R package for computing diefficiency metrics dief@t and dief@k.
The metrics dief@t and dief@k allow for measuring the diefficiency during an elapsed time period t or while k answers are produced, respectively. dief@t and dief@k rely on the computation of the area under the curve of answer traces, and thus capturing the answer rate concentration over a time interval.
To download the development version of the dief package directly from GitHub, type the following at the R command line:
# If you have not installed the "devtools" package.
install.packages("devtools")
# Install the dief package.
devtools::install_github("maribelacosta/dief")library("dief")
# Use answer traces provided in the package: Compare three approaches "Selective", "Not Adaptive", "Random" when executing the test "Q9.sparql".
traces
# Plot answer traces for test "Q9.sparql".
plotAnswerTrace(traces, "Q9.sparql")
# Compute dief@t when t is the time where the slowest approach produced the last answer.
dieft(traces, "Q9.sparql")
# Compute dief@t after 7.5 time units (seconds) of execution.
dieft(traces, "Q9.sparql", 7.5)Learn step by step to use the dief R package with Jupyter Notebooks.
- Introduction to the
diefpackage and reproducibility of the experimental results reported at [1]: https://github.com/maribelacosta/dief-notebooks/blob/master/Dief-Intro.ipynb
Check the dief-app Shiny app.
- Visualize the
dief-appat: http://km.aifb.kit.edu/services/dief-app/
This package is licensed under the MIT License.
If you are using the dief package to compute dief@t or dief@k, please cite the dief package using the citation generated with the R built-in command citation("dief") as follows:
library("dief")
citation("dief")In addition, if you are reporting dief@t or dief@k, please cite our main publication [1].
[1] Maribel Acosta, Maria-Esther Vidal, York Sure-Vetter. Diefficiency Metrics: Measuring the Continuous Efficiency of Query Processing Approaches. In Proceedings of the International Semantic Web Conference, 2017. Nominated to Best Paper Award at the Resource Track. https://doi.org/10.1007/978-3-319-68204-4_1
[2] Maribel Acosta, Maria-Esther Vidal. Measuring the Performance of Continuous Query Processing Approaches with dief@t and dief@k. In the International Semantic Web Conference, Posters and Demos, 2017.