Heya, I'm looking for more detailed advice about how many regions a table should run. Disabling automatic splits (often hand-in-hand with disabling automatic compactions) is often described as advanced practice, at least when guaranteeing latency SLAs. Which begs the question: how many regions should I have? Surely this depends on both the shape of your data and expected workload. I've seen "10-20 Regions per RS" thrown around as a stock answer. My question is: why? Presumably that's 10-20 regions per RS for all tables rather than per-table. That advice is centered around a regular region size, but surely distribution of ops/load matters more. But still, where does 10-20 come from? Is it a calculation vs the number of cores on the RS, like advice given around parallelizing builds? If so, how many cores are we assuming the RS has? Is it a calculation vs the amount of RAM available? Is 20 regions based on a trade-off between static allocations and per-region memory overhead? Does 10-20 become 5-15 in a memory-restricted environment and bump to 20-40 when more RAM is available? Does it have to do with the number of spindles available on the machine? Threads like this one [0] give some hint about how the big players work. However, that advice looks heavily influenced by concerns when there are 1000's of regions to manage. How does advice for larger clusters (>50 nodes) differ from smaller clusters (<20 nodes)?
Thanks, -n [0]: http://thread.gmane.org/gmane.comp.java.hadoop.hbase.user/22451
