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INTRODUCTION to hash functions - Hash Functions - Algorithm
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Algorithm - Hash Functions - Introduction to hash functions
Introduction to hash functions

Hash function h() is an arbitrary function which mapped data x ∈ X of arbitrary size to value y ∈ Y of fixed size: y = h(x). Good hash functions have follows restrictions:

  • hash functions behave likes uniform distribution
  • hash functions is deterministic. `h(x)` should always return the same value for a given `x`
  • fast calculating (has runtime O(1))
  • In general case size of hash function less then size of input data: |y| < |x|. Hash functions are not reversible or in other words it may be collision: ∃ x1, x2 ∈ X, x1 ≠ x2: h(x1) = h(x2). X may be finite or infinite set and Y is finite set.

    Hash functions are used in a lot of parts of computer science, for example in software engineering, cryptography, databases, networks, machine learning and so on. There are many different types of hash functions, with differing domain specific properties.

    Often hash is an integer value. There are special methods in programmning languages for hash calculating. For example, in C# GetHashCode() method for all types returns Int32 value (32 bit integer number). In Java every class provides hashCode() method which return int. Each data type has own or user defined implementations.

    Hash methods

    There are several approaches for determinig hash function. Without loss of generality, lets x ∈ X = {z ∈ ℤ: z ≥ 0} are positive integer numbers. Often m is prime (not too close to an exact power of 2).

    Method Hash function
    Division method h(x) = x mod m
    Multiplication method h(x) = ⌊m (xA mod 1)⌋, A ∈ {z ∈ ℝ: 0 < z < 1}

    Hash table

    Hash functions used in hash tables for computing index into an array of slots. Hash table is data structure for implementing dictionaries (key-value structure). Good implemented hash tables have O(1) time for the next operations: insert, search and delete data by key. More than one keys may hash to the same slot. There are two ways for resolving collision:

  • Chaining: linked list is used for storing elements with the same hash value in slot
  • Open addressing: zero or one element is stored in each slot
  • The next methods are used to compute the probe sequences required for open addressing

    Method Formula
    Linear probing h(x, i) = (h'(x) + i) mod m
    Quadratic probing h(x, i) = (h'(x) + c1*i + c2*i^2) mod m
    Double hashing h(x, i) = (h1(x) + i*h2(x)) mod m

    Where i ∈ {0, 1, ..., m-1}, h'(x), h1(x), h2(x) are auxiliary hash functions, c1, c2 are positive auxiliary constants.

    Examples

    Lets x ∈ U{1, 1000}, h = x mod m. The next table shows the hash values in case of not prime and prime. Bolded text indicates the same hash values.

    x m = 100 (not prime) m = 101 (prime)
    723 23 16
    103 3 2
    738 38 31
    292 92 90
    61 61 61
    87 87 87
    995 95 86
    549 49 44
    991 91 82
    757 57 50
    920 20 11
    626 26 20
    557 57 52
    831 31 23
    619 19 13
  • Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein. Introduction to Algorithms.
  • [Overview of Hash Tables](https://courses.csail.mit.edu/6.006/spring11/rec/rec05.pdf)
  • [Wolfram MathWorld - Hash Function](http://mathworld.wolfram.com/HashFunction.html)
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