A framework for RDFizing query logs and benchmarking queries and graph patterns.
LSQ2 introduces significant improvements over the prior version in every aspect: Ease-of-use, flexibility, modularity, consintency in the data model and generated IDs.
For detailed documentation about setup, use and concepts of the LSQ command line tool please refer to our LSQ Website.
This is a typical maven project and can is thus built with mvn clean install
.
For Ubuntu/Debian users: The build process creates a .deb
package that can be conviently installed after build with
./reinstall-deb.sh
(requires root access).
A quick reference for the typical process is as follows:
lsq rx probe file.log
lsq rx rdfize -e http://server.from/which/the/log/is/from file.log > file.log.trig
lsq rx benchmark create -d myDatasetLabel -e http://localhost:8890/sparql -o > benchmark.conf.ttl
lsq rx benchmark prepare -c benchmark.conf.ttl -o > benchmark.run.ttl
lsq rx benchmark run -c benchmark.run.ttl *.log.trig
The -o
option causes the settings to be written to the console. Omit -o
to have LSQ auto-generate files.
Run example running LSQ to RDFize SPARQL logs, input and output files in the current working directory (replace $(pwd)
by ${PWD}
for Windows PowerShell):
docker run -it -v $(pwd):/data ghcr.io/aksw/lsq rx rdfize --endpoint=http://dbpedia.org/sparql virtuoso.dbpedia.log
Build the Docker image from the source code:
docker build -t ghcr.io/aksw/lsq .
The source code of this repo is published under the Apache License Version 2.0.