Fuseki Base Docker Image

Yet another Apache Fuseki Docker distribution.

Project goals

The Docker image provided by this distribution shall:

• Allow the full Fuseki configuration
• Allow adding extensions
• Use Maven to get an up-to-date version of Fuseki
• Be extendible to allow creation of custom distributions as extending images

Building

docker build -t linkedsolutions/fuseki-base . 

Running

docker-compose up

or

docker run --rm -v `pwd`/base:/fuseki/base -p 3030:3030 linkedsolutions/fuseki-base

You might have 'pwd/base' with the full path to the FUSEKI_BASE directory, see https://jena.apache.org/documentation/fuseki2/fuseki-layout.html to learn about the contents of this directory.

Configuration

The image starts by default with a minimal configuration file at /config.ttl that defines an empty Fuseki server with no datasets. This allows Fuseki to start successfully while providing a base for customization.

You can mount a local folder at the container path /fuseki/base and put any fuseki configuration file in that folder. When the image is run for the first time a default configuration is created in that directory. With this default configuration the environment variable ADMIN_PASSWORD can be used to set the password of the admin user on startup.

To use a custom configuration, simply mount your configuration file at /config.ttl:

-v $(pwd)/my-config.ttl:/config.ttl

Extending

Any jar in the folder at the container path /fuseki/extensions is added to the classpath.

Any script in the folder at the container path /fuseki/set-up-scripts is executed when the container is started without shiro.ini file in the FUSEKI_BASE directory. These allows extending images to provide additional default configuration.

Examples

All example files mentioned in this documentation are available in the examples/ directory.

Prerequisites

Build the Docker image first:

docker build -t linkedsolutions/fuseki-base .

Basic Dataset Operations

Start Fuseki with a dataset

# In-memory dataset
docker run --rm -p 3030:3030 linkedsolutions/fuseki-base \
  sh -c "java \$JAVA_OPTS -cp /fuseki/home/fuseki.jar org.apache.jena.fuseki.cmd.FusekiCmd --mem --port 3030 /books"

# Persistent TDB dataset (create directory first: mkdir -p ./fuseki-data/databases/books)
docker run --rm -p 3030:3030 \
  -v $(pwd)/fuseki-data:/fuseki-data \
  linkedsolutions/fuseki-base \
  sh -c "java \$JAVA_OPTS -cp /fuseki/home/fuseki.jar org.apache.jena.fuseki.cmd.FusekiCmd --loc=/fuseki-data/databases/books --update --port 3030 /books"

Upload data

curl -X POST -H "Content-Type: text/turtle" \
  --data-binary "@examples/sample-data.ttl" \
  "http://localhost:3030/books/data"

Query data

# Query people
curl -X POST -H "Content-Type: application/sparql-query" \
  --data-binary "@examples/query-people.sparql" \
  "http://localhost:3030/books/query"

# Query books  
curl -X POST -H "Content-Type: application/sparql-query" \
  --data-binary "@examples/query-books.sparql" \
  "http://localhost:3030/books/query"

Update data

curl -X POST -H "Content-Type: application/sparql-update" \
  --data-binary "@examples/insert-data.sparql" \
  "http://localhost:3030/books/update"

Configuration-based Setup

# Using a custom configuration file (replaces the default /config.ttl)
docker run --rm -p 3030:3030 \
  -v $(pwd)/fuseki-data:/fuseki/base \
  -v $(pwd)/examples/config.ttl:/config.ttl \
  linkedsolutions/fuseki-base

# Or run with the default minimal configuration (no datasets)
docker run --rm -p 3030:3030 \
  -v $(pwd)/fuseki-data:/fuseki/base \
  linkedsolutions/fuseki-base

Docker Compose With Configuration

services:
  fuseki:
    image: "linkedsolutions/fuseki-base"
    ports:
      - "3030:3030"
    volumes:
      - ./fuseki-data:/fuseki/base
      - ./examples/config.ttl:/config.ttl  # Override default config
    environment:
      - ADMIN_PASSWORD=your-secure-password

Text Search with Lucene

Start with Lucene

docker run --rm -p 3030:3030 \
  -v $(pwd)/fuseki-data:/fuseki-data \
  -v $(pwd)/examples/config-lucene.ttl:/config.ttl \
  linkedsolutions/fuseki-base

Upload searchable data

curl -X POST -H "Content-Type: text/turtle" \
  --data-binary "@examples/lucene-data.ttl" \
  "http://localhost:3030/books/data"

Text search query

curl -X POST -H "Content-Type: application/sparql-query" \
  --data-binary "@examples/query-text-search.sparql" \
  "http://localhost:3030/books/query"

Comparison: Regular vs Text Search Queries

With the same dataset name (/books), you can see the difference:

Regular SPARQL query (works without Lucene):

PREFIX dc: <http://purl.org/dc/elements/1.1/>
SELECT ?book ?title WHERE {
  ?book dc:title ?title .
  FILTER(CONTAINS(LCASE(?title), "sparql"))
}

Text search query (requires Lucene configuration):

PREFIX text: <http://jena.apache.org/text#>
PREFIX dc: <http://purl.org/dc/elements/1.1/>
SELECT ?book ?score ?title WHERE {
  (?book ?score) text:query "SPARQL" .
  ?book dc:title ?title .
}

The text search provides relevance scoring and performs much better on large datasets.

Web Interface

Fuseki provides a web interface at http://localhost:3030 where you can:

• Browse datasets
• Execute SPARQL queries interactively
• Upload data files
• Monitor server statistics
• Manage dataset configurations

Common HTTP Status Codes

• 200 OK: Successful query/operation
• 204 No Content: Successful update with no response body
• 400 Bad Request: Malformed SPARQL or invalid data
• 401 Unauthorized: Authentication required
• 404 Not Found: Dataset or endpoint not found
• 500 Internal Server Error: Server error (check logs)

Tips

1. Data Formats: Fuseki supports RDF/XML, Turtle, N-Triples, JSON-LD, and more
2. Authentication: Use HTTP Basic Auth for protected endpoints
3. Performance: Use TDB for better performance with large datasets
4. Monitoring: Check server logs and the /$/stats endpoint for monitoring
5. Backup: Regularly backup your TDB database directories
6. Text Search: Full-text search with Lucene is now included by default
7. Memory: Increase JVM memory with JAVA_OPTS="-Xmx4g" for large datasets
8. Security: Always change default passwords in production environments