One aspect that neither Ryan nor anybody else in this thread touched
upon is the entity hierarchy relationship. I understand that
transactions that involve multiple records are only honored among
entities that have the same GAE ancestry. This along with hints in the
documentation and presentations leads me to believe that records with
same ansestry are kept as close as possible (same machine, cluster,
data center). Again, my understanding is that ancestry is orthogonal
to entity kind so some Foos and some Bars might be in one location
because all of them have the same parent entity while other Foos and
Bars might migrare somewhere else.

Anyway, I would appreciate if Ryan or somebody else who is familiar
with the implementation elaborate further on whether today's
implementation uses the ancestry hints when it decides how to
partition the application data.

On Apr 22, 7:36 am, ryan <[email protected]> wrote:
> On Apr 22, 2:49 am, javaDinosaur <[email protected]> wrote:
>
>
>
> > Last year I noticed that GAE hosted my trial App within 30ms of my UK
> > location i.e. somewhere in Europe. Such automatic hosting geo affinity
> > is highly impressive but what if an App's admin is UK based but the
>
> you might be reading more into that number than it warrants. first,
> was that measurement on static files? or dynamic requests? we're more
> opportunistic about serving static files from multiple geographic
> locations and out of edge caches since, naturally, they're static
> files.
>
> second, users often see low latency because requests are picked up by
> a google frontend near the user's geographic location, then travel to
> and from the location serving the app over google's network, which is
> usually higher quality and less loaded than the commodity internet.
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