R
Riverside Software
Guest
Just ran a quick test (for what it's worth), and wanted to see the behavior ; DB with a single 400 Mb table and 100 Mb index, started with : proserve xx -Mn 20 -n 20 -B 150000 -prefetchDelay -prefetchNumRecs 100 -lruskips 100 proserve xx -m3 -Mpb 1 -Mi 1 -Ma 5 -S 30000 -minport 20000 -maxport 21000 -Mm 8192 proserve xx -m3 -Mpb 5 -Mi 1 -Ma 1 -S 30001 -minport 20000 -maxport 21000 -Mm 8192 Batch clients always running a for each table, then quitting. Connected with -db xx -H localhost -S 3000x -Mm 8192 First execution is shared-memory to load the entire table in -B, then a second one in shared memory to verify there are no more DB reads. 35 seconds to execute the procedure. Then followed by one thread, first on first broker, then on second broker. Results are consistent on each run (20 seconds in my case, fun result as is twice as fast as shared-memory mode). Then 5 parallel threads, also on first broker then on second one, and results are quite different : * With 5 clients per server, each session run in around 1 minutes 40 seconds. Server is attached to one CPU, and this CPU is running at 100%. Promon shows 380k reads per second. * With 1 client per server, each session run in around 1 minute and 25 second. Promon shows 450k reads per second. Only 2 CPU, and the process are usually running on different CPU (according to top) --> 1 to 1.2 ratio That was executed on a small server, with only 2 quick CPU. Client sessions were competing with server processes for CPU. The 5 servers were also competing for CPU. When running client sessions on a different server : * 1 minute 35 with 5 clients per server (and only one CPU working). 400k reads in promon * 45 seconds with 1 client per server (and two CPU working). 750k records in promon --> 1 to 2.1 ratio I'll redo the test with the QA server, where I could leverage the 24 cores and run more sessions in parallel. As with any bench done in less than an hour, that won't reflect reality. But at least it gives some figures.
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