How to test a hash function?

Question

Is there a way to test the quality of a hash function? I want to have a good spread when used in the hash table, and it would be great if this is verifyable in a unit test.

EDIT: For clarification, my problem was that I have used long values in Java in such a way that the first 32 bit encoded an ID and the second 32 bit encoded another ID. Unfortunately Java's hash of long values just XORs the first 32 bit with the second 32 bits, which in my case led to very poor performance when used in a HashMap. So I need a different hash, and would like to have a Unit Test so that this problem cannot creep in any more.

Answer 1

Based on your clarification:

I have used long values in Java in such a way that the first 32 bit encoded an ID and the second 32 bit encoded another ID. Unfortunately Java's hash of long values just XORs the first 32 bit with the second 32 bits, which in my case led to very poor performance when used in a HashMap.

it appears you have some unhappy "resonances" between the way you assign the two ID values and the sizes of your HashMap instances.

Are you explicitly sizing your maps, or using the defaults? A QAD check seems to indicate that a HashMap<Long,String> starts with a 16-bucket structure and doubles on overflow. That would mean that only the low-order bits of the ID values are actually participating in the hash bucket selection. You could try using one of the constructors that takes an initial-size parameter and create your maps with a prime initial size.

Alternately, Dave L's suggestion of defining your own hashing of long keys would allow you to avoid the low-bit-dependency problem.

Another way to look at this is that you're using a primitive type (long) as a way to avoid defining a real class. I'd suggest looking at the benefits you could achieve by defining the business classes and then implementing hash-coding, equality, and other methods as appropriate on your own classes to manage this issue.

Answer 2

You have to test your hash function using data drawn from the same (or similar) distribution that you expect it to work on. When looking at hash functions on 64-bit longs, the default Java hash function is excellent if the input values are drawn uniformly from all possible long values.

However, you've mentioned that your application uses the long to store essentially two independent 32-bit values. Try to generate a sample of values similar to the ones you expect to actually use, and then test with that.

For the test itself, take your sample input values, hash each one and put the results into a set. Count the size of the resulting set and compare it to the size of the input set, and this will tell you the number of collisions your hash function is generating.

For your particular application, instead of simply XORing them together, try combining the 32-bit values in ways a typical good hash function would combine two indepenet ints. I.e. multiply by a prime, and add.

Answer 3

First I think you have to define what you mean by a good spread to yourself. Do you mean a good spread for all possible input, or just a good spread for likely input?

For example, if you're hashing strings that represent proper full (first+last) names, you're not going to likely care about how things with the numerical ASCII characters hash.

As for testing, your best bet is to probably get a huge or random input set of data you expect, and push it through the hash function and see how the spread ends up. There's not likely going to be a magic program that can say "Yes, this is a good hash function for your use case.". However, if you can programatically generate the input data, you should easily be able to create a unit test that generates a significant amount of it and then verify that the spread is within your definition of good.

Edit: In your case with a 64 bit long, is there even really a reason to use a hash map? Why not just use a balanced tree directly, and use the long as the key directly rather than rehashing it? You pay a little penalty in overall node size (2x the size for the key value), but may end up saving it in performance.

Answer 4

If your using a chaining hash table, what you really care about is the number of collisions. This would be trivial to implement as a simple counter on your hash table. Every time an item is inserted and the table has to chain, increment a chain counter. A better hashing algorithm will result in a lower number of collisions. A good general purpose table hashing function to check out is: djb2