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From "Benedict (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (CASSANDRA-3852) use LIFO queueing policy when queue size exceeds thresholds
Date Wed, 04 Feb 2015 16:42:35 GMT

    [ https://issues.apache.org/jira/browse/CASSANDRA-3852?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14305466#comment-14305466
] 

Benedict commented on CASSANDRA-3852:
-------------------------------------

bq. It's about scope

Also making a general statement, but mentioning one consideration (difficulty of changes,
length of time to bed in, etc.) does not preclude the consideration of the other aspects without
explicit mention, such as how isolated the change is, how it fits in with other parallel changes.
My reading of that statement was that these considerations were considered likely met, and
thus the consideration fell to the mentioned considerations. Of course, I could be wrong,
and I do agree with your point in general.

> use LIFO queueing policy when queue size exceeds thresholds
> -----------------------------------------------------------
>
>                 Key: CASSANDRA-3852
>                 URL: https://issues.apache.org/jira/browse/CASSANDRA-3852
>             Project: Cassandra
>          Issue Type: Improvement
>            Reporter: Peter Schuller
>              Labels: performance
>             Fix For: 3.0
>
>
> A strict FIFO policy for queueing (between stages) is detrimental to latency and forward
progress. Whenever a node is saturated beyond incoming request rate, *all* requests become
slow. If it is consistently saturated, you start effectively timing out on *all* requests.
> A much better strategy from the point of view of latency is to serve a subset requests
quickly, and letting some time out, rather than letting all either time out or be slow.
> Care must be taken such that:
> * We still guarantee that requests are processed reasonably timely (we couldn't go strict
LIFO for example as that would result in requests getting stuck potentially forever on a loaded
node).
> * Maybe, depending on the previous point's solution, ensure that some requests bypass
the policy and get prioritized (e.g., schema migrations, or anything "internal" to a node).
> A possible implementation is to go LIFO whenever there are requests in the queue that
are older than N milliseconds (or a certain queue size, etc).
> Benefits:
> * All cases where the client is directly, or is indirectly affecting through other layers,
a system which has limited concurrency (e.g., thread pool size of X to serve some incoming
request rate), it is *much* better for a few requests to time out while most are serviced
quickly, than for all requests to become slow, as it doesn't explode concurrency. Think any
random non-super-advanced php app, ruby web app, java servlet based app, etc. Essentially,
it optimizes very heavily for improved average latencies.
> * Systems with strict p95/p99/p999 requirements on latencies should greatly benefit from
such a policy. For example, suppose you have a system at 85% of capacity, and it takes a write
spike (or has a hiccup like GC pause, blocking on a commit log write, etc). Suppose the hiccup
racks up 500 ms worth of requests. At 15% margin at steady state, that takes 500ms * 100/15
= 3.2 seconds to recover. Instead of *all* requests for an entire 3.2 second window being
slow, we'd serve requests quickly for 2.7 of those seconds, with the incoming requests during
that 500 ms interval being the ones primarily affected. The flip side though is that once
you're at the point where more than N percent of requests end up having to wait for others
to take LIFO priority, the p(100-N) latencies will actually be *worse* than without this change
(but at this point you have to consider what the root reason for those pXX requirements are).
> * In the case of complete saturation, it allows forward progress. Suppose you're taking
25% more traffic than you are able to handle. Instead of getting backed up and ending up essentially
timing out *every single request*, you will succeed in processing up to 75% of them (I say
"up to" because it depends; for example on a {{QUORUM}} request you need at least two of the
requests from the co-ordinator to succeed so the percentage is brought down) and allowing
clients to make forward progress and get work done, rather than being stuck.



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