On Thu, 2004-10-14 at 16:57 -0700, Josh Berkus wrote:
> <lots of good stuff clipped>
> > If you draw a graph of speedup (y) against cache size as a
> > % of total database size, the graph looks like an upside-down "L" - i.e.
> > the graph rises steeply as you give it more memory, then turns sharply at a
> > particular point, after which it flattens out. The "turning point" is the
> > "sweet spot" we all seek - the optimum amount of cache memory to allocate -
> > but this spot depends upon the worklaod and database size, not on available
> > RAM on the system under test.
> Hmmm ... how do you explain, then the "camel hump" nature of the real
> performance? That is, when we allocated even a few MB more than the
> "optimum" ~190MB, overall performance stated to drop quickly. The result is
> that allocating 2x optimum RAM is nearly as bad as allocating too little
> (e.g. 8MB).
> The only explanation I've heard of this so far is that there is a significant
> loss of efficiency with larger caches. Or do you see the loss of 200MB out
> of 3500MB would actually affect the Kernel cache that much?
In a past life there seemed to be a sweet spot around the
working set. Performance went up until you got just a little larger
the cache needed to hold the working set and then went down. Most of
the time a nice looking hump. It seems to have to do with the
not increasing your hit ratio but increasing the amount of work to get a
hit in cache. This seemed to be independent of the actual database
software being used. (I observed this running Oracle, Informix, Sybase
> Anyway, one test of your theory that I can run immediately is to run the exact
> same workload on a bigger, faster server and see if the desired quantity of
> shared_buffers is roughly the same. I'm hoping that you're wrong -- not
> because I don't find your argument persuasive, but because if you're right it
> leaves us without any reasonable ability to recommend shared_buffer settings.
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