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Which hash function is fastest?
SHA-1 is fastest hashing function with ~587.9 ms per 1M operations for short strings and 881.7 ms per 1M for longer strings. MD5 is 7.6% slower than SHA-1 for short strings and 1.3% for longer strings. SHA-256 is 15.5% slower than SHA-1 for short strings and 23.4% for longer strings.
Is hashing always one way?
The answer is simple: each hash can be the result of an infinite number of strings being hashed, so there is no way of knowing which one a hash was meant to represent – even more simply put, a hash doesn’t represent any one value.
What makes a bad hash function?
Bad Hash. Words that contain the same combination of letters in different order (anagrams), have the same hash value. e.g. SAUCE has the same hash value as CAUSE. You can add an arbitrary value to one letter e.g.+1 to C to make a D, then subtract the same value from another letter e.g. -1 from U to make T.
How can you tell if a hash function is working?
A good way to determine whether your hash function is working well is to measure clustering. If bucket i contains xi elements, then a good measure of clustering is (∑ i(xi2)/n) – α. A uniform hash function produces clustering near 1.0 with high probability.
What are the disadvantages of a hash function?
Edit: The biggest disadvantage of this hash function is that it preserves divisibility, so if your integers are all divisible by 2 or by 4 (which is not uncommon), their hashes will be too. This is a problem in hash tables – you can end up with only 1/2 or 1/4 of the buckets being used.
Are there any advantages to using a wacky hash?
Here are two possible (and worthwhile, as far as I can see) advantages to using a “wacky” hash over a normal hash:
Which is a good hash function for random values?
For random hash values, some engineers said golden ratio prime number (2654435761) is a bad choice, with my testing results, I found that it’s not true; instead, 2654435761 distributes the hash values pretty good. The hash table size must be a power of two.