在每行上前两个字符拆分一个大的平面文件

Question

I have a large file ~10 GB that is comma delimited. Each row starts with a 2 character code that tells what type of row it is as each row is a different type of event. Currently I read the file into R, then use a regex to split it into different pieces based on code then write the resulting objects to a flat file.

I'm curious if there's a more direct way to do this (read a row, determine row type and append the row to the appropriate flat file (there will be 7 total)) in Python, bash, sed/awk, etc.

Data looks like this:

01,tim@bigcompany.com,20140101120000,campaign1
02,201420140101123000,123321,Xjq12090,TX
02,201420140101123000,123321,Xjq12090,AK
...

Any suggestions would be appreciated.

Answer 1

Using awk you can do:

awk -F, '{fn=$1 ".txt"; print > fn}' file

If you want to keep it clean by closing all file handles in the end use this awk :

awk -F, '!($1 in files){files[$1]=$1 ".txt"} {print > files[$1]}
    END {for (f in files) close(files[$f])}' file

Answer 2

If you don't care about performance, or trust your OS/filesystem/drive's disk caching:

with open('hugedata.txt') as infile:
    for line in infile:
        with open(line[:2] + '.txt', 'a') as outfile:
            outfile.write(line)

However, constantly reopening and reclosing (and therefore flushing) the files is going to mean you never get the benefit of buffering, and there's only so much a disk cache can do to make up for that, so, you might want to consider pre-opening all the files. Since there are only 7 of them, that's pretty easy:

files = { format(i, '{:02}'): open(format(i, '{:02}.txt'), 'w') for i in range(1, 8)}
try:
    with open('hugedata.txt') as infile:
        for line in infile:
            files[line[:2]].write(line)
finally:
    for file in files:
        file.close()

Or, more robustly:

files = collections.defaultdict(lambda s: open(s+'.txt', 'w'))
try:
    with open('hugedata.txt') as infile:
        for line in infile:                
            files[line[:2]].write(line)
finally:
    for file in files:
        file.close()

(You can write a with statement that does the closing automatically, but it'll be different in different Python versions; this is a bit clunky, but works with everything from 2.4 to 3.5, and probably beyond, and since you haven't told us your platform or Python version, it seemed safer.)

Answer 3

How about something like this in Python:

for line in file('hugedata.txt'):
    fh = file(line[:2] + '.txt', 'a')
    fh.write(line)

Answer 4

I would do something like this:

grep '^01' your-10gb-file > 01.csv

You can then wrap this inside a foreach (for tcsh) like this:

foreach n ( `seq -f '%02g' 7` )
    grep '^$n' your-10gb-file > $n.csv
end

Answer 5

from itertools import groupby
with open("largefile.txt") as f:
    for k,v in groupby(f,lambda x: x[:2]):
        with open("{}.txt".format(k),"w") as f1:
            f1.writelines(v)