"Kevin Grittner" <kevin.gritt...@wicourts.gov> wrote: > Performance tests to follow in a day or two. I'm looking to beg another week or so on this to run more tests. What I can have by the end of today is pretty limited, mostly because I decided it made the most sense to test this with big complex databases, and it just takes a fair amount of time to throw around that much data. (This patch didn't seem likely to make a significant difference on smaller databases.) My current plan is to test this on a web server class machine and a distributed application class machine. Both database types have over 300 tables with tables with widely ranging row counts, widths, and index counts. It would be hard to schedule the requisite time on our biggest web machines, but I assume an 8 core 64GB machine would give meaningful results. Any sense what numbers of parallel jobs I should use for tests? I would be tempted to try 1 (with the -1 switch), 8, 12, and 16 -- maybe keep going if 16 beats 12. My plan here would be to have the dump on one machine, and run pg_restore there, and push it to a database on another machine through the LAN on a 1Gb connection. (This seems most likely to be what we'd be doing in real life.) I would run each test with the CVS trunk tip with and without the patch applied. The database is currently 1.1TB. The application machine would have 2 cores and about 4GB RAM. I'm tempted to use Milwaukee County's database there, as it has the most rows per table, even though some of the counties doing a lot of document scanning now have bigger databases in terms of disk space. It's 89GB. I'd probably try job counts starting at one and going up by one until performance starts to drop off. (At one I would use the -1 switch.) In all cases I was planning on using a "conversion" postgresql.conf file, turning off fsync, archiving, statistics, etc. Does this sound like a sane approach to testing whether this patch actually improves performance? Any suggestions before I start this, to ensure most meaningful results? -Kevin
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