hi! (ben just sent his mail and he covered some similar topics to me, but I'll keep my comments intact since they are slightly different)
* I think there are a lot of metrics that should be exposed for all transforms - everything from JB's list (mile number of split, throughput, reading/writing rate, number of splits, etc..) also apply to splittableDoFns. * I also think there are data source specific metrics that a given IO will want to expose (ie, things like kafka backlog for a topic.) No one on this thread has specifically addressed this, but Beam Sources & Sinks do not presently have the ability to report metrics even if a given IO writer wanted to - depending on the timeline for SplittableDoFn and the move to that infrastructure, I don't think we need that support in Sources/Sinks, but I do think we should make sure SplittableDoFn has the necessary support. * I think there are ways to do many metrics such that they are not too expensive to calculate all the time. (ie, reporting per bundle rather than per item) I think we should ask whether we want/need are metrics that are expensive to calculate before going to the effort of adding enable/disable. * I disagree with ben about showing the amount of splitting - I think especially with IOs it's useful to understand/diagnose reading problems since that's one potential source of problems, especially given that the user can write transforms that split now in SplittableDoFn. But I look forward to discussing that further +1 on talking about specific examples S On Tue, Feb 14, 2017 at 8:29 AM Jean-Baptiste Onofré <j...@nanthrax.net> wrote: > Hi Aviem > > Agree with your comments, it's pretty close to my previous ones. > > Regards > JB > > On Feb 14, 2017, 12:04, at 12:04, Aviem Zur <aviem...@gmail.com> wrote: > >Hi Ismaël, > > > >You've raised some great points. > >Please see my comments inline. > > > >On Tue, Feb 14, 2017 at 3:37 PM Ismaël Mejía <ieme...@gmail.com> wrote: > > > >> Hello, > >> > >> The new metrics API allows us to integrate some basic metrics into > >the Beam > >> IOs. I have been following some discussions about this on JIRAs/PRs, > >and I > >> think it is important to discuss the subject here so we can have more > >> awareness and obtain ideas from the community. > >> > >> First I want to thank Ben for his work on the metrics API, and Aviem > >for > >> his ongoing work on metrics for IOs, e.g. KafkaIO) that made me aware > >of > >> this subject. > >> > >> There are some basic ideas to discuss e.g. > >> > >> - What are the responsibilities of Beam IOs in terms of Metrics > >> (considering the fact that the actual IOs, server + client, usually > >provide > >> their own)? > >> > > > >While it is true that many IOs provide their own metrics, I think that > >Beam > >should expose IO metrics because: > > > >1. Metrics which help understanding performance of a pipeline which > >uses > > an IO may not be covered by the IO . > >2. Users may not be able to setup integrations with the IO's metrics to > >view them effectively (And correlate them to a specific Beam pipeline), > >but > > still want to investigate their pipeline's performance. > > > > > >> - What metrics are relevant to the pipeline (or some particular IOs)? > >Kafka > >> backlog for one could point that a pipeline is behind ingestion rate. > > > > > >I think it depends on the IO, but there is probably overlap in some of > >the > >metrics so a guideline might be written for this. > >I listed what I thought should be reported for KafkaIO in the following > >JIRA: https://issues.apache.org/jira/browse/BEAM-1398 > >Feel free to add more metrics you think are important to report. > > > > > >> > >> > >- Should metrics be calculated on IOs by default or no? > >> - If metrics are defined by default does it make sense to allow users > >to > >> disable them? > >> > > > >IIUC, your concern is that metrics will add overhead to the pipeline, > >and > >pipelines which are highly sensitive to this will be hampered? > >In any case I think that yes, metrics calculation should be > >configurable > >(Enable/disable). > >In Spark runner, for example the Metrics sink feature (not the metrics > >calculation itself, but sinks to send them to) is configurable in the > >pipeline options. > > > > > >> Well these are just some questions around the subject so we can > >create a > >> common set of practices to include metrics in the IOs and eventually > >> improve the transform guide with this. What do you think about this? > >Do you > >> have other questions/ideas? > >> > >> Thanks, > >> Ismaël > >> >