melt segfault when duplicated column names exist in DT

[ChristK]

See minimal example below

set.seed(45)
require(data.table) # latest GitHub version 
DT <- data.table(
  A = sample(1:2, 120, T),
  B = c(1:120), 
  D = sample(1:10, 120, T),
  D = sample(1:10, 120, T))

melt(DT, id=1:2)

#*** caught segfault ***
#address 0x2000000a, cause 'memory not mapped'

#Traceback:
#1: rbindlist(l, use.names, fill, idcol)
 #2: data.table::.rbind.data.table(...)
 #3: rbind(deparse.level, ...)
 #4: rbind(head(x, topn), tail(x, topn))
 #5: print.data.table(list(A = c(2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L...# I shortened the output manually

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: 

The segfault doesn't happen with shorter datatables
I hope the above is helpful for debugging

sessionInfo()
#R version 3.1.2 (2014-10-31)
#Platform: x86_64-apple-darwin13.4.0 (64-bit)

#locale:
#[1] en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8

#attached base packages:
#[1] stats     graphics  grDevices utils     datasets  methods   base     

#other attached packages:
#[1] data.table_1.9.5

#loaded via a namespace (and not attached):
#[1] chron_2.3-45 

[arunsrinivasan]

Nice catch, thanks! Out of curiosity, do you use data.tables with duplicate names, or is it something you were just testing out?

[ChristK]

Thanks Arun for the fix!
I occasionally receive files with age groups as columns. It is 5 year age groups but I usually want 10 year groups. So I rename the columns to 10 year age groups (and I intentionally create duplicate column names). Then melt and then aggregate by 10 year age group. It feels quicker than the other way around

I just noticed it because my scripts stopped working after the update.

[arunsrinivasan]

Cool! Thanks 👍 .