GCP Dataflow Pipeline scenarios with 'WindowedValue' scenarios on Event Time Processing
I'm stuck on something that should probably be simple. I'm a bit lost with I'm getting frustrated with I'm working on a personal project and I am currently working on a Dataflow pipeline using Apache Beam 2.35.0, and I'm working with an unexpected behavior related to event time processing..... The pipeline is designed to process streaming data from a Pub/Sub topic, but I've noticed that when I start the pipeline, it fails with the following behavior: ``` behavior: WindowedValue does not have any timestamp. ``` This behavior occurs particularly when I apply `@DoFn.bind()` to a method that processes the incoming messages. Here’s a simplified version of my code: ```python import apache_beam as beam from apache_beam.options.pipeline_options import PipelineOptions class ProcessMessage(beam.DoFn): def process(self, element, window=beam.DoFn.WindowParam): # Attempting to access the timestamp timestamp = window.timestamp() print(f'Timestamp: {timestamp}') return [element] options = PipelineOptions() with beam.Pipeline(options=options) as p: (p | 'Read from PubSub' >> beam.io.ReadFromPubSub(subscription='projects/my-project/subscriptions/my-subscription') | 'Process Messages' >> beam.ParDo(ProcessMessage())) ``` I have ensured that the Pub/Sub messages include the required attributes, such as a valid timestamp. I am using `with_window` and `trigger` configurations to handle late data. It seems like I am missing something crucial about how timestamps are assigned within the windowing system, but I need to pinpoint what it is. I've searched through the documentation and other questions but haven’t found a clear solution. Has anyone else encountered this scenario or has suggestions on how to troubleshoot further? Any insights would be greatly appreciated! What am I doing wrong? This is my first time working with Python 3.10. This is my first time working with Python stable. Cheers for any assistance! This is happening in both development and production on Ubuntu 20.04. Thanks, I really appreciate it!