Re: Use extended statistics to estimate (Var op Var) clauses - Mailing list pgsql-hackers
From | Mark Dilger |
---|---|
Subject | Re: Use extended statistics to estimate (Var op Var) clauses |
Date | |
Msg-id | 5E98F67D-73C7-4E7B-AEDE-DBABB13C09B0@enterprisedb.com Whole thread Raw |
In response to | Re: Use extended statistics to estimate (Var op Var) clauses (Dean Rasheed <dean.a.rasheed@gmail.com>) |
Responses |
Re: Use extended statistics to estimate (Var op Var) clauses
Re: Use extended statistics to estimate (Var op Var) clauses Re: Use extended statistics to estimate (Var op Var) clauses |
List | pgsql-hackers |
> On Aug 11, 2021, at 5:08 AM, Dean Rasheed <dean.a.rasheed@gmail.com> wrote: > > This feels like rather an artificial example though. Is there any real > use for this sort of clause? The test generated random combinations of clauses and then checked if any had consistently worse performance. These cameup. I don't know that they represent anything real. What was not random in the tests was the data in the tables. I've gotten curious if these types of clauses (with columnscompared against themselves) would still be bad for random rather than orderly data sets. I'll go check.... testing.... Wow. Randomizing the data makes the problems even more extreme. It seems my original test set was actually playing to thispatch's strengths, not its weaknesses. I've changed the columns to double precision and filled the columns with random()data, where column1 gets random()^1, column2 gets random()^2, etc. So on average the larger numbered columns willbe smaller, and the mcv list will be irrelevant, since values should not tend to repeat. Over all queries, 47791 have better estimates after the patch, but 34802 had worse estimates after the patch (with the remaining17407 queries having roughly equal quality). The worst estimates are still ones that have a column compared to itself: better:0, worse:33: A <= B or A <= A or A <= A better:0, worse:33: A <= B or A = A or not A <> A better:0, worse:33: A <= B or A >= A or not A <> A better:0, worse:33: A <> B or A <= A better:0, worse:33: A <> B or A <= A or A <> A better:0, worse:33: A <> B or A <= A or A >= A better:0, worse:33: A <> B or A <= A or not A = A better:0, worse:33: A <> B or A > A or not A < A better:0, worse:33: A <> B or A >= A better:0, worse:33: A <> B or A >= A and A <= A better:0, worse:33: A = B or not A > A or not A > A better:0, worse:33: A >= B or not A <> A or A = A better:0, worse:39: B <= A or B <= B or B <= B better:0, worse:39: B <= A or B = B or not B <> B better:0, worse:39: B <= A or B >= B or not B <> B better:0, worse:39: B <> A or B <= B better:0, worse:39: B <> A or B <= B or B <> B better:0, worse:39: B <> A or B <= B or B >= B better:0, worse:39: B <> A or B <= B or not B = B better:0, worse:39: B <> A or B > B or not B < B better:0, worse:39: B <> A or B >= B better:0, worse:39: B <> A or B >= B and B <= B better:0, worse:39: B = A or not B > B or not B > B better:0, worse:39: B >= A or not B <> B or B = B But there are plenty that got worse without that, such as the following examples: better:25, worse:39: A < B and A < B or B > A better:10, worse:48: A < B and A < C better:10, worse:54: A < B and A < C or C > A I'll go test random data designed to have mcv lists of significance.... — Mark Dilger EnterpriseDB: http://www.enterprisedb.com The Enterprise PostgreSQL Company
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