Re: [Rd] we need an exists/get hybrid
All,
So that suggests that .GlobalEnv[[X]] is more efficient than get(X,
pos=1L). What about .GlobalEnv[[X]] - value, compared to assign(X,
value)?
Dave
On Wed, Dec 3, 2014 at 3:30 PM, Peter Haverty haverty.pe...@gene.com
wrote:
Thanks Winston! I'm amazed that [[ beats calling the .Internal
directly. I guess the difference between .Primitive vs. .Internal is
pretty significant for things on this time scale.
NULL meaning NULL and NULL meaning undefined would lead to the same path
for much of my code. I'll be swapping out many exists and get calls later
today. Thanks!
I do still think it would be very useful to have some way to discriminate
the two NULL cases. I'm reminded of how perl does the same thing. It's
been a while, but it was something like
if (defined(x{'c'})) { print x{'c'}; } # This is still two lookups, but it
has the defined concept.
or maybe even
if (defined( foo = x{'c'} ) ) { print foo; }
Thanks again for the timings!
Pete
Peter M. Haverty, Ph.D.
Genentech, Inc.
phave...@gene.com
On Wed, Dec 3, 2014 at 12:48 PM, Winston Chang winstoncha...@gmail.com
wrote:
I've looked at related speed issues in the past, and have a couple
related points to add. (I've put the info below at
http://rpubs.com/wch/46428.)
There's a significant amount of overhead just from calling the R
function get(). This is true even when you skip the pos argument and
provide envir. For example, if you call get(), it takes much more time
than .Internal(get()), which is what get() does.
If you already know that the object exists in an environment, it's
faster to use e$x, and slightly faster still to use e[[x]]:
e - new.env()
e$a - 1
# Accessing objects in environments
microbenchmark(
get(a, e, inherits = FALSE),
get(a, envir = e, inherits = FALSE),
.Internal(get(a, e, any, FALSE)),
e$a,
e[[a]],
.Primitive([[)(e, a),
unit = us
)
# median name
# 1 1.0300 get(a, e, inherits = FALSE)
# 2 0.9425 get(a, envir = e, inherits = FALSE)
# 3 0.3080 .Internal(get(a, e, any, FALSE))
# 4 0.2305 e$a
# 5 0.1740 e[[a]]
# 6 0.2905 .Primitive([[)(e, a)
A similar thing happens with exists(): the R function wrapper adds
significant overhead on top of .Internal(exists()). It's also faster
to use $ and [[, then test for NULL, but of course this won't
distinguish between objects that don't exist, and those that do exist
but have a NULL value:
# Test for existence of `a` (which exists), and `c` (which doesn't)
microbenchmark(
exists('a', e, inherits = FALSE),
exists('a', envir = e, inherits = FALSE),
.Internal(exists('a', e, 'any', FALSE)),
'a' %in% ls(e, all.names = TRUE),
is.null(e[['a']]),
is.null(e$a),
exists('c', e, inherits = FALSE),
exists('c', envir = e, inherits = FALSE),
.Internal(exists('c', e, 'any', FALSE)),
'c' %in% ls(e, all.names = TRUE),
is.null(e[['c']]),
is.null(e$c),
unit = us
)
#median name
# 1 1.2015 exists(a, e, inherits = FALSE)
# 2 1.0545 exists(a, envir = e, inherits = FALSE)
# 3 0.3615 .Internal(exists(a, e, any, FALSE))
# 4 7.6345 a %in% ls(e, all.names = TRUE)
# 5 0.3055is.null(e[[a]])
# 6 0.3270 is.null(e$a)
# 7 1.1890 exists(c, e, inherits = FALSE)
# 8 1.0370 exists(c, envir = e, inherits = FALSE)
# 9 0.3465 .Internal(exists(c, e, any, FALSE))
# 10 7.5475 c %in% ls(e, all.names = TRUE)
# 11 0.2675is.null(e[[c]])
# 12 0.3010 is.null(e$c)
-Winston
On Tue, Dec 2, 2014 at 8:46 PM, Peter Haverty haverty.pe...@gene.com
wrote:
Hi All,
I've been looking into speeding up the loading of packages that use a
lot
of S4. After profiling I noticed the exists function accounts for a
surprising fraction of the time. I have some thoughts about speeding
up
exists (below). More to the point of this post, Martin Mächler noted
that
'exists' and 'get' are often used in conjunction. Both functions are
different usages of the do_get C function, so it's a pity to run that
twice.
