Re: [Rd] readLines() segfaults on large file & question on how to work around
As of R-devel 72925 one gets a proper error message instead of the crash.
Tomas
On 09/04/2017 08:46 AM, rh...@eoos.dds.nl wrote:
Although the problem can apparently be avoided in this case. readLines
causing a segfault still seems unwanted behaviour to me. I can
replicate this with the example below (sessionInfo is further down):
# Generate an example file
l <- paste0(sample(c(letters, LETTERS), 1E6, replace = TRUE),
collapse="")
con <- file("test.txt", "wt")
for (i in seq_len(2500)) {
writeLines(l, con, sep ="")
}
close(con)
# Causes segfault:
readLines("test.txt")
Also the error reported by readr is also reproduced (a more
informative error message and checking for integer overflows would be
nice). I will report this with readr.
library(readr)
read_file("test.txt")
# Error in read_file_(ds, locale) : negative length vectors are not
# allowed
--
Jan
> sessionInfo()
R version 3.4.1 (2017-06-30)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 17.04
Matrix products: default
BLAS: /usr/lib/libblas/libblas.so.3.7.0
LAPACK: /usr/lib/lapack/liblapack.so.3.7.0
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=nl_NL.UTF-8
[4] LC_COLLATE=en_US.UTF-8 LC_MONETARY=nl_NL.UTF-8
LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=nl_NL.UTF-8 LC_NAME=C LC_ADDRESS=C
[10] LC_TELEPHONE=C LC_MEASUREMENT=nl_NL.UTF-8
LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] readr_1.1.1
loaded via a namespace (and not attached):
[1] compiler_3.4.1 R6_2.2.2 hms_0.3tools_3.4.1
tibble_1.3.3 Rcpp_0.12.12 rlang_0.1.2
On 03-09-17 20:50, Jennifer Lyon wrote:
Jeroen:
Thank you for pointing me to ndjson, which I had not heard of and is
exactly my case.
My experience:
jsonlite::stream_in - segfaults
ndjson::stream_in - my fault, I am running Ubuntu 14.04 and it is too
old
so it won't compile the package
corpus::read_ndjson - works!!! Of course it does a different
simplification
than jsonlite::fromJSON, so I have to change some code, but it
works
beautifully at least in simple tests. The memory-map option may
be of
use in the future.
Another correspondent said that strings in R can only be 2^31-1 long,
which
is why any "solution" that tries to load the whole file into R first
as a
string, will fail.
Thanks for suggesting a path forward for me!
Jen
On Sun, Sep 3, 2017 at 2:15 AM, Jeroen Ooms
wrote:
On Sat, Sep 2, 2017 at 8:58 PM, Jennifer Lyon
wrote:
I have a 2.1GB JSON file. Typically I use readLines() and
jsonlite:fromJSON() to extract data from a JSON file.
If your data consists of one json object per line, this is called
'ndjson'. There are several packages specialized to read ndjon files:
- corpus::read_ndjson
- ndjson::stream_in
- jsonlite::stream_in
In particular the 'corpus' package handles large files really well
because it has an option to memory-map the file instead of reading all
of its data into memory.
If the data is too large to read, you can preprocess it using
https://stedolan.github.io/jq/ to extract the fields that you need.
You really don't need hadoop/spark/etc for this.
[[alternative HTML version deleted]]
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Re: [Rd] readLines() segfaults on large file & question on how to work around
Although the problem can apparently be avoided in this case. readLines
causing a segfault still seems unwanted behaviour to me. I can replicate
this with the example below (sessionInfo is further down):
# Generate an example file
l <- paste0(sample(c(letters, LETTERS), 1E6, replace = TRUE),
collapse="")
con <- file("test.txt", "wt")
for (i in seq_len(2500)) {
writeLines(l, con, sep ="")
}
close(con)
# Causes segfault:
readLines("test.txt")
Also the error reported by readr is also reproduced (a more informative
error message and checking for integer overflows would be nice). I will
report this with readr.
library(readr)
read_file("test.txt")
# Error in read_file_(ds, locale) : negative length vectors are not
# allowed
--
Jan
> sessionInfo()
R version 3.4.1 (2017-06-30)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 17.04
Matrix products: default
BLAS: /usr/lib/libblas/libblas.so.3.7.0
LAPACK: /usr/lib/lapack/liblapack.so.3.7.0
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
LC_TIME=nl_NL.UTF-8
[4] LC_COLLATE=en_US.UTF-8 LC_MONETARY=nl_NL.UTF-8
LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=nl_NL.UTF-8 LC_NAME=C LC_ADDRESS=C
[10] LC_TELEPHONE=C LC_MEASUREMENT=nl_NL.UTF-8
LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] readr_1.1.1
loaded via a namespace (and not attached):
[1] compiler_3.4.1 R6_2.2.2 hms_0.3tools_3.4.1
tibble_1.3.3 Rcpp_0.12.12 rlang_0.1.2
On 03-09-17 20:50, Jennifer Lyon wrote:
Jeroen:
Thank you for pointing me to ndjson, which I had not heard of and is
exactly my case.
