Can do you do: iostat -dmx 2 10
On Tue, Jul 12, 2016 at 11:20 AM Yuan Fang <y...@kryptoncloud.com> wrote: > Hi Jeff, > > The read being low is because we do not have much read operations right > now. > > The heap is only 4GB. > > MAX_HEAP_SIZE=4GB > > On Thu, Jul 7, 2016 at 7:17 PM, Jeff Jirsa <jeff.ji...@crowdstrike.com> > wrote: > >> EBS iops scale with volume size. >> >> >> >> A 600G EBS volume only guarantees 1800 iops – if you’re exhausting those >> on writes, you’re going to suffer on reads. >> >> >> >> You have a 16G server, and probably a good chunk of that allocated to >> heap. Consequently, you have almost no page cache, so your reads are going >> to hit the disk. Your reads being very low is not uncommon if you have no >> page cache – the default settings for Cassandra (64k compression chunks) >> are really inefficient for small reads served off of disk. If you drop the >> compression chunk size (4k, for example), you’ll probably see your read >> throughput increase significantly, which will give you more iops for >> commitlog, so write throughput likely goes up, too. >> >> >> >> >> >> >> >> *From: *Jonathan Haddad <j...@jonhaddad.com> >> *Reply-To: *"user@cassandra.apache.org" <user@cassandra.apache.org> >> *Date: *Thursday, July 7, 2016 at 6:54 PM >> *To: *"user@cassandra.apache.org" <user@cassandra.apache.org> >> *Subject: *Re: Is my cluster normal? >> >> >> >> What's your CPU looking like? If it's low, check your IO with iostat or >> dstat. I know some people have used Ebs and say it's fine but ive been >> burned too many times. >> >> On Thu, Jul 7, 2016 at 6:12 PM Yuan Fang <y...@kryptoncloud.com> wrote: >> >> Hi Riccardo, >> >> >> >> Very low IO-wait. About 0.3%. >> >> No stolen CPU. It is a casssandra only instance. I did not see any >> dropped messages. >> >> >> >> >> >> ubuntu@cassandra1:/mnt/data$ nodetool tpstats >> >> Pool Name Active Pending Completed Blocked >> All time blocked >> >> MutationStage 1 1 929509244 0 >> 0 >> >> ViewMutationStage 0 0 0 0 >> 0 >> >> ReadStage 4 0 4021570 0 >> 0 >> >> RequestResponseStage 0 0 731477999 0 >> 0 >> >> ReadRepairStage 0 0 165603 0 >> 0 >> >> CounterMutationStage 0 0 0 0 >> 0 >> >> MiscStage 0 0 0 0 >> 0 >> >> CompactionExecutor 2 55 92022 0 >> 0 >> >> MemtableReclaimMemory 0 0 1736 0 >> 0 >> >> PendingRangeCalculator 0 0 6 0 >> 0 >> >> GossipStage 0 0 345474 0 >> 0 >> >> SecondaryIndexManagement 0 0 0 0 >> 0 >> >> HintsDispatcher 0 0 4 0 >> 0 >> >> MigrationStage 0 0 35 0 >> 0 >> >> MemtablePostFlush 0 0 1973 0 >> 0 >> >> ValidationExecutor 0 0 0 0 >> 0 >> >> Sampler 0 0 0 0 >> 0 >> >> MemtableFlushWriter 0 0 1736 0 >> 0 >> >> InternalResponseStage 0 0 5311 0 >> 0 >> >> AntiEntropyStage 0 0 0 0 >> 0 >> >> CacheCleanupExecutor 0 0 0 0 >> 0 >> >> Native-Transport-Requests 128 128 347508531 2 >> 15891862 >> >> >> >> Message type Dropped >> >> READ 0 >> >> RANGE_SLICE 0 >> >> _TRACE 0 >> >> HINT 0 >> >> MUTATION 0 >> >> COUNTER_MUTATION 0 >> >> BATCH_STORE 0 >> >> BATCH_REMOVE 0 >> >> REQUEST_RESPONSE 0 >> >> PAGED_RANGE 0 >> >> READ_REPAIR 0 >> >> >> >> >> >> >> >> >> >> >> >> On Thu, Jul 7, 2016 at 5:24 PM, Riccardo Ferrari <ferra...@gmail.com> >> wrote: >> >> Hi Yuan, >> >> >> >> You machine instance is 4 vcpus that is 4 threads (not cores!!!), aside >> from any Cassandra specific discussion a system load of 10 on a 4 threads >> machine is way too much in my opinion. If that is the running average >> system load I would look deeper into system details. Is that IO wait? Is >> that CPU Stolen? Is that a Cassandra only instance or are there other >> processes pushing the load? >> >> What does your "nodetool tpstats" say? Hoe many dropped messages do you >> have? >> >> >> >> Best, >> >> >> >> On Fri, Jul 8, 2016 at 12:34 AM, Yuan Fang <y...@kryptoncloud.com> wrote: >> >> 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/ >> <https://urldefense.proofpoint.com/v2/url?u=https-3A__www.instaclustr.com_blog_2016_01_07_multi-2Ddata-2Dcenter-2Dapache-2Dspark-2Dand-2Dapache-2Dcassandra-2Dbenchmark_&d=CwMFaQ&c=08AGY6txKsvMOP6lYkHQpPMRA1U6kqhAwGa8-0QCg3M&r=yfYEBHVkX6l0zImlOIBID0gmhluYPD5Jje-3CtaT3ow&m=Ltg5YUTZbI4Ixf7UjzKW636Llz6zXXurTveCLptZwio&s=MU4-NWBjvVO95HnxQtkYk4xkApq4X4IiVy8tPCgj4KU&e=> >> >> >> >> Although the focus is on Spark and Cassandra and multi-DC there are also >> some single DC benchmarks of m4.xl >> <https://urldefense.proofpoint.com/v2/url?u=http-3A__m4.xl&d=CwQFaQ&c=08AGY6txKsvMOP6lYkHQpPMRA1U6kqhAwGa8-0QCg3M&r=yfYEBHVkX6l0zImlOIBID0gmhluYPD5Jje-3CtaT3ow&m=Ltg5YUTZbI4Ixf7UjzKW636Llz6zXXurTveCLptZwio&s=m3DfZk3YOaf0W2OvACsqDWXp-vdlkP-cC0WnEouZwkk&e=> >> 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 >> >> >> >> >> >> >> >> >
