Thanks Ben! For the post, it seems they got a little better but similar result than i did. Good to know it. I am not sure if a little fine tuning of heap memory will help or not.
On Thu, Jul 7, 2016 at 2:58 PM, Ben Slater <ben.sla...@instaclustr.com> wrote: > Hi Yuan, > > You might find this blog post a useful comparison: > > https://www.instaclustr.com/blog/2016/01/07/multi-data-center-apache-spark-and-apache-cassandra-benchmark/ > > Although the focus is on Spark and Cassandra and multi-DC there are also > some single DC benchmarks of m4.xl clusters plus some discussion of how we > went about benchmarking. > > Cheers > Ben > > > On Fri, 8 Jul 2016 at 07:52 Yuan Fang <y...@kryptoncloud.com> wrote: > >> Yes, here is my stress test result: >> Results: >> op rate : 12200 [WRITE:12200] >> partition rate : 12200 [WRITE:12200] >> row rate : 12200 [WRITE:12200] >> latency mean : 16.4 [WRITE:16.4] >> latency median : 7.1 [WRITE:7.1] >> latency 95th percentile : 38.1 [WRITE:38.1] >> latency 99th percentile : 204.3 [WRITE:204.3] >> latency 99.9th percentile : 465.9 [WRITE:465.9] >> latency max : 1408.4 [WRITE:1408.4] >> Total partitions : 1000000 [WRITE:1000000] >> Total errors : 0 [WRITE:0] >> total gc count : 0 >> total gc mb : 0 >> total gc time (s) : 0 >> avg gc time(ms) : NaN >> stdev gc time(ms) : 0 >> Total operation time : 00:01:21 >> END >> >> On Thu, Jul 7, 2016 at 2:49 PM, Ryan Svihla <r...@foundev.pro> wrote: >> >>> Lots of variables you're leaving out. >>> >>> Depends on write size, if you're using logged batch or not, what >>> consistency level, what RF, if the writes come in bursts, etc, etc. >>> However, that's all sort of moot for determining "normal" really you need a >>> baseline as all those variables end up mattering a huge amount. >>> >>> I would suggest using Cassandra stress as a baseline and go from there >>> depending on what those numbers say (just pick the defaults). >>> >>> Sent from my iPhone >>> >>> On Jul 7, 2016, at 4:39 PM, Yuan Fang <y...@kryptoncloud.com> wrote: >>> >>> yes, it is about 8k writes per node. >>> >>> >>> >>> On Thu, Jul 7, 2016 at 2:18 PM, daemeon reiydelle <daeme...@gmail.com> >>> wrote: >>> >>>> Are you saying 7k writes per node? or 30k writes per node? >>>> >>>> >>>> *.......* >>>> >>>> >>>> >>>> *Daemeon C.M. ReiydelleUSA (+1) 415.501.0198 >>>> <%28%2B1%29%20415.501.0198>London (+44) (0) 20 8144 9872 >>>> <%28%2B44%29%20%280%29%2020%208144%209872>* >>>> >>>> On Thu, Jul 7, 2016 at 2:05 PM, Yuan Fang <y...@kryptoncloud.com> >>>> wrote: >>>> >>>>> writes 30k/second is the main thing. >>>>> >>>>> >>>>> On Thu, Jul 7, 2016 at 1:51 PM, daemeon reiydelle <daeme...@gmail.com> >>>>> wrote: >>>>> >>>>>> Assuming you meant 100k, that likely for something with 16mb of >>>>>> storage (probably way small) where the data is more that 64k hence will >>>>>> not >>>>>> fit into the row cache. >>>>>> >>>>>> >>>>>> *.......* >>>>>> >>>>>> >>>>>> >>>>>> *Daemeon C.M. ReiydelleUSA (+1) 415.501.0198 >>>>>> <%28%2B1%29%20415.501.0198>London (+44) (0) 20 8144 9872 >>>>>> <%28%2B44%29%20%280%29%2020%208144%209872>* >>>>>> >>>>>> On Thu, Jul 7, 2016 at 1:25 PM, Yuan Fang <y...@kryptoncloud.com> >>>>>> wrote: >>>>>> >>>>>>> >>>>>>> >>>>>>> I have a cluster of 4 m4.xlarge nodes(4 cpus and 16 gb memory and >>>>>>> 600GB ssd EBS). >>>>>>> I can reach a cluster wide write requests of 30k/second and read >>>>>>> request about 100/second. The cluster OS load constantly above 10. Are >>>>>>> those normal? >>>>>>> >>>>>>> Thanks! >>>>>>> >>>>>>> >>>>>>> Best, >>>>>>> >>>>>>> Yuan >>>>>>> >>>>>>> >>>>>> >>>>> >>>> >>> >> -- > ———————— > Ben Slater > Chief Product Officer > Instaclustr: Cassandra + Spark - Managed | Consulting | Support > +61 437 929 798 >