My experience:
jsonlite::stream_in - segfaults
ndjson::stream_in - my fault, I am running Ubuntu 14.04 and it is too old
so it won't compile the package
corpus::read_ndjson - works!!! Of course it does a different simplification
than jsonlite::fromJSON, so I have to change some code, but it works
beautifully at least in simple tests. The memory-map option may be of
use in the future.
Another correspondent said that strings in R can only be 2^31-1 long, which
is why any "solution" that tries to load the whole file into R first as a
string, will fail.
Thanks for suggesting a path forward for me!
Jen
On Sun, Sep 3, 2017 at 2:15 AM, Jeroen Ooms wrote:
On Sat, Sep 2, 2017 at 8:58 PM, Jennifer Lyon
wrote:
I have a 2.1GB JSON file. Typically I use readLines() and
jsonlite:fromJSON() to extract data from a JSON file.
If your data consists of one json object per line, this is called
'ndjson'. There are several packages specialized to read ndjon files:
- corpus::read_ndjson
- ndjson::stream_in
- jsonlite::stream_in
In particular the 'corpus' package handles large files really well
because it has an option to memory-map the file instead of reading all
of its data into memory.
If the data is too large to read, you can preprocess it using
https://stedolan.github.io/jq/ to extract the fields that you need.
You really don't need hadoop/spark/etc for this.
[[alternative HTML version deleted]]
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Re: [Rd] readLines() segfaults on large file & question on how to work around
Jeroen: Thank you for pointing me to ndjson, which I had not heard of and is exactly my case. My experience: jsonlite::stream_in - segfaults ndjson::stream_in - my fault, I am running Ubuntu 14.04 and it is too old so it won't compile the package corpus::read_ndjson - works!!! Of course it does a different simplification than jsonlite::fromJSON, so I have to change some code, but it works beautifully at least in simple tests. The memory-map option may be of use in the future. Another correspondent said that strings in R can only be 2^31-1 long, which is why any "solution" that tries to load the whole file into R first as a string, will fail. Thanks for suggesting a path forward for me! Jen On Sun, Sep 3, 2017 at 2:15 AM, Jeroen Ooms wrote: > On Sat, Sep 2, 2017 at 8:58 PM, Jennifer Lyon > wrote: > > I have a 2.1GB JSON file. Typically I use readLines() and > > jsonlite:fromJSON() to extract data from a JSON file. > > If your data consists of one json object per line, this is called > 'ndjson'. There are several packages specialized to read ndjon files: > > - corpus::read_ndjson > - ndjson::stream_in > - jsonlite::stream_in > > In particular the 'corpus' package handles large files really well > because it has an option to memory-map the file instead of reading all > of its data into memory. > > If the data is too large to read, you can preprocess it using > https://stedolan.github.io/jq/ to extract the fields that you need. > > You really don't need hadoop/spark/etc for this. > [[alternative HTML version deleted]] __ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
Re: [Rd] readLines() segfaults on large file & question on how to work around
On Sat, Sep 2, 2017 at 8:58 PM, Jennifer Lyon wrote: > I have a 2.1GB JSON file. Typically I use readLines() and > jsonlite:fromJSON() to extract data from a JSON file. If your data consists of one json object per line, this is called 'ndjson'. There are several packages specialized to read ndjon files: - corpus::read_ndjson - ndjson::stream_in - jsonlite::stream_in In particular the 'corpus' package handles large files really well because it has an option to memory-map the file instead of reading all of its data into memory. If the data is too large to read, you can preprocess it using https://stedolan.github.io/jq/ to extract the fields that you need. You really don't need hadoop/spark/etc for this. __ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
Re: [Rd] readLines() segfaults on large file & question on how to work around
Jennifer, Why do you try Sparkr?
https://spark.apache.org/docs/1.6.1/api/R/read.json.html
On 2 September 2017 at 23:15, Jennifer Lyon wrote:
> Thank you for your suggestion. Unfortunately, while R doesn't segfault
> calling readr::read_file() on the test file I described, I get the error
> message:
>
> Error in read_file_(ds, locale) : negative length vectors are not allowed
>
> Jen
>
> On Sat, Sep 2, 2017 at 1:38 PM, Ista Zahn wrote:
>
>> As s work-around I suggest readr::read_file.
