JBR Hook - SPARQL Endpoint Linked Data Fragments Server

A jbr hook type for an LDF server-based SPARQL endpoint.

Concretely, this hook will start a Triple Pattern Fragments (TPF) server and an NGINX proxy server that acts as a cache for this TPF server.

Requirements

• Node.js (1.12 or higher)
• Docker (required for starting a LDF server-based SPARQL endpoint inside a Docker container)
• An existing jbr experiment that requires a SPARQL endpoint hook.

Configure an experiment hook

If an experiment requires a hook for a SPARQL endpoint, then you can install this LDF server-based SPARQL endpoint as follows.

$ jbr set-hook someHookSparqlEndpoint sparql-endpoint-ldf

This hook depends on another sub-hook for enabling full SPARQL query execution over the TPF interface, such as sparql-endpoint-comunica:

$ jbr set-hook someHookSparqlEndpoint/hookSparqlEndpointLdfEngine sparql-endpoint-comunica

Output

The following output is generated after an experiment with this hook has run.

output/stats-sparql-endpoint-ldf-server.csv and output/stats-sparql-endpoint-ldf-cache.csv: Per second of the experiment: CPU percentage, memory usage (bytes), memory percentage, received bytes, transmitted bytes.

cpu_percentage,memory,memory_percentage,received,transmitted
9.915362228116711,10489856,0.5024267940030527,488,0
9.863725050505051,17354752,0.8312308965993495,648,0
9.64850952141058,19116032,0.915589944401502,738,0
9.345685076142132,23072768,1.105103526208198,738,0
10.029959365079364,26759168,1.2816689750964243,738,0
10.25411566137566,30363648,1.45431074734269,738,0

output/logs/sparql-endpoint-ldf-server.txt: Logs of the TPF server.

output/logs/sparql-endpoint-ldf-cache.txt: Logs of the proxy cache.

Configuration

When installing this hook, your configuration file (jbr-experiment.json) will contain the following:

...
  "someHookSparqlEndpoint": {
    "@id": "urn:jrb:bb:hookSparqlEndpoint",
    "@type": "HookSparqlEndpointLdf",
    "dockerfile": "input/dockerfiles/Dockerfile-ldf-server",
    "dockerfileCache": "input/dockerfiles/Dockerfile-ldf-server-cache",
    "resourceConstraints": {
      "@type": "StaticDockerResourceConstraints",
      "cpu_percentage": 100
    },
    "config": "input/config-ldf-server.json",
    "portServer": 2999,
    "portCache": 3000,
    "workers": 4,
    "maxMemory": 8192,
    "dataset": "generated/dataset.hdt",
    "hookSparqlEndpointLdfEngine": {
      "@id": "urn:jrb:bb:hookSparqlEndpoint_hookSparqlEndpointLdfEngine",
      "@type": "HookNonConfigured"
    }
  }
...

Any config changes require re-running the prepare step.

More background information on these config options can be found on https://github.com/LinkedDataFragments/Server.js/.

Configuration fields

• dockerfile: Path to the Dockerfile of the LDF server.
• dockerfileClient: Path to the Dockerfile of the cache proxy.
• resourceConstraints: Resource constraints for the Docker container.
• config: Path to the configuration file of an LDF server.
• portServer: HTTP port on which the LDF server will be exposed on the Docker host.
• portCache: HTTP port on which the NGINX server will be exposed on the Docker host.
• workers: Number of worker threads for the LDF server.
• maxMemory: Maximum amount of Memory for the LDF serve
• dataset: HDT file to use as dataset.
• hookSparqlEndpointLdfEngine: Sub-hook for an engine that exposes a SPARQL endpoint over this hook.

Networks

The TPF and NGINX servers will be available in the same Docker virtual network with the names ldfserver (port 3000) and cache (port 80). Any (Docker-supporting) hooks that are plugged into this hook as sub-hook will automatically be part of the same network.

Make sure to target the cache:80/dataset as source when executing queries. If you want to experiment without this cache, you can target ldfserver:3000/dataset instead.

By default, the TPF server will be bound to the host machine on port 2999, and the cache will be bound to port 3000.

License

jbr.js is written by Ruben Taelman.

This code is copyrighted by Ghent University – imec and released under the MIT license.