Summarize mark results.
# S3 method for bench_mark
summary(object, filter_gc = TRUE, relative = FALSE, time_unit = NULL, ...)bench_mark object to summarize.
If TRUE remove iterations that contained at least one
garbage collection before summarizing. If TRUE but an expression had
a garbage collection in every iteration, filtering is disabled, with a warning.
If TRUE all summaries are computed relative to the minimum
execution time rather than absolute time.
If NULL the times are reported in a human readable
fashion depending on each value. If one of 'ns', 'us', 'ms', 's', 'm', 'h',
'd', 'w' the time units are instead expressed as nanoseconds, microseconds,
milliseconds, seconds, hours, minutes, days or weeks respectively.
Additional arguments ignored.
A tibble with the additional summary columns. The following summary columns are computed
expression - bench_expr The deparsed expression that was evaluated
(or its name if one was provided).
min - bench_time The minimum execution time.
median - bench_time The sample median of execution time.
itr/sec - double The estimated number of executions performed per
second.
mem_alloc - bench_bytes Total amount of memory allocated by R while
running the expression. Memory allocated outside the R heap, e.g. by
malloc() or new directly is not tracked, take care to avoid
misinterpreting the results if running code that may do this.
gc/sec - double The number of garbage collections per second.
n_itr - integer Total number of iterations after filtering
garbage collections (if filter_gc == TRUE).
n_gc - double Total number of garbage collections performed over all
iterations. This is a psudo-measure of the pressure on the garbage collector, if
it varies greatly between to alternatives generally the one with fewer
collections will cause fewer allocation in real usage.
total_time - bench_time The total time to perform the benchmarks.
result - list A list column of the object(s) returned by the
evaluated expression(s).
memory - list A list column with results from Rprofmem().
time - list A list column of bench_time vectors for each evaluated
expression.
gc - list A list column with tibbles containing the level of
garbage collection (0-2, columns) for each iteration (rows).
If filter_gc == TRUE (the default) runs that contain a garbage
collection will be removed before summarizing. This is most useful for fast
expressions when the majority of runs do not contain a gc. Call
summary(filter_gc = FALSE) if you would like to compute summaries with
these times, such as expressions with lots of allocations when all or most
runs contain a gc.
dat <- data.frame(x = runif(10000, 1, 1000), y=runif(10000, 1, 1000))
# `bench::mark()` implicitly calls summary() automatically
results <- bench::mark(
dat[dat$x > 500, ],
dat[which(dat$x > 500), ],
subset(dat, x > 500))
# However you can also do so explicitly to filter gc differently.
summary(results, filter_gc = FALSE)
#> # A tibble: 3 × 13
#> expression min median `itr/sec` mem_alloc `gc/sec` n_itr n_gc total_time
#> <bch:expr> <bch> <bch:> <dbl> <bch:byt> <dbl> <int> <dbl> <bch:tm>
#> 1 dat[dat$x > … 390µs 401µs 1558. 379KB 8.00 779 4 500ms
#> 2 dat[which(da… 289µs 297µs 2851. 261KB 10.0 1426 5 500ms
#> 3 subset(dat, … 517µs 530µs 1596. 496KB 10.0 798 5 500ms
#> # ℹ 4 more variables: result <list>, memory <list>, time <list>, gc <list>
# Or output relative times
summary(results, relative = TRUE)
#> # A tibble: 3 × 13
#> expression min median `itr/sec` mem_alloc `gc/sec` n_itr n_gc total_time
#> <bch:expr> <dbl> <dbl> <dbl> <dbl> <dbl> <int> <dbl> <bch:tm>
#> 1 dat[dat$x > … 1.35 1.35 1.31 1.45 1.08 775 4 316ms
#> 2 dat[which(da… 1 1 1.78 1 1 1421 5 424ms
#> 3 subset(dat, … 1.79 1.79 1 1.90 1.00 793 5 423ms
#> # ℹ 4 more variables: result <list>, memory <list>, time <list>, gc <list>