get gives an error when a symbol is not found, so you can't just do a
'get'. With R's C library, one might do
SEXP x = findVarInFrame3(symbol,env);
if (x != R_UnboundValue) {
// do stuff with x
}
It would be very convenient to have something like this at the R level.
We
don't want to do any tryCatch stuff or to add args to get (That would
kill
any speed advantage. The overhead for handling redundant args accounts
for
30% of the time used by exists). Michael Lawrence and I worked out
that
we need a function that returns either the
Re: [Rd] we need an exists/get hybrid
David, 'assign' is slower than '-':
## median expr
## 1 0.1440 X - letters
## 2 0.4420 .Internal(assign(X, letters, e, F))
## 3 1.1820 e[[X]] - letters
## 4 1.2570e$X - letters
## 5 1.8380 assign(X, letters, envir = e, inherits = F)
## 6 1.9415 assign(X, letters, e, inherits = F)
(micro seconds, 500 times, see http://rpubs.com/setempler/46568)
---
Two questions:
'X-letters' is the fastest since it does not need to change the
environment from 'benchmark' to 'e'?
Why is the call to '.Internal' faster than '[[-' as compared to the
'get'/'[[' functions/benchmark of Winston?
thanks,
s
On 4 December 2014 at 15:24, Lorenz, David lor...@usgs.gov wrote:
All,
So that suggests that .GlobalEnv[[X]] is more efficient than get(X,
pos=1L). What about .GlobalEnv[[X]] - value, compared to assign(X,
value)?
Dave
On Wed, Dec 3, 2014 at 3:30 PM, Peter Haverty haverty.pe...@gene.com
wrote:
Thanks Winston! I'm amazed that [[ beats calling the .Internal
directly. I guess the difference between .Primitive vs. .Internal is
pretty significant for things on this time scale.
NULL meaning NULL and NULL meaning undefined would lead to the same path
for much of my code. I'll be swapping out many exists and get calls later
today. Thanks!
I do still think it would be very useful to have some way to discriminate
the two NULL cases. I'm reminded of how perl does the same thing. It's
been a while, but it was something like
if (defined(x{'c'})) { print x{'c'}; } # This is still two lookups, but it
has the defined concept.
or maybe even
if (defined( foo = x{'c'} ) ) { print foo; }
Thanks again for the timings!
Pete
Peter M. Haverty, Ph.D.
Genentech, Inc.
phave...@gene.com
On Wed, Dec 3, 2014 at 12:48 PM, Winston Chang winstoncha...@gmail.com
wrote:
I've looked at related speed issues in the past, and have a couple
related points to add. (I've put the info below at
http://rpubs.com/wch/46428.)
There's a significant amount of overhead just from calling the R
function get(). This is true even when you skip the pos argument and
provide envir. For example, if you call get(), it takes much more time
than .Internal(get()), which is what get() does.
