Sorry for the late response. I prefer to use `table.exec.udf-metric-enabled` as the option name.
Best, Shengkai Weiqing Yang <yangweiqing...@gmail.com> 于2025年8月13日周三 23:54写道： > Hi Shengkai, Alan, Xuyang, and all, > > Since there have been no further objections, I’ll proceed to start the VOTE > on this proposal shortly. > > Thanks, > Weiqing > > On Thu, Jul 31, 2025 at 10:26 PM Weiqing Yang <yangweiqing...@gmail.com> > wrote: > > > Hi Shengkai, Alan and Xuyang, > > > > Just checking in - do you have any concerns or feedback? > > > > If there are no further objections from anyone, I’ll mark the FLIP as > > ready for voting. > > > > > > Best, > > Weiqing > > > > > > On Mon, Jul 14, 2025 at 9:10 PM Weiqing Yang <yangweiqing...@gmail.com> > > wrote: > > > >> Hi Xuyang, > >> > >> Thank you for reviewing the proposal! > >> > >> I’m planning to use: *udf.metrics.process-time* and > >> *udf.metrics.exception-count*. These follow the naming convention used > >> in Flink (e.g., RocksDB native metrics > >> < > https://nightlies.apache.org/flink/flink-docs-master/docs/deployment/config/#rocksdb-native-metrics > >). > >> I’ve added these names to the proposal doc. > >> > >> Alternatively, I also considered: *metrics.udf.process-time.enabled* and > >> *metrics.udf.exception-count.enabled. * > >> > >> Happy to hear any feedback on which style might be more appropriate. > >> > >> > >> Best, > >> Weiqing > >> > >> On Mon, Jul 14, 2025 at 2:55 AM Xuyang <xyzhong...@163.com> wrote: > >> > >>> Hi, Weiqing. > >>> > >>> Thanks for driving to improve this. I just have one question. I notice > a > >>> new configuration is introduced in this flip. I just wonder what the > >>> configuration name is. Could you please include the full name of this > >>> configuration? (just similar to the other names in MetricOptions?) > >>> > >>> > >>> > >>> > >>> -- > >>> > >>> Best！ > >>> Xuyang > >>> > >>> > >>> > >>> > >>> > >>> 在 2025-07-13 12:03:59，"Weiqing Yang" <yangweiqing...@gmail.com> 写道： > >>> >Hi Alan, > >>> > > >>> >Thanks for reviewing the proposal and for highlighting the ASYNC_TABLE > >>> work. > >>> > > >>> >Yes, I’ve updated the proposal to cover both ASYNC_SCALAR and > >>> ASYNC_TABLE. > >>> >For async UDFs, the plan is to instrument both the invokeAsync() call > >>> and > >>> >the async callback handler to measure the full end-to-end latency > until > >>> the > >>> >result or error is returned from the future. > >>> > > >>> >Let me know if you have any further questions or suggestions. > >>> > > >>> >Best, > >>> >Weiqing > >>> > > >>> >On Thu, Jul 10, 2025 at 4:15 PM Alan Sheinberg > >>> ><asheinb...@confluent.io.invalid> wrote: > >>> > > >>> >> Hi Weiqing, > >>> >> > >>> >> From your doc, the entrypoint for UDF calls in the codegen is > >>> >> ExprCodeGenerator which should invoke BridgingSqlFunctionCallGen, > >>> which > >>> >> could be instrumented with metrics. This works well for synchronous > >>> calls, > >>> >> but what about ASYNC_SCALAR and the soon to be merged ASYNC_TABLE ( > >>> >> https://github.com/apache/flink/pull/26567)? Timing metrics would > >>> only > >>> >> account for what it takes to call invokeAsync, not for the result to > >>> >> complete (with a result or error from the future object). > >>> >> > >>> >> There are appropriate places which can handle the async callbacks, > >>> but they > >>> >> are in other locations. Will you be able to support those as well? > >>> >> > >>> >> Thanks, > >>> >> Alan > >>> >> > >>> >> On Wed, Jul 9, 2025 at 7:52 PM Shengkai Fang <fskm...@gmail.com> > >>> wrote: > >>> >> > >>> >> > I just have some questions: > >>> >> > > >>> >> > 1. The current metrics hierarchy shows that the UDF metric group > >>> belongs > >>> >> to > >>> >> > the TaskMetricGroup. I think it would be better for the UDF metric > >>> group > >>> >> to > >>> >> > belong to the OperatorMetricGroup instead, because a UDF might be > >>> used by > >>> >> > multiple operators. > >>> >> > 2. What are the naming conventions for UDF metrics? Could you > >>> provide an > >>> >> > example? Do the metric name contains the UDF name? > >>> >> > 3. Why is the UDFExceptionCount metric introduced? If a UDF throws > >>> an > >>> >> > exception, the job fails immediately. Why do we need to track this > >>> value? > >>> >> > > >>> >> > Best > >>> >> > Shengkai > >>> >> > > >>> >> > > >>> >> > Weiqing Yang <yangweiqing...@gmail.com> 于2025年7月9日周三 12:59写道： > >>> >> > > >>> >> > > Hi all, > >>> >> > > > >>> >> > > I’d like to initiate a discussion about adding UDF metrics. > >>> >> > > > >>> >> > > *Motivation* > >>> >> > > > >>> >> > > User-defined functions (UDFs) are essential for custom logic in > >>> Flink > >>> >> > jobs > >>> >> > > but often act as black boxes, making debugging and performance > >>> tuning > >>> >> > > difficult. When issues like high latency or frequent exceptions > >>> occur, > >>> >> > it's > >>> >> > > hard to pinpoint the root cause inside UDFs. > >>> >> > > > >>> >> > > Flink currently lacks built-in metrics for key UDF aspects such > as > >>> >> > > per-record processing time or exception count. This limits > >>> >> observability > >>> >> > > and complicates: > >>> >> > > > >>> >> > > - Debugging production issues > >>> >> > > - Performance tuning and resource allocation > >>> >> > > - Supplying reliable signals to autoscaling systems > >>> >> > > > >>> >> > > Introducing standard, opt-in UDF metrics will improve platform > >>> >> > > observability and overall health. > >>> >> > > Here’s the proposal document: Link > >>> >> > > < > >>> >> > > > >>> >> > > >>> >> > >>> > https://docs.google.com/document/d/1ZTN_kSxTMXKyJcrtmP6I9wlZmfPkK8748_nA6EVuVA0/edit?tab=t.0#heading=h.ljww281maxj1 > >>> >> > > > > >>> >> > > > >>> >> > > Your feedback and ideas are welcome to refine this feature. > >>> >> > > > >>> >> > > > >>> >> > > Thanks, > >>> >> > > Weiqing > >>> >> > > > >>> >> > > >>> >> > >>> > >> >
