![]() ![]() A byte-by-byte compare doesn't need to do this. So under the assumption that I don't usually have a ready calculated and automatically updated table of all files hashes I need to calculate the hash and read every byte of duplicates candidates. Best duplicate file finder mac hashcheck full#And there is the hash function which generates an ID out of so and so many bytes - lets say the first 10k bytes of a terabyte or the full terabyte if the first 10k are the same. So there a byte-by-byte-compare on the one hand, which only compares so many bytes of every duplicate-candidate function till the first differing position. But to generate a hash of a file the first time the files needs to be read fully byte by byte. But that seems to be a misconception out of the general use of "hash tables speed up things". There seems to be some opinion that hashing might be faster than comparing. I found one (Windows) app which states to be fast by not using this common hashing scheme.Īm I totally wrong with my ideas and opinion? a hash calculation is a lot slower than just byte-by-byte compare.by using a hash instead just comparing the files byte by byte we introduce a (low) probability of a false negative.duplicate candidates get read from the slow HDD again (first chunk) and again (full md5) and again (sha1).So I've got the opinion that this scheme is broken in two different dimensions: Another improvement is to first only hash a small chunk to sort out totally different files. Sometimes the speed gets increased by first using a faster hash algorithm (like md5) with more collision probability and second if the hash is the same use a second slower but less collision-a-like algorithm to prove the duplicates. same has means identical files - a duplicate is found.calculate the hash of all the files with a same size and compare the hashes.generate a sorted list of all files (path, Size, id).So the usual algorithm seems to work like this: So I found Detecting duplicate files where the topic quite fast slided towards hashing and comparing hashes which is not the best and fastest way in my opinion. The author states that it was faster than any other alternative which I couldn't believe. Essentially its based on find and hashing (md5 and SHA1). So I analyzed the internals of the core tool findup which is implemented as very well written and documented shell script using an ultra-long pipe. In the process of finding duplicates in my 2 terabytes of HDD stored images I was astonished about the long run times of the tools fslint and fslint-gui. ![]()
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