Serverless Data Processing with Dataflow - Using Dataflow for Streaming Analytics (Python)

Serverless Data Processing with Dataflow - Using Dataflow for Streaming Analytics (Python)

In this lab, you take many of the concepts introduced in a batch context and apply them in a streaming context to create a pipeline similar to batch_minute_traffic_pipeline, but which operates in real time. The finished pipeline will first read JSON messages from Pub/Sub and parse those messages before branching. One branch writes some raw data to BigQuery and takes note of event and processing time. The other branch windows and aggregates the data and then writes the results to BigQuery.

Objectives
- Read data from a streaming source.
- Write data to a streaming sink.
- Window data in a streaming context.
- Experimentally verify the effects of lag.

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