You can try to limit input by particular subset of ranges, if that
helps. Here's my count m-r snippet:
{
"inputs":{
"bucket":"data",
"index":"numero_int",
"start":0,
"end":1212
},
"query":[
{"map":
{"language":"erlang","module":"riak_kv_mapreduce","function":"map_object_value","arg":"filter_notfound"}
},
{"reduce": {"language":"erlang",
"module":"riak_kv_mapreduce","function":"reduce_count_inputs","arg":"filter_notfound"}}
], "timeout": 9000
}
hope it helps,
-fyodor
On Tue, Nov 22, 2011 at 3:26 AM, Stephen Bennett <st...@bennettweb.org> wrote:
> I have a bucket which contains images refernced by a key which is made up
> from a guid. I have a number of servers in my cluster and my bucket is set
> up to store 3 versions of every item in the bucket across the servers in the
> cluster. I'd like to understand a little bit more about how my cluster is
> performing in terms of data storage. I can find out how much space each
> bitcask is currently taking up on each server, but I'd like to compare
> reference this against the number of unique keys that are being stored in
> the system.
>
> I've tried to use map-reduce methods using the erlang methods defined in the
> riak_kv_mapreduce, calling them against the HTTP interface but my queries
> are timing out. I've tried to extend the timeout, but it's still timing out.
>
> What's the most efficient way to find out how many keys exist in a
> particular bucket?
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>
>
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