That sounds quite disconcerting. What happens to the performance of the cluster when this occurs?*
<http://www.loomlearning.com/> Jonathan Langevin Systems Administrator Loom Inc. Wilmington, NC: (910) 241-0433 - jlange...@loomlearning.com - www.loomlearning.com - Skype: intel352 * On Thu, May 26, 2011 at 1:54 AM, Greg Nelson <gro...@dropcam.com> wrote: > I've been doing some digging through the details of how a node joins a > cluster. When you hear that Riak uses consistent hashing, you'd expect it > to distribute keys to nodes by hashing keys onto the ring AND hashing nodes > onto the ring. Keys belong to the closest node on the ring, in the > clockwise direction. Add a node, it hashes onto the ring and takes over > some keys. Ordinarily the node would hash onto the ring in several places, > to achieve better spread. Some data (roughly 1 / #nodes) moves to the new > node from each of the other nodes, and everything else stays the same. > > In what Amazon describes as operationally simpler (strategy 3 in the Dynamo > paper), the ring is instead divided into equally-sized partitions. Nodes > are hashed onto the ring, and preflists are calculated by walking clockwise > from a partition, skipping partitions on already visited nodes. Riak does > something similar: it divides the ring into equally-sized partitions, then > nodes "randomly" claim partitions. However, the skipping bit isn't part of > Riak's preflist calculation. Instead, nodes claim partitions in such a way > as to be spaced out by target_n_val, to obviate the need for skipping. > > Now, getting back to what happens when a node joins. The new node > calculates a new ring state that maintains the target_n_val invariant, as > well as trying to keep even spread of partitions per node. The algorithm > (default_choose_claim) is heuristic and greedy in nature, and recursively > transfers partitions to the new node until optimal spread is achieved, > maintaining target_n_val along the way. But if -- during one of those > recursive calls -- it can't meet the target_n_val, it will throw up its > hands and completely re-do the whole ring (by calling claim_rebalance_n). > Striping the partitions across nodes, in a round-robin fashion. When that > happens, most of the data needs to be handed off between nodes. > > This happens a lot, with many ring sizes. With ring_creation_size=128 > (i.e., 128 partitions), it will happen when adding node 9 (87.5% of data > moves), adding node 12 (82%), adding node 15 (80%), adding node 19 (94%). > It happens with all ring sizes >= 128 (256, 512, 1024, ...). It appears > that any ring_creation_size (64 by default) is safe for growing to 8 nodes > or so. But if you want to go beyond that... A ring size of >= 128 with > more than 8 nodes doesn't seem all that unusual, surely someone has hit this > before? I've filed a bug report here: > https://issues.basho.com/show_bug.cgi?id=1111 > > Anyway, this feels like a bit of a departure from consistent hashing. In > fact, could this not be replaced by normal hashing + a lookup table mapping > intervals of the hash space to nodes? And isn't that simply sharding? > > At any rate, I believe the claim algorithm can be improved to avoid those > "throw up hands and stripe everything" scenarios. In fact, here is such an > implementation: https://github.com/basho/riak_core/pull/55. It is still > heuristic and greedy, but it seems to do a better job of avoiding re-stripe. > Test results are attached in a zip on the bug linked above. I'd love to > get the riak_core gurus at Basho to look at this and help validate it. It > probably could use some cleaning up, but I want to make sure there aren't > other invariants or considerations I'm leaving out -- besides maintaining > target_n_val, keeping optimal partition spread, and minimizing handoff > between ring states. > > -Greg > > _______________________________________________ > riak-users mailing list > riak-users@lists.basho.com > http://lists.basho.com/mailman/listinfo/riak-users_lists.basho.com > >
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