I too am interested in this custom load balancer, as I was actually just starting to look into writing one that does the same thing for my heterogeneous cluster!
Is this available somewhere? On Sat, Dec 8, 2012 at 9:17 AM, James Chang <[email protected]> wrote: > By the way, I saw you mentioned that you > have built a "LoadBalancer", could you kindly > share some detailed info about it? > > Jean-Marc Spaggiari 於 2012年12月8日星期六寫道： > > > Hi, > > > > Here is the situation. > > > > I have an heterogeneous cluster with 2 cores CPUs, 4 cores CPUs and 8 > > cores CPUs servers. The performances of those different servers allow > > them to handle different size of load. So far, I built a LoadBalancer > > which balance the regions over those servers based on the > > performances. And it’s working quite well. The RowCounter went down > > from 11 minutes to 6 minutes. However, I can still see that the tasks > > are run on some servers accessing data on other servers, which > > overwhelme the bandwidth and slow done the process since some 2 cores > > servers are assigned to count some rows hosted on 8 cores servers. > > > > I’m looking for a way to “force” the tasks to run on the servers where > > the regions are assigned. > > > > I first tried to reject the tasks on the Mapper setup method when the > > data was not local to see if the tracker will assign it to another > > server. No. It’s just failing and mostly not re-assigned. I tried > > IOExceptions, RuntimeExceptions, InterruptionExceptions with no > > success. > > > > So now I have 3 possible options. > > > > The first one is to move from the MapReduce to the Coprocessor > > EndPoint. Running locally on the RegionServer, it’s accessing only the > > local data and I can manually reject all what is not local. Therefor > > it’s achieving my needs, but it’s not my preferred options since I > > would like to keep the MR features. > > > > The second option is to tell Hadoop where the tasks should be > > assigned. Should that be done by HBase? By Hadoop? I don’t know. > > Where? I don’t know either. I have started to look at JobTracker and > > JobInProgress code but it seems it will be a big task. Also, doing > > that will mean I will have to re-patch the distributed code each time > > I’m upgrading the version, and I will have to redo everything when I > > will move from 1.0.x to 2.x… > > > > Third option is to not process the task if the data is not local. I > > mean, on the map method, simply have a if (!local) return; right from > > the beginning and just do nothing. This will not work for things like > > RowCount since all the entries are required, but for some of my > > usecases this might work where I don’t necessary need all the data to > > be processed. I will not be efficient stlil the task will still scan > > the entire region. > > > > My preferred option is definitively the 2nd one, but it seems also to > > be the most difficult one. The Third one is very easy to implement. > > Need 2 lines to see if the data is local. But it’s not working for all > > the scenarios, and is more like a dirty fix. The coprocessor option > > might be doable too since I already have all the code for my MapReduce > > jobs. So it might be an acceptable option. > > > > I’m wondering if anyone already faced this situation and worked on > > something, and if not, do you have any other ideas/options to propose, > > or can someone point me to the right classes to look at to implement > > the solution 2? > > > > Thanks, > > > > JM > > > -- Robert Dyer [email protected]
