On Thu, Aug 18, 2011 at 5:01 AM, Stephen Henderson <stephen.henderson@cognitivematch.com> wrote:

We're currently in the planning stage of a new project which needs a low latency, persistent key/value store with a roughly 60:40 read/write split. We're trying to establish if Cassandra is a good fit for this and in particular what the hardware requirements would be to have the majority of rows cached in memory (other nosql platforms like Couchbase/Membase seem like a more natural fit but we're already reasonably familiar with cassandra and would rather stick with what we know if it can work).

If anyone could help answer/clarify the following questions it would be a great help (all assume that row-caching is enabled for the column family).

Q. If we're using read consistency ONE does the read request get sent to all nodes in the replica set and the first to reply is returned (i.e. all replica nodes will then have that row in their cache), OR does the request only get sent to a single node in the replica set? If it's the latter would the same node generally be used for all requests to the same key or would it always be a random node in the replica set? (i.e. if we have multiple reads for one key in quick succession would this entail potentially multiple disk lookups until all nodes in the set have been hit?).

Q. Related to the above, if only one node recieves the request would the client (hector in this case) know which node to send the request to directly or would there be potentially one extra network hop involved (client -> random node -> node with key).

Q. Is it possible to do a warm cache load of the most recently accessed keys on node startup or would we have to do this with a client app?

Q. With write consistency ANY is it correct that following a write request all nodes in the replica set will end up with that row in their cache, as well as on disk, once they receive the write? i.e. total cache size is (cache_memory_per_node * num_nodes) / num_replicas.

Q. If the cluster only has a single column family, random partitioning and no secondary indexes, is there a good metric for estimating how much heap space we would need to leave aside for everything that isn't the row-cache? Would it be proportional to the row-cache size or fairly constant?


Stephen Henderson - Lead Developer (Onsite), Cognitive Match
stephen.henderson@cognitivematch.com | http://www.cognitivematch.com

I did a small presentation on this topic a while back. http://www.edwardcapriolo.com/roller/edwardcapriolo/resource/memcache.odp

a) All reads go to all replica nodes. Even those at READ.ONE. UNLESS you lower the read_repair_chance for the column family. 
b) Read could hit random nodes same node unless you confirgure dynamic snitch to pin the request to a single node. This is described in the cassandra.yaml

2. Hector and no client that I know of routes requests to proper nodes based on topology. No information of know of has proven this matters.

3. Cassandra allows you to save your caches so your node will start up warn (saving large rowcache is hard, large key cache is easy)

4. Write.ANY would not change how caching works.

5. There are some calculations out there based on size of rows. One of the newer features of cassandra is it automatically resizes the row cache under memory pressure now. You still have to feel it out but you do not have to worry about setting it too high as much anymore.

One more note. I you have mentioned the row cache which is awesome it you can utilize it correctly and your use case is prefect but key cache + page cache can server very fast as well.

Thank you,