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This keeps the infrastructure that builds docker images for GraphDB

Check Docker Hub Images for information on how to use the images.

Building a docker image

You will need docker and make installed on your machine.

  1. Checkout this repository
  2. Run
make build-image VERSION=<the-version-that-you-want>

for example the most recent version as of this writing is 10.2.2 so run

make build-image VERSION=10.2.2

this will build an image that you can use called ontotext/graphdb:10.2.2 You can run the image now with

docker run -d -p 7200:7200 ontotext/graphdb:10.2.2

Consult the docker hub documentation for more information.

Preload a repository

Go to the preload folder to run the bulk load data when GraphDB is stopped.

cd preload

By default it will:

  • Create or override a repository defined in the graphdb-repo-config.ttl file (can be changed manually in the file, default is demo)
  • Upload a test ntriple file from the preload/import subfolder.

See the GraphDB preload documentation for more details.

When running the preload docker-compose various parameters can be provided in the preload/.env file:

GRAPHDB_VERSION=10.2.2
GRAPHDB_HEAP_SIZE=3g
GRAPHDB_HOME=../graphdb-data
REPOSITORY_CONFIG_FILE=./graphdb-repo.ttl

Build and run:

docker-compose build
docker-compose up -d

GraphDB data will go to /data/graphdb

Go back to the root of the git repository to start GraphDB:

cd ..

Start GraphDB

To start GraphDB run the following from the root of the git repository:

docker-compose up -d --build

It will use the repo created by the preload in graphdb-data/

Feel free to add a .env file similar to the preload repository to define variables.

Issues

You can report issues in the GitHub issue tracker or at graphdb-support at ontotext.com

Contributing

You are invited to contribute new features, fixes, or updates, large or small; we are always thrilled to receive pull requests, and do our best to process them as fast as we can.

Before you start to code, we recommend discussing your plans through a GitHub issue, especially for more ambitious contributions. This gives other contributors a chance to point you in the right direction, give you feedback on your design, and help you find out if someone else is working on the same thing.