> > *Case 1:* > Number of Tables in db.py: ~100 (all with migrate=False) > No. of concurrent requests: 1 > Time taken per request: 900 ms > > *Case 2:* > Number of Tables in db.py: ~100 (all with migrate=False) > No. of concurrent requests: 25 > Time taken per request: 4440 ms >
For apples to apples comparison, you should look at the "(mean, across all concurrent requests)" value. In case #2, that is only 177.6 ms. With multiple concurrent requests, of course each request is going to take longer to complete from start to finish (each thread is sharing system resources, so can't run as fast as when only a single thread is processing a request). However, because the requests are being processed in parallel, you have to divide the overall average time per request by the concurrency level to get the true time spent on each request (i.e., if 50 requests take an average of 4.4 seconds per request processed 25 at a time, then the true time spent on each request is 4.4 seconds / 25 = 177.6 ms). This is the number that should be compared to the single request case. Alternatively, you can just compare the total test time in both cases (assuming you ran the same number of total requests in each case). Anthony -- Resources: - http://web2py.com - http://web2py.com/book (Documentation) - http://github.com/web2py/web2py (Source code) - https://code.google.com/p/web2py/issues/list (Report Issues) --- You received this message because you are subscribed to the Google Groups "web2py-users" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. For more options, visit https://groups.google.com/groups/opt_out.