>>
>> --Ista
>>
>>
>> On Sep 2, 2017 2:58 PM, "Jennifer Lyon" wrote:
>>
>>> Hi:
>>>
>>> I have a 2.1GB JSON file. Typically I use readLines() and
>>> jsonlite:fromJSON() to extract data from a JSON file.
>>>
>>> When I try and read in this file using readLines() R segfaults.
>>>
>>> I believe the two salient issues with this file are
>>> 1). Its size
>>> 2). It is a single line (no line breaks)
>>>
>>> I can reproduce this issue as follows
>>> #Generate a big file with no line breaks
>>> # In R
>>> > writeLines(paste0(c(letters, 0:9), collapse=""), "alpha.txt", sep="")
>>>
>>> # in unix shell
>>> cp alpha.txt file.txt
>>> for i in {1..26}; do cat file.txt file.txt > file2.txt && mv -f file2.txt
>>> file.txt; done
>>>
>>> This generates a 2.3GB file with no line breaks
>>>
>>> in R:
>>> > moo <- readLines("file.txt")
>>>
>>> *** caught segfault ***
>>> address 0x7cff, cause 'memory not mapped'
>>>
>>> Traceback:
>>> 1: readLines("file.txt")
>>>
>>> Possible actions:
>>> 1: abort (with core dump, if enabled)
>>> 2: normal R exit
>>> 3: exit R without saving workspace
>>> 4: exit R saving workspace
>>> Selection: 3
>>>
>>> I conclude:
>>> I am potentially running up against a limit in R, which should give a
>>> reasonable error, but currently just segfaults.
>>>
>>> My question:
>>> Most of the content of the JSON is an approximately 100K x 6K JSON
>>> equivalent of a dataframe, and I know R can handle much bigger than this
>>> size. I am expecting these JSON files to get even larger. My R code lives
>>> in a bigger system, and the JSON comes in via stdin, so I have absolutely
>>> no control over the data format. I can imagine trying to incrementally
>>> parse the JSON so I don't bump up against the limit, but I am eager for
>>> suggestions of simpler solutions.
>>>
>>> Also, I apologize for the timing of this bug report, as I know folks are
>>> working to get out the next release of R, but like so many things I have
>>> no
>>> control over when bugs leap up.
>>>
>>> Thanks.
>>>
>>> Jen
>>>
>>> > sessionInfo()
>>> R version 3.4.1 (2017-06-30)
>>> Platform: x86_64-pc-linux-gnu (64-bit)
>>> Running under: Ubuntu 14.04.5 LTS
>>>
>>> Matrix products: default
>>> BLAS: R-3.4.1/lib/libRblas.so
>>> LAPACK:R-3.4.1/lib/libRlapack.so
>>>
>>> locale:
>>> [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
>>> [3] LC_TIME=en_US.UTF-8LC_COLLATE=en_US.UTF-8
>>> [5] LC_MONETARY=en_US.UTF-8LC_MESSAGES=en_US.UTF-8
>>> [7] LC_PAPER=en_US.UTF-8 LC_NAME=C
>>> [9] LC_ADDRESS=C LC_TELEPHONE=C
>>> [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
>>>
>>> attached base packages:
>>> [1] stats graphics grDevices utils datasets methods base
>>>
>>> loaded via a namespace (and not attached):
>>> [1] compiler_3.4.1
>>>
>>> [[alternative HTML version deleted]]
>>>
>>> __
>>> R-devel@r-project.org mailing list
>>> https://stat.ethz.ch/mailman/listinfo/r-devel
>>>
>>
>
> [[alternative HTML version deleted]]
>
> __
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Re: [Rd] readLines() segfaults on large file & question on how to work around
2017-09-02 20:58 GMT+02:00 Jennifer Lyon : > Hi: > > I have a 2.1GB JSON file. Typically I use readLines() and > jsonlite:fromJSON() to extract data from a JSON file. > > When I try and read in this file using readLines() R segfaults. > > I believe the two salient issues with this file are > 1). Its size > 2). It is a single line (no line breaks) As a workaround you can pipe something like "sed s/,/,\\n/g" before your R script to insert line breaks. Iñaki __ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
Re: [Rd] readLines() segfaults on large file & question on how to work around
Thank you for your suggestion. Unfortunately, while R doesn't segfault
calling readr::read_file() on the test file I described, I get the error
message:
Error in read_file_(ds, locale) : negative length vectors are not allowed
Jen
On Sat, Sep 2, 2017 at 1:38 PM, Ista Zahn wrote:
> As s work-around I suggest readr::read_file.
