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From Brett Wooldridge <brett.wooldri...@gmail.com>
Subject Re: SELECT query takes 5 secs, what can I do?
Date Tue, 15 Sep 2009 15:16:12 GMT
Because the query specified an id != ... (NOT equal), your specificity will
be extremely low (almost every row meets that criteria), therefore adding id
to the index will do little but increase the overhead of the index.
Similarly, it seems the archived flag would offer little in the way of
narrowing the result set -- unless the number of archived items is extremely
small compared to the total row count.

But you said something interesting, you said it is "looping through all the
messages".  That sounds like more of an algorithmic issue than a DB one.
For example, rather than looping and firing off 10000 select statements at 5
seconds each -- processing each message -- is there a way to devise 1 select
(or some similary small number) that returns 10000 rows that you can cursor
through and process?

Anytime I see a pattern like that -- looping over some X programatically and
running a query for each -- it is a red flag.  In the past I've converted
similar onesy-twosy patterns to bulk operations with generally one or two
orders of magnitude improvement.  I worked on a project where a "clean-up"
job was deleting data one row at a time based on some algorithm, but doing
it for thousands of rows.  It was taking hours.  After some thinking and
creative querying (and sub-querying) we were able to generate a bulk delete
that took less than two minutes.  It involved creating a temporary table
(this was mysql) with ids to be deleted (populated by a few choice queries)
and then doing a bulk delete based on a join with that table.

Anyway, the point is, rather than trying to optimize a query that is run
thousands of times, try to optimize the algorithm so that it doesn't need to
do that.

Just my thoughts.

-Brett


On Tue, Sep 15, 2009 at 10:02 PM, Andrew Bruno <andrew.bruno@gmail.com>wrote:

> Thank you all for the responses.
>
> The db runs as part of an applicatioon that sits on  a windows box, and we
> have many installed version around the world, so we don't control
> hardware,etc..  It only has a few db connections, and at the momement this
> particular instancee is looping through all the messages, and seeing whether
> they have been archived in the  cloud yet... And as you can imagine, at
> 5secs a message its taking  a long time.
>
> The message table has a bunch of other columns, and since I am using
> hibernate I need all columns... But I wonder if it would be quicker to
> select just the id column, and then load/select all columns using where
> id=.. Sounds crazy.. Kinda like 1+N selects...But any thoughts?
>
> As for the compund index, I thought it was not possible to add a pk index
> I.e. Id as part of a compound, but either way I will try.
>
> Also, if I do a count(messageid) instead, are there any other optimization
> tricks?
>
> Keep all thoughts coming, crazy or sound :)
>
> Appreciated
> Andrew
>
>
>
> -----Original Message-----
> From: Rick Hillegas <Richard.Hillegas@Sun.COM>
> Sent: Tuesday, 15 September 2009 10:32 PM
> To: Derby Discussion <derby-user@db.apache.org>
> Subject: Re: SELECT query takes 5 secs, what can I do?
>
> Hi Andrew,
>
> You might try adding more columns to your index so that it covers the
> whole WHERE clause:
>
> CREATE INDEX IDX_Message_MessageId ON ExchangeSync.Message (messageId,
> archived, id)
>
> Hope this helps,
> -Rick
>
>
>
> Andrew Bruno wrote:
> > Hello,
> >
> > I have a query that used to take 10secs to run, i.e.
> >
> > select * from Message m where
> > m.messageId='<7997716ED1AF3D47A35D74FA2CB610920255303F@somedomain.com>'
> > and m.id != 933927 and m.archived=1
> >
> > The Message table has around one million rows.
> >
> > I added the following index
> >
> > CREATE INDEX IDX_Message_MessageId ON ExchangeSync.Message (messageId)
> >
> > and now it takes 5secs.
> >
> > Is there anything else I can do?
> >
> > Should I add an index on the boolean "archived" column too?
> >
> > Any performance hints appreciated.
> >
> > Thanks
> > Andrew
> >
>
>
>

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