As we saw with binary search, certain data
structures such as a binary search tree
can help improve the
efficiency of searches.
From linear search to binary search, we improved our search efficiency
from
*O*(*n*)
to
*O*(*logn*)
. We now present a new data structure, called
a hash table, that will increase our efficiency to
*O*(1)
, or
constant time.

A hash table is made up of two parts: an array (the actual table where the data to be searched is stored) and a mapping function, known as a hash function. The hash function is a mapping from the input space to the integer space that defines the indices of the array. In other words, the hash function provides a way for assigning numbers to the input data such that the data can then be stored at the array index corresponding to the assigned number.

Let's take a simple example. First, we start with a hash table array of strings (we'll use strings as the data being stored and searched in this example). Let's say the hash table size is 12:

Figure %: The empty hash table of strings

Next we need a hash function. There are many possible ways to construct a hash function. We'll discuss these possibilities more in the next section. For now, let's assume a simple hash function that takes a string as input. The returned hash value will be the sum of the ASCII characters that make up the string mod the size of the table:

int hash(char *str, int table_size) { int sum; /* Make sure a valid string passed in */ if (str==NULL) return -1; /* Sum up all the characters in the string */ for( ; *str; str++) sum += *str; /* Return the sum mod the table size */ return sum % table_size; }

Now that we have a framework in place, let's try using it. First, let's
store a string into the table: "Steve". We run "Steve" through the hash
function, and find that `hash("Steve",12)` yields `3`:

Figure %: The hash table after inserting "Steve"

Let's try another string: "Spark". We run the string through the hash
function and find that `hash("Spark",12)` yields `6`. Fine. We
insert it into the hash table: