[Rd] sum() returns NA on a long *logical* vector when nb of TRUE values exceeds 2^31

Martin Maechler maechler at stat.math.ethz.ch
Thu Feb 1 16:34:04 CET 2018


>>>>> Hervé Pagès <hpages at fredhutch.org>
>>>>>     on Tue, 30 Jan 2018 13:30:18 -0800 writes:

    > Hi Martin, Henrik,
    > Thanks for the follow up.

    > @Martin: I vote for 2) without *any* hesitation :-)

    > (and uniformity could be restored at some point in the
    > future by having prod(), rowSums(), colSums(), and others
    > align with the behavior of length() and sum())

As a matter of fact, I had procrastinated and worked at
implementing '2)' already a bit on the weekend and made it work
- more or less.  It needs a bit more work, and I had also been considering
replacing the numbers in the current overflow check

	if (ii++ > 1000) {	 \
	    ii = 0;							\
	    if (s > 9000000000000000L || s < -9000000000000000L) {	\
		if(!updated) updated = TRUE;				\
		*value = NA_INTEGER;					\
		warningcall(call, _("integer overflow - use sum(as.numeric(.))")); \
		return updated;						\
	    }								\
	}								\

i.e. think of tweaking the '1000' and '9000000000000000L', 
but decided to leave these and add comments there about why. For
the moment.
They may look arbitrary, but are not at all: If you multiply
them (which looks correct, if we check the sum 's' only every 1000-th
time ...((still not sure they *are* correct))) you get  9*10^18
which is only slightly smaller than  2^63 - 1 which may be the
maximal "LONG_INT" integer we have.

So, in the end, at least for now, we do not quite go all they way
but overflow a bit earlier,... but do potentially gain a bit of
speed, notably with the ITERATE_BY_REGION(..) macros
(which I did not show above).

Will hopefully become available in R-devel real soon now.

Martin

    > Cheers,
    > H.


