lower impact on old-gen promotion of slow nodes or connections
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Key: CASSANDRA-3853
URL: https://issues.apache.org/jira/browse/CASSANDRA-3853
Project: Cassandra
Issue Type: Improvement
Reporter: Peter Schuller
Assignee: Peter Schuller
Cassandra has the unfortunate behavior that when things are "slow" (nodes
overloaded, etc) there is a tendency for cascading failure if the system is
overall under high load. This is generally true of most systems, but one way in
which it is worse than desired is the way we queue up things between stages and
outgoing requests.
First off, I use the following premises:
* The node is not running Azul ;)
* The total cost of ownership (in terms of allocation+collection) of an object
that dies in old-gen is *much* higher than that of an object that dies in young
gen.
* When CMS fails (concurrent mode failure or promotion failure), the resulting
full GC is *serial* and does not use all cores, and is a stop-the-world pause.
Here is how this very effectively leads to cascading failure of the "fallen and
can't get up" kind:
* Some node has a problem and is slow, even if just for a little while.
* Other nodes, especially neighbors in the replica set, start queueing up
outgoing requests to the node for {{rpc_timeout}} milliseconds.
* You have a high (let's say write) throughput of 50 thousand or so requests
per second per node.
* Because you want writes to be highly available and you are okay with high
latency, you have an {{rpc_timeout}} of 60 seconds.
* The total amount of memory used for 60 * 50 000 requests is freaking high.
* The young gen GC pauses happen *much* more frequently than every 60 seconds.
* The result is that when a node goes down, other nodes in the replica set
start *massively* increasing their promotion rate into old gen. A cluster whose
nodes are normally completely fine, with slow nice promotion into old-gen, will
now exhibit vastly different behavior than normal: While the total allocation
rate doesn't change (or not very much, perhaps a little if clients are doing
re-tries), the promotion rate into old-gen increases massively.
* This increases the total cost of ownership, and thus demand for CPU resources.
* You will *very* easily see CMS' sweeping phase not stand a chance to sweep up
fast enough to keep up with the incoming request rate, even with a hugely
inflated heap (CMS sweeping is not parallel, even though marking is).
* This leads to promotion failure/conc mode failure, and you fall into full GC.
* But now, your full GC is effectively stealing CPU resources since you are
forcing all cores but one to be completely idle on your system.
* Once you go out of GC, you now have a huge backlog of work to do that you get
bombarded with from other nodes that thought it was a good idea to retain 30
seconds worth of messages in *their* heap. So you're now being instantly shot
down again by your neighbors, falling into the next full GC cycle even easier
than originally.
* Meanwhile, the fact that you are in full gc, is causing your neighbors to
enter the same predicament.
The "solution" to this in production is to rapidly restart all nodes in the
replica set. Doing a live-change of RPC timeouts to something very very low
might also do the trick.
This is a specific instance of the overall problem that we should IMO not be
queueing up huge amounts of data in memory. Just recently I saw a node with *10
million* requests pending.
We need to:
* Have support for more aggressively dropping requests instead of queueing them
when sending to other nodes.
* More aggressively drop requests internally; there is very little use to
queueing up hundreds of thousands of requests pending for MutationStage or
ReadStage, etc. Especially not ReadStage where any response is irrelevant once
timeout has been reached.
A complication here is that we *cannot* just drop requests so quickly that we
never promote into old-gen. If we were to drop requests that quickly when
outgoing, we would be dropping requests every time another node goes into young
gc. And if we retain requests long enough for other node's young gc, it also
means we retain them long enough for promotion into old-gen with us (not
strictly true with survivor spaces, but we can't assume to target the
distinction there with any accuracy).
A possible alternative is to ask users to be better about using short timeouts,
but that probably ups the priority on controlling timeouts on a per-request
basis rather than as coarse-grained server-side settings. Even with shorter
timeouts though, we still need to be careful about dropping requests in places
it makes sense to avoid accumulating more than a timeout's worth of data.
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