What happens when an async put, results in a contention exception, after the request has ended, on Appengine with NDB? - google-app-engine

Question

Using ndb, lets say I put_async'd 40 elements, with #ndb.toplevel, wrote an output to user and ended the request, however one of those put_async's resulted in a contention exception, would the response be 500 or 200? Or lets say If it it a task, would the task get re-executed?
One solution is get_result()'ing all those 40 requests before the request ending and catching those exceptions -if they occur- but I'm not sure whether it will affect performance.

Answer 1

As far as I understand, using #ndb.toplevel causes the handler wait for all async operations to finish before exiting.
From the docs:
As a convenience, you can decorate the request handler with #ndb.toplevel. This tells the handler not to exit until its asynchronous requests have finished. This in turn lets you send off the request and not worry about the result. https://developers.google.com/appengine/docs/python/ndb/async#intro
So by adding #ndb.toplevel that the response doesn't actually get returned until after the async methods have finished executing. Using #ndb.toplevel removes the need to call get_result on all the async calls that were fired off (for convenience). So based on this, the request would still return 500 if the async queries failed, because all the async queries needed to complete before returning. Updated: below
If using a task (I assume you mean task queue) the task queue will retry the request if the request fails.
So your handler could be something like:
def get(self):
deferred.defer(execute_stuff_in_background, param,param1)
template.render(...)
and execute_stuff_in_background would do all the expensive puts once the handler had returned. If there was a contention issue in the task, your original handler would still return 200.
If you suspect there is going to be a contention issue, perhaps consider sharding or using a fork-join queue implementation to handle the writes (see implementation here: http://www.youtube.com/watch?v=zSDC_TU7rtc#t=41m35)
Edit: Short answer
The request will fail (return 500) if the async requests fail, because #ndb.toplevel waits
for all results to finish before exiting.
Updated:Having looked at #alexis's answer below, I re-ran my original test (where I turned off datastore writes and called put_async in the handler decorated with #ndb.toplevel), the response raises 500 intermittently (I assume this depends on execution time). Based on this and #alexis's answer below, don't expect the result to be 500 if an async task throws an exception and the calling function is decorated with #ndb.toplevel

Answer 2

That's odd, I use toplevel and expect the opposite behavior. And that's what I observe. Did something change since the first answer to this question?
As the doc says:
This in turn lets you send off the request and not worry about the
result.
You can try the following unittest (using testbed):
#ndb.tasklet
def raiseSomething():
yield ndb.Key('foo','bar').get_async()
raise Exception()
#ndb.toplevel
def callRaiseSomething():
future = raiseSomething()
return "hello"
response = callRaiseSomething()
self.assertEqual(response, "hello")
This test passes. NDB logs a warning: "suspended generator raiseSomething(tests.py:90) raised Exception()", but it does not re-raise the exception.
ndb.toplevel only waits for the RPCs, but does nothing of the actual result.
If your decorated function is itself a tasklet, it will call get_result() on it first. At this point exceptions will be raised. Then it will wait for remaining 'orphaned' RPCs, and will only log something if an exception is raised.
So my response is: the request will succeed (return 200)