This repository helps spin up an Elasticsearch-Siren instance and connected Jupyter server. The goal here is to demonstrate some programmatic interaction between Notebooks and Siren, as well as create an easy-to-reproduce-environment for demonstrations or bug reporting.
To get started, clone this repo and run docker-compose up --build -d && docker-compose logs -f. It will take a few minutes to build the Docker images, and may take a little longer for the Siren web-server to start even once the image is running.
Look in the Jupyter logs for a link to your server with the access token (something like http://127.0.0.1:8888/?token=68b704d7cdee14b75051daa4efe55c6d69ee8a306ab29e1f). The Siren/Kibana UI will be available at http://localhost:5606, and ES endpoints at https://localhost:9220 (note that Jupyter is running in the same Docker network so you'll see Notebooks connect to https://siren:9220 vice localhost).
Log in to the Siren Investigate / Kibana UI using sirenadmin / password, sirenuser / password, or sirennoinvestor / password. Check out the Demo data documentation at https://docs.siren.io/siren-platform-user-guide/11.1/getting-started/getting-started-with-demo-data.html#_username_and_passwords_at_login.
Siren is an Elasticsearch plugin that adds several features to the base Elasticsearch/Kibana stack, most noteably relationships between tables. See https://siren.io/getting-started/ for more details.
If you're using WSL, you will need to set your docker desktop system vm.max_map_count to 262144 or higher. Note this does not persist over system restarts. See https://community.siren.io/t/discovery-type-single-node-not-working-as-expected/390 for discussion at the Siren community. If Siren is not starting, this is probably the reason why. You can sanity check by exec'ing into the Siren container and looking at /opt/platform/elasticsearch/logs/siren-distribution.log.
The University of Prague hosts a variety of Relational Dataset Repositories at https://relational.fit.cvut.cz/. If you want to see how Siren works with data besides the demo data, check out cvut's awesome resources. Thanks CTU !!
The Siren container has the mysql-connector jdbc driver installed and copied into the right directory. To add any of the CVUT tables to your Siren instance via Kibana/Siren-Investigate UI, go to Management -> Datasources -> JDBC.
- Database type: Mysql
- Username:
guest - Password:
relational - Connection string:
jdbc:mysql://relational.fit.cvut.cz:3306?useLegacyDatetimeCode=false&useCursorFetch=true&enabledTLSProtocols=TLSv1.2
After that, follow the prompts to create a virtual index and index pattern search. Alternatively, pull the data in via Notebooks and write to Elasticsearch programmatically.