| Rprof {utils} | R Documentation |
Enable or disable profiling of the execution of R expressions.
Rprof(filename = "Rprof.out", append = FALSE, interval = 0.02,
memory.profiling = FALSE, gc.profiling = FALSE,
line.profiling = FALSE, numfiles = 100L, bufsize = 10000L)
filename |
The file to be used for recording the profiling results.
Set to |
append |
logical: should the file be over-written or appended to? |
interval |
real: time interval between samples. |
memory.profiling |
logical: write memory use information to the file? |
gc.profiling |
logical: record whether GC is running? |
line.profiling |
logical: write line locations to the file? |
numfiles, bufsize |
integers: line profiling memory allocation |
Enabling profiling automatically disables any existing profiling to another or the same file.
Profiling works by writing out the call stack every interval
seconds, to the file specified. Either the summaryRprof
function or the wrapper script R CMD Rprof can be used to
process the output file to produce a summary of the usage; use
R CMD Rprof --help for usage information.
How time is measured varies by platform:
Exactly what the time interval measures is subtle: it is time that the
R process is running and executing an R command. It is not however just
CPU time, for if readline() is waiting for input, that counts
(on Windows, but not on a Unix-alike).
Note that the timing interval cannot be too small, for the time spent in each profiling step is added to the interval. What is feasible is machine-dependent, but 10ms seemed as small as advisable on a 1GHz machine.
it is the CPU
time of the R process, so for example excludes time when R is waiting
for input or for processes run by system to return.
Note that the timing interval cannot usefully be too small: once the timer goes off, the information is not recorded until the next timing click (probably in the range 1–10 ms).
Functions will only be recorded in the profile log if they put a
context on the call stack (see sys.calls). Some
primitive functions do not do so: specifically those which are
of type "special" (see the ‘R Internals’ manual
for more details).
Individual statements will be recorded in the profile log if
line.profiling is TRUE, and if the code being executed
was parsed with source references. See parse for a
discussion of source references. By default the statement locations
are not shown in summaryRprof, but see that help page
for options to enable the display.
Profiling is not available on all platforms. By default, support for profiling is compiled in if possible – configure R with --disable-R-profiling to change this.
As R profiling uses the same mechanisms as C profiling, the two
cannot be used together, so do not use Rprof in an executable
built for C-level profiling.
filename can be a UTF-8-encoded filepath that cannot be translated to
the current locale.
The profiler interrupts R asynchronously, and it cannot allocate
memory to store results as it runs. This affects line profiling,
which needs to store an unknown number of file pathnames. The
numfiles and bufsize arguments control the size of
pre-allocated buffers to hold these results: the former counts the
maximum number of paths, the latter counts the numbers of bytes in
them. If the profiler runs out of space it will skip recording the
line information for new files, and issue a warning when
Rprof(NULL) is called to finish profiling.
The chapter on “Tidying and profiling R code” in “Writing R Extensions” (see the ‘doc/manual’ subdirectory of the R source tree).
summaryRprof to analyse the output file.
tracemem, Rprofmem for other ways to track
memory use.
## Not run: Rprof() ## some code to be profiled Rprof(NULL) ## some code NOT to be profiled Rprof(append = TRUE) ## some code to be profiled Rprof(NULL) \dots ## Now post-process the output as described in Details ## End(Not run)