qacompany/qendpoint repository overview

⁠Quick Reference

• Maintained by : The QA Company https://the-qa-company.com/⁠

⁠What is the qEndpoint?

A highly scalable triple store with full-text and GeoSPARQL support.

⁠How to run this image

You just have to run the image and it will prepare the environment by downloading the index and setting up the repository

docker run -p 1234:1234 --name qendpoint qacompany/qendpoint

You can also specify the size of the memory allocated by setting the docker environnement value MEM_SIZE. By default this value is set to 6G. You should not set this value below 4G because you will certainly run out of memory.

docker run -p 1234:1234 --name qendpoint --env MEM_SIZE=6G qacompany/qendpoint

You can stop the container and rerun it at anytime maintaining the data inside (qendpoint is the name of the container):

docker stop qendpoint

docker start qendpoint

Note: this container may occupy a huge portion of the disk due to the size of the data index, so make sure to delete the container if you don't need it anymore like so

docker rm qendpoint

⁠Useful tools

You can access http://localhost:1234⁠ where there is a nice GUI where you can write SPARQL queries and execute them, and there is the RESTful API available which you can use to run queries from any application over HTTP like so:

curl -H 'Accept: application/sparql-results+json' localhost:1234/api/endpoint/sparql --data-urlencode 'query=select * where{ ?s ?p ?o } limit 10'

Note: first query will take some time in order to map the index to memory, later on it will be much faster!

Available result format:

• JSON: application/sparql-results+json
• XML: application/sparql-results+xml
• Binary RDF: application/x-binary-rdf-results-table

⁠Related thing

• In this repository⁠ you'll find this endpoint pre-configured with the Wikidata dataset