Re: Question about disk IO an index use and seeking advice - Mailing list pgsql-performance

From Matthew Wakeling
Subject Re: Question about disk IO an index use and seeking advice
Date
Msg-id Pine.LNX.4.64.0804241610300.13221@aragorn.flymine.org
Whole thread Raw
In response to Question about disk IO an index use and seeking advice  ("Nikolas Everett" <nik9000@gmail.com>)
List pgsql-performance
On Thu, 24 Apr 2008, Nikolas Everett wrote:
> The setup is kind of a beast.

No kidding.

> When I run dstat I see only around 2M/sec and it is not consistent at all.

Well, it is having to seek over the disc a little. Firstly, your table may
not be wonderfully ordered for index scans, but goodness knows how long a
CLUSTER operation might take with that much data. Secondly, when doing an
index scan, Postgres unfortunately can only use the performance equivalent
of a single disc, because it accesses the pages one by one in a
single-threaded manner. A large RAID array will give you a performance
boost if you are doing lots of index scans in parallel, but not if you are
only doing one. Greg Stark has a patch in the pipeline to improve this
though.

> When I do a similar set of queries on the hardware raid I see similar
> performance except the numbers are both more than doubled.

Hardware RAID is often better than software RAID. 'Nuff said.

> Here is the explain output for the queries:

EXPLAIN ANALYSE is even better.

> Sort  (cost=16948.80..16948.81 rows=1 width=10)"
>   Sort Key: count(*)"
>   ->  HashAggregate  (cost=16948.78..16948.79 rows=1 width=10)"
>         ->  Index Scan using date_idx on bigtable (cost=0.00..16652.77 rows=59201 width=10)"
>               Index Cond: (date > '2008-04-21 00:00:00'::timestamp without time zone)"

That doesn't look like it should take too long. How long does it take?
(EXPLAIN ANALYSE, in other words). It's a good plan, anyway.

> So now the asking for advice part.  I have two questions:
> What is the fastest way to copy data from the smaller table to the larger
> table?

INSERT INTO bigtable (field1, field2) SELECT whatever FROM staging_table
        ORDER BY staging_table.date

That will do it all in Postgres. The ORDER BY clause may slow down the
insert, but it will certainly speed up your subsequent index scans.

If the bigtable isn't getting any DELETE or UPDATE traffic, you don't need
to vacuum it. However, make sure you do vacuum the staging table,
preferably directly after moving all that data to the bigtable and
deleting it from the staging table.

> Can someone point me to a good page on partitioning? My
> gut tells me it should be better, but I'd like to learn more about why.

You could possibly not bother with a staging table, and replace the mass
copy with making a new partition. Not sure of the details myself though.

Matthew

--
Me... a skeptic?  I trust you have proof?

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