Thanks Alex. Yes, they are writable; however, I can't find any errors in
the logs, other than the name errors themselves (and those occur right
after "Final result for job … is 'success'). The mapreduce code gets
through files.finalize(filename), but blows up in get_blob_key because the
filename is no shorter than before.

Ben, I wish I could do that, the mapreduce lib is creating
a __BlobFileIndex__
datastore key using this filename as the id, so I don't know what sort of
change I could make there. Unfortunately it's not something I'm storing as
a property on my own model.

Jamie

On Tue, Mar 5, 2013 at 4:48 PM, Alex Burgel <[email protected]> wrote:

> On Friday, March 1, 2013 11:25:17 PM UTC-5, Jamie Niemasik wrote:
>
>> Some of the filenames are 288 bytes long, while some are 992. The M/R
>> spec name and id in each case is nearly the same and is very short; I don't
>> see where this variance comes from.
>>
>
> Have you noticed if the long file names contain the word 'writable' at the
> beginning?
>
> If so, it might similar to an issue that I had (my issue was with google
> storage, not blobstore, but their APIs are similar):
>
>
> https://groups.google.com/forum/?fromgroups=#!topic/app-engine-pipeline-api/vfWakN0NKSw
>
> It seems that when a file is writable, its in a special state with a
> filename that is very long. When the MR job finishes, it finalizes the file
> and gets another filename that is shorter. My issue had to do with the MR
> job not finishing properly. Some of my code was throwing exceptions but it
> wasn't causing the job to finalize properly and therefore not getting the
> shorter filename.
>
> I would take a look at your logs to see if there are any errors. They may
> be causing the MR job to not finish properly and then return unfinalized
> filenames.
>
> --Alex
>
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