Using Logstash to synchronize an Elasticsearch index with MySQL data

With related repo

This project is a working example demonstrating how to use Logstash to link Elasticsearch to a MySQL database in order to:

• Build an Elasticsearch index from scratch
• Continuously monitor changes on the database records and replicate any of those changes to Elasticsearch (create, update, delete)

It uses:

• MySQL as the main database of a given business architecture (version 8.0)
• Elasticsearch as a text search engine (version 7.9.3)
• Logstash as a connector or data pipe from MySQL to Elasticsearch (version 7.9.3)
• Kibana for monitoring, data visualization, and debuging tool (version 7.9.3)

This repo is a valid prototype and works as it is, however it is not suitable for a production environment. Please refer to the official documentation of each of the above technologies for instructions on how to go live in your production environment.

On your development/local environment, run the following commands on a terminal:

Note: Make sure to install Docker and Docker Compose

# Clone this project and cd into it
git clone https://github.com/iColdPlayer/es-sql

# Start the whole architecture
docker-compose up # add -d for detached mode

# To keep an eye on the logs
docker-compose logs -f --tail 111 <service-name>

To start services separately or in a different order, you can run:

docker-compose up -d mysql
docker-compose up -d elasticsearch kibana
docker-compose up logstash

Please refer to the above article for testing steps.

• Inspiration by How to keep Elasticsearch synchronized with a relational database using Logstash and JDBC. However the article does not deal with indexing from scratch and deleted records.
• Data used for this project is available in the Kaggle dataset Goodreads-books
• Logstash JDBC input plugin
• Logstash Mutate filter plugin
• Logstash Elasticsearch output plugin