If you already know that the object exists in an environment, it's
faster to use e$x, and slightly faster still to use e[[x]]:
e - new.env()
e$a - 1
# Accessing objects in environments
microbenchmark(
get(a, e, inherits = FALSE),
get(a, envir = e, inherits = FALSE),
.Internal(get(a, e, any, FALSE)),
e$a,
e[[a]],
.Primitive([[)(e, a),
unit = us
)
# median name
# 1 1.0300 get(a, e, inherits = FALSE)
# 2 0.9425 get(a, envir = e, inherits = FALSE)
# 3 0.3080 .Internal(get(a, e, any, FALSE))
# 4 0.2305 e$a
# 5 0.1740 e[[a]]
# 6 0.2905 .Primitive([[)(e, a)
A similar thing happens with exists(): the R function wrapper adds
significant overhead on top of .Internal(exists()). It's also faster
to use $ and [[, then test for NULL, but of course this won't
distinguish between objects that don't exist, and those that do exist
but have a NULL value:
# Test for existence of `a` (which exists), and `c` (which doesn't)
microbenchmark(
exists('a', e, inherits = FALSE),
exists('a', envir = e, inherits = FALSE),
.Internal(exists('a', e, 'any', FALSE)),
'a' %in% ls(e, all.names = TRUE),
is.null(e[['a']]),
is.null(e$a),
exists('c', e, inherits = FALSE),
exists('c', envir = e, inherits = FALSE),
.Internal(exists('c', e, 'any', FALSE)),
'c' %in% ls(e, all.names = TRUE),
is.null(e[['c']]),
is.null(e$c),
unit = us
)
#median name
# 1 1.2015 exists(a, e, inherits = FALSE)
# 2 1.0545 exists(a, envir = e, inherits = FALSE)
# 3 0.3615 .Internal(exists(a, e, any, FALSE))
# 4 7.6345 a %in% ls(e, all.names = TRUE)
# 5 0.3055is.null(e[[a]])
# 6 0.3270 is.null(e$a)
# 7 1.1890 exists(c, e, inherits = FALSE)
# 8 1.0370 exists(c, envir = e, inherits = FALSE)
# 9 0.3465 .Internal(exists(c, e, any, FALSE))
# 10 7.5475 c %in% ls(e, all.names = TRUE)
# 11 0.2675is.null(e[[c]])
# 12 0.3010 is.null(e$c)
-Winston
On Tue, Dec 2, 2014 at 8:46 PM, Peter Haverty haverty.pe...@gene.com
wrote:
Hi All,
I've been looking into speeding up the loading of packages that use a
lot
of S4. After profiling I noticed the exists function accounts for a
surprising fraction of the time. I have some thoughts about speeding
up
Re: [Rd] we need an exists/get hybrid
I've looked at related speed issues in the past, and have a couple
related points to add. (I've put the info below at
http://rpubs.com/wch/46428.)
There’s a significant amount of overhead just from calling the R
function get(). This is true even when you skip the pos argument and
provide envir. For example, if you call get(), it takes much more time
than .Internal(get()), which is what get() does.
If you already know that the object exists in an environment, it's
faster to use e$x, and slightly faster still to use e[[x]]:
e - new.env()
e$a - 1
# Accessing objects in environments
microbenchmark(
get(a, e, inherits = FALSE),
get(a, envir = e, inherits = FALSE),
.Internal(get(a, e, any, FALSE)),
e$a,
e[[a]],
.Primitive([[)(e, a),
unit = us
)
# median name
# 1 1.0300 get(a, e, inherits = FALSE)
# 2 0.9425 get(a, envir = e, inherits = FALSE)
# 3 0.3080 .Internal(get(a, e, any, FALSE))
# 4 0.2305 e$a
# 5 0.1740 e[[a]]
# 6 0.2905 .Primitive([[)(e, a)
A similar thing happens with exists(): the R function wrapper adds
significant overhead on top of .Internal(exists()). It’s also faster
to use $ and [[, then test for NULL, but of course this won’t
distinguish between objects that don’t exist, and those that do exist
but have a NULL value:
# Test for existence of `a` (which exists), and `c` (which doesn't)
microbenchmark(
exists('a', e, inherits = FALSE),
exists('a', envir = e, inherits = FALSE),
.Internal(exists('a', e, 'any', FALSE)),
'a' %in% ls(e, all.names = TRUE),
is.null(e[['a']]),
is.null(e$a),
exists('c', e, inherits = FALSE),
exists('c', envir = e, inherits = FALSE),
.Internal(exists('c', e, 'any', FALSE)),
'c' %in% ls(e, all.names = TRUE),
is.null(e[['c']]),
is.null(e$c),
unit = us
)
