Yes, you could make a different Splitter. Would be nice in the splitter if you could keep the locality where we have the Map task running on the TaskTracker that is adjacent to the hosting RegionServer. That shouldn't be hard. Study the current splitter and see how it juggles locations.
Can you put us in contact w/ the person running the cluster (offline if you prefer)? 150k sounds like regions need to be bigger. Thanks, St.Ack On Sat, Apr 9, 2011 at 9:33 AM, Avery Ching <ach...@yahoo-inc.com> wrote: > The number of regions is pretty insane, but not under my control > unfortunately. The workaround I suggested is to write another InputFormat > and InputSplit such that each InputSplit is responsible for a configurable > number of regions. For example, if i have 100k regions and I configure each > InputSplit to handle 1k regions, then I'll only have 100 map tasks. Just was > wondering if anyone else faced these issues. > > Thanks for your quick response on a Saturday morning =), > > Avery > > On Apr 9, 2011, at 9:26 AM, Jean-Daniel Cryans wrote: > >> You cannot have more mappers than you have regions, but you can have >> less. Try going that way. >> >> Also 149,624 regions is insane, is that really the case? I don't think >> i've ever seen such a large deploy and it's probably bound to hit some >> issues... >> >> J-D >> >> On Sat, Apr 9, 2011 at 9:15 AM, Avery Ching <ach...@yahoo-inc.com> wrote: >>> Hi, >>> >>> First off, I'd like to say thanks to the developers for HBase, it's been >>> fun to work with. >>> >>> I've been using TableInputFormat to run a Map-Reduce job and ran into an >>> issue. >>> >>> Exception in thread "main" org.apache.hadoop.ipc.RemoteException: >>> java.io.IOException: java.io.IOException: The number of tasks for this job >>> 149624 exceeds the configured limit 100000 >>> >>> The table i'm accessing has 149624 regions, however my Hadoop instance >>> won't allow me to start a job with that many map tasks. After briefly >>> looking at the TableInputFormatBase code, it appears that since TableSplit >>> only knows about a single region, my job will be forced into having mappers >>> == # of regions. Since the Hadoop instance I'm using is shared, I'm >>> concerned that even if configured limit was raised, having Jobs with so >>> many mappers would eventually cause havoc to the job tracker. >>> >>> Given that I have no control over the number of regions in the table >>> (maintained by someone else), is the only solution to implement another >>> input format (i.e. MultiRegionTableFormat) that allows InputSplits to have >>> more than one region? I don't mind doing it, but didn't want to write it >>> if another solution already exists. >>> >>> Apologies if this issue has been raised before, but a quick search didn't >>> turn anything up for me. >>> >>> Thanks, >>> >>> Avery >>> > >
