3 ms·
Aren't you still capping the throughput by the query rate of your connection pool though? By limiting that, you are limiting the application as a whole - i.e. y
by supermatt 6y ago
Aren't you still capping the throughput by the query rate of your connection pool though? By limiting that, you are limiting the application as a whole - i.e. your benchmark is bound by the speed of your database, and has (almost) nothing to do with the performance of a specific python implementation.
- arghwhat 6y agoOnly if there are spare resources left to saturate the connection pools, which didn't seem to be the case. If the system as a whole is well saturated, and the python processes dominate the system load with a DB load proportional to the requests served, then I don't think we would hit any external bottlenecks. The benchmarks performed are not that great (e.g., virtualized, same machine for all components, etc.), but I don't think the errors are enough to throw off the result. Note, of course, that such results are not universal, and some loads might perform better async.
- a1a1a1a1a1a1 6y agoIf the benchmark is bound by the database speed, wouldn't the expected result be that all implementations returned roughly the same number of requests per second?