    > On 01/27/2018 03:06 AM, Martin Maechler wrote:
    >>>>>>> Henrik Bengtsson <henrik.bengtsson at gmail.com>
    >>>>>>> on Thu, 25 Jan 2018 09:30:42 -0800 writes:
    >> 
    >> > Just following up on this old thread since matrixStats 0.53.0 is now
    >> > out, which supports this use case:
    >> 
    >> >> x <- rep(TRUE, times = 2^31)
    >> 
    >> >> y <- sum(x)
    >> >> y
    >> > [1] NA
    >> > Warning message:
    >> > In sum(x) : integer overflow - use sum(as.numeric(.))
    >> 
    >> >> y <- matrixStats::sum2(x, mode = "double")
    >> >> y
    >> > [1] 2147483648
    >> >> str(y)
    >> > num 2.15e+09
    >> 
    >> > No coercion is taking place, so the memory overhead is zero:
    >> 
    >> >> profmem::profmem(y <- matrixStats::sum2(x, mode = "double"))
    >> > Rprofmem memory profiling of:
    >> > y <- matrixStats::sum2(x, mode = "double")
    >> 
    >> > Memory allocations:
    >> > bytes calls
    >> > total     0
    >> 
    >> > /Henrik
    >> 
    >> Thank you, Henrik, for the reminder.
    >> 
    >> Back in June, I had mentioned to Hervé and R-devel that
    >> 'logical' should remain to be treated as 'integer' as in all
    >> arithmetic in (S and) R.     Hervé did mention the isum()
    >> function in the C code which is relevant here .. which does have
    >> a LONG INT counter already -- *but* if we consider that sum()
    >> has '...' i.e. a conceptually arbitrary number of long vector
    >> integer arguments that counter won't suffice even there.
    >> 
    >> Before talking about implementation / patch, I think we should
    >> consider 2 possible goals of a change --- I agree the status quo
    >> is not a real option
    >> 
    >> 1) sum(x) for logical and integer x  would return a double
    >> in any case and overflow should not happen (unless for
    >> the case where the result would be larger the
    >> .Machine$double.max which I think will not be possible
    >> even with "arbitrary" nargs() of sum.
    >> 
    >> 2) sum(x) for logical and integer x  should return an integer in
    >> all cases there is no overflow, including returning
    >> NA_integer_ in case of NAs.
    >> If there would be an overflow it must be detected "in time"
    >> and the result should be double.
    >> 
    >> The big advantage of 2) is that it is back compatible in 99.x %
    >> of use cases, and another advantage that it may be a very small
    >> bit more efficient.  Also, in the case of "counting" (logical),
    >> it is nice to get an integer instead of double when we can --
    >> entirely analogously to the behavior of length() which returns
    >> integer whenever possible.
    >> 
    >> The advantage of 1) is uniformity.
    >> 
    >> We should (at least provisionally) decide between 1) and 2) and then go for that.
    >> It could be that going for 1) may have bad
    >> compatibility-consequences in package space, because indeed we
    >> had documented sum() would be integer for logical and integer arguments.
    >> 
    >> I currently don't really have time to
    >> {work on implementing + dealing with the consequences}
    >> for either ..
    >> 
    >> Martin
    >> 
    >> > On Fri, Jun 2, 2017 at 1:58 PM, Henrik Bengtsson
    >> > <henrik.bengtsson at gmail.com> wrote:
    >> >> I second this feature request (it's understandable that this and
    >> >> possibly other parts of the code was left behind / forgotten after the
    >> >> introduction of long vector).
    >> >>
    >> >> I think mean() avoids full copies, so in the meanwhile, you can work
    >> >> around this limitation using:
    >> >>
    >> >> countTRUE <- function(x, na.rm = FALSE) {
    >> >> nx <- length(x)
    >> >> if (nx < .Machine$integer.max) return(sum(x, na.rm = na.rm))
    >> >> nx * mean(x, na.rm = na.rm)
    >> >> }
    >> >>
    >> >> (not sure if one needs to worry about rounding errors, i.e. where n %% 0 != 0)
    >> >>
    >> >> x <- rep(TRUE, times = .Machine$integer.max+1)
    >> >> object.size(x)
    >> >> ## 8589934632 bytes
    >> >>
    >> >> p <- profmem::profmem( n <- countTRUE(x) )
    >> >> str(n)
    >> >> ## num 2.15e+09
    >> >> print(n == .Machine$integer.max + 1)
    >> >> ## [1] TRUE
    >> >>
    >> >> print(p)
    >> >> ## Rprofmem memory profiling of:
    >> >> ## n <- countTRUE(x)
    >> >> ##
    >> >> ## Memory allocations:
    >> >> ##      bytes calls
    >> >> ## total     0
    >> >>
    >> >>
    >> >> FYI / related: I've just updated matrixStats::sum2() to support
    >> >> logicals (develop branch) and I'll also try to update
    >> >> matrixStats::count() to count beyond .Machine$integer.max.
    >> >>
    >> >> /Henrik
    >> >>
    >> >> On Fri, Jun 2, 2017 at 4:05 AM, Hervé Pagès <hpages at fredhutch.org> wrote:
    >> >>> Hi,
    >> >>>
    >> >>> I have a long numeric vector 'xx' and I want to use sum() to count
    >> >>> the number of elements that satisfy some criteria like non-zero
    >> >>> values or values lower than a certain threshold etc...
    >> >>>
    >> >>> The problem is: sum() returns an NA (with a warning) if the count
    >> >>> is greater than 2^31. For example:
    >> >>>
    >> >>> > xx <- runif(3e9)
    >> >>> > sum(xx < 0.9)
    >> >>> [1] NA
    >> >>> Warning message:
    >> >>> In sum(xx < 0.9) : integer overflow - use sum(as.numeric(.))
    >> >>>
    >> >>> This already takes a long time and doing sum(as.numeric(.)) would
    >> >>> take even longer and require allocation of 24Gb of memory just to
    >> >>> store an intermediate numeric vector made of 0s and 1s. Plus, having
    >> >>> to do sum(as.numeric(.)) every time I need to count things is not
    >> >>> convenient and is easy to forget.
    >> >>>
    >> >>> It seems that sum() on a logical vector could be modified to return
    >> >>> the count as a double when it cannot be represented as an integer.
    >> >>> Note that length() already does this so that wouldn't create a
    >> >>> precedent. Also and FWIW prod() avoids the problem by always returning
    >> >>> a double, whatever the type of the input is (except on a complex
    >> >>> vector).
    >> >>>
    >> >>> I can provide a patch if this change sounds reasonable.
    >> >>>
    >> >>> Cheers,
    >> >>> H.
    >> >>>
    >> >>> --
    >> >>> Hervé Pagès
    >> 
    >> 

    > -- 
    > Hervé Pagès

    > Program in Computational Biology
    > Division of Public Health Sciences
    > Fred Hutchinson Cancer Research Center
    > 1100 Fairview Ave. N, M1-B514
    > P.O. Box 19024
    > Seattle, WA 98109-1024

    > E-mail: hpages at fredhutch.org
    > Phone:  (206) 667-5791
    > Fax:    (206) 667-1319



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