Partition a large file into small files in R

Question

I need to break a large file (14 gigabytes) into smaller files. The format of this file is txt, the tab is ";" and I know it has 70 columns (string, double). I would like to read 1million and save them in different files, file1, file2 ... fileN.

after the help of @MKR

but process was very slow, I tried using fread, but it was not possible.

How can I optimize this code?

NEW CODE

chunkSize <- 10000
conex <- file(description = db, open = "r")
data <- read.table(conex, nrows = chunkSize, header=T, fill=TRUE, sep =";")

index <- 0
counter <- 0
total <- 0
chunkSize <- 500000 
conex <- file(description=db,open="r")   
dataChunk <- read.table(conex, nrows=chunkSize, header=T, fill=TRUE,sep=";")

repeat {
dataChunk <- read.table(conex, nrows=chunkSize, header=FALSE, fill = TRUE, sep=";", col.names=db_colnames)
total <- total + sum(dataChunk$total)
counter <- counter + nrow(dataChunk)
write.table(dataChunk, file = paste0("MY_FILE_new",index),sep=";", row.names = FALSE)

  if (nrow(dataChunk) != chunkSize){
    print('linesok')
    break}
    index <- index + 1
  print(paste('lines', index * chunkSize))
}

Answer 1

You are perfectly on right track to achieve a solution.

The approach should be:

1. Read 1 million lines 
2. Write to new files
3. Read next 1 million lines
4. Write to another new files

Lets convert the above logic in a loop in the line of OP's attempt:

index <- 0
counter <- 0
total <- 0
chunks <- 500000

repeat{
  dataChunk <- read.table(con, nrows=chunks, header=FALSE, fill = TRUE,                 
                          sep=";", col.names=db_colnames)

  # do processing on dataChunk (i.e adding header, converting data type) 

  # Create a new file name and write to it. You can have your own logic for file names 
  write.table(dataChunk, file = paste0("file",index))

  #check if file end has been reached and break from repeat
  if(nrow(dataChunk) < chunks){
    break
  }

  #increment the index to read next chunk
  index = index+1

}

Edited: Modified to add another option by reading file using data.table::fread as requested by OP.

library(data.table)

index <- 0
counter <- 0
total <- 0
chunks <- 1000000
fileName <- "myfile"

repeat{
  # With fread file is opened in each iteration
  dataChunk <- fread(input = fileName, nrows=chunks, header=FALSE, fill = TRUE,                 
                          skip = chunks*index, sep=";", col.names=db_colnames)

  # do processing on dataChunk (i.e adding header, converting data type) 

  # Create a new file name and write to it. You can have your own logic for file names
  write.table(dataChunk, file = paste0("file",index))

  #check if file end has been reached and break from repeat
  if(nrow(dataChunk) < chunks){
    break
  }

  #increment the index to read next chunk
  index = index+1

}

Note: The above code is just pseudo code of partial snippet to help OP. It will not run and produce result on its own.