@Tyler / @Rob,
As Ashish mentioned earlier, we have 9 nodes on AWS - 6 on EastCoast and 3
on Singapore. All 9 nodes uses EC2Snitch. The current ring ( across all
nodes in 2 DC ) looks like this:
ip11 - East Coast - m1.xlarge / us-east-1b - Size: 83 GB - Token: 0
ip21 - Singapore - m1.xlarge / ap-southeast-1a - Size: 88 GB - Token: 1001
ip12 - East Coast - m1.xlarge / us-east-1b - Size: 45 GB -
Token: 28356863910078205288614550619314017621
ip13 - East Coast - m1.xlarge / us-east-1c - Size: 93 GB -
Token: 56713727820156410577229101238628035241
ip22 - Singapore - m1.xlarge / ap-southeast-1b - Size: 73 GB -
Token: 56713727820156410577229101238628036241
ip14 - East Coast - m1.xlarge / us-east-1c - Size: 20 GB -
Token: 85070591730234615865843651857942052863
ip15 - East Coast - m1.xlarge / us-east-1d - Size: 89 GB -
Token: 113427455640312821154458202477256070484
ip23 - Singapore - m1.xlarge / ap-southeast-1b - Size: 56 GB -
Token: 113427455640312821154458202477256071484
ip16 - East Coast - m1.xlarge / us-east-1d - Size: 25 GB -
Token: 141784319550391026443072753096570088105
Regarding alternating racks solution, I've the following queries:
1) By alternating racks, do you mean to alternate racks between all nodes
in a single DC v/s multiple DCs? AWS EastCoast has 4 AZs
and Singapore has 2 AZs. So is the final solution something like this:
ip11 - East Coast - m1.xlarge / us-east-1b - Token: 0
ip21 - Singapore - m1.xlarge / ap-southeast-1a - Token: 1001
ip12 - East Coast - m1.xlarge / us-east-*1c* -
Token: 28356863910078205288614550619314017621
ip13 - East Coast - m1.xlarge / us-east-*1d* -
Token: 56713727820156410577229101238628035241
ip22 - Singapore - m1.xlarge / ap-southeast-1b -
Token: 56713727820156410577229101238628036241
ip14 - East Coast - m1.xlarge / us-east-*1a* -
Token: 85070591730234615865843651857942052863
ip15 - East Coast - m1.xlarge / us-east-*1b* -
Token: 113427455640312821154458202477256070484
ip23 - Singapore - m1.xlarge / ap-southeast-*1a* -
Token: 113427455640312821154458202477256071484
ip16 - East Coast - m1.xlarge / us-east-*1c* -
Token: 141784319550391026443072753096570088105
Is this what you had suggested?
2) How does dynamic_snitch_badness_threshold: 0.1 effect the CPU load? On
the node ( ip11 ) which was high CPU ( system load > 30 ), I checked the
attribute score ( via JMX
bean org.apache.cassandra.db:type=DynamicEndpointSnitch ) and saw the
following:
EastCoast:
*ip11 = 1.6813321647677475*
ip12 = 1.0003505696757231
ip13 = 1.1324160525509974
ip14 = 1.000350569675723
ip15 = 1.0007011393514456
ip16 = 1.0005258545135842
Singapore:
ip21 = 1.095880806310253
ip22 = 1.4100000000000001
ip23 = 1.0953549517966696
So ip11 node is indeed having higher score - but not sure why traffic is
still going to that replica as opposed to some other node?
Thanks!
On Fri, Nov 1, 2013 at 3:13 PM, Ashish Tyagi <tyagi.i...@gmail.com> wrote:
> Hi Evan,
>
> The clients connect to all nodes. We tried shutting the thrift server on
> the affected node. Loads did not come down.
>
>
>
> On Fri, Nov 1, 2013 at 12:59 AM, Evan Weaver <e...@fauna.org> wrote:
>
>> Are all your clients only connecting to your first node? I would
>> probably strace it and compare the trace to one from a lightly loaded
>> node.
>>
>> On Thu, Oct 31, 2013 at 7:12 PM, Ashish Tyagi <tyagi.i...@gmail.com>
>> wrote:
>> > We have a 9 node cluster. 6 nodes are in one data-center and 3 nodes in
>> the
>> > other. All machines are Amazon M1.XLarge configuration.
>> >
>> > Datacenter: DC1
>> > ==========
>> > Address Rack Status State Load Owns
>> > Token
>> >
>> > ip11 1b Up Normal 76.46 GB 16.67% 0
>> > ip12 1b Up Normal 44.66 GB 16.67%
>> > 28356863910078205288614550619314017621
>> > ip13 1c Up Normal 85.94 GB 16.67%
>> > 56713727820156410577229101238628035241
>> > ip14 1c Up Normal 17.55 GB 16.67%
>> > 85070591730234615865843651857942052863
>> > ip15 1d Up Normal 80.74 GB 16.67%
>> > 113427455640312821154458202477256070484
>> > ip16 1d Up Normal 20.88 GB 16.67%
>> > 141784319550391026443072753096570088105
>> >
>> > Datacenter: DC2
>> > ==========
>> > Address Rack Status State Load Owns
>> > Token
>> >
>> > ip21 1a Up Normal 78.32 GB 0.00%
>> 1001
>> > ip22 1b Up Normal 71.23 GB 0.00%
>> > 56713727820156410577229101238628036241
>> > ip23 1b Up Normal 53.49 GB 0.00%
>> > 113427455640312821154458202477256071484
>> >
>> > Problem is that node with ip address: ip11 often has 5-10 times more
>> load
>> > than any other node. Most of the operations are on counters. The primary
>> > column family (which receives most writes) has a replication factor of
>> 2 in
>> > DataCenter DC1 and also in DataCenter DC2. The traffic is write heavy
>> (reads
>> > are less than 10% of total requests). We are using size-tiered
>> compaction.
>> > Both writes and reads happen with a consistency factor of LOCAL_QUORUM.
>> >
>> > More information:
>> >
>> > 1. cassandra.yaml - http://pastebin.com/u344fA6z
>> > 2. Jmap heap when node under high loads - http://pastebin.com/ib3D0Pa
>> > 3. Nodetool tpstats - http://pastebin.com/s0AS7bGd
>> > 4. Cassandra-env.sh - http://pastebin.com/ubp4cGUx
>> > 5. GC log lines - http://pastebin.com/Y0TKphsm
>> >
>> > Am I doing anything wrong. Any pointers will be appreciated.
>> >
>> > Thanks in advance,
>> > Ashish
>>
>
>
