Re: Automatic function replanning

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От Bruce Momjian
Тема Re: Automatic function replanning
Дата
Msg-id 200512222120.jBMLKvZ29992@candle.pha.pa.us
обсуждение исходный текст
Ответ на Re: Automatic function replanning  ("Jim C. Nasby" <jnasby@pervasive.com>)
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We need invalidation anyway, so I don't see why an intermediate step
makes sense.

---------------------------------------------------------------------------

Jim C. Nasby wrote:
> Well, not just rows; total tuples, both base heap and index. ISTM that
> would be a better metric than just plain rows read out of base or rows
> returned.
> 
> Depending on how far down this road we want to go, this would allow for
> detecting what parameter values require different query plans, and then
> using different query plans for different sets of values. Simply
> invalidating the cached plan means you could potentially end up needing
> to re-plan very frequently. But given the current speed of our
> optimizer, it's probably not worth going to this extent.
> 
> Another concern I have is: is cardinality the only metric we need to
> look at when deciding to re-plan or are there others?
> 
> In either case, my guess is that tracking the info needed to make this
> idea happen is probably much easier than doing automatic plan
> invalidation based on cardinality, so it would be a useful interum step.
> But if we could actually get cardinality invalidation into 8.2, I'd say
> put the effort into that...
> 
> On Thu, Dec 22, 2005 at 03:14:09PM -0500, Bruce Momjian wrote:
> > 
> > Oh, OK, so you are logging prepared queries where the plan generates a
> > significantly different number of rows from previous runs.  I am not
> > sure why that is better, or easier, than just invalidating the  cached
> > plan if the cardinality changes.
> > 
> > ---------------------------------------------------------------------------
> > 
> > Jim C. Nasby wrote:
> > > On Wed, Dec 21, 2005 at 11:00:31PM -0500, Bruce Momjian wrote:
> > > > > Track normal resource consumption (ie: tuples read) for planned queries
> > > > > and record parameter values that result in drastically different
> > > > > resource consumption.
> > > > > 
> > > > > This would at least make it easy for admins to identify prepared queries
> > > > > that have a highly variable execution cost.
> > > > 
> > > > We have that TODO already:
> > > > 
> > > >     * Log statements where the optimizer row estimates were dramatically
> > > >       different from the number of rows actually found?
> > > 
> > > Does the stored plan also save how many rows were expected? Otherwise
> > > I'm not sure how that TODO covers it... If it does then please ignore my
> > > ramblings below. :)
> > > 
> > > My idea has nothing to do with row estimates. It has to do with the
> > > amount of work actually done to perform a query. Consider this example:
> > > 
> > > CREATE TABLE queue (status char NOT NULL, queue_item text NOT NULL);
> > > CREATE INDEX queue__status ON queue (status);
> > > 
> > > Obviously, to process this you'll need a query like:
> > > SELECT * FROM queue WHERE status='N' -- N for New;
> > > 
> > > Say you also occasionally need to see a list of items that have been
> > > processed:
> > > SELECT * FROM queue WHERE status='D' -- D for Done;
> > > 
> > > And let's say you need to keep done items around for 30 days.
> > > 
> > > Now, if both of these are done using a prepared statement, it's going to
> > > look like:
> > > 
> > > SELECT * FROM queue WHERE status='?';
> > > 
> > > If the first one to run is the queue processing one, the planner will
> > > probably choose the index. This means that when we're searching on 'N',
> > > there will be a fairly small number of tuples read to execute the query,
> > > but when searching for 'D' a very large number of tuples will be read.
> > > 
> > > What I'm proposing is to keep track of the 'normal' number of tuples
> > > read when executing a prepared query, and logging any queries that are
> > > substantially different. So, if you normally have to read 50 tuples to
> > > find all 'N' records, when the query looking for 'D' records comes along
> > > and has to read 5000 tuples instead, we want to log that. Probably the
> > > easiest way to accomplish this is to store a moving average of tuples
> > > read with each prepared statement entry.
> > > -- 
> > > Jim C. Nasby, Sr. Engineering Consultant      jnasby@pervasive.com
> > > Pervasive Software      http://pervasive.com    work: 512-231-6117
> > > vcard: http://jim.nasby.net/pervasive.vcf       cell: 512-569-9461
> > > 
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> > > 
> > 
> > -- 
> >   Bruce Momjian                        |  http://candle.pha.pa.us
> >   pgman@candle.pha.pa.us               |  (610) 359-1001
> >   +  If your life is a hard drive,     |  13 Roberts Road
> >   +  Christ can be your backup.        |  Newtown Square, Pennsylvania 19073
> > 
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> > 
> 
> -- 
> Jim C. Nasby, Sr. Engineering Consultant      jnasby@pervasive.com
> Pervasive Software      http://pervasive.com    work: 512-231-6117
> vcard: http://jim.nasby.net/pervasive.vcf       cell: 512-569-9461
> 
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--  Bruce Momjian                        |  http://candle.pha.pa.us pgman@candle.pha.pa.us               |  (610)
359-1001+  If your life is a hard drive,     |  13 Roberts Road +  Christ can be your backup.        |  Newtown Square,
Pennsylvania19073
 


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