Re: [Bioc-devel] Help understanding an R performance issue

[juliosarmientota]

66

Sent from my MetroPCS 4G LTE Android deviceOn Jun 30, 2017 5:32 AM, Bernat Gel 
 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 s
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Re: [Bioc-devel] Help understanding an R performance issue

[Bernat Gel]

Ok, that makes sense

In my current use case I think I'll be able to filter out first the 
elements that will miss, so this behaviour is not triggered.


But it's good to know this happens so I can try to avoid it in the future.

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, Camí de les Escoles s/n
08916 Badalona, Barcelona, Spain

Tel: (+34) 93 554 3068
Fax: (+34) 93 497 8654
08916 Badalona, Barcelona, Spain
b...@igtp.cat 
www.germanstrias.org 









El 06/30/2017 a las 03:20 PM, Michael Lawrence escribió:

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  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, Camí de les Escoles s/n
08916 Badalona, Barcelona, Spain

Tel: (+34) 93 554 3068
Fax: (+34) 93 497 8654
08916 Badalona, Barcelona, Spain
b...@igtp.cat 
www.germanstrias.org 










El 06/30/2017 a las 11:21 AM, Hervé Pagès escribió:

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, Camí de les Escoles s/n
08916 Badalona, Barcelona, Spain

Tel: (+34) 93 554 3068
Fax: (+34) 93 497 8654
08916 Badalona, Barcelona, Spain
b...@igtp.cat 
www.germanstrias.org












El 06/29/2017 a las 08:48 PM, Michael Lawrence escribió:

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  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 1011
1213
14151617
chr18 chr19 chr20 chr21 chr22  chrX  chrY
 18192021222324

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.

Howe

Re: [Bioc-devel] Help understanding an R performance issue

[Michael Lawrence]

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  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, Camí de les Escoles s/n
> 08916 Badalona, Barcelona, Spain
>
> Tel: (+34) 93 554 3068
> Fax: (+34) 93 497 8654
> 08916 Badalona, Barcelona, Spain
> b...@igtp.cat 
> www.germanstrias.org 
>
> 
>
>
>
>
>
>
>
>
> El 06/30/2017 a las 11:21 AM, Hervé Pagès escribió:
>>
>> 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, Camí de les Escoles s/n
>>> 08916 Badalona, Barcelona, Spain
>>>
>>> Tel: (+34) 93 554 3068
>>> Fax: (+34) 93 497 8654
>>> 08916 Badalona, Barcelona, Spain
>>> b...@igtp.cat 
>>> www.germanstrias.org
>>>
>>> >>  >
>>>
>>>
>>> >>  >
>>>
>>>
>>>
>>>
>>>
>>>
>>>
>>> El 06/29/2017 a las 08:48 PM, Michael Lawrence escribió:

 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  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 1011
> 1213
> 14151617
> chr18 chr19 chr20 chr21 chr22  chrX  chrY
> 18192021222324
>
> 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),
> 

Re: [Bioc-devel] Help understanding an R performance issue

[Bernat Gel]

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, Camí de les Escoles s/n
08916 Badalona, Barcelona, Spain

Tel: (+34) 93 554 3068
Fax: (+34) 93 497 8654
08916 Badalona, Barcelona, Spain
b...@igtp.cat 
www.germanstrias.org 









El 06/30/2017 a las 11:21 AM, Hervé Pagès escribió:

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, Camí de les Escoles s/n
08916 Badalona, Barcelona, Spain

Tel: (+34) 93 554 3068
Fax: (+34) 93 497 8654
08916 Badalona, Barcelona, Spain
b...@igtp.cat 
www.germanstrias.org










El 06/29/2017 a las 08:48 PM, Michael Lawrence escribió:

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  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 1011
1213
14151617
chr18 chr19 chr20 chr21 chr22  chrX  chrY
18192021222324

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 Researc

Re: [Bioc-devel] Help understanding an R performance issue

[Hervé Pagès]

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, Camí de les Escoles s/n
08916 Badalona, Barcelona, Spain

Tel: (+34) 93 554 3068
Fax: (+34) 93 497 8654
08916 Badalona, Barcelona, Spain
b...@igtp.cat 
www.germanstrias.org










El 06/29/2017 a las 08:48 PM, Michael Lawrence escribió:

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  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 91011
1213
14151617
chr18 chr19 chr20 chr21 chr22  chrX  chrY
18192021222324

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, Camí de les Escoles s/n
08916 Badalona, Barcelona, Spain

Tel: (+34) 93 554 3068
Fax: (+34) 93 497 8654
08916 Badalona, Barcelona, Spain
b...@igtp.cat 
www.germanstrias.org










___

Re: [Bioc-devel] Help understanding an R performance issue

[Bernat Gel]

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, Camí de les Escoles s/n
08916 Badalona, Barcelona, Spain

Tel: (+34) 93 554 3068
Fax: (+34) 93 497 8654
08916 Badalona, Barcelona, Spain
b...@igtp.cat 
www.germanstrias.org 









El 06/29/2017 a las 08:48 PM, Michael Lawrence escribió:

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  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 91011 1213
14151617
chr18 chr19 chr20 chr21 chr22  chrX  chrY
18192021222324

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, Camí de les Escoles s/n
08916 Badalona, Barcelona, Spain

Tel: (+34) 93 554 3068
Fax: (+34) 93 497 8654
08916 Badalona, Barcelona, Spain
b...@igtp.cat 
www.germanstrias.org 









___
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https://stat.ethz.ch/mailman/listinfo/bioc-devel


___
Bioc-devel@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/bioc-devel

Re: [Bioc-devel] Help understanding an R performance issue

[Michael Lawrence]

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  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 91011 1213
> 14151617
> chr18 chr19 chr20 chr21 chr22  chrX  chrY
>18192021222324
>
> 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, Camí de les Escoles s/n
> 08916 Badalona, Barcelona, Spain
>
> Tel: (+34) 93 554 3068
> Fax: (+34) 93 497 8654
> 08916 Badalona, Barcelona, Spain
> b...@igtp.cat 
> www.germanstrias.org 
>
> 
>
>
>
>
>
>
>
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