#median name
# 1 1.2015 exists(a, e, inherits = FALSE)
# 2 1.0545 exists(a, envir = e, inherits = FALSE)
# 3 0.3615 .Internal(exists(a, e, any, FALSE))
# 4 7.6345 a %in% ls(e, all.names = TRUE)
# 5 0.3055is.null(e[[a]])
# 6 0.3270 is.null(e$a)
# 7 1.1890 exists(c, e, inherits = FALSE)
# 8 1.0370 exists(c, envir = e, inherits = FALSE)
# 9 0.3465 .Internal(exists(c, e, any, FALSE))
# 10 7.5475 c %in% ls(e, all.names = TRUE)
# 11 0.2675is.null(e[[c]])
# 12 0.3010 is.null(e$c)
-Winston
On Tue, Dec 2, 2014 at 8:46 PM, Peter Haverty haverty.pe...@gene.com wrote:
Hi All,
I've been looking into speeding up the loading of packages that use a lot
of S4. After profiling I noticed the exists function accounts for a
surprising fraction of the time. I have some thoughts about speeding up
exists (below). More to the point of this post, Martin Mächler noted that
'exists' and 'get' are often used in conjunction. Both functions are
different usages of the do_get C function, so it's a pity to run that twice.
get gives an error when a symbol is not found, so you can't just do a
'get'. With R's C library, one might do
SEXP x = findVarInFrame3(symbol,env);
if (x != R_UnboundValue) {
// do stuff with x
}
It would be very convenient to have something like this at the R level. We
don't want to do any tryCatch stuff or to add args to get (That would kill
any speed advantage. The overhead for handling redundant args accounts for
30% of the time used by exists). Michael Lawrence and I worked out that
we need a function that returns either the desired object, or something
that represents R_UnboundValue. We also need a very cheap way to check if
something equals this new R_UnboundValue. This might look like
if (defined(x - fetch(symbol, env))) {
do_stuff_with_x(x)
}
A few more thoughts about exists:
Moving the bit of R in the exists function to C saves 10% of the time.
Dropping the redundant pos and frame args entirely saves 30% of the time
used by this function. I suggest that the arguments of both get and
exists should
be simplified to (x, envir, mode, inherits). The existing C code handles
numeric, character, and environment input for where. The arg frame is
rarely used (0/128 exists calls in the methods package). Users that need to
can call sys.frame themselves. get already lacks a frame argument and the
manpage for exists notes that envir is only there for backwards
compatibility. Let's deprecate the extra args in exists and get and perhaps
move the extra argument handling to C in the interim. Similarly, the
assign function does nothing with the immediate argument.
I'd be interested to hear if there is any support for a fetch-like
function (and/or deprecating some unused arguments).
All the best,
Pete
Pete
Peter M. Haverty, Ph.D.
Genentech, Inc.
phave...@gene.com
[[alternative HTML version
Re: [Rd] we need an exists/get hybrid
Thanks Winston! I'm amazed that [[ beats calling the .Internal
directly. I guess the difference between .Primitive vs. .Internal is
pretty significant for things on this time scale.
NULL meaning NULL and NULL meaning undefined would lead to the same path
for much of my code. I'll be swapping out many exists and get calls later
today. Thanks!
I do still think it would be very useful to have some way to discriminate
the two NULL cases. I'm reminded of how perl does the same thing. It's
been a while, but it was something like
if (defined(x{'c'})) { print x{'c'}; } # This is still two lookups, but it
has the defined concept.
or maybe even
if (defined( foo = x{'c'} ) ) { print foo; }
Thanks again for the timings!
Pete
Peter M. Haverty, Ph.D.
Genentech, Inc.
phave...@gene.com
On Wed, Dec 3, 2014 at 12:48 PM, Winston Chang winstoncha...@gmail.com
wrote:
I've looked at related speed issues in the past, and have a couple
related points to add. (I've put the info below at
http://rpubs.com/wch/46428.)
