Tim Peters wrote:
I don't know. The last time I know of that anyone tried to use these was in
2003, when Jeremy & I were studying alternative cache designs.
Yeah, I saw Jeremy's wiki page about that. It seemed you guys made a lot of progress, did anything get taken forward to a release?
stats.py told me I had a 98% hit rate, while http://www.zope.org/Wikis/ZODB/HowtoTraceZEOCache/trace.html says the theoretical maximum is 90%.
I can't read "90% is probably close to the theoretical maximum" that way. Sounds like nonsense anyway, if read literally. IIRC, 90% was actually just the largest "theoretically perfect" hit rate we measured on actual trace files from various Zope sites. A hit rate arbitrarily close to 100% is certainly possible.
OK, that makes me think that maybe simul.py has just got out of sync, it seems to have attracted less attention...
Try various sizes and judge results against whatever function you're trying to optimize.
Urg. simul.py was supposed to provide an alternative *schniff*
The obvious one is more disk space required. If you use a persistent ZEO cache, then cache verification time at ZEO client connect/reconnect times may also increase proportionately. Other than those, bigger is probably better, and the 20MB (? whatever) default size is much smaller than usually desirable (it's left over from days when typical disks were much smaller than they are now). Try, e.g., 200MB. Like the results better? Iterate.
Note that while the ZEO cache is disk-based, it does have in-memory index structures taking space proportional to the number of objects cached. I suppose that if the cache file were big enough to hold millions of objects, the RAM consumed by those indices could become burdensome. Haven't heard of that happening in real life, though.
OK, so what would you recommend for acheiving best "zodb speed" (ie: don't care about disk or memory usage, unless they affect speed) on ZEO client servers that are dual processor boxes and have one zeo client per processor? How about 2 clients per processor?
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