> our histograms when built with a Meter use a ExponentiallyDecayingReservoir > but our histograms built directly use DecayingEstimatedHistogramReservoir > algorithm
Meters dont use a decaying reservoir, they use EMWA <https://github.com/dropwizard/metrics/blob/4.1-development/metrics-core/src/main/java/com/codahale/metrics/EWMA.java>. Did you mean Timers? They use the DecayingEH <https://github.com/apache/cassandra/blob/9a47974d6378b62dd2cdb2d3e509374b002caa2c/src/java/org/apache/cassandra/metrics/CassandraMetricsRegistry.java#L94>'s as well, nothing should be using the decaying reservoir atm afaik beyond the dynamic snitch. values and recentValues gives access to the EH beneath (lower memory, slightly faster than HDR but with less features and possibly worse error bounds) the Decaying EH. The decaying EH was added in CASSANDRA-11752 <https://issues.apache.org/jira/browse/CASSANDRA-11752> because after moving from reservoir (randomly throws out data means it could lose everything in 99th percentile for example - in CASSANDRA-5667) to histograms, it did not provide any recency in the tools output which was difficult for adhoc analysis. The inverse is getting an "approximate last 1 min" is lossy and inaccurate for tooling/graphing/SLAs so both are supported. A little bit of history in the metrics I talked about in https://www.youtube.com/watch?v=vcniEFmFY0E <https://www.youtube.com/watch?v=vcniEFmFY0E> (includes histogram storage issues). I think metrics drastically changing every other year has made things increasingly complex while trying to maintain backwards support and not wanting to break everyones tooling at same time. If we could improve the performance of the metrics without changing everything (again) I think that would be ideal for us operations folk who consume the metrics. Could an attempt at tuning existing be made first before another rewrite? Chris > On Feb 28, 2018, at 7:47 AM, Michael Burman <mibur...@redhat.com> wrote: > > Hi, > > I wrote CASSANDRA-14281 for the initial idea and where I ended up with my > current prototype. This maintains the current layout of the JMX metrics so it > shouldn't be visible to users. Should, because I couldn't really find any > definition of our metrics. For example, our histograms when built with a > Meter use a ExponentiallyDecayingReservoir but our histograms built directly > use DecayingEstimatedHistogramReservoir algorithm. So these two histograms > behave differently, but the JMX requester has no idea which way they're built. > > Also, recentValues() for example does not use either behavior, but actually > follows two different behaviors again (!). CASSANDRA-13642 added the > recentValues() which uses values() underneath. The ticket itself did not > really describe what's the behavior that should be exposed (luckily it was in > 4.0, so it technically is not in any released version yet). > > I doubt anyone really knows how our metrics are supposed to work? What if I > change how they decay? Or should we use a single decay strategy for all our > histograms (and related) ? > > I guess my ticket became suddenly slightly more complex ;) > > - Micke > > On 02/28/2018 12:25 AM, Nate McCall wrote: >> Hi Micke, >> There is some good research in here - have you had a chance to create >> some issues in Jira from this? >> >> On Fri, Feb 23, 2018 at 6:28 AM, Michael Burman <mibur...@redhat.com> wrote: >>> Hi, >>> >>> I was referring to this article by Shipilev (there are few small issues >>> forgotten in that url you pasted): >>> >>> https://shipilev.net/blog/2014/nanotrusting-nanotime/ >>> >>> And his lovely recommendation on it: "System.nanoTime is as bad as >>> String.intern now: you can use it, but use it wisely. ". And Cassandra uses >>> it quite a lot in the write path at least. There isn't necessarily a better >>> option in Java for it, but for that reason we shouldn't push them everywhere >>> in the code "for fun". >>> >>> - Micke >>> >>> >>> >>> On 02/22/2018 06:08 PM, Jeremiah D Jordan wrote: >>>> re: nanoTime vs currentTimeMillis there is a good blog post here about the >>>> timing of both and how your choice of Linux clock source can drastically >>>> effect the speed of the calls, and also showing that in general on linux >>>> there is no perf improvement for one over the other. >>>> http://pzemtsov.github.io/2017/07/23/the-slow-currenttimemillis.html >>>> >>>>> On Feb 22, 2018, at 11:01 AM, Blake Eggleston <beggles...@apple.com> >>>>> wrote: >>>>> >>>>> Hi Micke, >>>>> >>>>> This is really cool, thanks for taking the time to investigate this. I >>>>> believe the metrics around memtable insert time come in handy in >>>>> identifying >>>>> high partition contention in the memtable. I know I've been involved in a >>>>> situation over the past year where we got actionable info from this >>>>> metric. >>>>> Reducing resolution to milliseconds is probably a no go since most things >>>>> in >>>>> this path should complete in less than a millisecond. >>>>> >>>>> Revisiting the use of the codahale metrics in the hot path like this >>>>> definitely seems like a good idea though. I don't think it's been >>>>> something >>>>> we've talked about a lot, and it definitely looks like we could benefit >>>>> from >>>>> using something more specialized here. I think it's worth doing, >>>>> especially >>>>> since there won't be any major changes to how we do threading in 4.0. It's >>>>> probably also worth opening a JIRA and investigating the calls to nano >>>>> time. >>>>> We at least need microsecond resolution here, and there could be something >>>>> we haven't thought of? It's worth a look at least. >>>>> >>>>> Thanks, >>>>> >>>>> Blake >>>>> >>>>> On 2/22/18, 6:10 AM, "Michael Burman" <mibur...