Hi Ben : D

Sure, that's reasonable. And perhaps I started the discussion in the wrong
direction. I'm not questioning the utility of Gauge metrics.

What I'm saying is that Beam only supports integers,, but Gauges are
aggregated by dropping old values depending on their update times; so it
might be desirable to not restrict the data type to just integers.


On Fri, Apr 6, 2018 at 9:19 AM Ben Chambers <bchamb...@apache.org> wrote:

> See for instance how gauge metrics are handled in Prometheus, Datadog and
> Stackdriver monitoring. Gauges are perfect for use in distributed systems,
> they just need to be properly labeled. Perhaps we should apply a default
> tag or allow users to specify one.
> On Fri, Apr 6, 2018, 9:14 AM Ben Chambers <bchamb...@apache.org> wrote:
>> Some metrics backend label the value, for instance with the worker that
>> sent it. Then the aggregation is latest per label. This makes it useful for
>> holding values such as "memory usage" that need to hold current value.
>> On Fri, Apr 6, 2018, 9:00 AM Scott Wegner <sweg...@google.com> wrote:
>>> +1 on the proposal to support a "String" gauge.
>>> To expand a bit, the current API doesn't make it clear that the gauge
>>> value is based on local state. If a runner chooses to parallelize a DoFn
>>> across many workers, each worker will have its own local Gauge metric and
>>> its updates will overwrite other values. For example, from the API it looks
>>> like you could use a gauge to implement your own element count metric:
>>> long count = 0;
>>> @ProcessElement
>>> public void processElement(ProcessContext c) {
>>>   myGauge.set(++count);
>>>   c.output(c.element());
>>> }
>>> This looks correct, but each worker has their own local 'count' field,
>>> and gauge metric updates from parallel workers will overwrite each other
>>> rather than get aggregated. So the final value would be "the number of
>>> elements processed on one of the workers". (The correct implementation uses
>>> a Counter metric).
>>> I would be in favor of replacing the existing Gauge.set(long) API with
>>> the String version and removing the old one. This would be a breaking
>>> change. However this is a relatively new API and is still marked
>>> @Experimental. Keeping the old API would retain the potential confusion.
>>> It's better to simplify the API surface: having two APIs makes it less
>>> clear which one users should choose.
>>> On Fri, Apr 6, 2018 at 8:28 AM Pablo Estrada <pabl...@google.com> wrote:
>>>> Hello all,
>>>> As I was working on adding support for Gauges in Dataflow, some noted
>>>> that Gauge is a fairly unusual kind of metric for a distributed
>>>> environment, since many workers will report different values and stomp on
>>>> each other's all the time.
>>>> We also looked at Flink and Dropwizard Gauge metrics [1][2], and we
>>>> found that these use generics, and Flink explicitly mentions that a
>>>> toString implementation is required[3].
>>>> With that in mind, I'm thinking that it might make sense to 1) expand
>>>> Gauge to support string values (keep int-based API for backwards
>>>> compatibility), and migrate it to use string behind the covers.
>>>> What does everyone think about this?
>>>> Best
>>>> -P.
>>>> 1 -
>>>> https://ci.apache.org/projects/flink/flink-docs-release-1.3/monitoring/metrics.html#metric-types
>>>> 2 - https://metrics.dropwizard.io/3.1.0/manual/core/#gauges
>>>> 3 -
>>>> https://github.com/apache/flink/blob/master/docs/monitoring/metrics.md#gauge
>>>> JIRA issue for Gauge metrics -
>>>> https://issues.apache.org/jira/browse/BEAM-1616
>>>> --
>>>> Got feedback? go/pabloem-feedback
>>>> <https://goto.google.com/pabloem-feedback>
>>> --
>>> Got feedback? http://go/swegner-feedback
>> --
Got feedback? go/pabloem-feedback

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