Yes, you can do this.
You will want to have three DCs: DC1 with [1, 2, 3], DC2 with [4, 5, 6],
and DC3 with [7, 8, 9]. For your normal data keyspace, the replication
strategy should be NTS, and the strategy_options should have some replicas
in each of the three DCs. For example: {DC1: 3, DC2: 3, DC3: 3} if you
need that level of replication in each one (although you probably only want
an RF of 1 for DC3).
Your clients that are performing writes should only open connections
against the nodes in DC1, and you should write at CL.ONE or
CL.LOCAL_QUORUM. Likewise for reads, your clients should only connect to
nodes in DC2, and you should read at CL.ONE or CL.LOCAL_QUORUM.
The nodes in DC3 should run as analytics nodes. I believe the default CL
for m/r jobs is ONE, which would work.
As far as tokens go, interleaving all three DCs and evenly spacing the
tokens will work. For example, the ordering of your nodes might be [1, 4,
7, 2, 5, 8, 3, 6, 9].
On Wed, Mar 14, 2012 at 12:05 PM, Alexandru Sicoe <adsi...@gmail.com> wrote:
> Hi everyone,
> I want to test out the Datastax Enterprise software to have a mixed
> workload setup with an analytics and a real time part.
>
> However I am not sure how to configure it to achieve what I want: I will
> have 3 real machines on one side of a gateway (1,2,3) and 6 VMs on
> another(4,5,6).
> 1,2,3 will each have a normal Cassandra node that just takes data
> directly from my data sources. I want them to replicate the data to the
> other 6 VMs. Now, out of those 6 VMs 4,5,6 will run normal Cassandra nodes
> and 7,8,9 will run Analytics nodes. So I only want to write to the 1,2,3
> and I only want to serve user reads from 4,5,6 and do analytics on 7,8,9.
> Can I achieve this by configuring 1,2,3,4,5,6 as normal nodes and the rest
> as analytics nodes? If I alternate the tokens as it's explained in
> http://www.datastax.com/docs/1.0/datastax_enterprise/init_dse_cluster#init-dseis
> it analoguous to achieving something like 3 DCs each getting their own
> replica?
>
> Thanks,
> Alex
>
>
--
Tyler Hobbs
DataStax <http://datastax.com/>
