Re: DELETE performance problem

From: Kris Kewley <kris(dot)kewley(at)gmail(dot)com>
To: Jerry Champlin <jchamplin(at)absolute-performance(dot)com>
Cc: Luca Tettamanti <kronos(dot)it(at)gmail(dot)com>, "<pgsql-performance(at)postgresql(dot)org>" <pgsql-performance(at)postgresql(dot)org>
Subject: Re: DELETE performance problem
Date: 2009-11-25 00:47:46
Message-ID: CA8B1F99-C0BD-4584-B89C-75BBA6A59DB7@gmail.com
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Even though the column in question is not unique on t2 could you not
index it? That should improve the performance of the inline query.

Are dates applicable in any way? In some cases adding a date field,
partitioning or indexing on that and adding where date>x days. That
can be an effective way to limit records searched.

Kris

On 24-Nov-09, at 9:59, "Jerry Champlin" <jchamplin(at)absolute-performance(dot)com
> wrote:

> You may want to consider using partitioning. That way you can drop
> the
> appropriate partition and never have the overhead of a delete.
>
> Jerry Champlin|Absolute Performance Inc.|Mobile: 303-588-2547
>
> -----Original Message-----
> From: pgsql-performance-owner(at)postgresql(dot)org
> [mailto:pgsql-performance-owner(at)postgresql(dot)org] On Behalf Of Luca
> Tettamanti
> Sent: Tuesday, November 24, 2009 6:37 AM
> To: pgsql-performance(at)postgresql(dot)org
> Subject: [PERFORM] DELETE performance problem
>
> Hello,
> I've run in a severe performance problem with the following statement:
>
> DELETE FROM t1 WHERE t1.annotation_id IN (
> SELECT t2.annotation_id FROM t2)
>
> t1 contains about 48M record (table size is 5.8GB), while t2
> contains about
> 60M
> record (total size 8.6GB). annotation_id is the PK in t1 but not in
> t2 (it's
> not even unique, in fact there are duplicates - there are about 20M
> distinct
> annotation_id in this table). There are no FKs on either tables.
> I've killed the query after 14h(!) of runtime...
>
> I've reproduced the problem using a only the ids (extracted from the
> full
> tables) with the following schemas:
>
> test2=# \d t1
> Table "public.t1"
> Column | Type | Modifiers
> ---------------+--------+-----------
> annotation_id | bigint | not null
> Indexes:
> "t1_pkey" PRIMARY KEY, btree (annotation_id)
>
> test2=# \d t2
> Table "public.t2"
> Column | Type | Modifiers
> ---------------+--------+-----------
> annotation_id | bigint |
> Indexes:
> "t2_idx" btree (annotation_id)
>
> The query above takes about 30 minutes to complete. The slowdown is
> not as
> severe, but (IMHO) the behaviour is strange. On a win2k8 with 8.3.8
> using
> procexp I see the process churning the disk and using more memory
> until it
> hits
> some limit (at about 1.8GB) then the IO slows down considerably. See
> this
> screenshot[1].
> This is exactly what happens with the full dataset.
>
> This is the output of the explain:
>
> test2=> explain analyze delete from t1 where annotation_id in (select
> annotation
> _id from t2);
> QUERY
> PLAN
>
> ---
> ---
> ----------------------------------------------------------------------
> ----
> ---------------------------------------------------------
> Hash Join (cost=1035767.26..2158065.55 rows=181605 width=6) (actual
> time=64339
> 5.565..1832056.588 rows=26185953 loops=1)
> Hash Cond: (t1.annotation_id = t2.annotation_id)
> -> Seq Scan on t1 (cost=0.00..661734.12 rows=45874812 width=14)
> (actual
> tim
> e=0.291..179119.487 rows=45874812 loops=1)
> -> Hash (cost=1033497.20..1033497.20 rows=181605 width=8) (actual
> time=6433
> 93.742..643393.742 rows=26185953 loops=1)
> -> HashAggregate (cost=1031681.15..1033497.20 rows=181605
> width=8) (a
> ctual time=571807.575..610178.552 rows=26185953 loops=1)
> -> Seq Scan on t2 (cost=0.00..879289.12 rows=60956812
> width=8)
> (actual time=2460.595..480446.581 rows=60956812 loops=1)
> Total runtime: 2271122.474 ms
> (7 rows)
>
> Time: 2274723,284 ms
>
>
> An identital linux machine (with 8.4.1) shows the same issue; with
> strace I
> see
> a lots of seeks:
>
> % time seconds usecs/call calls errors syscall
> ------ ----------- ----------- --------- --------- ----------------
> 90.37 0.155484 15 10601 read
> 9.10 0.015649 5216 3 fadvise64
> 0.39 0.000668 0 5499 write
> 0.15 0.000253 0 10733 lseek
> 0.00 0.000000 0 3 open
> 0.00 0.000000 0 3 close
> 0.00 0.000000 0 3 semop
> ------ ----------- ----------- --------- --------- ----------------
> 100.00 0.172054 26845 total
>
> (30s sample)
>
> Before hitting the memory "limit" (AS on win2k8, unsure about Linux)
> the
> trace
> is the following:
>
> % time seconds usecs/call calls errors syscall
> ------ ----------- ----------- --------- --------- ----------------
> 100.00 0.063862 0 321597 read
> 0.00 0.000000 0 3 lseek
> 0.00 0.000000 0 76 mmap
> ------ ----------- ----------- --------- --------- ----------------
> 100.00 0.063862 321676 total
>
>
> The machines have 8 cores (2 Xeon E5320), 8GB of RAM. Postgres data
> directory
> is on hardware (Dell PERC5) raid mirror, with the log on a separate
> array.
> One machine is running linux 64bit (Debian/stable), the other win2k8
> (32
> bit).
>
> shared_buffers = 512MB
> work_mem = 512MB
> maintenance_work_mem = 1GB
> checkpoint_segments = 16
> wal_buffers = 8MB
> fsync = off # Just in case... usually it's enabled
> effective_cache_size = 4096MB
>
> (the machine with win2k8 is running with a smaller shared_buffers -
> 16MB)
>
> Any idea on what's going wrong here?
>
> thanks,
> Luca
> [1] http://img10.imageshack.us/i/psql2.png/
>
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