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What are Hash Functions and How to choose a good Hash Function?

Last Updated : 21 Feb, 2023
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Prerequisite: Hashing | Set 1 (Introduction) 

What is a Hash Function? 

A function that converts a given big phone number to a small practical integer value. The mapped integer value is used as an index in the hash table. In simple terms, a hash function maps a big number or string to a small integer that can be used as the index in the hash table. 

What is meant by Good Hash Function? 

A good hash function should have the following properties: 

  1. Efficiently computable.
  2. Should uniformly distribute the keys (Each table position equally likely for each key)

For example: For phone numbers, a bad hash function is to take the first three digits. A better function is considered the last three digits. Please note that this may not be the best hash function. There may be better ways. 

Rules for choosing good hash function:

1. The hash function should be simple to compute.

2. Number of collisions should be less while placing the record in the hash table.Ideally no collision should occur. Such a function is called perfect hash function.

3. Hash function should produce such keys which will get distributed uniformly over an array.

4. The hash function should depend on every bit of the key. Thus the hash function that simply extracts the portion of a key is not suitable.

In practice, we can often employ heuristic techniques to create a hash function that performs well. Qualitative information about the distribution of the keys may be useful in this design process. In general, a hash function should depend on every single bit of the key, so that two keys that differ in only one bit or one group of bits (regardless of whether the group is at the beginning, end, or middle of the key or present throughout the key) hash into different values. Thus, a hash function that simply extracts a portion of a key is not suitable. Similarly, if two keys are simply digited or character permutations of each other (such as 139 and 319), they should also hash into different values. 

The two heuristic methods are hashing by division and hashing by multiplication which are as follows: 

  1. The mod method: 
    • In this method for creating hash functions, we map a key into one of the slots of table by taking the remainder of key divided by table_size. That is, the hash function is 
h(key) = key mod table_size 

i.e. key % table_size
  • Since it requires only a single division operation, hashing by division is quite fast.
  • When using the division method, we usually avoid certain values of table_size like table_size should not be a power of a number suppose r, since if table_size = r^p, then h(key) is just the p lowest-order bits of key. Unless we know that all low-order p-bit patterns are equally likely, we are better off designing the hash function to depend on all the bits of the key.
  • It has been found that the best results with the division method are achieved when the table size is prime. However, even if table_size is prime, an additional restriction is called for. If r is the number of possible character codes on an computer, and if table_size is a prime such that r % table_size equal 1, then hash function h(key) = key % table_size is simply the sum of the binary representation of the characters in the key mod table_size.
  • Suppose r = 256 and table_size = 17, in which r % table_size i.e. 256 % 17 = 1.
  • So for key = 37599, its hash is 
37599 % 17 = 12
  • But for key = 573, its hash function is also
573 % 17 = 12
  • Hence it can be seen that by this hash function, many keys can have the same hash. This is called Collision.
  • A prime not too close to an exact power of 2 is often good choice for table_size.
  1. The multiplication method: 
    • In multiplication method, we multiply the key k by a constant real number c in the range 0 < c < 1 and extract the fractional part of k * c.
    • Then we multiply this value by table_size m and take the floor of the result. It can be represented as
h(k) = floor (m * (k * c mod 1))
h(k) = floor (m * frac (k * c))
  • where the function floor(x), available in standard library math.h, yields the integer part of the real number x, and frac(x) yields the fractional part. [frac(x) = x – floor(x)] 
  • An advantage of the multiplication method is that the value of m is not critical, we typically choose it to be a power of 2 (m = 2p for some integer p), since we can then easily implement the function on most computers
  • Suppose that the word size of the machine is w bits and that key fits into a single word.
  • We restrict c to be a fraction of the form s / (2w), where s is an integer in the range 0 < s < 2w
  • Referring to figure, we first multiply key by the w-bit integer s = c * 2w. The result is a 2w-bit value
r1 * 2w + r0

where r1 = high-order word of the product
      r0 = lower order word of the product
  • Although this method works with any value of the constant c, it works better with some values than the others.
c ~ (sqrt (5) – 1) / 2 = 0.618033988 . . .
  • is likely to work reasonably well.
  • Suppose k = 123456, p = 14,
  • m = 2^14 = 16384, and w = 32.
  • Adapting Knuth’s suggestion, c to be fraction of the form s / 2^32.
  • Then key * s = 327706022297664 = (76300 * 2^32) + 17612864,
  • So r1 = 76300 and r0 = 176122864.
  • The 14 most significant bits of r0 yield the value h(key) = 67.

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