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admin | Getting An Ex Back | 23.10.2015
Stack Overflow is a community of 4.7 million programmers, just like you, helping each other. I'm seeing very poor performance when fetching multiple keys from Memcache using ndb.get_multi() in App Engine (Python). This is interesting, but isn't really a solution for me since the set of items I need to fetch isn't static. Update: Out of interest I also profiled this with all the app engine performance settings increased to maximum (F4 instance, 2400Mhz, dedicated memcache). This means that, if you really want to, you can avoid ndb and instead fetch and deserialize from memcache directly.
So ndb takes 1ms per entity fetched, even if the entity has one single property and is in memcache.

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All these measurements are on the default App Engine production config (F1 instance, shared memcache). I profiled the code line by line using time.clock() calls and I see roughly similar numbers (3x faster than what I see in AppStats, but still very slow). The reason things are so incredibly slow is partly deserialization (explains about 30% of the time), and the rest seems to be overhead in ndb's task queue implementation. In my test case with 500 small entities, this gives a massive 2.5x speedup (650ms vs 1600ms on an F1 instance in production, or 200ms vs 500ms on an F4 instance).

Note the timings don't match appstats because they're running on an F1 instance, so real time is 3x clock time.
On the faster instance the App Stats timings now match my time.clock() profile (so 500ms to fetch 500 small objects instead of 1500ms). This is a serious practical limitation: if you want to maintain reasonable latency, you can't fetch more than ~100 entities of any kind when handling a user request on an F1 instance. At least it seems so based on my use case of a lot of get_multi calls for small objects, with a high expected memcache hit rate.

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