Re: [DISCUSS] Bridge beam metrics to underlying runners to support metrics reporters?
Hi guys, I've drafted a simple one-page doc for my proposal, please help review, comments are welcome: https://docs.google.com/document/d/1-35iyCIJ9P4EQONlakgXBFRGUYoOLanq2Uf2sw5EjJw/edit?usp=sharing On Sat, Jun 24, 2017 at 1:31 AM, Ben Chambers <bchamb...@apache.org> wrote: > I think the distinction between metrics being reported (the API we give > users to create Metrics) from getting metrics out of (currently either > using the PipelineResult to query results or connecting to an external > metric store) is important. > > There is an additional distinction to be made in data processing systems -- > specifically whether the metric value represents a physical quantity such > as the number of RPCs issued during processing which should be counted > across all attempts at processing elements or a logical value such as the > number of elements processed that should only be aggregated across the > successful attempt at an element. > > This distinction requires deeper runner involvement since that is the only > point that knows for sure whether an element has been successfully > processed. It is also the only form of Metrics that are not subject to > potential data loss (over or under counting). > > Allowing Metrics to preserve this distinction and each runner to choose > which of committed and attempted Metrics to support (or possibly even both) > is part of the reason why the existing API is the way it is. > > On Fri, Jun 23, 2017 at 2:41 AM Ismaël Mejía <ieme...@gmail.com> wrote: > > > That seems like a great idea (improving the current metrics design), I > > suppose there is a tradeoff between complexity and simplicity, and > > when I read the design document I think that some design decisions > > were done for the sake of simplicity, however as dropwizard is the > > 'de-facto' standard for metrics (at least in the java world), then it > > makes sense to align more with it, and that also reminds me that Aviem > > also wanted to add dropwizard's EWMA to the metrics API, so there is > > still some work to do. > > > > > > On Fri, Jun 23, 2017 at 11:00 AM, Cody Innowhere <e.neve...@gmail.com> > > wrote: > > > Hi Ismaël, > > > Yes Distribution is similar to codahale's Histogram without the > > quantiles, > > > and what I meant "adding support of Histogram" might be extending > > > Distribution > > > so that quantiles can be supported. > > > I think in metrics area dropwizard metrics is more or less a standard > and > > > many frameworks have direct support for this including Spark, Flink and > > > JStorm > > > (Well I happen to be the developer of JStorm metrics and our internal > > alert > > > engine), and you're right if beam metrics are compatible with > dropwizard > > we > > > can surely benefit from it. > > > > > > I've also read the design doc and IMHO it's not easy to support > > > Meter/Histogram (currently Distribution is a bit too simple). I'm > > thinking > > > about adding full > > > support of dropwizard metrics and will come up with a doc later so that > > we > > > can discuss this in detail. > > > > > > On Fri, Jun 23, 2017 at 4:30 PM, Ismaël Mejía <ieme...@gmail.com> > wrote: > > > > > >> Cody not sure if I follow, but isn't Distribution on Beam similar to > > >> codahale/dropwizard's HIstogram (without the quantiles) ? > > >> > > >> Meters are also in the plan but not implemented yet, see the Metrics > > >> design doc: > > >> https://s.apache.org/beam-metrics-api > > >> > > >> If I understand what you want is to have some sort of compatibility > > >> with dropwizard so we can benefit of their sinks ? Is this or I am > > >> misreading it, if so, that would be neat, however the only problem is > > >> the way the aggregation phase passes on Beam because of distribution > > >> vs dropwizard (not sure if they have some implementation that takes > > >> distribution into account). > > >> > > >> Improving metrics is in the agenda and contributions are welcomed > > >> because the API is still evolving and we can have new ideas as part of > > >> it. > > >> > > >> Regards, > > >> Ismaël > > >> > > >> > > >> On Fri, Jun 23, 2017 at 9:29 AM, Cody Innowhere <e.neve...@gmail.com> > > >> wrote: > > >> > Yes I agree with you and sorry for messing them together in this > > >> discussion. > > >>
Re: [DISCUSS] Bridge beam metrics to underlying runners to support metrics reporters?
