I reduced the number of shards to 1, and it uses an ascending index,
but still only 44399 out of 500k+ entities are processed. Confused!

Ben


On Jul 7, 1:02 pm, Ben Nevile <[email protected]> wrote:
> Just found the thread that talks about needing the descending index
> for __key__ --- definitely seems like something that should be added
> to the documentation!
>
> Ben
>
> On Jul 7, 12:56 pm, Ben Nevile <[email protected]> wrote:
>
>
>
> > I have a job with 8 shards but only one of the shards is processing
> > any entities. Think this is related?
>
> > mapreduce_id=159013376839436
>
> > Ben
>
> > On Jun 16, 8:28 am, "Nick Johnson (Google)" <[email protected]>
> > wrote:
>
> > > Hi Jason,
>
> > > It's possible to do that right now. You simply need to define your own
> > > InputReader - see the existing ones for examples 
> > > how:http://code.google.com/p/appengine-mapreduce/source/browse/trunk/pyth...
>
> > > The best option is probably to extend the existing DatastoreInputReader, 
> > > and
> > > override the split_input method.
>
> > > -Nick Johnson
>
> > > On Wed, Jun 16, 2010 at 4:17 PM, Jason C <[email protected]> 
> > > wrote:
> > > > Nick,
>
> > > > It would be a great feature to allow us (developers) to define a
> > > > custom partitioning function for the shards - unless you guys have
> > > > some better magic in mind.
>
> > > > It is very normal for us to see very poor distribution across our
> > > > shards in practise - in fact, we've only seen poor distributions.
>
> > > > j
>
> > > > On Jun 15, 8:04 am, "Nick Johnson (Google)" <[email protected]>
> > > > wrote:
> > > > > Hi Jason,
>
> > > > > The current implementation of the datastore mapper uses 
> > > > > lexicographical
> > > > > sharding over keys to assign datastore shards. Unfortunately, this can
> > > > lead
> > > > > to very inconsistent shard sizes, as you observe.
>
> > > > > -Nick Johnson
>
> > > > > On Fri, Jun 11, 2010 at 4:17 PM, Jason C <[email protected]>
> > > > wrote:
> > > > > > We've been usingMapReducefor App Engine for a couple of different
> > > > > > jobs.
>
> > > > > > Typically, we use 8 shards (the default), but it seems that only 3,
> > > > > > sometime 4, of the shards have any items in them? E.g., we're
> > > > > > currently running one job and three of the shards have >218,000 
> > > > > > items
> > > > > > processed, but the other 5 shards appear to have zero.
>
> > > > > > I can understand that a particular key distribution would have
> > > > > > different amounts in each shard, but with so many at zero, I suspect
> > > > > > there is something else happening?
>
> > > > > > BTW, we have applied themapreduce-recommended __key__ DESC index, 
> > > > > > but
> > > > > > we still see this strange shard distribution.
>
> > > > > > Is anyone else seeing this?
>
> > > > > > j
>
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> > > > > --
> > > > > Nick Johnson, Developer Programs Engineer, App Engine Google Ireland 
> > > > > Ltd.
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> > > --
> > > Nick Johnson, Developer Programs Engineer, App Engine Google Ireland Ltd. 
> > > ::
> > > Registered in Dublin, Ireland, Registration Number: 368047
> > > Google Ireland Ltd. :: Registered in Dublin, Ireland, Registration Number:
> > > 368047

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