Title: | Simple Memory Profiling for R |
---|---|
Description: | A simple and light-weight API for memory profiling of R expressions. The profiling is built on top of R's built-in memory profiler ('utils::Rprofmem()'), which records every memory allocation done by R (also native code). |
Authors: | Henrik Bengtsson [aut, cre, cph] |
Maintainer: | Henrik Bengtsson <[email protected]> |
License: | LGPL (>= 2.1) |
Version: | 0.6.0 |
Built: | 2024-11-30 04:32:56 UTC |
Source: | https://github.com/HenrikBengtsson/profmem |
profmem()
evaluates and memory profiles an R expression.
profmem_begin()
starts the memory profiling of all the following R
evaluations until profmem_end()
is called.
profmem( expr, envir = parent.frame(), substitute = TRUE, threshold = getOption("profmem.threshold", 0L) ) profmem_begin(threshold = getOption("profmem.threshold", 0L)) profmem_end() profmem_suspend() profmem_resume() profmem_status() profmem_depth()
profmem( expr, envir = parent.frame(), substitute = TRUE, threshold = getOption("profmem.threshold", 0L) ) profmem_begin(threshold = getOption("profmem.threshold", 0L)) profmem_end() profmem_suspend() profmem_resume() profmem_status() profmem_depth()
expr |
An R expression to be evaluated and profiled. |
envir |
The environment in which the expression should be evaluated. |
substitute |
Should |
threshold |
The smallest memory allocation (in bytes) to log. |
In order for memory profiling to work, R must have been built with memory
profiling enabled. Function
base::capabilities("profmem")
will
return TRUE
of it is enabled, otherwise FALSE
.
If memory profiling is not supported, profmem()
and profmem_begin()
will produce an informative error. The pre-built R binaries on
CRAN support memory profiling.
What is logged? The profmem()
function uses utils::Rprofmem()
for
logging memory, which logs all memory allocations that are done via the
R framework. Specifically, the logger is tied to allocVector3()
part
of R's native API. This means that nearly all memory allocations done
in R are logged. Neither memory deallocations nor garbage collection
events are logged. Furthermore, allocations done by non-R native libraries
or R packages that use native code Calloc() / Free()
for internal objects
are also not logged.
Any memory events that would occur due to calling any of the profmem functions themselves will not be logged and not be part of the returned profile data (regardless whether memory profiling is active or not). This is intentional.
If a profmem profiling is already active, profmem()
and profmem_begin()
performs an independent, nested profiling, which does not affect the
already active one. When the active one completes, it will contain all
memory events also collected by the nested profiling as if the nested one
never occurred.
Profiling gathered by profmem will be corrupted if the code profiled
calls utils::Rprofmem()
, with the exception of such calls done via the
profmem package itself.
profmem()
and profmem_end()
returns the collected allocation
data as an Rprofmem
data.frame with additional attributes set.
An Rprofmem
data.frame has columns what
, bytes
, and trace
, with:
what
: (character) type of memory event;
either "alloc"
or "new page"
bytes
: (numeric) number of bytes allocated or NA_real_
(when what
is "new page"
)
trace
: (list of character vectors) zero or more function names
The attributes set are:
threshold
: The threshold used (= argument threshold
)
expression
: The expression profiled (= argument expr
)
value
: The value of the evaluated expression
(only set if there was no error)
error
: The error object in case the evaluation failed
(only set if there was an error)
profmem_begin()
returns (invisibly) the number of nested profmem
session currently active.
profmem_suspend()
and profmem_resume()
returns nothing.
profmem_status()
returns "inactive"
, "active"
,
or "suspended"
.
promem_depth()
returns a non-negative integer.
if (capabilities("profmem")) { ## Memory profile an R expression p <- profmem({ x <- raw(1000) A <- matrix(rnorm(100), ncol = 10) }) ## Display the results print(p) ## Total amount of memory allocation total(p) ## Allocations greater than 1 kB p2 <- subset(p, bytes > 1000) print(p2) ## The expression is evaluated in the calling environment str(x) str(A) }
if (capabilities("profmem")) { ## Memory profile an R expression p <- profmem({ x <- raw(1000) A <- matrix(rnorm(100), ncol = 10) }) ## Display the results print(p) ## Total amount of memory allocation total(p) ## Allocations greater than 1 kB p2 <- subset(p, bytes > 1000) print(p2) ## The expression is evaluated in the calling environment str(x) str(A) }
Reads and parses an Rprofmem log file that was created by
utils::Rprofmem()
.
readRprofmem(pathname, as = c("Rprofmem", "fixed", "raw"), drop = 0L, ...)
readRprofmem(pathname, as = c("Rprofmem", "fixed", "raw"), drop = 0L, ...)
pathname |
The Rprofmem log file to be read. |
as |
Specifies in what format data should be returned.
If |
drop |
Number of levels to drop from the top of the call stack. |
... |
Not used |
An Rprofmem
data.frame or a character vector (if as
is "raw"
or "fixed"
).
An Rprofmem
data.frame has columns what
, bytes
, and trace
, with:
what
: (character) type of memory event;
either "alloc"
or "new page"
bytes
: (numeric) number of bytes allocated or NA_real_
(when what
is "new page"
)
trace
: (list of character vectors) zero or more function names
Ref. 1: https://github.com/HenrikBengtsson/Wishlist-for-R/issues/25
file <- system.file("extdata", "example.Rprofmem.out", package = "profmem") raw <- readRprofmem(file, as = "raw") cat(raw, sep = "\n") profmem <- readRprofmem(file, as = "Rprofmem") print(profmem)
file <- system.file("extdata", "example.Rprofmem.out", package = "profmem") raw <- readRprofmem(file, as = "raw") cat(raw, sep = "\n") profmem <- readRprofmem(file, as = "Rprofmem") print(profmem)