Confluent KSQL Training in Copenhagen, Denmark

This course introduces participants to Confluent KSQL (now known as ksqlDB), a powerful stream processing engine built on Apache Kafka. It allows users to write continuous queries against Kafka topics using SQL syntax. The course covers real-time data filtering, transformations, joins, aggregations, and materialized views, enabling fast development of stream processing applications without writing Java code.

Introduction and Core KSQL Concepts

• Introduction to Stream Processing & ksqlDB

  • What is ksqlDB?

  • Use cases and architecture

  • Kafka + ksqlDB integration

• Setting up the Environment

  • Confluent Cloud and local Docker setup

  • ksqlDB CLI and Web UI walkthrough

• Creating and Querying Streams

  • Defining a stream from Kafka topics

  • SELECT and WHERE clauses

  • Stream-to-stream operations

• Filtering and Transforming Data

  • Expressions and functions

  • Renaming, casting, and formatting fields

  • Time-based transformations

Joins, Aggregations, and Deployment

• Stream and Table Joins

  • Stream-to-stream joins

  • Stream-to-table joins

  • WINDOWED joins

• Aggregations and Materialized Views

  • COUNT, SUM, MAX, MIN, GROUP BY

  • Creating stateful tables from streams

  • Materialized views and persistent queries

• Using Kafka Connect with ksqlDB

  • Source and sink connectors overview

  • Streaming data from external systems

• Operational Considerations

  • Deploying persistent queries

  • Query monitoring and scaling

  • Best practices and performance tuning

• Hands-on Labs

• Summary and Conclusion