relationships_followerId_followeeId_idx" on relationships
Index Cond: ("followerId" = 1)
Heap Fetches: 0
Planning Time: 0.762 ms
Execution Time: 43.816 ms
Limit (cost=10818.83..10819.07 rows=2 width=21)
-> Gather Merge (cost=10818.83..10819.07 rows=2 width=21)
Workers Planned: 2
Workers Launched: 2
-> Sort (cost=9818.81..9818.81 rows=1 width=21)
Sort Key: objects.id DESC
Sort Method: quicksort Memory: 25kB
Worker 0: Sort Method: quicksort Memory: 25kB
Worker 1: Sort Method: quicksort Memory: 25kB
-> Parallel Seq Scan on objects
Filter: ((hashed SubPlan 1) OR ("userId" = 4))
Rows Removed by Filter: 183477
SubPlan 1
-> Nested Loop (cost=0.56..8.61 rows=1 width=4)
-> Index Only Scan using
"relationships_followerId_followeeId_idx" on relationships
Index Cond: ("followerId" = 4)
Heap Fetches: 0
-> Index Only Scan using users_pkey
Index Cond: (id = 4)
Heap Fetches: 0
Planning Time: 0.646 ms
Execution Time: 30.824 ms
But this was achieved just because of parallel workers utilisation.
Disabling them we get:
Limit (cost=14635.07..14635.08 rows=2 width=21) (actual
time=75.941..75.943 rows=0 loops=1)
-> Sort (cost=14635.07..14635.08 rows=2 width=21) (actual
time=75.939..75.940 rows=0 loops=1)
Sort Key: objects.id DESC
Sort Method: quicksort Memory: 25kB
-> Seq Scan on objects (cost=8.61..14635.06 rows=2 width=21)
(actual time=75.931..75.932 rows=0 loops=1)
Filter: ((hashed SubPlan 1) OR ("userId" = 4))
Rows Removed by Filter: 550430
SubPlan 1
-> Nested Loop (cost=0.56..8.61 rows=1 width=4)
(actual time=0.039..0.040 rows=0 loops=1)
-> Index Only Scan using
"relationships_followerId_followeeId_idx" on relationships
(cost=0.28..4.29 rows=1 width=8) (actual time=0.038..0.038 rows=0 loops=1)
Index Cond: ("followerId" = 4)
Heap Fetches: 0
-> Index Only Scan using users_pkey on users
(cost=0.29..4.31 rows=1 width=4) (never executed)
Index Cond: (id = 4)
Heap Fetches: 0
Planning Time: 0.945 ms
Execution Time: 76.123 ms
So, from the optimiser's point of view, it has done the best it could.
Theoretically, if you have a big table with indexes and must select a
small number of tuples, the ideal query plan will include parameterised
NestLoop JOINs. Unfortunately, parameterisation in PostgreSQL can't pass
inside a subquery. It could be a reason for new development because
MSSQL can do such a trick, but it is a long way.
You can try to rewrite your schema and query to avoid subqueries in
expressions at all.
I hope this message gave you some insights.
[1] https://github.com/postgrespro/aqo
--
regards, Andrei Lepikhov
-- Achilleas Mantzios IT DEV - HEAD IT DEPT Dynacom Tankers Mgmt (as agents only)
