Looks like HBASE-2214 'Do HBASE-1996 -- setting size to return in scan
rather than count of rows -- properly' may help you.
But that is only in 0.96
Lars H presented some performance numbers in:
HBASE-7008 Set scanner caching to a better default, disable Nagles
where default for "hbase.client.scanner.caching" changed to 100
On Fri, Jan 25, 2013 at 3:59 PM, David Koch <[EMAIL PROTECTED]> wrote:
> Is there a rule to determine the best batch/caching combination for
> maximizing scan performance as a function of KV size and (average) number
> of columns per row key?
> I have 0.5kb per value (constant), an average of 10 values per row key -
> heavy tailed so some outliers have 100k KVs, around 100million rows in the
> table. The cluster consists of 30 region servers, 24gb of RAM each, nodes
> are connecting with a 1gbit connection. I am running Map/Reduce jobs on the
> table, also with 30 task trackers.
> I tried:
> cache: 1, no batching -> 14min
> cache 1000, batch 50 -> 11min
> cache 5000, batch 25 -> crash (timeouts)
> cache 2000, batch 25 -> 15min
> Job time can vary quite significantly according to whatever activity
> (compactions?) are going on in the background. Also, I cannot probe for the
> best combination indefinitely since there actual production jobs queued. I
> did expect a larger speed-up with respect to no caching/batching at all -
> is this unjustified?
> In short, I am looking for some tips for making scans in a Map/Reduce
> context faster :-)
> Thank you,