I found the bug that leads to this in the mapreduce framework. The patch to 
fix is attached to the 
issue: http://code.google.com/p/appengine-mapreduce/issues/detail?id=154

On Thursday, 20 December 2012 15:34:52 UTC-6, Jason Collins wrote:
>
> We are using the "legacy" (non-PipelineAPI) version of the mapreduce 
> library: http://code.google.com/p/appengine-mapreduce/
>
> The issue is that we can only ever get one shard processing, even for 
> kinds that have >150,000 entities. We have tried different shard_count 
> configurations, e.g, 4, 16, 128, but always only one shard processing 
> entire dataset, which is very slow.
>
> I feel like I've missed a step (e.g., creating an index or something).
>
> Crossing my fingers that someone knows an offhand answer.
>
> Thanks,
> j
>

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