No idea, but have you tried using ?scan to read those next 5 rows? It might
give you a better idea of the pathologies that are causing problems. For
example, an unmatched quote might result in some huge number of characters
trying to be read into a single element of a character variable. As your
previous respondent said, resolving such problems can be a challenge.

Cheers,
Bert



On Mon, Apr 8, 2024 at 8:06 AM Dave Dixon <ddi...@swcp.com> wrote:

> Greetings,
>
> I have a csv file of 76 fields and about 4 million records. I know that
> some of the records have errors - unmatched quotes, specifically.
> Reading the file with readLines and parsing the lines with read.csv(text
> = ...) is really slow. I know that the first 2459465 records are good.
> So I try this:
>
>  > startTime <- Sys.time()
>  > first_records <- read.csv(file_name, nrows = 2459465)
>  > endTime <- Sys.time()
>  > cat("elapsed time = ", endTime - startTime, "\n")
>
> elapsed time =   24.12598
>
>  > startTime <- Sys.time()
>  > second_records <- read.csv(file_name, skip = 2459465, nrows = 5)
>  > endTime <- Sys.time()
>  > cat("elapsed time = ", endTime - startTime, "\n")
>
> This appears to never finish. I have been waiting over 20 minutes.
>
> So why would (skip = 2459465, nrows = 5) take orders of magnitude longer
> than (nrows = 2459465) ?
>
> Thanks!
>
> -dave
>
> PS: readLines(n=2459470) takes 10.42731 seconds.
>
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