What is the fastest way to read in a large data file of text columns?

Question

I have a data file of almost 9 million lines (soon to be more than 500 million lines) and I'm looking for the fastest way to read it in. The five aligned columns are padded and separated by spaces, so I know where on each line to look for the two fields that I want. My Python routine takes 45 secs:

import sys,time

start = time.time()
filename = 'test.txt'    # space-delimited, aligned columns
trans=[]
numax=0
for line in open(linefile,'r'):
    nu=float(line[-23:-11]); S=float(line[-10:-1])
    if nu>numax: numax=nu
    trans.append((nu,S))
end=time.time()
print len(trans),'transitions read in %.1f secs' % (end-start)
print 'numax =',numax

whereas the routine I've come up with in C is a more pleasing 4 secs:

#include <stdio.h>
#include <stdlib.h>
#include <time.h>

#define BPL 47
#define FILENAME "test.txt"
#define NTRANS 8858226

int main(void) {
  size_t num;
  unsigned long i;
  char buf[BPL];
  char* sp;
  double *nu, *S;
  double numax;
  FILE *fp;
  time_t start,end;

  nu = (double *)malloc(NTRANS * sizeof(double));
  S = (double *)malloc(NTRANS * sizeof(double));

  start = time(NULL);
  if ((fp=fopen(FILENAME,"rb"))!=NULL) {
    i=0;
    numax=0.;
    do {
      if (i==NTRANS) {break;}
      num = fread(buf, 1, BPL, fp);
      buf[BPL-1]='\0';
      sp = &buf[BPL-10]; S[i] = atof(sp);
      buf[BPL-11]='\0';
      sp = &buf[BPL-23]; nu[i] = atof(sp);
      if (nu[i]>numax) {numax=nu[i];}
      ++i;
    } while (num == BPL);
    fclose(fp);
    end = time(NULL);
    fprintf(stdout, "%d lines read; numax = %12.6f\n", (int)i, numax);
    fprintf(stdout, "that took %.1f secs\n", difftime(end,start));
  } else {
    fprintf(stderr, "Error opening file %s\n", FILENAME);
    free(nu); free(S);
    return EXIT_FAILURE;
  }

  free(nu); free(S);
  return EXIT_SUCCESS;
  }

Solutions in Fortran, C++ and Java take intermediate amounts of time (27 secs, 20 secs, 8 secs). My question is: have I made any outrageous blunders in the above (particularly the C-code)? And is there any way to speed up the Python routine? I quickly realised that storing my data in an array of tuples was better than instantiating a class for each entry.

Answer 1

Some points:

1. Your C routine is cheating; it is being tipped off with the filesize, and is pre-allocating ...

2. Python: consider using array.array('d') ... one each for S and nu. Then try pre-allocation.

3. Python: write your routine as a function and call it -- accessing function-local variables is rather faster than accessing module-global variables.

Answer 2

In the C implementation, you could try swapping the fopen()/fread()/fclose() library functions for the lower-level system calls open()/read()/close(). A speedup may come from the fact that fread() does a lot of buffering, whereas read() does not.

Additionally, calling read() less often with bigger chunks will reduce the number of system calls and therefore you'll have less switching between userspace and kernelspace. What the kernel does when you issue a read() system call (doesn't matter if it was invoked from the fread() library function) is read the data from the disk and then copy it to the userspace. The copying part becomes expensive if you issue the system call very often in your code. By reading in larger chunks you'll end up with less context switches and less copying.

Keep in mind though that read() isn't guaranteed to return a block of the exact number of bytes you wanted. This is why in a reliable and proper implementation you always have to check the return value of the read().

Answer 3

An approach that could probably be applied to the C, C++ and python version would be to use memory map the file. The most signficant benefit is that it can reduce the amount of double-handling of data as it is copied from one buffer to another. In many cases there are also benefits due to the reduction in the number of system calls for I/O.

Answer 4

You have the 1 and the BPL arguments the wrong way around in fread() (the way you have it, it could read a partial line, which you don't test for). You should also be testing the return value of fread() before you try and use the returned data.

You can might be able to speed the C version up a bit by reading more than a line at a time

#define LINES_PER_READ 1000
char buf[LINES_PER_READ][BPL];

/* ... */

   while (i < NTRANS && (num = fread(buf, BPL, LINES_PER_READ, fp)) > 0) {
      int line;

      for (line = 0; i < NTRANS && line < num; line++)
      {
          buf[line][BPL-1]='\0';
          sp = &buf[line][BPL-10]; S[i] = atof(sp);
          buf[line][BPL-11]='\0';
          sp = &buf[line][BPL-23]; nu[i] = atof(sp);
          if (nu[i]>numax) {numax=nu[i];}
          ++i;
      }
    }

On systems supporting posix_fadvise(), you should also do this upfront, after opening the file:

posix_fadvise(fileno(fp), 0, 0, POSIX_FADV_SEQUENTIAL);

Answer 5

Another possible speed-up, given the number of times you need to do it, is to use pointers to S and nu instead of indexing into arrays, e.g.,

double *pS = S, *pnu = nu;
...
*pS++ = atof(sp);
*pnu = atof(sp);
...

Also, since you are always converting from char to double at the same locations in buf, pre-compute the addresses outside of your loop instead of computing them each time in the loop.