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What this implies is a single dataset doesn't have to be uniform in size, e.g. we can generate the values whose size follow Gaussian distribution, now if we want to remember the association between keys and their sizes (e.g. to ensure the test results don't vary too much between runs) we may need to do something clever in terms of encoding information into keys. Otoh, each load *is* associated with a single dataset, and the presence of multi-tenant datasets implies multiple workloads (which, in implementation may also have threading implication??).\r\n\r\nFor each workload (as corresponds to a single dataset), again I think there are two dimensions we need to consider. The naive one is where different access patterns simply happen concurrently and independently, this dimension the current rpc-perf specification already captures and supports. The other dimension reflects the existence of a command sequence, comparable to a \"transaction\" without the usual atomicity constraints in the database context. E.g. `gets -> cas` and `incr->add` reflect logic of typical use cases. If we could come up with a language to describe that state machine, it could be embedded in the load gen. 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