From: | Szymon Guz <mabewlun(at)gmail(dot)com> |
---|---|
To: | CS DBA <cs_dba(at)consistentstate(dot)com> |
Cc: | "pgsql-performance(at)postgresql(dot)org" <pgsql-performance(at)postgresql(dot)org> |
Subject: | Re: Query tuning help |
Date: | 2011-10-11 18:03:45 |
Message-ID: | CAFjNrYt2JP-w731bkWhm_b3--mw8X+VD5PJ=pP5b_K=WGRucGQ@mail.gmail.com |
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Thread: | |
Lists: | pgsql-performance |
On 11 October 2011 19:52, CS DBA <cs_dba(at)consistentstate(dot)com> wrote:
> Hi all ;
>
> I'm trying to tune a difficult query.
>
> I have 2 tables:
> cust_acct (9million rows)
> cust_orders (200,000 rows)
>
> Here's the query:
>
> SELECT
> a.account_id, a.customer_id, a.order_id, a.primary_contact_id,
> a.status, a.customer_location_id, a.added_date,
> o.agent_id, p.order_location_id_id,
> COALESCE(a.customer_location_id, p.order_location_id) AS
> order_location_id
> FROM
> cust_acct a JOIN
> cust_orders o
> ON a.order_id = p.order_id;
>
> I can't get it to run much faster that about 13 seconds, in most cases it's
> more like 30 seconds.
> We have a box with 8 2.5GZ cores and 28GB of ram, shared_buffers is at 8GB
>
>
> I've tried separating the queries as filtering queries & joining the
> results, disabling seq scans, upping work_mem and half a dozen other
> approaches. Here's the explain plan:
>
> Hash Join (cost=151.05..684860.30 rows=9783130 width=100)
> Hash Cond: (a.order_id = o.order_id)
> -> Seq Scan on cust_acct a (cost=0.00..537962.30 rows=9783130
> width=92)
> -> Hash (cost=122.69..122.69 rows=2269 width=12)
> -> Seq Scan on cust_orders o (cost=0.00..122.69 rows=2269
> width=12)
>
> Thanks in advance for any help, tips, etc...
>
>
>
>
Hi,
two simple questions:
- do you really need getting all 9M rows?
- show us the table structure, together with index definitions
regards
Szymon
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