On 30.11.2023 11:30, Andrei Lepikhov wrote:
> On 30/11/2023 15:00, Alena Rybakina wrote:
>> 2. The second patch is my patch version when I moved the OR
>> transformation in the s index formation stage:
>>
>> So, I got the best query plan despite the possible OR to ANY
>> transformation:
>
> If the user uses a clause like "x IN (1,2) AND y=100", it will break
> your 'good' solution.
No, unfortunately I still see the plan with Seq scan node:
postgres=# explain analyze select * from test where x in (1,2) and y = 100;
QUERY PLAN
--------------------------------------------------------------------------------------------------------------------
Gather (cost=1000.00..12690.10 rows=1 width=12) (actual
time=72.985..74.832 rows=0 loops=1)
Workers Planned: 2
Workers Launched: 2
-> Parallel Seq Scan on test (cost=0.00..11690.00 rows=1 width=12)
(actual time=68.573..68.573 rows=0 loops=3)
Filter: ((x = ANY ('{1,2}'::integer[])) AND (y = '100'::double
precision))
Rows Removed by Filter: 333333
Planning Time: 0.264 ms
Execution Time: 74.887 ms
(8 rows)
> In my opinion, the general approach here is to stay with OR->ANY
> transformation at the parsing stage and invent one more way for
> picking an index by looking into the array and attempting to find a
> compound index.
> Having a shorter list of expressions, where uniform ORs are grouped
> into arrays, the optimizer will do such work with less overhead.
Looking at the current index generation code, implementing this approach
will require a lot of refactoring so that functions starting with
get_indexes do not rely on the current baserestrictinfo, but use only
the indexrestrictinfo, which is a copy of baserestrictinfo. And I think,
potentially, there may be complexity also with the equivalences that we
can get from OR expressions. All interesting transformations are
available only for OR expressions, not for ANY, that is, it makes sense
to try the last chance to find a suitable plan with the available OR
expressions and if that plan turns out to be better, use it.
--
Regards,
Alena Rybakina
Postgres Professional