👀 Views: 1596 💬 Answers: 1 📅 Created: 2025-06-12

gcp dataflow apache-beam pubsub Python

I've been struggling with this for a few days now and could really use some help. I need help solving Quick question that's been bugging me - I'm sure I'm missing something obvious here, but I'm working with an scenario with a Google Cloud Dataflow job that processes streaming data. The job fails to execute and throws a 'Windowing function not supported' behavior. I'm using Python with Apache Beam SDK version 2.34.0. My data is coming from a Pub/Sub topic, and I want to apply a windowing function to group my data by minute before aggregation. Here’s a snippet of my pipeline code: ```python import apache_beam as beam from apache_beam.options.pipeline_options import PipelineOptions options = PipelineOptions( project='my-gcp-project', runner='DataflowRunner', temp_location='gs://my-bucket/temp', ) with beam.Pipeline(options=options) as p: (p | 'Read from Pub/Sub' >> beam.io.ReadFromPubSub(topic='projects/my-gcp-project/topics/my-topic') | 'Window by minute' >> beam.WindowInto(beam.window.FixedWindows(60)) | 'Count elements' >> beam.CombineGlobally(beam.combiners.CountCombineFn())) ``` I've ensured that my Dataflow job has the appropriate IAM permissions, and I have the necessary libraries installed. However, I keep getting this behavior, and I'm not sure if it's because of how I'm using the windowing function or if there's a version compatibility scenario. I've also tried switching to different windowing strategies, like `SlidingWindows`, but I still face the same behavior. Any advice on how to resolve this? Am I missing something fundamental in my implementation? For context: I'm using Python on Linux. What am I doing wrong? Thanks in advance! Am I missing something obvious?