stain/jena-fuseki Docker 镜像 - 轩辕镜像

Jena Fuseki docker image

• Docker image: stain/jena-fuseki
• Base images: openjdk:11-jre-slim-buster
• Source: Dockerfile, Apache Jena Fuseki

![Build Status]([***]

This is a Docker image for running Apache Jena Fuseki, which is a SPARQL 1.1 server with a web interface, backed by the Apache Jena TDB RDF triple store.

Feel free to contact the jena users list for any questions on using Jena or Fuseki.

License

Different licenses apply to files added by different Docker layers:

• stain/jena-fuseki Dockerfile: Apache License, version 2.0
• Apache Jena (/jena-fuseki in the image): Apache License, version 2.0 See also: docker run stain/jena-fuseki cat /jena-fuseki/NOTICE
• OpenJDK (/usr/local/openjdk-11/ in the image): GPL 2.0 with Classpath exception See /usr/local/openjdk-11/legal/ in image
• Debian GNU/Linux (rest of /): GPL 3 and compatible licenses, see /usr/share/*/license in image

Use

To try out this image, try:

docker run -p 3030:3030 stain/jena-fuseki

The Apache Jena Fuseki should then be available at http://localhost:3030/

To expose Fuseki on a different port, simply modify first part of -p:

docker run -p 8080:3030 stain/jena-fuseki

To load RDF graphs, you will need to log in as the admin user. To see the automatically generated admin password, see the output from above, or use docker logs with the name of your container.

Note that the password is only generated on the first run, e.g. when the volume /fuseki is an empty directory.

You can override the admin-password using the form -e ADMIN_PASSWORD=pw123:

docker run -p 3030:3030 -e ADMIN_PASSWORD=pw123 stain/jena-fuseki

To specify Java settings such as the amount of memory to allocate for the heap (default: 1200 MiB), set the JVM_ARGS environment with -e:

docker run -p 3030:3030 -e JVM_ARGS=-Xmx2g stain/jena-fuseki

Data persistence

Fuseki's data is stored in the Docker volume /fuseki within the container. Note that unless you use docker restart or one of the mechanisms below, data is lost between each run of the jena-fuseki image.

To store the data in a named Docker volume container fuseki-data (recommended), create it first as:

docker run --name fuseki-data -v /fuseki busybox

Then start fuseki using --volumes-from. This allows you to later upgrade the jena-fuseki docker image without losing the data. The command below also uses -d to start the container in the background.

docker run -d --name fuseki -p 3030:3030 --volumes-from fuseki-data stain/jena-fuseki

If you want to store fuseki data in a specified location on the host (e.g. for disk space or speed requirements), specify it using -v:

docker run -d --name fuseki -p 3030:3030 -v /ssd/data/fuseki:/fuseki stain/jena-fuseki

Note that the /fuseki volume must only be accessed from a single Fuseki container at a time.

To check the logs for the container you gave --name fuseki, use:

docker logs fuseki

To stop the named container, use:

docker stop fuseki

.. or press Ctrl-C.

To restart a named container (it will remember the volume and port config)

docker restart fuseki

Using TDB 2

To use TDB v2 you can pass the environment variable with -e TDB=2

 docker run -p 3030:3030 -e TDB=2 stain/jena-fuseki

If you do so, then you need to use the appropriate tdbloader2 for your data, see below for more details.

Upgrading Fuseki

If you want to upgrade the Fuseki container named fuseki which use the data volume fuseki-data as recommended above, do:

docker pull stain/jena-fuseki
docker stop fuseki
docker rm fuseki
docker run -d --name fuseki -p 3030:3030 --volumes-from fuseki-data stain/jena-fuseki

Create empty datasets

You can create empty datasets at startup with:

docker run -d --name fuseki -p 3030:3030 -e FUSEKI_DATASET_1=mydataset -e FUSEKI_DATASET_2=otherdataset stain/jena-fuseki

This will create 2 empty datasets: mydataset and otherdataset.

