there is a JIRA completed in 0.7.x that "Prefers" a certain node in snitch, so this does roughly what you want MOST of the time
but the problem is that it does not GUARANTEE that the same node will always be read. I recently read into the HBase vs Cassandra comparison thread that started after Facebook dropped Cassandra for their messaging system, and understood some of the differences. what you want is essentially what HBase does. the fundamental difference there is really due to the gossip protocol: it's a probablistic, or eventually consistent failure detector while HBase/Google Bigtable use Zookeeper/Chubby to provide a strong failure detector (a distributed lock). so in HBase, if a tablet server goes down, it really goes down, it can not re-grab the tablet from the new tablet server without going through a start up protocol (notifying the master, which would notify the clients etc), in other words it is guaranteed that one tablet is served by only one tablet server at any given time. in comparison the above JIRA only TRYIES to serve that key from one particular replica. HBase can have that guarantee because the group membership is maintained by the strong failure detector.
just for hacking curiosity, a strong failure detector + Cassandra replicas is not impossible (actually seems not difficult), although the performance is not clear. what would such a strong failure detector bring to Cassandra besides this ONE-ONE strong consistency ? that is an interesting question I think.
considering that HBase has been deployed on big clusters, it is probably OK with the performance of the strong Zookeeper failure detector. then a further question was: why did Dynamo originally choose to use the probablistic failure detector? yes Dynamo's main theme is "eventually consistent", so the Phi-detector is **enough**, but if a strong detector buys us more with little cost, wouldn't that be great?
On Fri, Jul 1, 2011 at 6:53 PM, AJ <firstname.lastname@example.org>
Is this possible?
All reads and writes for a given key will always go to the same node from a client. It seems the only thing needed is to allow the clients to compute which node is the closes replica for the given key using the same algorithm C* uses. When the first replica receives the write request, it will write to itself which should complete before any of the other replicas and then return. The loads should still stay balanced if using random partitioner. If the first replica becomes unavailable (however that is defined), then the clients can send to the next repilca in the ring and switch from ONE write/reads to QUORUM write/reads temporarily until the first replica becomes available again. QUORUM is required since there could be some replicas that were not updated after the first replica went down.
Will this work? The goal is to have strong consistency with a read/write consistency level as low as possible while secondarily a network performance boost.