[Bioc-devel] Help understanding an R performance issue
The reason it's faster when shuffled vs. all that end is that when a miss happens R compares the string to all strings before it in the subscript. So it's a lot worse to have a miss towards the end. As Martin wrote, there are basically two possible improvements that are somewhat complementary: 1) Tell stringSubscript() that it is not replacing so there is no need to do that scan. This would require passing an argument down the call stack. 2) Do a self match on the subscript like in Martin's patch, although it should probably be done lazily on the first miss. Michael
On Fri, Jun 30, 2017 at 3:32 AM, Bernat Gel <bgel at igtp.cat> wrote:
Ok, so it seems more like a bug somewhere than something I falied to understand, then. One of the surprises for me is that shuffling the data so the misses do not happen one after the other seems to solve the issue... Thanks, Bernat *Bernat Gel Moreno* Bioinformatician Hereditary Cancer Program Program of Predictive and Personalized Medicine of Cancer (PMPPC) Germans Trias i Pujol Research Institute (IGTP) Campus Can Ruti Carretera de Can Ruti, Cam? de les Escoles s/n 08916 Badalona, Barcelona, Spain Tel: (+34) 93 554 3068 Fax: (+34) 93 497 8654 08916 Badalona, Barcelona, Spain bgel at igtp.cat <mailto:bgel at igtp.cat> www.germanstrias.org <http://www.germanstrias.org/> <http://www.germanstrias.org/> El 06/30/2017 a las 11:21 AM, Herv? Pag?s escribi?:
Hi Bernat, Michael, FWIW I reported this issue on R-devel a couple of times. Last time was in 2013: https://stat.ethz.ch/pipermail/r-devel/2013-May/066616.html Cheers, H. On 06/29/2017 11:58 PM, Bernat Gel wrote:
Yes, that would explain part of the situation. But example cc5 shows that hash misses would account only for part of the time. Thanks for taking a look into it Bernat *Bernat Gel Moreno* Bioinformatician Hereditary Cancer Program Program of Predictive and Personalized Medicine of Cancer (PMPPC) Germans Trias i Pujol Research Institute (IGTP) Campus Can Ruti Carretera de Can Ruti, Cam? de les Escoles s/n 08916 Badalona, Barcelona, Spain Tel: (+34) 93 554 3068 Fax: (+34) 93 497 8654 08916 Badalona, Barcelona, Spain bgel at igtp.cat <mailto:bgel at igtp.cat> www.germanstrias.org <https://urldefense.proofpoint.com/v2/url?u=http-3A__www.germanstrias.org_&d=DwIGaQ&c=eRAMFD45gAfqt84VtBcfhQ&r=BK7q3XeAvimeWdGbWY_wJYbW0WYiZvSXAJJKaaPhzWA&m=J5Gs0N5MH_g9sSCZ6jNoZm_Dkc0EcHLbOVPcNwdqZ_4&s=xNWXpfkTzxBoF_c0HoPoyQ0c3v6DA9_xY2WLtwleFlA&e=
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El 06/29/2017 a las 08:48 PM, Michael Lawrence escribi?:
Preliminary analysis suggests that this is due to hash misses. When that happens, R ends up doing costly string comparisons that are on the order of n^2 where 'n' is the length of the subscript. Looking into it. On Thu, Jun 29, 2017 at 10:43 AM, Bernat Gel <bgel at igtp.cat> wrote:
Hi all,
This is not strictly a Bioconductor question, but I hope some of the
experts
here can help me understand what's going on with a performance issue
I've
found working on a package.
It has to do with selecting elements from a named vector.
If we have a vector with the names of the chromosomes and their order
chrs <- setNames(1:24, paste0("chr", c(1:22, "X", "Y")))
chrs
chr1 chr2 chr3 chr4 chr5 chr6 chr7 chr8 chr9 chr10 chr11
chr12 chr13
chr14 chr15 chr16 chr17
1 2 3 4 5 6 7 8 9 10 11
12 13
14 15 16 17
chr18 chr19 chr20 chr21 chr22 chrX chrY
18 19 20 21 22 23 24
And we have a second vector of chromosomes (in this case, the
chromosomes
from SNP-array probes)
And we want to use the second vector to select from the first one by
name
cc <- c(rep("chr17", 19891), rep("chr18", 21353), rep("chr19",
14726),
rep("chr20", 18135), rep("chr21", 10068), rep("chr22", 10252),
rep("chrX", 17498), rep("chrY", 1296))
print(system.time(replicate(10, chrs[cc])))
user system elapsed
0.136 0.004 0.141
It's fast.
However, if I get the wrong names for the last two chromosomes (chr23
and
chr24 instead of chrX and chrY)
cc2 <- c(rep("chr17", 19891), rep("chr18", 21353), rep("chr19",
14726),
rep("chr20", 18135), rep("chr21", 10068), rep("chr22", 10252),
rep("chr23", 17498), rep("chr24", 1296))
print(system.time(replicate(10, chrs[cc2])))
user system elapsed
144.672 0.012 144.675
It is MUCH slower. (1000x)
BUT, if I shuffle the elements in the second vector
cc3 <- sample(cc2, length(cc), replace = FALSE)
print(system.time(replicate(10, chrs[cc3])))
user system elapsed
0.096 0.004 0.102
It's fast again!!!
The elapsed time is related to the number of elements BEFORE the
failing
names,
cc4 <- c(rep("chr22", 10252), rep("chr23", 17498), rep("chr24",
1296))
print(system.time(replicate(10, chrs[cc4])))
user system elapsed
17.332 0.004 17.336
cc5 <- c(rep("chr23", 17498), rep("chr24", 1296))
print(system.time(replicate(10, chrs[cc5])))
user system elapsed
1.872 0.000 1.901
so my guess is that it might come from moving around the vector in
memory
for each "failed" selection or something similar...
Is it correct? Is there anything I'm missing?
Thanks a lot
Bernat
--
*Bernat Gel Moreno*
Bioinformatician
Hereditary Cancer Program
Program of Predictive and Personalized Medicine of Cancer (PMPPC)
Germans Trias i Pujol Research Institute (IGTP)
Campus Can Ruti
Carretera de Can Ruti, Cam? de les Escoles s/n
08916 Badalona, Barcelona, Spain
Tel: (+34) 93 554 3068
Fax: (+34) 93 497 8654
08916 Badalona, Barcelona, Spain
bgel at igtp.cat <mailto:bgel at igtp.cat>
www.germanstrias.org
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