new URNs is to specifically be able to add new formats and
> specifications over time.
>
> On Fri, Oct 1, 2021 at 10:34 AM Ajo Thomas wrote:
>
>> Thanks for the pointers, Luke and sorry for replying late on this thread.
>>
>> Distribution metric's - *void update(long
/beam/pull/7183
> 2:
> https://github.com/apache/beam/blob/a7b706cb9d1e84709f89fe98d1dda94d4eb1243b/model/pipeline/src/main/proto/metrics.proto#L110
> 3:
> https://lists.apache.org/thread.html/rfc1ff850ed2eaa9057ba9fb34286c19a802bc2720424afc0dffa3b1b%40%3Cdev.beam.apache.org%3E
>
> On Mon,
they see fit. I'd love to see a proposal / PR for this.
>
> fyi @Robert Bradshaw
>
> On Wed, Sep 15, 2021 at 10:37 AM Ajo Thomas
> wrote:
>
>> Thanks for the response, Alexey and Ke.
>> Agree with your point to introduce a new metric type (say Percentiles)
>> instead o
Thanks for the link to the doc.
I think it should be okay to include percentiles in Distribution given that
it was intended to be extensible. As for the user facing Metrics API, there
will be no changes unless we want to allow the user to specify custom
percentiles aside from a set of defaults.
/blob/master/sdks/java/core/src/main/java/org/apache/beam/sdk/metrics/Distribution.java
>
>
> On Sep 7, 2021, at 1:28 PM, Ajo Thomas wrote:
>
> Hi All,
>
> I am working on adding support for some additional distribution metrics
> like std dev, percentiles to the Metrics API. T
Hi All,
I am working on adding support for some additional distribution metrics
like std dev, percentiles to the Metrics API. The runner of interest here
is Samza runner. I wanted to get the opinion of fellow beam devs on this.
One way to do this would be to make changes to the existing
in SparkRunner.
Switching to ReadAllFromAvro worked as it relies on
filebasedsource.ReadAllFiless which uses a different approach to splitting
the work.
Thanks
Ajo
On Fri, Jun 11, 2021 at 8:18 AM Ajo Thomas wrote:
> Hi folks,
>
> I am working on running a Portable Python pipeline on Spark.
&
Hi folks,
I am working on running a Portable Python pipeline on Spark.
The test pipeline is very straightforward where I am trying to read some
avro data in hdfs using avroio (native io and not an external transform)
and write it back to hdfs. Here is the pipeline:
Pipeline:
pipeline_options =
Hello,
I am Ajo Thomas and I was hoping to work on making some improvements to the
beam KinesisIO java SDK.
I have created a ticket for it [
https://issues.apache.org/jira/browse/BEAM-7240 ] and was hoping to assign
it to myself.
Requesting the admins to please add me as a contributor for Beam's
