Hi Lenny,

If you find the answer to this one please post it here, since it seems
quite a few interesting questions go unanswered in this group.

I'm no expert on this matter, but there's something hard to understand
indeed. The CPU cost (without API) makes sense if you think about the
following. In the middle of the graph, between 20 ms / 21 ms get / set
memcache calls there is a gap, about 600 ms in length. That is your
could executing, without RPCs, so that explains about 0.6s of the 2s
of CPU usage. Presumably, the remaining 1.4s would be code executing
after the last memcache get RPC, and so wouldn't be visible on the
timeline (perhaps you've got something slow there?).

Now, what doesn't make sense to me is the CPU + API grand total. There
are 66 ms of RPC API summed up at the RPC total. That makes sense,
it's the two datastore calls, a get and a query. But where does the
remaining API time come from? I thought API times only came from RPC
calls. It seems something else must be responsible for that. I'm
curious what.

BTW, can't you merge the memcache gets, sets and deletes in only three
RPC calls? E.g. memcache.get_multi()?



On Jun 27, 11:54 pm, Lenny Rachitsky <[email protected]> wrote:
> I'm having trouble understanding where the usage costs are coming
> from, specifically arround the CPU/API usage. I'm looking at the
> following app stats example:
>
> http://img.skitch.com/20100627-x6s7s988y2kg2at3kg3t6984ig.png
>
> To me this looks rather well optimized, except when you get to the
> "Grand Total" which has a huge cpu+api cost. Can anyone help me
> understand what could be causing this? My costs are growing quickly,
> and I'm considering some major revamping to deal with this situtation
> I can't explain.
>
> Any help would be much appreaciated,
> Lenny

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