From: | "Andrey V(dot) Lepikhov" <a(dot)lepikhov(at)postgrespro(dot)ru> |
---|---|
To: | Tomas Vondra <tomas(dot)vondra(at)enterprisedb(dot)com>, Teodor Sigaev <teodor(at)sigaev(dot)ru> |
Cc: | Tomas Vondra <tomas(dot)vondra(at)2ndquadrant(dot)com>, PostgreSQL Developers <pgsql-hackers(at)lists(dot)postgresql(dot)org> |
Subject: | Re: POC: GROUP BY optimization |
Date: | 2022-02-01 09:48:11 |
Message-ID: | 82114b8f-d3a1-ee58-f840-466e695f90c0@postgrespro.ru |
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Lists: | pgsql-hackers |
> On 7/22/21 3:58 AM, Tomas Vondra wrote:
> I've simplified the costing a bit, and the attached version actually
> undoes all the "suspicious" plan changes in postgres_fdw. It changes one
> new plan, but that seems somewhat reasonable, as it pushes sort to the
> remote side.
I tried to justify heap-sort part of the compute_cpu_sort_cost() routine
and realized, that here we may have a mistake.
After a week of efforts, I don't found any research papers on dependence
of bounded heap-sort time compexity on number of duplicates.
So, I suppose self-made formula, based on simple logical constructions:
1. We should base on initial formula: cost ~ N*LOG2(M), where M -
output_tuples.
2. Realize, that full representation of this formula is:
cost ~ N*LOG2(min{N,M})
3. In the case of multicolumn, number of comparisons for each next
column can be estimated by the same formula, but arranged to a number of
tuples per group:
comparisons ~ input * LOG2(min{input,M})
4. Realize, that for the case, when M > input, we should change this
formula a bit:
comparisons ~ max{input,M} * LOG2(min{input,M})
Remember, that in our case M << tuples.
So, general formula for bounded heap sort can be written as:
cost ~ N * sum(max{n_i,M}/N * LOG2(min{n_i,M})), i=1,ncols
where n_1 == N, n_i - number of tuples per group, estimated from
previous iteration.
In attachment - an implementation of this approach.
--
regards,
Andrey Lepikhov
Postgres Professional
Attachment | Content-Type | Size |
---|---|---|
bounded_heap_sort_fix.txt | text/plain | 3.1 KB |
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