- Getting Started With Pyflink on AWS
- Apache Flink is widely used for building real-time stream processing applications. On AWS, Amazon Managed Service for Apache Flink is the easiest option to develop a Flink app as it provides the underlying infrastructure. Updating a guide from AWS, this series of posts discuss how to develop and deploy a Flink (Pyflink) application on AWS where the data source and sink are Kafka topics.
- Kafka, Flink and DynamoDB for Real Time Fraud Detection
- Re-implementing a solution from an AWS workshop, this series of posts discuss how to develop and deploy a fraud detection app using Kafka, Flink and DynamoDB. Part 1 covers local development using Docker while deployment on AWS will be discussed in part 2.
- Building Apache Flink Applications in Python
- Building Apache Flink Applications in Java by Confluent is a course to introduce Apache Flink through a series of hands-on exercises. Utilising the Flink DataStream API, the course develops three Flink applications from ingesting source data into calculating usage statistics. As part of learning the Flink DataStream API in Pyflink, I converted the Java apps into Python equivalent while performing the course exercises in Pyflink. This post summarises the progress of the conversion and shows the final output.
- Run Flink SQL Cookbook in Docker
- The Flink SQL Cookbook is a practical guide packed with self-contained examples for learning Apache Flink SQL, covering everything from basic queries to advanced stream processing patterns. Since it's designed for the Ververica Platform and lacks cluster setup instructions, this post shows how to run the examples locally using Docker Compose for a smooth, hands-on experience.
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Apache Flink (Pyflink) and Related Projects