benchr
Package benchr
provides an infrastructure (framework) for precise
measurement of R expressions execution time.
Key features:
- Cross-platform implementation of the timer (the same code for all supported platforms);
- High precision measurement of time intervals: usually nano or microseconds;
- The reliability of the results due to a preliminary estimation of the timer error and subsequent correction of measurement results;
- The stability of the results due to multiple repetitions of the measurements and the use of robust (resistant to outliers) statistics (quantile);
- Informative output, including measurement accuracy, execution regime and descriptive statistics for each expression;
- Various graphical representation of measurement results, including box plots, scatter plots and violin plots.
Installation
To install the package from the CRAN run the following command:
install.packages("benchr", repos = "https://cloud.r-project.org/")
To install the development version the following command can be used:
install.packages("benchr", repos = "https://artemklevtsov.gitlab.io/benchr")
This package contains the compiled code, so to install it on Windows you will also need Rtools.
Usage
To measure execution time of arbitrary R code, benchr
provides
function benchmark()
, as well as a number of additional methods for
analysis and representation of results. Here’s an example of time
measurement for several expressions.
library(benchr)
benchmark(rep(1:100, each = 10), rep.int(1:100, rep.int(10, 100)))
#> Benchmark summary:
#> Time units : microseconds
#> expr n.eval min lw.qu median mean up.qu max total relative
#> rep(1:100, each = 10) 100 20.7 21.10 21.20 22.60 21.40 48.3 2260 2.97
#> rep.int(1:100, rep.int(10, 100)) 100 6.4 6.89 7.16 7.52 7.43 27.4 752 1.00
identical(rep(1:100, each = 10), rep.int(1:100, rep.int(10, 100)))
#> [1] TRUE
The resulting object can be saved as a variable and reused later in further methods:
res <- benchmark(NULL, {NULL}, {{{NULL}}})
summary(res)
#> Time units : nanoseconds
#> expr n.eval min lw.qu median mean up.qu max total relative
#> NULL 100 4 7 13.0 11.4 14 50 1140 1.00
#> { NULL } 100 38 43 48.5 58.6 55 850 5860 3.73
#> { { { NULL } } } 100 118 122 129.0 428.0 138 29100 42800 9.92
To present the results of measurements implemented additional methods
for the class benchmark
object:
mean
– means and confidence intervals for each R expression;summary
– statistics (quantiles, means) for each R expression;print
– text representation of results based on methodsummary
;plot
– scatter plot the execution time of each expression measure;boxplot
– box plot the execution time of each expression.
For further details refer to the manual pages and vignettes:
help(package = "benchr")
Bug reports
Use the following command to go to the page for bug report submissions:
bug.report(package = "benchr")
Before reporting a bug or submitting an issue, please do the following:
- Make sure that no error was found and corrected previously identified. You can use the search by the bug tracker;
- Check the news list for the current version of the package. An error
it might have been caused by changes in the package. This can be
done with
news(package = "benchr", Version == packageVersion("benchr"))
command; - Make a minimal reproducible example of the code that consistently causes the error;
- Make sure that the error triggered in the function from the
benchr
package, rather than in the code that you pass, that is other functions or packages; - Try to reproduce the error with the last development version of the package from the git repository.
When submitting a bug report please include the output produced by
functions traceback()
and sessionInfo()
. This may save a lot of
time.
License
The benchr
package is distributed under
GPLv2 license.