I'm pondering order preservation and TimeUUID keys, in particular how to get distribution across the cluster while maintaining "rangeability".
Basically, I'm working on a logging app, where rows are TimeUUIDs. To be able to do range scans we're using OrderPreservingPartitioner. To get partitioning working, I've currently transformed keys, prepending a partitioning token (in my testcase, the day-of-week). Basically, this means two range queries to get data for a set spanning two days. Crude, but kinda works, and the specialization is alright for my case. But it feels a bit hackish, so I begun studying the partitioner code a bit, seeking enlightenment. Has anybody already spent energy + time thinking about generic TimeUUID partitioning? Seems like it could be a useful thing, since time series data is quite common. Perhaps a TimeUUIDPartitioner with configurable time resolution for tokenization (token = uuid.time % resolution, more or less) would be sufficient? Or could it be even more general, i e no configuration necessary? /d
