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 <jeroeno...@gmail.com> wrote:
On Sat, Sep 2, 2017 at 8:58 PM, Jennifer Lyon <jennifer.s.l...@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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