
Data augmentation in Beam Python by calling a gRPC service once per input element, running on a local Flink cluster with Kafka as the source.

Data augmentation in Beam Python by calling a gRPC service once per input element, running on a local Flink cluster with Kafka as the source.

A sport activity tracker in Beam Python, built first with native transforms and then with Beam SQL, showing the limits of Beam SQL in the Python SDK.

Two Beam Python pipelines compute average word length from a Kafka topic, one emitting a global average and one using a sliding time window.

Set up a local Apache Flink and Kafka environment, then build two Beam Python streaming pipelines for top K frequent words and longest word length.

Deploy an Apache Beam Python pipeline to a Flink session cluster on minikube, packaged as a Docker image and submitted as a Kubernetes job.

Deploy a PyFlink application to minikube with the Flink Kubernetes Operator, alongside a Kafka cluster that provides its source and sink topics.

Unit test batch and streaming Apache Beam pipelines in Python, using TestStream to advance watermarks and processing time across scenarios.

A streaming Apache Beam pipeline in Python that aggregates page visits by user in fixed 20 second windows, written with and without Beam SQL.

The Apache Beam portability layer explained, with bash scripts that manage local Flink and Kafka clusters and a streaming pipeline on the Flink Runner.

Batch Apache Beam pipelines in Python that aggregate website visit logs by user and time, written with and without Beam SQL and run in notebooks.