There's a significant amount of overhead just from calling the R
function get(). This is true even when you skip the pos argument and
provide envir. For example, if you call get(), it takes much more time
than .Internal(get()), which is what get() does.
If you already know that the object exists in an environment, it's
faster to use e$x, and slightly faster still to use e[[x]]:
e - new.env()
e$a - 1
# Accessing objects in environments
microbenchmark(
get(a, e, inherits = FALSE),
get(a, envir = e, inherits = FALSE),
.Internal(get(a, e, any, FALSE)),
e$a,
e[[a]],
.Primitive([[)(e, a),
unit = us
)
# median name
# 1 1.0300 get(a, e, inherits = FALSE)
# 2 0.9425 get(a, envir = e, inherits = FALSE)
# 3 0.3080 .Internal(get(a, e, any, FALSE))
# 4 0.2305 e$a
# 5 0.1740 e[[a]]
# 6 0.2905 .Primitive([[)(e, a)
A similar thing happens with exists(): the R function wrapper adds
significant overhead on top of .Internal(exists()). It's also faster
to use $ and [[, then test for NULL, but of course this won't
distinguish between objects that don't exist, and those that do exist
but have a NULL value:
# Test for existence of `a` (which exists), and `c` (which doesn't)
microbenchmark(
exists('a', e, inherits = FALSE),
exists('a', envir = e, inherits = FALSE),
.Internal(exists('a', e, 'any', FALSE)),
'a' %in% ls(e, all.names = TRUE),
is.null(e[['a']]),
is.null(e$a),
exists('c', e, inherits = FALSE),
exists('c', envir = e, inherits = FALSE),
.Internal(exists('c', e, 'any', FALSE)),
'c' %in% ls(e, all.names = TRUE),
is.null(e[['c']]),
is.null(e$c),
unit = us
)
#median name
# 1 1.2015 exists(a, e, inherits = FALSE)
# 2 1.0545 exists(a, envir = e, inherits = FALSE)
# 3 0.3615 .Internal(exists(a, e, any, FALSE))
# 4 7.6345 a %in% ls(e, all.names = TRUE)
# 5 0.3055is.null(e[[a]])
# 6 0.3270 is.null(e$a)
# 7 1.1890 exists(c, e, inherits = FALSE)
# 8 1.0370 exists(c, envir = e, inherits = FALSE)
# 9 0.3465 .Internal(exists(c, e, any, FALSE))
# 10 7.5475 c %in% ls(e, all.names = TRUE)
# 11 0.2675is.null(e[[c]])
# 12 0.3010 is.null(e$c)
-Winston
On Tue, Dec 2, 2014 at 8:46 PM, Peter Haverty haverty.pe...@gene.com
wrote:
Hi All,
I've been looking into speeding up the loading of packages that use a lot
of S4. After profiling I noticed the exists function accounts for a
surprising fraction of the time. I have some thoughts about speeding up
exists (below). More to the point of this post, Martin M�chler noted that
'exists' and 'get' are often used in conjunction. Both functions are
different usages of the do_get C function, so it's a pity to run that
twice.
get gives an error when a symbol is not found, so you can't just do a
'get'. With R's C library, one might do
SEXP x = findVarInFrame3(symbol,env);
if (x != R_UnboundValue) {
// do stuff with x
}
It would be very convenient to have something like this at the R level.
We
don't want to do any tryCatch stuff or to add args to get (That would
kill
any speed advantage. The overhead for handling redundant args accounts
for
30% of the time used by exists). Michael Lawrence and I worked out
that
we need a function that returns either the desired object, or something
that represents R_UnboundValue. We also need a very cheap way to check if
something equals this new R_UnboundValue. This might look like
if (defined(x - fetch(symbol, env))) {
do_stuff_with_x(x)
}
A few more thoughts about exists:
Moving the bit of R in the exists function to C saves 10% of the time.