Yes I agree with you and sorry for messing them together in this discussion. I just wonder if someone plans to support Meters/Histograms in the near future. If so, we might need to modify metrics a bit in beam sdk IMHO, that's the reason I started this discussion. On Fri, Jun 23, 2017 at 3:21 PM, Jean-Baptiste Onofré <j...@nanthrax.net> wrote: > Hi Codi, > > I think there are two "big" topics around metrics: > > - what we collect > - where we send the collected data > > The "generic metric sink" (BEAM-2456) is for the later: we don't really > change/touch the collected data (or maybe just in case of data format) we > send to the sink. > > The Meters/Histograms is both more the collected data IMHO. > > Regards > JB > > > On 06/23/2017 04:09 AM, Cody Innowhere wrote: > >> Hi JB, >> Glad to hear that. >> Still, I'm thinking about adding support of Meters & Histograms(maybe >> extending Distribution). As the discussion mentions, problem is that >> Meter/Histogram >> cannot be updated directly in current way because their internal data >> decays after time. Do you plan to refactor current implementation so that >> they can be supported while working on the generic metric sink? >> >> On Thu, Jun 22, 2017 at 9:37 PM, Jean-Baptiste Onofré <j...@nanthrax.net> >> wrote: >> >> Hi >>> >>> Agree with Aviem and yes actually I'm working on a generic metric sink. I >>> created a Jira about that. I'm off today, I will send some details asap. >>> >>> Regards >>> JB >>> >>> On Jun 22, 2017, 15:16, at 15:16, Aviem Zur <aviem...@gmail.com> wrote: >>> >>>> Hi Cody, >>>> >>>> Some of the runners have their own metrics sink, for example Spark >>>> runner >>>> uses Spark's metrics sink which you can configure to send the metrics >>>> to >>>> backends such as Graphite. >>>> >>>> There have been ideas floating around for a Beam metrics sink extension >>>> which will allow users to send Beam metrics to various metrics >>>> backends, I >>>> believe @JB is working on something along these lines. >>>> >>>> On Thu, Jun 22, 2017 at 2:00 PM Cody Innowhere <e.neve...@gmail.com> >>>> wrote: >>>> >>>> Hi guys, >>>>> Currently metrics are implemented in runners/core as CounterCell, >>>>> GaugeCell, DistributionCell, etc. If we want to send metrics to >>>>> >>>> external >>>> >>>>> systems via metrics reporter, we would have to define another set of >>>>> metrics, say, codahale metrics, and update codahale metrics >>>>> >>>> periodically >>>> >>>>> with beam sdk metrics, which is inconvenient and inefficient. >>>>> >>>>> Another problem is that Meter/Histogram cannot be updated directly in >>>>> >>>> this >>>> >>>>> way because their internal data decays after time. >>>>> >>>>> My opinion would be bridge beam sdk metrics to underlying runners so >>>>> >>>> that >>>> >>>>> updates would directly apply to underlying runners (Flink, Spark, >>>>> >>>> etc) >>>> >>>>> without conversion. >>>>> >>>>> Specifically, currently we already delegate >>>>> Metrics.counter/gauge/distribution to >>>>> >>>> DelegatingCounter/Gauge/Distribution, >>>> >>>>> which uses MetricsContainer to store the actual metrics with the >>>>> implementation of MetricsContainerImpl. If we can add an API in >>>>> MetricsEnvironment to allow runners to override the default >>>>> >>>> implementation, >>>> >>>>> say, for flink, we have FlinkMetricsContainerImpl, then all metric >>>>> >>>> updates >>>> >>>>> will directly apply to metrics in FlinkMetricsContainerImpl without >>>>> intermediate conversion and updates. And since the metrics are >>>>> runner-specific, it would be a lot easier to support metrics >>>>> >>>> reporters as >>>> >>>>> well as Meters/Histograms. >>>>> >>>>> What do you think? >>>>> >>>>> >>> >> > -- > Jean-Baptiste Onofré > jbono...@apache.org > http://blog.nanthrax.net > Talend - http://www.talend.com >
Re: [DISCUSS] Bridge beam metrics to underlying runners to support metrics reporters?
