Hi Jack, As mentioned before I've used m3.xlarge instance types together with two ephemeral disks in raid 0 and, according to Amazon, they have "high" network performance.
I ran many tests starting with a brand-new cluster every time and I got consistent results. I believe there's something that I cannot explain yet with the client used by cassandra-stress to connect to the nodes, I'd like to understand why there is such a big difference: Multi-AZ, CL=ONE, "--nodes node1,node2,node3,node4,node5,node6" -> 95th percentile: 38.14ms Multi-AZ, CL=ONE, "--nodes node1" -> 95th percentile: 5.9ms Hope you can help to figure it out. Cheers, Alessandro On Tue, Apr 12, 2016 at 5:43 PM, Jack Krupansky <jack.krupan...@gmail.com> wrote: > Which instance type are you using? Some may be throttled for EBS access, > so you could bump into a rate limit, and who knows what AWS will do at that > point. > > -- Jack Krupansky > > On Tue, Apr 12, 2016 at 6:02 AM, Alessandro Pieri <alessan...@getstream.io > > wrote: > >> Thanks Chris for your reply. >> >> I ran the tests 3 times for 20 minutes/each and I monitored the network >> latency in the meanwhile, it was very low (even the 99th percentile). >> >> I didn't notice any cpu spike caused by the GC but, as you pointed out, I >> will look into the GC log, just to be sure. >> >> In order to avoid the problem you mentioned with EBS and to keep the >> deviation under control I used two ephemeral disks in raid 0. >> >> I think the odd results come from the way cassandra-stress deals with >> multiple nodes. As soon as possible I will go through the Java code to get >> some more detail. >> >> If you have something else in your mind please let me know, your comments >> were really appreciated. >> >> Cheers, >> Alessandro >> >> >> On Mon, Apr 11, 2016 at 4:15 PM, Chris Lohfink <clohfin...@gmail.com> >> wrote: >> >>> Where do you get the ~1ms latency between AZs? Comparing a short term >>> average to a 99th percentile isn't very fair. >>> >>> "Over the last month, the median is 2.09 ms, 90th percentile is >>> 20ms, 99th percentile is 47ms." - per >>> https://www.quora.com/What-are-typical-ping-times-between-different-EC2-availability-zones-within-the-same-region >>> >>> Are you using EBS? That would further impact latency on reads and GCs >>> will always cause hiccups in the 99th+. >>> >>> Chris >>> >>> >>> On Mon, Apr 11, 2016 at 7:57 AM, Alessandro Pieri <siri...@gmail.com> >>> wrote: >>> >>>> Hi everyone, >>>> >>>> Last week I ran some tests to estimate the latency overhead introduces >>>> in a Cassandra cluster by a multi availability zones setup on AWS EC2. >>>> >>>> I started a Cassandra cluster of 6 nodes deployed on 3 different AZs (2 >>>> nodes/AZ). >>>> >>>> Then, I used cassandra-stress to create an INSERT (write) test of 20M >>>> entries with a replication factor = 3, right after, I ran cassandra-stress >>>> again to READ 10M entries. >>>> >>>> Well, I got the following unexpected result: >>>> >>>> Single-AZ, CL=ONE -> median/95th percentile/99th percentile: >>>> 1.06ms/7.41ms/55.81ms >>>> Multi-AZ, CL=ONE -> median/95th percentile/99th percentile: >>>> 1.16ms/38.14ms/47.75ms >>>> >>>> Basically, switching to the multi-AZ setup the latency increased of >>>> ~30ms. That's too much considering the the average network latency between >>>> AZs on AWS is ~1ms. >>>> >>>> Since I couldn't find anything to explain those results, I decided to >>>> run the cassandra-stress specifying only a single node entry (i.e. "--nodes >>>> node1" instead of "--nodes node1,node2,node3,node4,node5,node6") and >>>> surprisingly the latency went back to 5.9 ms. >>>> >>>> Trying to recap: >>>> >>>> Multi-AZ, CL=ONE, "--nodes node1,node2,node3,node4,node5,node6" -> 95th >>>> percentile: 38.14ms >>>> Multi-AZ, CL=ONE, "--nodes node1" -> 95th percentile: 5.9ms >>>> >>>> For the sake of completeness I've ran a further test using a >>>> consistency level = LOCAL_QUORUM and the test did not show any large >>>> variance with using a single node or multiple ones. >>>> >>>> Do you guys know what could be the reason? >>>> >>>> The test were executed on a m3.xlarge (network optimized) using the >>>> DataStax AMI 2.6.3 running Cassandra v2.0.15. >>>> >>>> Thank you in advance for your help. >>>> >>>> Cheers, >>>> Alessandro >>>> >>> >>> >> >> >> -- >> *Alessandro Pieri* >> *Software Architect @ Stream.io Inc* >> e-Mail: alessan...@getstream.io - twitter: sirio7g >> <http://twitter.com/sirio7g> >> >> >
