Counter of dropwizard is thread-safe. I think dropwizard metrics are implemented fairly well and used quite widely in open source projects, I personally on the side of using dropwizard metrics rather than re-implement them, unless for performance reasons. Still, I'm +1 for adding a wrapper on top of dropwizard metrics.
On Tue, Jun 14, 2016 at 10:45 PM, Till Rohrmann <trohrm...@apache.org> wrote: > +1 for the thread safe metrics. This should be a rather low hanging fruit > and easily added. > > If we decide to add a histogram, then I would also be in favour of > implementing our own version of a histogram. This avoids adding a hard > dependency on Dropwizard or another metrics library to Flink core. Adding > our own implementation would of course entail to also add a Dropwizard > wrapper for reporting. Thus, if a user component required a Dropwizard > histogram, then one could simply use the wrapper. > > Alternatively, one could also rely on external system to compute > histograms. For example, statsD supports the generation of histograms from > a stream of measurements. However, these histograms couldn't be used within > Flink. > > Implementation wise, the histogram would most likely follow the > implementation of Dropwizard's histogram: > > The basic idea is that a histogram can add samples to a reservoir which it > uses to calculate a set of statistics when queried. The statistics > comprises percentiles, mean, standard deviation and number of elements, for > example. > > The reservoir defines the strategy of how to sample the input stream. There > are different strategies conceivable: Uniform sampling, which constructs a > long term distribution of the seen elements, exponentially decaying > sampling, which favours more recent elements, sliding window or buckets. > > The question is now whether such an implementation already covers most use > cases or whether histograms should support more functionaly. Feedback is > highly appreciated :-) > > Cheers, > Till > > On Mon, Jun 13, 2016 at 6:37 PM, Stephan Ewen <se...@apache.org> wrote: > > > I think it is totally fine to add a "ThreadsafeCounter" that uses an > atomic > > long internally > > > > On Sat, Jun 11, 2016 at 7:25 PM, Steve Cosenza <scose...@twitter.com> > > wrote: > > > > > Also, we may be able to avoid the need for concurrent metrics by > > > configuring each Finagle source to use a single thread. We'll > investigate > > > the performance implications this week and update you with the results. > > > > > > Thanks, > > > Steve > > > > > > > > > On Friday, June 10, 2016, Steve Cosenza <scose...@twitter.com> wrote: > > > > > >> +Chris Hogue who is also working on operationalizing Flink with me > > >> > > >> Hi Stephan, > > >> > > >> Thanks for the background on your current implementations! > > >> > > >> While we don't require a specific implementation for histogram, > counter, > > >> or gauge, it just became clear that we'll need threadsafe versions of > > all > > >> three of these metrics. This is because our messaging source is > > implemented > > >> using Finagle, and Finagle expects to be able to emit stats > concurrently > > >> from its managed threads. > > >> > > >> That being said, if adding threadsafe versions of the Flink counters > is > > >> not an option, we'd also be fine with directly reading and writing > from > > the > > >> singleton Codahale MetricsRegistry that you start up in each > > TaskManager. > > >> > > >> Thanks, > > >> Steve > > >> > > >> On Fri, Jun 10, 2016 at 7:10 AM, Stephan Ewen <se...@apache.org> > wrote: > > >> > > >>> A recent discussion brought up the point of adding a "histogram" > metric > > >>> type to Flink. This open thread is to gather some more of the > > requirements > > >>> for that metric. > > >>> > > >>> The most important question is whether users need Flink to offer > > >>> specific implementations of "Histogram", like for example the " > > >>> com.codahale.metrics.Histogram", or if a " > > >>> org.apache.flink.metrics.Histogram" interface would work as well. > > >>> The histogram could still be reported for example via dropwizard > > >>> reporters. > > >>> > > >>> *Option (1):* If a Flink Histogram works as well, it would be simple > to > > >>> add one. The dropwizard reporter would need to wrap the Flink > > Histogram for > > >>> reporting. > > >>> > > >>> *Option (2)*: If the code needs the specific Dropwizard Histogram > type, > > >>> then one would need a wrapper class that makes a Flink Histogram look > > like > > >>> a dropwizard histogram. > > >>> > > >>> ---------- > > >>> > > >>> As a bit of background for the discussion, here are some thoughts > > behind > > >>> the way that Metrics are currently implemented in Flink. > > >>> > > >>> - The metric types in Flink are independent from libraries like > > >>> "dropwizard" to reduce dependencies and retain freedom to swap > > >>> implementations. > > >>> > > >>> - Metric reporting allows to reuse reporters from dropwizard > > >>> > > >>> - Some Flink metric implementations are also more lightweight than > > for > > >>> example in dropwizard. Counters for example are not thread safe, but > > do not > > >>> impose memory barriers. That is important for metrics deep in the > > streaming > > >>> runtime. > > >>> > > >>> > > >>> > > >> > > > > > > -- > > > -Steve > > > > > > Sent from Gmail Mobile > > > > > >
