This is kind of related to Which hashing algorithm is best for uniqueness and speed?. In that question, the excellently written top answer notes,


The other subjective measure is how randomly distributed the hashes are. Mapping the resulting HashTables shows how evenly the data is distributed.

(here, "random" is not being used to mean "deterministic" — all of the functions under consideration are deterministic.)

Based on that question's excellent answer, I implemented FNV-1A. However, the results I'm getting do not seem particularly "random"ly distributed:

In [19]: for x in xrange(10):
   ....:     h = Fnv1A(); h.update(b'testing' + str(x)); print hex(h.value)

Notice that the vast majority of the bits in the output here are the same.

Is FNV-1A supposed to be an extremely discontinuous function? i.e., the output changes drastically for small changes in the input; it exhibits the Avalanche effect.

Note that this is orthogonal to being uniformly distributed, which I also want.

I'm attempting to use FNV-1A to simply randomly distribute users into one of n weighted buckets. None of the inputs are user-controlled, so security is not of much concern, but the inputs are highly not random (they're auto-incrementing integers…); I do, however, need the output two be random (but deterministic): for a given user ID, it should be random which bucket they end up in.

I actually asked another similar question a while ago; I understand that hash outputs don't necessarily need to be random (for hashtables, all you really care about is that they don't collide). For my particular application, I unfortunately need randomness.

(In case you're curious about the correctness of my implementation,

In [22]: h = experiment.Fnv1A(); h.update(b'foobar'); h.value
Out[22]: 9625390261332436968L

…as this is for work, I'm trying to share as little code as needed. This question is more about FNV-1A itself, rather than my particular implementation.)

  • 3
    I think the term you're looking for is discontinuous, or the avalanche effect. Random means unpredictable, which makes it kind of the opposite of deterministic. It's also not the opposite of uniformly distributed, which you do want, because that's how you avoid collisions. – Doval Feb 20 '15 at 1:24
  • 1
    @Doval Along those lines, is the statement in the Wikipedia article about the weak diffusion also a potential concern, since we know the numbers are incrementing? It sounds like it may be more a concern for cryptography but less for this problem... – J Trana Feb 20 '15 at 2:03
  • @Doval: Ah, I didn't mean to imply that randomness and uniformly distributed were opposites, merely that they're orthogonal. I see how that's confusing. The avalanche effect is definitely a good way of describing what I need. I'll edit these into the question. – Thanatos Feb 20 '15 at 6:35
  • Consider SipHash. It's simple, relatively fast and secure. – CodesInChaos Feb 20 '15 at 15:36

From your requirements it rather sounds like you should be using a secure (cryptographic) hash.

To your actual question:

Is FNV-1A supposed to be an extremely discontinuous function? i.e., the output changes drastically for small changes in the input; it exhibits the Avalanche effect.

we can quickly get an answer of No by looking at the FNV test vectors linked from the FNV homepage. Your foobar => 0x85944171f73967e8 test case is here, and also here we find these test cases:

input    output
"a"      0xaf63dc4c8601ec8c
"b"      0xaf63df4c8601f1a5
"c"      0xaf63de4c8601eff2
"d"      0xaf63d94c8601e773
"e"      0xaf63d84c8601e5c0
"f"      0xaf63db4c8601ead9

It's clear that this hash is not one to use if you want small changes to avalanche.

  • Indeed, the code is now using SHA2. – Thanatos Feb 20 '15 at 18:37

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