Connecting RDBs and Search Engines — Chapter 4 Part 2

This chapter details integrating Kafka CDC data with OpenSearch using Flink SQL. The architecture involves capturing data changes from PostgreSQL using Debezium, streaming them via Kafka, and processing them with Flink before writing to OpenSearch. Setting up the necessary components like PostgreSQL, Kafka, Debezium, Flink, and OpenSearch is crucial, often managed using Docker Compose. Specific Flink connector JARs for Kafka and OpenSearch need to be added to the Flink library. An OpenSearch index with a predefined mapping is created to store the data. A Flink SQL script is defined to read CDC data from Kafka and write it to OpenSearch. The script creates Kafka source and OpenSearch sink tables, transforming and routing data using an INSERT statement. The Flink job is then executed using the Flink SQL client, processing the data. Finally, the data is verified in OpenSearch by querying the index. This demonstrates a complete CDC pipeline from database changes to a searchable index in OpenSearch. The process enables near real-time indexing of database changes for search and analysis.