lydian opened a new issue, #25598:
URL: https://github.com/apache/beam/issues/25598
### What would you like to happen?
I want to back up events from Kafka to S3 every minute. For example:
```
(
pipeline
| "Read from Kafka" >> ReadFromKafka(consumer_config, topics,
with_metadata=False)
| "Transformed" >> beam.Map(my_transform)
| "Add timestamp" >> beam.Map(add_timestamp)
| "window" >> beam.WindowInto(window.FixedWindows(60)) # 1 mins
| "writing to parquet" >> beam.io.WriteToParquet('s3://test-bucket/',
pyarrow_schema)
)
```
However, when executing this pipeline, I got
```
ValueError: GroupByKey cannot be applied to an unbounded PCollection with
global windowing and a default trigger
```
Which is coming from
https://github.com/apache/beam/blob/v2.41.0/sdks/python/apache_beam/io/iobase.py#L1145
where it always trying to create a global window. Also I found in
[here](https://github.com/apache/beam/blob/v2.41.0/sdks/python/apache_beam/io/iobase.py#L1033):
> Currently only batch workflows support custom sinks.
The same function seems have no problem to be run in Java, but for python it
is not supported. It would be nice to figured out a way to support this.
### Issue Priority
Priority: 2 (default / most feature requests should be filed as P2)
### Issue Components
- [X] Component: Python SDK
- [ ] Component: Java SDK
- [ ] Component: Go SDK
- [ ] Component: Typescript SDK
- [X] Component: IO connector
- [ ] Component: Beam examples
- [ ] Component: Beam playground
- [ ] Component: Beam katas
- [ ] Component: Website
- [ ] Component: Spark Runner
- [X] Component: Flink Runner
- [ ] Component: Samza Runner
- [ ] Component: Twister2 Runner
- [ ] Component: Hazelcast Jet Runner
- [ ] Component: Google Cloud Dataflow Runner
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