Hi JB, Glad to hear that. Still, I'm thinking about adding support of Meters & Histograms(maybe extending Distribution). As the discussion mentions, problem is that Meter/Histogram cannot be updated directly in current way because their internal data decays after time. Do you plan to refactor current implementation so that they can be supported while working on the generic metric sink? On Thu, Jun 22, 2017 at 9:37 PM, Jean-Baptiste Onofré <j...@nanthrax.net> wrote: > Hi > > Agree with Aviem and yes actually I'm working on a generic metric sink. I > created a Jira about that. I'm off today, I will send some details asap. > > Regards > JB > > On Jun 22, 2017, 15:16, at 15:16, Aviem Zur <aviem...@gmail.com> wrote: > >Hi Cody, > > > >Some of the runners have their own metrics sink, for example Spark > >runner > >uses Spark's metrics sink which you can configure to send the metrics > >to > >backends such as Graphite. > > > >There have been ideas floating around for a Beam metrics sink extension > >which will allow users to send Beam metrics to various metrics > >backends, I > >believe @JB is working on something along these lines. > > > >On Thu, Jun 22, 2017 at 2:00 PM Cody Innowhere <e.neve...@gmail.com> > >wrote: > > > >> Hi guys, > >> Currently metrics are implemented in runners/core as CounterCell, > >> GaugeCell, DistributionCell, etc. If we want to send metrics to > >external > >> systems via metrics reporter, we would have to define another set of > >> metrics, say, codahale metrics, and update codahale metrics > >periodically > >> with beam sdk metrics, which is inconvenient and inefficient. > >> > >> Another problem is that Meter/Histogram cannot be updated directly in > >this > >> way because their internal data decays after time. > >> > >> My opinion would be bridge beam sdk metrics to underlying runners so > >that > >> updates would directly apply to underlying runners (Flink, Spark, > >etc) > >> without conversion. > >> > >> Specifically, currently we already delegate > >> Metrics.counter/gauge/distribution to > >DelegatingCounter/Gauge/Distribution, > >> which uses MetricsContainer to store the actual metrics with the > >> implementation of MetricsContainerImpl. If we can add an API in > >> MetricsEnvironment to allow runners to override the default > >implementation, > >> say, for flink, we have FlinkMetricsContainerImpl, then all metric > >updates > >> will directly apply to metrics in FlinkMetricsContainerImpl without > >> intermediate conversion and updates. And since the metrics are > >> runner-specific, it would be a lot easier to support metrics > >reporters as > >> well as Meters/Histograms. > >> > >> What do you think? > >> >
Re: Beam spark 2.x runner status
or us, but maybe the best approach would be >>>>>>> to continue the work only in the spark 2 runner (both refining the >>>>>>> RDD >>>>>>> based translator and starting to create the Dataset one there that >>>>>>> co-exist until the DataSet API is mature enough) and keep the spark 1 >>>>>>> runner only for bug-fixes for the users who are still using it (like >>>>>>> this we don’t have to keep backporting stuff). Do you see any other >>>>>>> particular issue? >>>>>>> >>>>>>> Ismaël >>>>>>> >>>>>>> On Wed, Mar 15, 2017 at 3:39 PM, Amit Sela <amitsel...@gmail.com> >>>>>>> >>>>>> wrote: >>>>> >>>>>> So you propose to have the Spark 2 branch a clone of the current one >>>>>>>> >>>>>>> with >>>>> >>>>>> adaptations around Context->Session, Accumulator->AccumulatorV2 etc. >>>>>>>> >>>>>>> while >>>>>>> >>>>>>>> still using the RDD API ? >>>>>>>> >>>>>>>> I think that having another Spark runner is great if it has value, >>>>>>>> otherwise, let's just bump the version. >>>>>>>> My idea of having another runner for Spark was not to support more >>>>>>>> >>>>>>> versions >>>>>>> >>>>>>>> - we should always support the most popular version in terms of >>>>>>>> compatibility - the idea was to try and make Beam work with >>>>>>>> >>>>>>> Structured >>> >>>> Streaming, which is still not fully mature so that's why we're not >>>>>>>> >>>>>>> heavily >>>>>>> >>>>>>>> investing there. >>>>>>>> >>>>>>>> We could think of starting to migrate the Spark 1 runner to Spark 2 >>>>>>>> >>>>>>> and >>>>> >>>>>> follow with Dataset API support feature-by-feature as ot advances, >>>>>>>> >>>>>>> but I >>>>> >>>>>> think most Spark installations today still run 1.X, or am I wrong ? >>>>>>>> >>>>>>>> On Wed, Mar 15, 2017 at 4:26 PM Ismaël Mejía <ieme...