Finding Duplicate Files in Linux - The Hard Way

11 July, 2020 linux 5 Mins

Duplicate files, in Layman’s term, are the files which are exactly a copy of one another. For example, if we have two files biz A and B; A would be a duplicate of B if it has the same content as file B.

Duplicates are generally unavoidable. No matter what you do, you would always end up getting a few of them. Going through the whole file system and finding them one by one is a tedious job. And no sane person would ever think of doing that manually when the file count is literally in thousands.

Filtering them out and removing is quite easy though. All you need to do is install some tools like rdfind, fslint etc. Run a few commands, and duplicates would vanish. Here is a guide to help you out.

If that’s what you are here for, you won’t have to read any further. Download any one of those tools and get your job done. This post emphasizes on how to build one such tool for your use :)

1. Comparing File Content

The first way is to compare the contents of one file with all available files in that directory. So, if you have like 10 files: choose a random file and read its content. Store its content in a variable. Loop through rest of the files and compare their contents with the one you have stored in a variable. If matches, delete that file. If not, move on.

A simple code example would help better in understanding (for simplicity, I am ignoring directories):


# program to find a duplicate
# public key file

for f in `ls -p | grep -v /`      # filter files
  f_CONTENT=`cat "$f"`;
  for g in `ls -p | grep -v /`
    g_CONTENT=`cat "$g"`
    if [[ $f_CONTENT == $g_CONTENT && $f != $g ]]; then
      # duplicate
      echo "DUPLICATE: $f === $g";

As you might have already understood how resource hungry this program would be. I mean, it is not. But compared to other possible ways, it’s a resource-hungry process.

This program would have a time complexity of O(n^2). Not ideal.


So, here’s a summary of why I think this approach is bad:

  • Takes up more resources than it should
  • Have a complexity of O(n^2)

2. Using Hashing Technique

My second option is to use file-hash. This method would be quite similar to the previous one, except that instead of storing file content, I would be storing the hash value of that content :)

If you are wondering what a hash is; well, it is a unique string of alphanumeric characters generated from a given object.

For a given object(like ASCII characters, binary files etc), the generated hash would always be the same. Change a character(even space), and it would differ.

Generation of hash is done by using algorithms. You feed an algorithm with data, and it calculates the hash value of that data. There are so many hashing algorithms that are available out there. A few among them are SHA, BlowFish, MD5 etc which are quite popular.

One more unique thing about hash is, it is irreversible. You can’t extract the content from which the hash was generated.

Note that, this method won’t give much better result over the previous method as hashing is a slow process and it does consume a lot of resources.

In Linux, there are tools for generating a hash of any given files. In most of the distributions, they are pre-installed.

Following is a Bash Script which would implement whatever I said so far.


# find duplicate using hashing technique
for f in `ls -p | grep -v /`
  f_sha=`sha1sum "$f" | awk '{ print $1 }'`;
  for g in `ls -p | grep -v /`
    g_sha=`sha1sum "$g" | awk '{ print $1 }'`

    if [[ $f_sha == $g_sha && $f != $g ]]; then
      # duplicate
      echo "SAME: $f === $g";

As you can see, it does not make any huge difference. Worse, it adds an extra step of calculating SHA1SUM of each file.

3. Maps (or HashMaps)

Or Dictionary, Object, Associative array, HashTable … whatever you call them. Hashmaps are a collection of pairs of key-value stored inside a variable. One prominent benefit of the hashtable is that complexity of searching an element is O(1). Read more about hash-table on Wikipedia.

What does this mean? I could reduce the time complexity of my code to O(n).

Combining Everything …

Since I can combine the hashing technique(mentioned in the previous method) with HashTable, the program would be more efficient and simple. I won’t have to use two for loops. This would also reduce time complexity.

I am not using file content as key in hashtable. I could have stored either a file name or file content as a key. But neither of then would work.

  • Two files would never have the same name under a single context.
  • File content could be of any type, ranging from ASCII to Multimedia etc. This does not make it ideal for using as Key.
  • Just imagine, what if the file size is huge.. HUGE? like 2 or 3 GB! Or more! it would increase the space needed by the program to run, ultimately increasing the resource consumption.

So, I will be using SHA1SUM(generated using sha1sum tool) as key. For value, I would just set it to true since it does not matter what value it holds.

Since v4.0, Bash provides a native way of creating HashTables. I won’t have to look for another language to write this small program.

Enough explaining, here is the code:


declare -A checksums   # `checksums` is a hash-table

for f in `ls -pS | grep -v /`
  file_hash=`sha1sum "$f" | awk '{ print $1 }'`
  if [[ "${checksums[$file_hash]}" == true ]]; then
    echo "DUP: $f"


There is no point in reinventing the wheel. There are so many popular tools for finding and removing duplicates from the file system. Use any one of them.

I am learning algorithms. So, I thought of explaining some stuff which would help me understand it better. Hence, this article.

#algorithms #bash