If multiple tablet servers die in quick succession, such as from a rolling restart of the Accumulo cluster or a network partition, this behavior can cause a storm of reassignment and rebalancing, placing significant load on the master.
In the case of a rolling-restart, isn't that more of an operational issue to solve (give Accumulo time to process the reassignments before restarting more nodes)?
Can you expand a bit more on the specifics behind a network partition that you're trying to solve with this? Say, you lose a node? A rack? Half of your racks? Are we talking about a 5second interruption/delay? 30s? Minutes?
To avert such load, Accumulo should be capable of maintaining a steady tablet assignment state in the face of transient tablet server loss. Instead of reassigning tablets as quickly as possible, Accumulo should be await the return of a temporarily downed tablet server (for some configurable duration) before assigning its tablets to other tablet servers.
I'm a little worried about this as a configuration knob – I feel like it kind of goes against the highly-available distributed database which we expect Accumulo to be. When we don't reassign tablets fast, that is a direct lack of availability for clients to read data.
placing significant load on the master
Can you expand on this some more? Given that assignment is arguably the most important thing for the Master to do, why are we concerned about letting the master do that as fast as it can (for the aforementioned reason)? Do we need to come up with a more efficient way for the master to handle the reassignment of many tablets? For example, I know that HBase has special logic to batch assignments together in one RPC call to regionservers in order to bring things online more quickly (I'm not sure if we have logic like that – instead we just spam requests to a tabletserver to load a tablet until it does so).
While seeing a pull request accompanying the issue reported, It seems a bit premature to me to see code without some discussion on what the problems are and how best to solve them.