Re: [GENERAL] Query plan for Merge Semi Join

Peter J. Holzer wrote:
> [PostgreSQL 9.5.9 on x86_64-pc-linux-gnu, compiled by gcc (Debian
> 4.9.2-10) 4.9.2, 64-bit]
> 
> While investigating a performance issue, I found this query plan:
> 
> wds=> explain analyze
>       select facttablename, columnname, term, concept_id, t.hidden, language, register, c.id, canonicalname,
description,parent, type, r.sortorder
 
>       from term t, concept c, relation r
>       where facttablename='facttable_kon_eh' and columnname='arbeitsvolumen'
>         and exists (select 1 from facttable_kon_eh f where f.arbeitsvolumen=t.term  and thema in (values (E'E')))
>         and c.id=concept_id and r.child=concept_id;
>
╔════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╗
> ║                                                                                               QUERY PLAN
                                                                                  ║
 
>
╟────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╢
> ║ Nested Loop  (cost=22984.13..241822.98 rows=1 width=169) (actual time=667.608..3275.037 rows=6 loops=1)
                                                                                  ║
 
> ║   ->  Nested Loop  (cost=22983.70..241822.50 rows=1 width=154) (actual time=667.587..3274.972 rows=6 loops=1)
                                                                                  ║
 
> ║         ->  Merge Semi Join  (cost=22983.27..241819.04 rows=1 width=87) (actual time=667.559..3274.877 rows=6
loops=1)                                                                                ║
 
> ║               Merge Cond: ((t.term)::text = (f.arbeitsvolumen)::text)
                                                                                  ║
 
> ║               ->  Index Scan using term_term_idx on term t  (cost=0.56..206841.09 rows=18 width=87) (actual
time=667.467..2929.430rows=7 loops=1)                                                     ║
 
> ║                     Filter: (((facttablename)::text = 'facttable_kon_eh'::text) AND ((columnname)::text =
'arbeitsvolumen'::text))                                                                    ║
 
> ║                     Rows Removed by Filter: 3874190
                                                                                  ║
 
> ║               ->  Materialize  (cost=0.43..399167.10 rows=3548798 width=7) (actual time=0.086..295.708 rows=184791
loops=1)                                                                           ║
 
> ║                     ->  Nested Loop Semi Join  (cost=0.43..390295.10 rows=3548798 width=7) (actual
time=0.076..278.006rows=184791 loops=1)                                                            ║
 
> ║                           Join Filter: ((f.thema)::text = ('E'::text))
                                                                                  ║
 
> ║                           ->  Index Scan using facttable_kon_eh_arbeitsvolumen_idx on facttable_kon_eh f
(cost=0.43..337063.11rows=3548798 width=9) (actual time=0.052..199.733 rows=184791 loops=1) ║
 
> ║                           ->  Materialize  (cost=0.00..0.03 rows=1 width=32) (actual time=0.000..0.000 rows=1
loops=184791)                                                                           ║
 
> ║                                 ->  Result  (cost=0.00..0.01 rows=1 width=0) (actual time=0.001..0.001 rows=1
loops=1)                                                                                ║
 
> ║         ->  Index Scan using concept_pkey on concept c  (cost=0.43..3.45 rows=1 width=67) (actual time=0.011..0.012
rows=1loops=6)                                                                    ║
 
> ║               Index Cond: (id = t.concept_id)
                                                                                  ║
 
> ║   ->  Index Scan using relation_child_idx on relation r  (cost=0.43..0.47 rows=1 width=19) (actual
time=0.008..0.009rows=1 loops=6)                                                                   ║
 
> ║         Index Cond: (child = c.id)
                                                                                  ║
 
> ║ Planning time: 15.624 ms
                                                                                  ║
 
> ║ Execution time: 3275.341 ms
                                                                                  ║
 
>
╚════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════╝
> 
> That is almost certainly not ideal, but this is not my question.
> 
> My question is what does that merge semi join actually do?

A semi join returns only rows from one (the left) of the joining
relations that match rows in the other relation.

> In general a merge join needs two inputs sorted by the merge key. It
> walks both in parallel and joins matching lines. Correct?

Correct.

> The first input is the index scan. 
> 
> The second is the output of the materialize. Since we need only the
> column arbeitsvolumen this would be something like
>     select arbeitsvolumen from facttable_kon_eh where thema='E'
>     order by arbeitsvolumen;

Right, that's why a semijoin is used.
We are not actually interested in the VALUES 'E', it is just
used as a filter condition.

> So far so good. But there are a few things I don't understand:
> 
> Where does Rows Removed by Filter: 3874190 come from? The number doesn't
> match any count I can come up with: It is a bit larger than the total number
> of rows where term is not null but smaller than the total number of
> rows where the filter doesn't match. And it is much larger than the
> number of rows I would expect if the merge stopped once there could not
> be a possible match any more. And does it really check the filter
> condition even for rows that don't satisfy the merge condition? Of
> course it makes sense from a modularization point of view, but that's a
> lot of random accesses, most of which are unneccessary.

PostgreSQL uses an index scan so that the rows are returned in the sort
order necessary for the merge join.

It uses a filter to only return the interesting rows.

The number is indeed surprising.
I *assume* that it refers to numbers eliminate from the merge join result,
but that's only guessing.

> The materialize returns 184791 rows. This one I understand: There are 6
> non-null distinct values of arbeitsvolumen in facttable_kon_eh, and each
> appears 36958 times. 36958 * 5 + 1 = 184791. So it stops once it reaches
> the largest value. Although now I'm wondering how it knows that this is
> the largest value without scanning to the end).

I don't know the index definitions, but probably the index is
sorted in a way that this can be predicted.

Yours,
Laurenz Albe


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