I have noticed some strange performance numbers on EC2. If someone can give
me some hints to improve performance that would be greatly appreciated.
Here are the details:
I have a process that runs a series of Jobs under Hadoop 0.20.1 & Hbase
0.20.2 I ran the *exact* same process with following configurations:
1) 1 Master & 4 Workers (*c1.xlarge* instances) & 1 Zookeeper (*c1.medium*)
with *8 Reducers *for every Reduce task. The process completed in *849*
seconds.
2) 1 Master, 4 Workers & 1 Zookeeper *ALL m1.small* instances with *8
Reducers *for every Reduce task. The process completed in *906* seconds.
3) 1 Master, *11* Workers & *3* Zookeepers *ALL m1.small* instances with *20
Reducers *for every Reduce task. The process completed in *984* seconds!
Two main questions:
1) It's totally surprising that when I have 11 workers with 20 Reducers it
runs slower than when I have exactly same type of fewer machines with fewer
reducers..
2) As expected it runs faster on c1.xlarge, but the performance improvement
doesn't justify the high cost difference. I must not be utilizing the
machine power, but I don't know how to do that.
Here are some of the performance improvements tricks that I have learnt from
this mailing list in the past that I am using:
1) conf.set("hbase.client.scanner.caching", "30"); I have this for all
jobs.
2) Using the following code every time I open a HTable:
this.table = new HTable(new HBaseConfiguration(), "tablenameXYZ");
table.setAutoFlush(false);
table.setWriteBufferSize(1024 * 1024 * 12);
3) For every Put I do this:
Put put = new Put(Bytes.toBytes(out));
put.setWriteToWAL(false);
4) Change the No. of Reducers as per the No. of Workers. I believe the
formula is: # of workers * 1.75.
Any other hints? As always, greatly appreciate the help. Thanks.
