From: Tom Lane <tgl@sss.pgh.pa.us>
To: Mike Broers <mbroers@gmail.com>
cc: pgsql-performance@postgresql.org
Subject: Re: wildcard text filter switched to boolean column,
 performance is way worse
In-reply-to: 
 <CAB9893ibPu+ABPfsxpL45GbcHZx4Heg4EndzuE=QPKHunNY68Q@mail.gmail.com>
References: 
 <CAB9893ibPu+ABPfsxpL45GbcHZx4Heg4EndzuE=QPKHunNY68Q@mail.gmail.com>
Comments: In-reply-to Mike Broers <mbroers@gmail.com>
 message dated "Tue, 07 Jul 2015 10:40:48 -0500"
Date: Tue, 07 Jul 2015 12:02:49 -0400
Message-ID: <27074.1436284969@sss.pgh.pa.us>
Precedence: bulk
Sender: pgsql-performance-owner@postgresql.org

Mike Broers <mbroers@gmail.com> writes:
> I had a query that was filtering with a wildcard search of a text field for
> %SUCCESS%. The query took about 5 seconds and was running often so I wanted
> to improve it.  I suggested that the engineers include a new boolean column
> for successful status.  They implemented the requested field, but the query
> that filters on that new column runs very long (i kill it after letting it
> run for about an hour).  Can someone help me understand why that is the
> case and how to resolve it?

It's hashing the subplan output in the first case and not the second:

> Seq Scan on lead  (cost=130951.81..158059.21 rows=139957 width=369) (actual
> time=4699.619..4699.869 rows=1 loops=1)
>     Filter: ((NOT (hashed SubPlan 1)) AND (("ReferenceNumber")::text <>
> ''::text) AND ((NOT (hashed SubPlan 2)) OR (NOT (hashed SubPlan 3))))
                                                   ^^^^^^^^^^^^^^^^
vs

>   Seq Scan on lead  (cost=85775.78..9005687281.12 rows=139957 width=369)
>     Filter: ((NOT (hashed SubPlan 1)) AND (("ReferenceNumber")::text <>
> ''::text) AND ((NOT (hashed SubPlan 2)) OR (NOT (SubPlan 3))))
                                                   ^^^^^^^^^

Presumably, the new more-accurate rows count causes the planner to realize
that the hash table will exceed work_mem so it doesn't choose to hash ...
but for your situation, you'd rather it did, because what you're getting
instead is a Materialize node that spills to disk (again, because the data
involved exceeds work_mem) and that's a killer for this query.  You should
be able to get back the old behavior if you raise work_mem enough.

Another idea you might think about is changing the OR'd IN conditions
to a single IN over a UNION ALL of the subselects.  I'm not really sure if
that would produce a better plan, but it's worth trying if it wouldn't
require too much app-side contortion.

			regards, tom lane


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