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Re: Metrics: Non-cumulative values for Distribution


I assumed that. Thanks for confirming it. This is what I end up doing, cumulative metrics via Metrics API and metrics with discarding panes custom alongside data. Problem is, that is is not natural and I have to "manually" sync the way I write these to target time series database. 

I understand that metrics are global as you are saying and not bounded to windows, but what I do at the end is still global window + discard fired panes. Would be great to have same option on Metrics API. Maybe possibility to consider in the new feature of metrics reporting independent from runners.

P.S.: I tried to do all metrics custom via side outputs, but I got quite noticeable performance degradation even when using combine, which I expected to reduce data considerable before shuffle.

On Tue, Jun 19, 2018 at 11:13 AM Etienne Chauchot <echauchot@xxxxxxxxxx> wrote:
Hi Scott and Jozef,

Sorry for the late answer, I missed the email.

Well, MetricsPusher will aggregate the metrics just as PipelineResult.metrics() does but it will do so at given configurable intervals and export the values. It means that if you configure the export to be every 5s, you will get the aggregated (between workers) value of the distribution every 5 sec. It will not be reset. For ex, at t = 0 + 5s if the max received until then is 10, then the value exported will be 10. Then, at t = 0 + 10s, it the distribution was updated with a 5 it will still report 10. Then at t = 0 + 15s, if the distribution was updated with a 11, then it will export 11.
As metrics are global and not bound to windows like PCollection elements, you will always have the cumulative value (essence of the distribution metric). So I agree with Scott, better for your use case is to treat the metric as if it was an element and compute it donwstream so that it could be bound to a window.

Etienne



Le samedi 02 juin 2018 à 08:01 +0300, Jozef Vilcek a écrit :
Hi Scott,

nothing special about the use-case. Just want to monitor upper and lower bound for some data floating in operator. 
The "report interval" is right now 30 seconds and it is independent of business logic. It is the one mentionedd here:

and value set with respect to how granular and fast do I want to see changes on what is going on in the pipeline compared to how much resources in time-series database I dedicate to it.

Thanks for looking into it   

On Fri, Jun 1, 2018 at 7:49 PM, Scott Wegner <swegner@xxxxxxxxxx> wrote:
Hi Jozef,

Can you elaborate a bit on your use-case; is the "report interval" a concept you depend on for your data processing logic?

The Metrics API in general is designed to serve data to the executing runner or external service which can then manage the aggregation and reporting through PipelineResult or monitoring UI. Etienne, do you know if MetricsPusher [1] would help at all?

I suspect you'd be better off calculating the Min/Max values in a downstream Combine transform and set the Windowing/Trigger strategy which captures the report interval you're looking for.


On Fri, Jun 1, 2018 at 3:39 AM Jozef Vilcek <jozo.vilcek@xxxxxxxxx> wrote:
Hi,

I am running a streaming job on flink and want to monitor MIN and MAX ranges of a metric floating through operator. I did it via  org.apache.beam.sdk.metrics.Distribution

Problem is, that it seems to report only cumulative values. What I would want instead is discrete report for MIN / MAX which were seen in each particular report interval.

Is there a way to get non-cumulative  data from beam distribution metrics? What are my options?
The obvious workaround is to track it "manually" and submit  2 gauge metrics. I hope there is a better way ... Is there?