I have a simple prototype of a service running successfully on app
engine, using the python runtime. For the most part, things are
working well. However, I'm continually getting warnings on the
dashboard about how my requests are about to exceed their CPU quota.
This is a bit mystifying since I haven't found any documentation
anywhere describing a per-request CPU quota - is it referring to the
overall CPU quota?
I've already profiled my services using cProfile and see no obvious
bottlenecks in my python, other than the inherent inefficiency of the
python protocol buffers implementation used by the datastore - and
regardless, my services' python only appears to be consuming a few
hundred milliseconds of CPU time. Almost all of the CPU time consumed
seems to be from the datastore.
Is there some way I can profile the datastore requests to figure out
what it is about my entities that causes them to take so much time to
submit? I'm storing relatively simple expando entities in batches of
6-8 at a time and this is consuming over ten seconds worth of API CPU
time per batch, and I really can't come up with a plausible
explanation for why this would be so expensive. Are there some good
rules of thumb or guidelines for how I can avoid spending large
amounts of CPU time to store data?
For reference, here is how I have defined the entity:
class Event(db.Expando):
playerId = db.IntegerProperty()
sessionId = db.IntegerProperty()
timeMs = db.IntegerProperty()
eventType = db.StringProperty()
And here is what a sample entity looks like:
{
"playerId": 1115,
"eventType": "BotchedCombo",
"sessionId": 233,
"timeMs": 261986,
"eventData": 4,
"playerX": -523,
"playerY": 248,
"levelName": "drowned_queen_arena"
}
I simply cannot figure out how it would take so much time to store
these entities. I considered the possibility that it was overhead from
indexing all my expando values, but the little documentation I did
find suggested that expando values are not indexed, in which case the
cost of indexing these entities should be trivial.
Thanks in advance,
-kg
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