jdupes VS xxHash

I recommend the use of jdupes, a fork of the well-known fdupes, to find duplicate files.

200 lines of Nim [1] seems to run about 9X faster than the 8000 lines of C in fdupes on a little test dir I have. If you need C, I think jdupes [2] is faster as @TacticalCoder points out a couple of times here. In my testing, `dups` is usually faster than `jdupes`, though.

[1] https://github.com/c-blake/bu/blob/main/dups.nim

[2] https://github.com/jbruchon/jdupes

There's always the well-respected tool, Czkawka. Or, of the CLI is your thing, jdupes is a good option.

My research into this many years ago turned out that jdupes was the right / best solution I could find for my usecase.

https://github.com/jbruchon/jdupes

Though that works fine from a script perspective I'd like some more interactive way of sorting directories etc. Identifying is just the first step, jdupes helps with linking the files (both soft and hard links comes with caveats though!) but that is mostly to save space, not to help in reorganisation.

I can work it out by looking at https://github.com/jbruchon/jdupes.

I have looked at a few alternatives and think jdupes is the one for me. Then I found out it was not multi-threaded so will give it a go but the developer of jdupes recomended fclones (https://github.com/jbruchon/jdupes/issues/186) if you were dealing with large file systems and wanted multi-threading. But as I am using a HD it may not be necessary.

jdupes is a fork of the old standby fdupes, but it has a Win32 release as well as supporting POSIX.

jdupes is a tuned fork of the well-known fdupes, and has Win32 releases.

> GPU Hash Table?

How bad would performance have suffered if you sha256'd the lines to build the map? I'm going to guess "badly"?

Maybe something like this in CUDA: https://github.com/Cyan4973/xxHash ?

Examples of fast, simple hashes that are independent enough includes murmur, xxHash, Fowler–Noll–Vo hash function and many others

If you're only using the hash for non-cryptographic applications, there are much faster hashes: https://github.com/Cyan4973/xxHash

I found the benchmark result of AMD ryzen 5950X

But what's the catch, you're thinking ? Well, it is a bit slower than its counterparts when it comes to deserializing (and marginally faster for serializing). To achieve smaller footprint, it uses a few tricks and notably a custom hash table to deduplicate strings. This comes at a cost of course (even when featuring xxHash to speed things up), but keeps the slowdown reasonable (I think).

Non cryptographic hashes has collisions, for example, assume you having content like "abcdefg" which hashed value is "123", in case of weak hash algorithm some other content like "abcdefZ" can also have a hash "123" which basically means such hash function is failed to be unique fingerprint of particular content. BLAKE3 for example can do 6-7Gb/s which make it pretty fast and secure. If your requirement accepts collision with defined error rate, I would advise you to take a look at XXH3 if you need very snappy hash algorithm, which can run at pace or RAM access (30GB/s+), but again, run tests at particular equipment you targeting, may be AES hardware accelerated MeowHash will serve you better.