Intersection of cryptography, software engineering, statistics, and performance:
If i want to do a random sample from a set of data, and I wish to simply do "hash(dataitem) & bitmask < value", what properties does my hash function need to be statistically sound? Clearly, a ...
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... cryptographic hash will suffice in terms of uniformity of sampling, but how about non-cryptographic hashes? Cityhash64?
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ah, uniformity is a harsher constraint than limiting P(collission), so not many hashes will be optimized for it. What kind of data (and amount of information, per hash) are we talking about?
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Millions, up to billions of elements. Should have ~30-40 bits of entropy in the input data.
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How large are the keys in terms of bytes on average?