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https://issues.apache.org/jira/browse/CASSANDRA-3852?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14366586#comment-14366586
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Jonathan Ellis commented on CASSANDRA-3852:
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bq. It's worth pointing out this change won't necessarily help tail latencies,
it will just shift the tail
I think the idea is not so much to improve latencies, so much as to allow
*some* work to succeed under overload conditions, vs FIFO where it's possible
for every request to time out as it's processed. Taking the newest to work on
instead of the oldest avoids this scenario.
> 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: 3.1
>
>
> 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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