maintaining dynamic consistency level in datastax

Question

I have a 5 node cluster and keyspace with replication factor of 3. The nature of operations are such that writes are much more important than read, but frequency of read operations are about 10 times higher than write. To achieve consistency while improving overall performance, I chose to set consistency level for writes as ALL, and ONE for read. But this causes operations to fail if even one node is down.

Is there a method by which I can simultaneously change consistency level for (Write,Read) from (ALL,ONE) to (QUORUM, QUORUM) if one node is detected down, or if there is a query-execution-exception; plus this be done in a manner that no operations pass through a temporary phase where it sees a temporary (QUORUM, ONE) setting.

We also plan to expand to twice the capacity, 3 datacenter with 4 nodes each. Is it possible to define custom consistency levels, like, (a level of ALL in any one datacenter and ONE in others). I'm thinking that a level of (EACH_ONE) for read, coupled with above level for write will insure consistency but will allow the cluster to remain available even if a node goes down.

Answer 1

The flexibility is there since you can set your consistency level at a per request basis. Depending on the client you are using, there are some nice capabilities. For example, the java driver has something called a DowngradingConsistencyRetryPolicy such that if a request fails, it will be retried with the next lowest consistency level until the request succeeds. This pushes the complexity of retrying into the client so you don't have to write a bunch of code for it, it's really nice!

The java driver also allows you to configure consistency level per request with Statement#setConsistencyLevel()

As far as custom consistency levels, this is not an option available to you (without changing the cassandra source code), however I think what is made available should be sufficient.

For reads, I don't find much value in ensuring consistency between Data Centers on read. I think LOCAL_QUORUM is more than sufficient, but if you really care, you can use something like EACH_QUORUM for to ensure all datacenters agree, but that will severely impact your response time and availability. For example, if one of your datacenters goes down completely, you won't be able to do reads at all (unless downgrading).

For writes, I'd strongly recommend not using ALL in a multi datacenter set up if you care about response time and availability. Depending on your requirements, LOCAL_QUORUM should likely be more than sufficient.

While one of the benefits of Cassandra is that consistency is tunable, you can have as much strong consistency as you like, but keep in mind that Cassandra is at its best as a Highly Available, Partition Tolerant system.

A really good presentation on consistency that I think really nails a lot of these points is Christos Kalazantis' talk 'Eventual Consistency != Hopeful Consistency' which suggests that a consistency level of ONE is sufficient for a lot of use cases.