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oxigraph/bench/README.md

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BSBM
====
The [Berlin SPARQL Benchmark (BSBM)](http://wifo5-03.informatik.uni-mannheim.de/bizer/berlinsparqlbenchmark/) is a simple SPARQL benchmark.
It provides a dataset generator and multiple set of queries grouped by "use cases".
## Results
We compare here Oxigraph with some existing SPARQL implementations (Blazegraph, Virtuoso and GraphDB).
The dataset used in the following charts is generated with 10k "products" (see [its spec](http://wifo5-03.informatik.uni-mannheim.de/bizer/berlinsparqlbenchmark/spec/Dataset/index.html)). It leads to the creation of 3.5M triples.
It has been executed on a Dell Precision 5520 with 16GB of RAM. For Oxigraph, available memory has been limited to 1GB.
### Explore
The [explore use case](http://wifo5-03.informatik.uni-mannheim.de/bizer/berlinsparqlbenchmark/spec/ExploreUseCase/index.html) is composed of 11 queries that do simple data retrieval.
Query 6 existed in previous versions of the benchmark as is now removed.
![explore use case results](bsbm.explore.svg)
### Business Intelligence
The [business intelligence use case](http://wifo5-03.informatik.uni-mannheim.de/bizer/berlinsparqlbenchmark/spec/BusinessIntelligenceUseCase/index.html) is composed of 8 complex analytics queries.
Query 4 seems to be failing on Virtuoso and query 5 on Blazegraph and GraphDB.
![explore use case results](bsbm.businessIntelligence.svg)
## How to reproduce the benchmark
The code of the benchmark is in the `bsbm-tools` submodule. You should pull it with a `git submodule update` before running the benchmark.
To run the benchmark for Oxigraph run `bash bsbm_oxigraph.sh`. It will compile the current Oxigraph code and run the benchmark against it.
You could tweak the number of products in the dataset and the available memory using the environment variables at the beginning of `bsbm_oxigraph.sh`.
To generate the plots run `python3 bsbsm-plot.py`.
Scripts are also provided for the other benchmarks (`bsbm_blazegraph.sh`, `bsbm_graphdb.sh` and `bsbm_virtuoso.sh`).