Achieve seamless integration of Apache Flink, Kafka, and PostgreSQL using Docker-Compose, leveraging pyFlink for real-time data processing. This guide provides practical tips, configures Flink in session mode, and demonstrates how to create custom Docker images for pyFlink to ensure Python jobs run smoothly. Additionally, the post covers setting up Kafka topics, creating Postgres tables, and handling sensor data streams. Follow the step-by-step guide to build and experiment with a streaming pipeline that efficiently processes and stores data.
Table of contents
Issues With Kafka Ports in docker-compose.ymlConfiguring Flink in Session ModeCustom Docker Image for PyFlinkIntegrating PostgreSQLSinking Data to KafkaLocal or Containerized configurationSort: