Print unique lines of a 10GB file - perl

Question

I have a 10GB file with 200 million lines. I need to get unique lines of this file.
My code:
while(<>) {
chomp;
$tmp{$_}=1;
}
#print...
I only have 2GB memory. How can I solve this problem?

Answer 1

As I commented on David's answer, a database is the way to go, but a nice one might be DBM::Deep since its pure-Perl and easy to install and use; its essentially a Perl hash tied to a file.
use DBM::Deep;
tie my %lines, 'DBM::Deep', 'data.db';
while(<>) {
chomp;
$lines{$_}=1;
}
This is basically what you already had, but the hash is now a database tied to a file (here data.db) rather than kept in memory.

Answer 2

If you don't care about preserving order, I bet the following is faster than the previously posted solutions (e.g. DBM::Deep):
sort -u file

Answer 3

In most cases, you could store the line as a key in a hash. However, when you get this big, this really isn't very efficient. In this case, you'd be better off using a database.
One thing to try is the Berkeley Database that use to be included in Unix (BDB). Now, it's apparently owned by Oracle.
Perl can use the BerkeleyDB module to talk with a BDB database. In fact, you can even tie a Perl hash to a BDB database. Once this is done, you can use normal Perl hashes to access and modify the database.
BDB is pretty robust. Bitcoins uses it, and so does SpamAssassin, so it is very possible that it can handle the type of database you have to create in order to find duplicate lines. If you already have DBD installed, writing a program to handle your task shouldn't take that long. If it doesn't work, you wouldn't have wasted too much time with this.
The only other thing I can think of is using an SQL database which would be slower and much more complex.
Addendum
Maybe I'm over thinking this...
I decided to try a simple hash. Here's my program:
#! /usr/bin/env perl
use strict;
use warnings;
use feature qw(say);
use autodie;
use constant DIR => "/usr/share/dict";
use constant WORD_LIST => qw(words web2a propernames connectives);
my %word_hash;
for my $count (1..100) {
for my $file (WORD_LIST) {
open my $file_fh, "<", DIR . "/$file";
while (my $word = <$file_fh>) {
chomp $word;
$word_hash{"$file-$word-$count"} = $word;
}
}
}
The files read in contain a total of about 313,000 lines. I do this 100 times to get a hash with 31,300,000 keys in it. It is about as inefficient as it can be. Each and every key will be unique. The amount of memory will be massive. Yet...
It worked. It took about 10 minutes to run despite the massive inefficiencies in the program, and it maxed out at around 6 gigabytes. However, most of that was in virtual memory. Strangely, even though it was running, gobbling memory, and taking 98% of the CPU, my system didn't really slow down all that much. I guess the question really is what type of performance are you expecting? If taking about 10 minutes to run isn't that much of an issue for you, and you don't expect this program to be used that often, then maybe go for simplicity and use a simple hash.
I'm now downloading DBD from Oracle, compiling it, and installing it. I'll try the same program using DBD and see what happens.
Using a BDB Database
After doing the work, I think if you have MySQL installed, using Perl DBI would be easier. I had to:
Download Berkeley DB from Oracle, and you need an Oracle account. I didn't remember my password, and told it to email me. Never got the email. I spent 10 minutes trying to remember my email address.
Once downloaded, it has to be compiled. Found directions for compiling for the Mac and it seemed pretty straight forward.
Running CPAN crashed. Ends up that CPAN is looking for /usr/local/BerkeleyDB and it was installed as /usr/local/BerkeleyDB.5.3. Creating a link fixed the issue.
All told, about 1/2 an hour getting BerkeleyDB installed. Once installed, modifying my program was fairly straight forward:
#! /usr/bin/env perl
use strict;
use warnings;
use feature qw(say);
use autodie;
use BerkeleyDB;
use constant {
DIR => "/usr/share/dict",
BDB_FILE => "bdb_file",
};
use constant WORD_LIST => qw(words web2a propernames connectives);
unlink BDB_FILE if -f BDB_FILE;
our %word_hash;
tie %word_hash, "BerkeleyDB::Hash",
-Filename => BDB_FILE,
-Flags => DB_CREATE
or die qq(Cannot create DBD_Database file ") . BDB_FILE . qq("\n);
for my $count (1..10) {
for my $file (WORD_LIST) {
open my $file_fh, "<", DIR . "/$file";
while (my $word = <$file_fh>) {
chomp $word;
$word_hash{"$file-$word-$count"} = $word;
}
}
}
All I had to do was add a few lines.
Running the program was a disappointment. It wasn't faster, but much, much slower. It took over 2 minutes while using a pure hash took a mere 13 seconds.
However, it used a lot less memory. While the old program gobbled gigabytes, the BDB version barely used a megabyte. Instead, it created a 20MB database file.
But, in these days of VM and cheap memory, did it accomplish anything? In the old days before virtual memory and good memory handling, a program would crash your computer if it used all of the memory (and memory was measured in megabytes and not gigabytes). Now, if your program wants more memory than is available, it simply is given virtual memory.
So, in the end, using a Berkeley database is not a good solution. Whatever I saved in programming time by using tie was wasted with the installation process. And, it was slow.
Using BDB simply used a DBD file instead of memory. A modern OS will do the same, and is faster. Why do the work when the OS will handle it for you?
The only reason to use a database is if your system really doesn't have the required resources. 200 million lines is a big file, but a modern OS will probably be okay with it. If your system really doesn't have the resource, use a SQL database on another system, and not a DBD database.

