I'm not using 50 thread but make it with 4 thread. I give 2 thread by server ip. So I insert using 2 thread on 1 machine and with 2 other on the second machine
I need to add a lot of thread to be able to insert this data quickly enough. but for you it's logical this behavior ? On Wed, Dec 16, 2009 at 4:45 PM, Jonathan Ellis <jbel...@gmail.com> wrote: > Sounds like you are using a single thread, so the increased latency is > artificially reducing your numbers. Add more threads (stress.py uses > 50 by default) to get more throughput. (Also true even for a single > node, but more noticable when you add network overhead to the > cluster.) > > -Jonathan > > On Wed, Dec 16, 2009 at 8:06 AM, Richard Grossman <richie...@gmail.com> > wrote: > > Hi > > > > I think someone ask already similar but can't find where. > > > > On 1 machine standalone I insert data I get ~850 rows / second > > On another machine I make exactly the same operation I get ~900/1000 rows > / > > second > > > > Now I remove all the data from the 2 machines. Take exactly the same > > storage-conf.xml but just add seed in both file nothing else. > > Make the insert I get ~90 rows / second. > > > > Someone have an idea why the performance could fall sharply like this. Or > > simply give a hint what or where to check why it's happend > > I've already checked network problem the 2 machines are identical. > > > > Thanks. > > > > > > >
