Hi Beam community, I got a quick question about GoupByKey operator. According to this doc<https://beam.apache.org/documentation/programming-guide/#groupbykey>, if we are using unbounded PCollection, it’s required to specify either non-global windowing<https://beam.apache.org/documentation/programming-guide/#setting-your-pcollections-windowing-function> or an aggregation trigger<https://beam.apache.org/documentation/programming-guide/#triggers> in order to perform a GroupByKey operation.
In comparison, KeyBy<https://ci.apache.org/projects/flink/flink-docs-stable/dev/stream/operators/> operator from flink does not have such a hard requirement for streamed data. In our use case, we do need to query all historical streamed data and group by keys. KeyBy from flink satisfies our need, but Beam GoupByKey does not satisfy this need. I thought about applying a sliding window with a very large size (say 1 year), thus we can query the past 1 year’s data. But not sure if this is feasible or a good practice. So what would the Beam solution be to implement this business logic? Is there a support from beam to process a relative long history of a unbounded PCollection? Thanks so much!