>
> --Ista
>
>
> On Sep 2, 2017 2:58 PM, "Jennifer Lyon" wrote:
>
>> Hi:
>>
>> I have a 2.1GB JSON file. Typically I use readLines() and
>> jsonlite:fromJSON() to extract data from a JSON file.
>>
>> When I try and read in this file using readLines() R segfaults.
>>
>> I believe the two salient issues with this file are
>> 1). Its size
>> 2). It is a single line (no line breaks)
>>
>> I can reproduce this issue as follows
>> #Generate a big file with no line breaks
>> # In R
>> > writeLines(paste0(c(letters, 0:9), collapse=""), "alpha.txt", sep="")
>>
>> # in unix shell
>> cp alpha.txt file.txt
>> for i in {1..26}; do cat file.txt file.txt > file2.txt && mv -f file2.txt
>> file.txt; done
>>
>> This generates a 2.3GB file with no line breaks
>>
>> in R:
>> > moo <- readLines("file.txt")
>>
>> *** caught segfault ***
>> address 0x7cff, cause 'memory not mapped'
>>
>> Traceback:
>> 1: readLines("file.txt")
>>
>> Possible actions:
>> 1: abort (with core dump, if enabled)
>> 2: normal R exit
>> 3: exit R without saving workspace
>> 4: exit R saving workspace
>> Selection: 3
>>
>> I conclude:
>> I am potentially running up against a limit in R, which should give a
>> reasonable error, but currently just segfaults.
>>
>> My question:
>> Most of the content of the JSON is an approximately 100K x 6K JSON
>> equivalent of a dataframe, and I know R can handle much bigger than this
>> size. I am expecting these JSON files to get even larger. My R code lives
>> in a bigger system, and the JSON comes in via stdin, so I have absolutely
>> no control over the data format. I can imagine trying to incrementally
>> parse the JSON so I don't bump up against the limit, but I am eager for
>> suggestions of simpler solutions.
>>
>> Also, I apologize for the timing of this bug report, as I know folks are
>> working to get out the next release of R, but like so many things I have
>> no
>> control over when bugs leap up.
>>
>> Thanks.
>>
>> Jen
>>
>> > sessionInfo()
>> R version 3.4.1 (2017-06-30)
>> Platform: x86_64-pc-linux-gnu (64-bit)
>> Running under: Ubuntu 14.04.5 LTS
>>
>> Matrix products: default
>> BLAS: R-3.4.1/lib/libRblas.so
>> LAPACK:R-3.4.1/lib/libRlapack.so
>>
>> locale:
>> [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
>> [3] LC_TIME=en_US.UTF-8LC_COLLATE=en_US.UTF-8
>> [5] LC_MONETARY=en_US.UTF-8LC_MESSAGES=en_US.UTF-8
>> [7] LC_PAPER=en_US.UTF-8 LC_NAME=C
>> [9] LC_ADDRESS=C LC_TELEPHONE=C
>> [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
>>
>> attached base packages:
>> [1] stats graphics grDevices utils datasets methods base
>>
>> loaded via a namespace (and not attached):
>> [1] compiler_3.4.1
>>
>> [[alternative HTML version deleted]]
>>
>> __
>> R-devel@r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-devel
>>
>
[[alternative HTML version deleted]]
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Re: [Rd] readLines() segfaults on large file & question on how to work around
As s work-around I suggest readr::read_file.
--Ista
On Sep 2, 2017 2:58 PM, "Jennifer Lyon" wrote:
> Hi:
>
> I have a 2.1GB JSON file. Typically I use readLines() and
> jsonlite:fromJSON() to extract data from a JSON file.
>
> When I try and read in this file using readLines() R segfaults.
