Sorry to raise up this topic again, but I did not find any still
opened for my additional questions.

I read a lot of information here saying that the way we store/retrieve
information in Datastore is particularly designed for high performance
and scalability. I hear this a lot in GAE, and I am sure Google
handles a very huge volume of data which makes practically impossible
to run traditional queries (full of sub-queries, join and group-by) as
we all know in the SQL world.

However, I still lack the experience of such number, and the
traditional way could just fit enough to my purposes. As GAE is
already built in with Google's premises to scalability, I kind of see
a lack of guidance on that matter. For example, in a simple model
where I am running polls for different purposes, storing who+option
values only, how could I report the total of hits on an option? Should
I:

a) just get them all and let the python code to loop and manually do
my group by action
(if that's the case, then I think we have the same problem for the
scalability, as the cost to reach and get all data may be even
higher)

or

b) create another model to add the counter for every option
(and t that's the case, it sounds to me very bad principle to try to
build a data warehousing model to generate proper reports for every
single formatting I may need, meaning too many insert queries for a
single poll vote)?

Could we have a more official solution or example for such cases? I
think this kind of question will be addressed oftenly around here.
Just reminding that the objective is not to add "join" or "group-by"
features to GQL, but rather have concrete workarounds that will give
the same results. This is very important for models requiring
reporting services.

I really would like someone to enlighten me on this.

Thanks in advance.

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