Answer 4

You might consider calculating a hash code for each line, and keeping track of (hash, position) mappings. You wouldn't need a complicated hash function (or even a large hash) for this; in fact, "smaller" is better than "more unique", if the primary concern is memory usage. Even a CRC, or summing up the chars' codes, might do. The point isn't to guarantee uniqueness at this stage -- it's just to narrow the candidate matches down from 200 million to a few dozen.
For each line, calculate the hash and see if you already have a mapping. If you do, then for each position that maps to that hash, read the line at that position and see if the lines match. If any of them do, skip that line. If none do, or you don't have any mappings for that hash, remember the (hash, position) and then print the line.
Note, i'm saying "position", not "line number". In order for this to work in less than a year, you'd almost certainly have to be able to seek right to a line rather than finding your way to line #1392499.

Answer 5

If you don't care about time/IO constraints, nor disk constraints (e.g. you have 10 more GB space), you can do the following dumb algorithm:
1) Read the file (which sounds like it has 50 character lines). While scanning it, remember the longest line length $L.
2) Analyze the first 3 characters (if you know char #1 is identical - say "[" - analyze the 3 characters in position N that is likely to have more diverse ones).
3) For each line with 3 characters $XYZ, append that line to file 3char.$XYZ and keep the count of how many lines in that file in a hash.
4) When your entire file is split up that way, you should have a whole bunch (if the files are A-Z only, then 26^3) of smaller files, and at most 4 files that are >2GB each.
5) Move the original file into "Processed" directory.
6) For each of the large files (>2GB), choose the next 3 character positions, and repeat steps #1-#5, with new files being 6char.$XYZABC
7) Lather, rinse, repeat. You will end up with one of the 2 options eventually:
8a) A bunch of smaller files each of which is under 2GB, all of which have mutually different strings, and each (due to its size) can be processed individually by standard "stash into a hash" solution in your question.
8b) Or, most of the files being smaller, but, you have exausted all $L characters while repeating step 7 for >2GB files, and you still have between 1-4 large files. Guess what - since
those up-to-4 large files have identical characters within a file in positions 1..$L, they can ALSO be processed using the "stash into a hash" method in your question, since they are not going to contain more than a few distinct lines despite their size!
Please note that this may require - at the worst possible distributions - 10GB * L / 3 disk space, but will ONLY require 20GB disk space if you change step #5 from "move" to "delete".
Voila. Done.
As an alternate approach, consider hashing your lines. I'm not a hashing expert but you should be able to compress a line into a hash <5 times line size IMHO.
If you want to be fancy about this, you will do a frequency analysis on character sequences on the first pass, and then do compression/encoding this way.

Answer 6

If you have more processor and have at least 15GB free space and your storage fast enough, you could try this out. This will process it in paralel.
split --lines=100000 -d 4 -d input.file
find . -name "x*" -print|xargs -n 1 -P10 -I SPLITTED_FILE sort -u SPLITTED_FILE>unique.SPLITTED_FILE
cat unique.*>output.file
rm unique.* x*

Answer 7

You could break you file into 10 1 Gbyte files Then reading in one file at a time, sorting lines from that file and writing it back out after they are sorted. Opening all of the 10 files and merge them back into one file (making sure you you merge them in the correct order). Open an output file to save the unique lines. Then read the merge file one line at a time, keeping the last line for comparison. If the last line and the current line are not a match, write out the last line and save the current line as the last line for comparison. Otherwise get the next line from the merged file. That will give you a file which has all of the unique lines.
It may take a while to do this, but if you are limited on memory, then breaking the file up and working on parts of it will work.
It may be possible to do the comparison when writing out the file, but that would be a bit more complicated.

Answer 8

Why use perl for this at all? posix shell:
sort | uniq
done, let's go drink beers.