>
> I believe the two salient issues with this file are
> 1). Its size
> 2). It is a single line (no line breaks)
>
> I can reproduce this issue as follows
> #Generate a big file with no line breaks
> # In R
> > writeLines(paste0(c(letters, 0:9), collapse=""), "alpha.txt", sep="")
>
> # in unix shell
> cp alpha.txt file.txt
> for i in {1..26}; do cat file.txt file.txt > file2.txt && mv -f file2.txt
> file.txt; done
>
> This generates a 2.3GB file with no line breaks
>
> in R:
> > moo <- readLines("file.txt")
>
> *** caught segfault ***
> address 0x7cff, cause 'memory not mapped'
>
> Traceback:
> 1: readLines("file.txt")
>
> Possible actions:
> 1: abort (with core dump, if enabled)
> 2: normal R exit
> 3: exit R without saving workspace
> 4: exit R saving workspace
> Selection: 3
>
> I conclude:
> I am potentially running up against a limit in R, which should give a
> reasonable error, but currently just segfaults.
>
> My question:
> Most of the content of the JSON is an approximately 100K x 6K JSON
> equivalent of a dataframe, and I know R can handle much bigger than this
> size. I am expecting these JSON files to get even larger. My R code lives
> in a bigger system, and the JSON comes in via stdin, so I have absolutely
> no control over the data format. I can imagine trying to incrementally
> parse the JSON so I don't bump up against the limit, but I am eager for
> suggestions of simpler solutions.
>
> Also, I apologize for the timing of this bug report, as I know folks are
> working to get out the next release of R, but like so many things I have no
> control over when bugs leap up.
>
> Thanks.
>
> Jen
>
> > sessionInfo()
> R version 3.4.1 (2017-06-30)
> Platform: x86_64-pc-linux-gnu (64-bit)
> Running under: Ubuntu 14.04.5 LTS
>
> Matrix products: default
> BLAS: R-3.4.1/lib/libRblas.so
> LAPACK:R-3.4.1/lib/libRlapack.so
>
> locale:
> [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
> [3] LC_TIME=en_US.UTF-8LC_COLLATE=en_US.UTF-8
> [5] LC_MONETARY=en_US.UTF-8LC_MESSAGES=en_US.UTF-8
> [7] LC_PAPER=en_US.UTF-8 LC_NAME=C
> [9] LC_ADDRESS=C LC_TELEPHONE=C
> [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
>
> attached base packages:
> [1] stats graphics grDevices utils datasets methods base
>
> loaded via a namespace (and not attached):
> [1] compiler_3.4.1
>
> [[alternative HTML version deleted]]
>
> __
> R-devel@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-devel
>
[[alternative HTML version deleted]]
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[Rd] readLines() segfaults on large file & question on how to work around
Hi:
I have a 2.1GB JSON file. Typically I use readLines() and
jsonlite:fromJSON() to extract data from a JSON file.
When I try and read in this file using readLines() R segfaults.
I believe the two salient issues with this file are
1). Its size
2). It is a single line (no line breaks)
I can reproduce this issue as follows
#Generate a big file with no line breaks
# In R
> writeLines(paste0(c(letters, 0:9), collapse=""), "alpha.txt", sep="")
# in unix shell
cp alpha.txt file.txt
for i in {1..26}; do cat file.txt file.txt > file2.txt && mv -f file2.txt
file.txt; done
This generates a 2.3GB file with no line breaks
in R:
> moo <- readLines("file.txt")
*** caught segfault ***
address 0x7cff, cause 'memory not mapped'
Traceback:
1: readLines("file.txt")
Possible actions:
1: abort (with core dump, if enabled)
2: normal R exit
3: exit R without saving workspace
4: exit R saving workspace
Selection: 3
I conclude:
I am potentially running up against a limit in R, which should give a
reasonable error, but currently just segfaults.
My question:
Most of the content of the JSON is an approximately 100K x 6K JSON
equivalent of a dataframe, and I know R can handle much bigger than this
size. I am expecting these JSON files to get even larger. My R code lives
in a bigger system, and the JSON comes in via stdin, so I have absolutely
no control over the data format. I can imagine trying to incrementally
parse the JSON so I don't bump up against the limit, but I am eager for
suggestions of simpler solutions.
Also, I apologize for the timing of this bug report, as I know folks are
working to get out the next release of R, but like so many things I have no
control over when bugs leap up.
Thanks.
Jen
> sessionInfo()
R version 3.4.1 (2017-06-30)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 14.04.5 LTS
Matrix products: default
BLAS: R-3.4.1/lib/libRblas.so
LAPACK:R-3.4.1/lib/libRlapack.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
loaded via a namespace (and not attached):
[1] compiler_3.4.1
[[alternative HTML version deleted]]
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