From: | Viktor Leis <leis(at)in(dot)tum(dot)de> |
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To: | Craig Ringer <craig(at)2ndquadrant(dot)com> |
Cc: | Tom Lane <tgl(at)sss(dot)pgh(dot)pa(dot)us>, Albe Laurenz <laurenz(dot)albe(at)wien(dot)gv(dot)at>, "pgsql-hackers(at)postgresql(dot)org" <pgsql-hackers(at)postgresql(dot)org> |
Subject: | Re: Experimental evaluation of PostgreSQL's query optimizer |
Date: | 2015-12-22 08:28:03 |
Message-ID: | 56790993.7060805@in.tum.de |
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Lists: | pgsql-hackers |
On 12/22/2015 02:40 AM, Craig Ringer wrote:
> On 21 December 2015 at 23:57, Viktor Leis <leis(at)in(dot)tum(dot)de <mailto:leis(at)in(dot)tum(dot)de>> wrote:
>
>
>
> Please have a look at Figure 6 (page 6) in
> http://www.vldb.org/pvldb/vol9/p204-leis.pdf Disabling nested loop
> joins without index scan (going from (a) to (b)) results in great
> improvements across the board. And even more importantly, it avoids
> most of the cases where queries took unreasonably long and timed
> out. Basically this amounts to the being able to run the query on
> PostgreSQL or not.
>
>
> For that data, yes. But you're ignoring other important cases. Small or even 1-element lookup tables can be one where a nestloop over a seqscan turns out to be by far the fastest way to do the job.
> This can really add up if it's deep in a subplan that's excuted repeatedly, or if it's part of queries that get run very frequently on a busy OLTP system.
Ok here's what I presume to be the extreme case: Joining a large table
with a 1-entry table.
create table r1 (a int not null);
create table r2 (b int not null);
insert into r1 select 1 from generate_series(1,1000000);
insert into r2 values (1);
analyze r1;
analyze r2;
set enable_mergejoin to off;
set enable_nestloop to on;
set enable_hashjoin to off;
explain select count(*) from r1, r2 where r1.a = r2.b;
\timing
select count(*) from r1, r2 where r1.a = r2.b;
\timing
set enable_nestloop to off;
set enable_hashjoin to on;
explain select count(*) from r1, r2 where r1.a = r2.b;
\timing
select count(*) from r1, r2 where r1.a = r2.b;
\timing
I get 128.894ms vs. 183.724ms, i.e., a 43% slowdown for the hash
join. However, let me stress that this is really the extreme case:
- If the join has few matches (due to inserting a value different from
1 into r2), hash and nested loop join have pretty much the same
performance.
- If you add just one more row to r2, the hash join is faster by a
similar margin.
- Also if there is disk IO or network involved, I suspect that you
will see no performance differences.
There are many difficult tradeoffs in any query optimizer, but I do
not think picking nested loops where a hash join can be used is one of
those. To me this seems more like a self-inflicted wound.
--
Viktor Leis
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