[Rd] readLines() segfaults on large file & question on how to work around

[rhelp at eoos.dds.nl]

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_0.3        tools_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 <jeroenooms at gmail.com> wrote:
> 
>> On Sat, Sep 2, 2017 at 8:58 PM, Jennifer Lyon <jennifer.s.lyon at gmail.com>
>> 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.
>>
> 
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> 
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