@gmail.com> >>>>>>>> >>>>>>> wrote: >>>>> >>>>>> BIG +1 JB, >>>>>>>>> >>>>>>>>> If we can just jump the version number with minor changes staying >>>>>>>>> as >>>>>>>>> close as possible to the current implementation for spark 1 we can >>>>>>>>> >>>>>>>> go >>> >>>> faster and offer in principle the exact same support but for version >>>>>>>>> 2. >>>>>>>>> >>>>>>>>> I know that the advanced streaming stuff based on the DataSet API >>>>>>>>> won't be there but with this common canvas the community can >>>>>>>>> iterate >>>>>>>>> to create a DataSet based translator at the same time. In >>>>>>>>> particular >>>>>>>>> >>>>>>>> I >>>>> >>>>>> consider the most important thing is that the spark 2 branch should >>>>>>>>> not live for long time, this should be merged into master really >>>>>>>>> >>>>>>>> fast >>> >>>> for the benefit of everybody. >>>>>>>>> >>>>>>>>> Ismaël >>>>>>>>> >>>>>>>>> >>>>>>>>> On Wed, Mar 15, 2017 at 1:57 PM, Jean-Baptiste Onofré < >>>>>>>>> >>>>>>>> j...@nanthrax.net> >>>>> >>>>>> wrote: >>>>>>>>> >>>>>>>>>> Hi Amit, >>>>>>>>>> >>>>>>>>>> What do you think of the following: >>>>>>>>>> >>>>>>>>>> - in the mean time that you reintroduce the Spark 2 branch, what >>>>>>>>>> >>>>>>>>> about >>>>> >>>>>> "extending" the version in the current Spark runner ? Still using >>>>>>>>>> RDD/DStream, I think we can support Spark 2.x even if we don't yet >>>>>>>>>> >>>>>>>>> leverage >>>>>>>>> >>>>>>>>>> the new provided features. >>>>>>>>>> >>>>>>>>>> Thoughts ? >>>>>>>>>> >>>>>>>>>> Regards >>>>>>>>>> JB >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> On 03/15/2017 07:39 PM, Amit Sela wrote: >>>>>>>>>> >>>>>>>>>>> Hi Cody, >>>>>>>>>>> >>>>>>>>>>> I will re-introduce this branch soon as part of the work on >>>>>>>>>>> >>>>>>>>>> BEAM-913 >>>>> >>>>>> <https://issues.apache.org/jira/browse/BEAM-913>. >>>>>>>>>>> For now, and from previous experience with the mentioned branch, >>>>>>>>>>> >>>>>>>>>> batch >>>>>>> >>>>>>>> implementation should be straight-forward. >>>>>>>>>>> Only issue is with streaming support - in the current runner >>>>>>>>>>> >>>>>>>>>> (Spark >>>>> >>>>>> 1.x) >>>>>>> >>>>>>>> we >>>>>>>>>>> have experimental support for windows/triggers and we're working >>>>>>>>>>> >>>>>>>>>> towards >>>>>>> >>>>>>>> full streaming support. >>>>>>>>>>> With Spark 2.x, there is no "general-purpose" stateful operator >>>>>>>>>>> >>>>>>>>>> for >>>>> >>>>>> the >>>>>>> >>>>>>>> Dataset API, so I was waiting to see if the new operator >>>>>>>>>>> <https://github.com/apache/spark/pull/17179> planned for next >>>>>>>>>>> >>>>>>>>>> version >>>>>>> >>>>>>>> could >>>>>>>>>>> help with that. >>>>>>>>>>> >>>>>>>>>>> To summarize, I will introduce a skeleton for the Spark 2 runner >>>>>>>>>>> >>>>>>>>>> with >>>>> >>>>>> batch >>>>>>>>>>> support as soon as I can as a separate branch. >>>>>>>>>>> >>>>>>>>>>> Thanks, >>>>>>>>>>> Amit >>>>>>>>>>> >>>>>>>>>>> On Wed, Mar 15, 2017 at 9:07 AM Cody Innowhere < >>>>>>>>>>> >>>>>>>>>> e.neve...@gmail.com> >>>>> >>>>>> wrote: >>>>>>>>>>> >>>>>>>>>>> Hi guys, >>>>>>>>>>>> Is there anybody who's currently working on Spark 2.x runner? A >>>>>>>>>>>> >>>>>>>>>>> old >>>>> >>>>>> PR >>>>>>> >>>>>>>> for >>>>>>>>>>>> spark 2.x runner was closed a few days ago, so I wonder what's >>>>>>>>>>>> >>>>>>>>>>> the >>>>> >>>>>> status >>>>>>>>> >>>>>>>>>> now, and is there a roadmap for this? >>>>>>>>>>>> Thanks~ >>>>>>>>>>>> >>>>>>>>>>>> -- >>>>>>>>>> Jean-Baptiste Onofré >>>>>>>>>> jbono...@apache.org >>>>>>>>>> http://blog.nanthrax.net >>>>>>>>>> Talend - http://www.talend.com >>>>>>>>>> >>>>>>>>> >>> >>> >>> >> > -- > Jean-Baptiste Onofré > jbono...@apache.org > http://blog.nanthrax.net > Talend - http://www.talend.com >