Data loading

Fuseki allows uploading of RDF datasets through the web interface and web services, but for large datasets it is more efficient to load them directly using the command line.

This docker image includes a shell script load.sh that invokes the tdbloader command line tool and load datasets from the docker volume /staging.

For help, try:

docker run stain/jena-fuseki ./load.sh

You will most likely want to load from a folder on the host computer by using -v, and into a data volume that you can then use with the regular fuseki.

Before data loading, you must either stop the Fuseki container, or load the data into a brand new dataset that Fuseki doesn't know about yet. To stop the docker container you named fuseki:

docker stop fuseki

The example below assume you want to populate the Fuseki dataset 'chembl19' from the Docker data volume fuseki-data (see above) by loading the two files cco.ttl.gz and void.ttl.gz from /home/stain/ops/chembl19 on the host computer:

docker run --volumes-from fuseki-data -v /home/stain/ops/chembl19:/staging \
   stain/jena-fuseki ./load.sh chembl19 cco.ttl.gz void.ttl.gz

Tip: You might find it benefitial to run data loading from the data staging directory in order to use tab-completion etc. without exposing the path on the host. The ./load.sh will expand patterns like *.ttl - you might have to use single quotes (e.g. '*.ttl') on the host to avoid them being expanded locally.

If you don't specify any filenames to load.sh, all filenames directly under /staging that match these GLOB patterns will be loaded:

*.rdf *.rdf.gz *.ttl *.ttl.gz *.owl *.owl.gz *.nt *.nt.gz *.nquads *.nquads.gz

load.sh populates the default graph. To populate named graphs, see the tdbloader section below.

NOTE: If you load data into a brand new /fuseki volume, a new random admin password will be set before you have started Fuseki. You can either check the output of the data loading, or later override the password using -e ADMIN_PASSWORD=pw123.

Using the tdbloader2 for TDB2

Assume you have already the container running named fuseki you can execute

docker exec -it fuseki  /bin/bash -c 'tdbloader2 --loc chembl19  /staging/{cco.ttl.gz,void.ttl.gz}'

Recognizing the dataset in Fuseki

If you loaded into an existing dataset, Fuseki should find the data after (re)starting with the same data volume (see Data persistence above):

docker restart fuseki

If you created a brand new dataset, then in Fuseki go to Manage datasets, click Add new dataset, tick Persistent and provide the database name exactly as provided to load.sh, e.g. chembl19.

Now go to Dataset, select from the dropdown menu, and try out Info and Query.

Tip: It is possible to load a new dataset into the volume of a running Fuseki server, as long as you don't "create" it in Fuseki before load.sh has finished.

Loading with tdbloader

If you have more advanced requirements, like loading multiple datasets or named graphs, you can use tdbloader directly together with a TDB assembler file.

Note that Fuseki TDB datasets are sub-folders in /fuseki/databases/.

You will need to provide the assembler file on a mounted Docker volume together with the data:

docker run --volumes-from fuseki-data -v /home/stain/data:/staging stain/jena-fuseki \
  ./tdbloader --desc=/staging/tdb.ttl

Remember to use the Docker container's data volume paths within the assembler file, e.g. /staging/dataset.ttl instead of /home/stain/data/dataset.ttl.

Customizing Fuseki configuration

If you need to modify Fuseki's configuration further, you can use the equivalent of:

docker run --volumes-from fuseki-data -it ubuntu bash

and inspect /fuseki with the shell. Remember to restart fuseki afterwards:

docker restart fuseki

### Additional JARs on Fuseki classpath

If you need to add additional JARs to the classpath, but do not want to modify the volume /fuseki, then add the JARs to /fuseki-extra which will be added as /fuseki/extra on start.

Contact

For any feedback or questions on Jena, Fuseki or SPARQ, please use the users@jena mailing list.

For any issues with Jena or Fuseki, feel free to raise a bug.

For any issues with the packaging in this Docker image, or its Dockerfile, please raise a pull request or issue.