Le mardi 20 octobre 2009 06:30:26, Greg Smith a écrit :
> On Mon, 19 Oct 2009, Jeff Davis wrote:
> > On Mon, 2009-10-19 at 21:22 -0500, Kevin Grittner wrote:
> >> I'd bet accounts receivable applications often hit that.
> >> (Most payments on recent billings; a sprinkling on older ones.)
> >> I'm sure there are others.
> >
> > You worded the examples in terms of writes (I think), and we're talking
> > about read caching, so I still don't entirely understand.
>
> No, that part was fair. The unfortunate reality of accounts receivable is
> that reports run to list people who owe one money happen much more often
> than posting payments into the system does.
>
> > Also, the example sounds like you'd like to optimize across queries.
> > There's no mechanism for the planner to remember some query executed a
> > while ago, and match it up to some new query that it's trying to plan.
>
> Some of the use-cases here involve situations where you know most of a
> relation is likely to be in cache just because there's not much going on
> that might evict it. In any case, something that attempts to model some
> average percentage you can expect a relation to be in cache is in effect
> serving as a memory of past queries.
>
> > I'm not clear on the scenario that we're trying to improve.
>
> Duh, that would be the situation where someone wants optimizer hints but
> can't call them that because then the idea would be reflexively rejected!
>
> Looks like I should dust off the much more complicated proposal for
> tracking and using in-cache hit percentages I keep not having time to
> finish writing up. Allowing a user-set value for that is a lot more
> reasonable if the system computes a reasonable one itself under normal
> circumstances. That's what I think people really want, even if it's not
> what they're asking for.
Have you already some work in a git or somewhere ?
>
> --
> * Greg Smith gsmith@gregsmith.com http://www.gregsmith.com Baltimore, MD
>
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