This section describes how to set up and run the Lehigh University Benchmark (LUBM) , using the scripts and configuration files included with the GraphDB-Lite distribution. Running the tests and the benchmarks may require minor modifications to these scripts and configuration files, as discussed in this section.
Running the benchmark (as well as the getting started application), can require modification of the script setvars (.cmd or .sh) in GraphDB-Lite's main folder. The most important setting is the specification of the Java virtual machine through the JAVA_HOME environment variable.
The performance of the benchmark can be tuned to the particular hardware on which it is running with modification of the repository specification file named lubm.ttl, which can be found in the lubm sub-directory of GraphDB-Lite's main directory.
To run the Lehigh University Benchmark (LUBM), it is necessary to generate the test file-set beforehand. This can be done using the lubm-generate (.cmd or .sh, respectively for Windows or Linux) script, which is part of the distribution's lubm sub-folder. The distribution includes a pre-built library of the benchmark's source code. The pre-built lubm.jar library is located in the ext distribution folder and also includes the wrapper classes that the benchmark's code-base uses in order to run against a Sesame repository (configured with GraphDB-Lite).
One should use the # symbol at the beginning of a line to comment it. The test should be launched via the lubm-benchmark script. Before either generation of datasets or execution of the test, GraphDB-Lite should be configured as discussed in the installation section by editing lubm.ttl, however the file provided is suitable for running the benchmark with small datasets. To find out more about this benchmark, visit the LUBM web site.
It is also possible to generate the LUBM datasets 'on-the-fly' during the loading stage. In order to do this, edit the lubm.config file and use a data directory with the format 'GENERATE-n' where 'n' is the number of universities, e.g.
This approach saves the extra step (and disk space) for generating data files.
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