Getting Started Analyzing Twitter Data in Apache Kafka through KSQL

What this post added

This post details how to ingest raw Twitter data into Apache Kafka using a Kafka Connect Twitter source connector. It then demonstrates how to use KSQL to define schemas for the incoming JSON data, query the raw stream, create derived streams with transformations (e.g., timestamp conversion, JSON field extraction, LCASE, pattern matching), and build aggregations (e.g., tweet counts per user per hour). It explains the concept of continuous queries and the distinction between streams and tables in KSQL, illustrating how aggregations result in tables. The post also shows how to create derived tables from aggregated data for easier querying.