Re: DB Performance decreases due to often written/accessed

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От Richard Huxton
Тема Re: DB Performance decreases due to often written/accessed
Дата
Msg-id 453791E6.4020600@archonet.com
обсуждение исходный текст
Ответ на DB Performance decreases due to often written/accessed table  ("Jens Schipkowski" <jens.schipkowski@apus.co.at>)
Ответы Re: DB Performance decreases due to often written/accessed table
Список pgsql-performance
Jens Schipkowski wrote:
> Hi,
>
> we've got performance problems due to repeating SELECT, UPDATE, DELETE,
> INSERT statements. This statements have to be executed every 10 seconds,
> but they run into a timeout.
> To obviate problems regarding to our Java Software and JDBC drivers, we
> put the repeating sequence of statements to a file more than 100k times
> (half a million statements) and executed "psql ourDB -f ourFile.sql -o
> /dev/null". To accelerate the occurence of the performance drop, we
> started 6 instances of this command.
> The performance drop occured after 10 minutes shifting the server to 0
> percent idle and 85 - 95 percent user.

After 10 minutes of what? Did the half-million statements complete? If
not, how many got completed? Were they all in separate transactions or
did you batch them? How ofternwere you vacuuming here?

> For tracing the statement which raised the load, we are using pg_locks,
> pg_stat_activity with current_query enabled. The responsible statement
> is the DELETE, it hangs until its canceled by timeout. The first run on
> an vacuumed DB took 300 - 600ms.
> In a second test we removed the DELETE statements to see wich statements
> also needs longer time by increasing the amount of data. After half an
> hour the SELECT statements timed out.
> An additional VACUUM - every 1 minute - does extend the timeout
> occurence by factor 5 - 6.

And running vacuum every 30 seconds does what?

> It does not sound professional, but the database seems to be aging by
> the increase of executed statements.

It sounds very likely if you aren't vacuuming enough or the tables are
growing rapidly.

> The Statements
> ---------------
> // normal insert - does not seem to be the problem - runtime is ok
> INSERT INTO tbl_reg(idreg,idtype,attr1,...,attr6,loc1,...,loc3,register)
> VALUES(nextval('tbl_reg_idreg_seq'),1,[attr],[loc],1);
>
> // select finds out which one has not an twin
> // a twin is defined as record with the same attr* values
> // decreases speed over time until timeout by postgresql
> SELECT *
> FROM tbl_reg reg
> WHERE register <> loc1 AND
>     idreg NOT IN
>         (
>         SELECT reg.idreg
>         FROM tbl_reg reg, tbl_reg regtwin
>         WHERE regtwin.register = 1 AND
>             regtwin.type <> 20 AND
>             reg.attr1 = regtwin.attr1 AND
>             reg.attr2 = regtwin.attr2 AND
>             reg.attr3 = regtwin.attr3 AND
>             reg.attr4 = regtwin.attr4 AND
>             reg.attr5 = regtwin.attr5 AND
>             reg.attr6 = regtwin.attr6 AND
>             reg.idreg <> regtwin.idreg AND
>             reg.register = 2
>         );
> I tried to optimize the seslect statement but the group by having count(*)
>> 1 solution is half as fast as this statement - relating to the query
> plan of EXPLAIN ANALYZE.

And what did EXPLAIN ANALYSE show here? I'm guessing you're getting time
increasing as the square of the number of rows in tbl_reg. So, if 50
rows takes 2500s then 100 rows will take 10000s. Now, if you had enough
RAM (or an index) I'd expect the planner to process the table in a
sorted manner so the query-time would increase linearly.

Oh, and you're doing one join more than you need to here (counting the
NOT IN as a join). You could get by with a LEFT JOIN and a test for
idreg being null on the right-hand table.

> // delete data without a twin
> // drastically decreases speed over time until timeout by postgresql
[snip delete doing the same query as above]
> The runtime of this statement increases until it will canceled by
> PostgreSQL.
>
> // the where clause of this update statement is normally build in java
> UPDATE tbl_reg SET loc1=2 WHERE idreg IN ('...',...,'...');
>
> The Table
> ---------------
> Tested with: 20.000, 80.000, 500.000 records
>
> CREATE TABLE tbl_reg
> (
>   idreg bigserial NOT NULL,
>   idtype int8 DEFAULT 0,

You can have more than 4 billion "types"?

>   attr1 int4,
>   attr2 int4,
>   attr3 varchar(20),
>   attr4 varchar(20),
>   attr5 int4,
>   attr6 varchar(140) DEFAULT ''::character varying,
>   loc1 int2 DEFAULT 0,
>   loc2 int2 DEFAULT 0,
>   loc3 int2 DEFAULT 0,
>   register int2 DEFAULT 1,
>   "timestamp" timestamp DEFAULT now(),

You probably want timestamp with time zone.

>   CONSTRAINT tbl_reg_pkey PRIMARY KEY (idreg)
> )
> WITHOUT OIDS;
>
> The Hardware
> ----------------
> Dual Xeon 3.2GHz Hyperthreading
> SCSI harddrives
> RAID and non-RAID tested
>
> We have the problem, that we cannot see any potential to improve SQL
> statements. Indexing the attr* columns seems not to be an solution,
> because the data mustn't be unique (twins) and changes really often so
> reindexing will took too long.

Eh? Why would an index force uniqueness? And are you sure that adding an
index makes updates too slow? What did your testing show as the
slow-down? I'd be tempted to put an index on attr1,attr2,attr5 (or
whichever combination provides the most selectivity) then make sure your
statistics are up to date (ANALYSE) and see if the plans change.

Of course, that's assuming your postgresql.conf has some reasonable
performance-related settings.

Oh, I'd also wonder whether, with "twin-ness" being such an important
concept it isn't its own thing and thus perhaps deserve its own table.

--
   Richard Huxton
   Archonet Ltd

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