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We are exploring using Cassandra as a way to store time series type data, so this may be somewhat of a noob question. One of the use cases is to read data from a Kafka stream, look for matches, and incrementing a counter (e.g. 5 customers have clicked through link alpha on page beta, increment (beta, alpha) by 5). However, we expect a very wide degree of parallelism to keep up with the load, so there may be more than one consumer reading from Kafka at the same time.

My question is: How would Cassandra resolve multiple simultaneous writes to a given counter from multiple sources?

It's my understanding that multiple writes to the counter with different timestamps will be added to the counter in the timestamp order received. However, if there were to be a simultaneous write with exact same timestamp, would the LWW model of Cassandra throw out one of those counter increments?

If we were to have a large cluster (100+ nodes), ALL or QUORUM writes may not be sufficient performant to keep up with the messasge traffic. Writes with THREE would seem to be likely to result in a situation where process #1 writes to nodes A, B, and C, but process #2 might write to X, Y, and Z. Would LWT work here, or do they not play well with counter activity?

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I would try out a proof of concept and benchmark it, it will most likely work just fine. Counters are not super performant in Cassandra though, especially if there will be a lot of contention.

Counters are not like the normal writes with a simple LWW, it uses paxos with some pessimistic locking and specialized caches. The partition lock contention will slow it down soome, and paxos is an expensive multiple network hop process with reads before writes.

Use quorum, don't try to do something funky with CL's with counters, especially before benchmarking to know if you need it. 100 node cluster should be able to handle a lot as long as your not trying to update all the same partitions constantly.