I just added this comment, which explains why the GAE result is
anemic. The GAE test was flawed to the point of irrelevance;
hopefully the author will retest with a realistic scenario.
My comment:
---
It is not quite correct to say that the problem with GAE is related to sharding.
As you know, you can only perform transactions within a single entity
group. The bottleneck is not that this restricts processing to a
single machine; the bottleneck is that each entity group (and thus
each transaction) has a single optimistic timestamp. By placing your
entire data structure in a single entity group, you have guaranteed
that *every single operation* contends for a single optimistic lock in
the database.
The analogue to an RDBMS is not condensing all requests to a single
machine; the analogue is putting an update of the exact same piece of
data in *every* transaction. This simply won't work.
To properly implement the GAE test, you can't just add sharding; you
must eliminate the transaction requirement and allow every piece of
data to live in its own entity group. Transactions in GAE are useful
in a few isolated cases but they are NOT equivalent to RDBMS
transactions and cannot be treated as such. Transactions as you are
accustomed to are not a supported feature of the GAE datastore.
I'm very interested in how GAE stacks up. You shouldn't need to
rewrite your tests to support sharding in any explicit way, just
remove the parent references and get rid of any transaction-related
code. This doesn't offer the same consistency requirements as the
other systems, but GAE doesn't support those kinds of consistency
requirements.
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On Fri, May 28, 2010 at 2:39 AM, Peter Knego pe...@knego.net wrote:
Has anyone read this?
http://highscalability.com/blog/2010/5/26/end-to-end-performance-study-of-cloud-services.html
Any thoughts on why App Engine seems to be slow?
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