The 429 is the mapreduce framework pushing back to the task queue because
there is not enough memory on the instance to handle the number of requests
it was given. This isn't necessarily a problem, and if there are no other
issues, can be safely ignored. However if it is occurring a lot, you could
improve performance by lowering "max-concurrent-requests" in your modules
configuration:
https://developers.google.com/appengine/docs/java/modules/#Java_Configuration

You should be able to see the progress of the shards in the lower right
panel of the UI. Provided all of the shards are making progress, you
probably have nothing to worry about.


On Mon, Jun 9, 2014 at 9:56 AM, Bill Speirs <[email protected]> wrote:

>
> I'm attempting to run a map-reduce job from Java. The job kicked off and
> started without a hitch, but now it's stuck waiting on ~34 tasks to finish.
> The job is stuck in the "ExamineStatusAndReturnResult" phase, after the
> ShardedJob phase. I see ~34 tasks in my queue all of the
> form: POST /mapreduce/workerCallback/map-*hex-numbers* They all say that
> the previous run returned a 429 Too Many Requests (
> http://tools.ietf.org/html/rfc6585#section-4). I'm guessing I've hit some
> kind of limit/quota, but I cannot tell what/where this quota is.
>
> How can I find out what is causing the 429 response code?
>
> Thanks!
>
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