@redhat.com> wrote: >>>>> >>>>> Hi, >>>>> >>>>> I wanted to get some input from the mailing list before making a JIRA >>>>> and potential fixes. I'll touch the performance more on latter part, >>>>> but >>>>> there's one important question regarding the write latency metric >>>>> recording place. Currently we measure the writeLatency (and metric >>>>> write >>>>> sampler..) in ColumnFamilyStore.apply() and this is also the metric >>>>> we >>>>> then replicate to Keyspace metrics etc. >>>>> >>>>> This is an odd place for writeLatency. Not to mention it is in a >>>>> hot-path of Memtable-modifications, but it also does not measure the >>>>> real write latency, since it completely ignores the CommitLog latency >>>>> in >>>>> that same process. Is the intention really to measure >>>>> Memtable-modification latency only or the actual write latencies? >>>>> >>>>> Then the real issue.. this single metric is a cause of huge overhead >>>>> in >>>>> Memtable processing. There are several metrics / events in the CFS >>>>> apply >>>>> method, including metric sampler, storageHook reportWrite, >>>>> colUpdateTimeDeltaHistogram and metric.writeLatency. These are not >>>>> free >>>>> at all when it comes to the processing. I made a small JMH benchmark >>>>> here: >>>>> https://gist.github.com/burmanm/b5b284bc9f1d410b1d635f6d3dac3ade >>>>> that I'll be referring to. >>>>> >>>>> The most offending of all these metrics is the writeLatency metric. >>>>> What >>>>> it does is update the latency in codahale's timer, doing a histogram >>>>> update and then going through all the parent metrics also which >>>>> update >>>>> the keyspace writeLatency and globalWriteLatency. When measuring the >>>>> performance of Memtable.put with parameter of 1 partition (to reduce >>>>> the >>>>> ConcurrentSkipListMap search speed impact - that's separate issue and >>>>> takes a little bit longer to solve although I've started to prototype >>>>> something..) on my machine I see 1.3M/s performance with the metric >>>>> and >>>>> when it is disabled the performance climbs to 4M/s. So the overhead >>>>> for >>>>> this single metric is ~2/3 of total performance. That's insane. My >>>>> perf >>>>> stats indicate that the CPU is starved as it can't get enough data >>>>> in. >>>>> >>>>> Removing the replication from TableMetrics to the Keyspace & global >>>>> latencies in the write time (and doing this when metrics are >>>>> requested >>>>> instead) improves the performance to 2.1M/s on my machine. It's an >>>>> improvement, but it's still huge amount. Even when we pressure the >>>>> ConcurrentSkipListMap with 100 000 partitions in one active Memtable, >>>>> the performance drops by about ~40% due to this metric, so it's never >>>>> free. >>>>> >>>>> i did not find any discussion replacing the metric processing with >>>>> something faster, so has this been considered before? At least for >>>>> these >>>>> performance sensitive ones. The other issue is obviously the use of >>>>> System.nanotime() which by itself is very slow (two System.nanotime() >>>>> calls eat another ~1M/s from the performance) >>>>> >>>>> My personal quick fix would be to move writeLatency to >>>>> Keyspace.apply, >>>>> change write time aggregates to read time processing (metrics are >>>>> read >>>>> less often than we write data) and maybe even reduce the nanotime -> >>>>> currentTimeMillis (even given it's relative lack of precision). That >>>>> is >>>>> - if these metrics make any sense at all at CFS level? Maybe these >>>>> should be measured from the network processing time (including all >>>>> the >>>>> deserializations and such) ? Especially if at some point the smarter >>>>> threading / eventlooping changes go forward (in which case they might >>>>> sleep at some "queue" for a while). >>>>> >>>>> - Micke >>>>> >>>>> >>>>> --------------------------------------------------------------------- >>>>> To unsubscribe, e-mail: dev-unsubscr...@cassandra.apache.org >>>>> For additional commands, e-mail: dev-h...@cassandra.apache.org >>>>> >>>>> >>>>> >>>>> >>>>> >>>>> --------------------------------------------------------------------- >>>>> To unsubscribe, e-mail: dev-unsubscr...@cassandra.apache.org >>>>> For additional commands, e-mail: dev-h...@cassandra.apache.org >>>>> >>>> --------------------------------------------------------------------- >>>> To unsubscribe, e-mail: dev-unsubscr...@cassandra.apache.org >>>> For additional commands, e-mail: dev-h...@cassandra.apache.org >>>> >>> >>> --------------------------------------------------------------------- >>> To unsubscribe, e-mail: dev-unsubscr...@cassandra.apache.org >>> For additional commands, e-mail: dev-h...@cassandra.apache.org >>> >> --------------------------------------------------------------------- >> To unsubscribe, e-mail: dev-unsubscr...@cassandra.apache.org >> For additional commands, e-mail: dev-h...@cassandra.apache.org >> > > > --------------------------------------------------------------------- > To unsubscribe, e-mail: dev-unsubscr...@cassandra.apache.org > For additional commands, e-mail: dev-h...@cassandra.apache.org >
