Table of contents | |
Hashing | |
Linear Probing | |
DataItem | |
Hash Method | |
Search Operation | |
Insert Operation | |
Delete Operation |
Hash Table is a data structure which stores data in an associative manner. In a hash table, data is stored in an array format, where each data value has its own unique index value. Access of data becomes very fast if we know the index of the desired data.
Thus, it becomes a data structure in which insertion and search operations are very fast irrespective of the size of the data. Hash Table uses an array as a storage medium and uses hash technique to generate an index where an element is to be inserted or is to be located from.
Hashing is a technique to convert a range of key values into a range of indexes of an array. We're going to use modulo operator to get a range of key values. Consider an example of hash table of size 20, and the following items are to be stored. Item are in the (key,value) format.
Sr. No. | Key | Hash | Array Index |
1 | 1 | 1 % 20 = 1 | 1 |
2 | 2 | 2 % 20 = 2 | 2 |
3 | 42 | 42 % 20 = 2 | 2 |
4 | 4 | 4 % 20 = 4 | 4 |
5 | 12 | 12 % 20 = 12 | 12 |
6 | 14 | 14 % 20 = 14 | 14 |
7 | 17 | 17 % 20 = 17 | 17 |
8 | 13 | 13 % 20 = 13 | 13 |
9 | 37 | 37 % 20 = 17 | 17 |
As we can see, it may happen that the hashing technique is used to create an already used index of the array. In such a case, we can search the next empty location in the array by looking into the next cell until we find an empty cell. This technique is called linear probing.
Sr. No. | Key | Hash | Array Index | After Linear Probing, Array Index |
1 | 1 | 1 % 20 = 1 | 1 | 1 |
2 | 2 | 2 % 20 = 2 | 2 | 2 |
3 | 42 | 42 % 20 = 2 | 2 | 3 |
4 | 4 | 4 % 20 = 4 | 4 | 4 |
5 | 12 | 12 % 20 = 12 | 12 | 12 |
6 | 14 | 14 % 20 = 14 | 14 | 14 |
7 | 17 | 17 % 20 = 17 | 17 | 17 |
8 | 13 | 13 % 20 = 13 | 13 | 13 |
9 | 37 | 37 % 20 = 17 | 17 | 18 |
Basic Operations
Following are the basic primary operations of a hash table.
Search − Searches an element in a hash table.
Insert − inserts an element in a hash table.
delete − Deletes an element from a hash table.
Define a data item having some data and key, based on which the search is to be conducted in a hash table.
struct DataItem {
int data;
int key;
};
Define a hashing method to compute the hash code of the key of the data item.
int hashCode(int key){
return key % SIZE;
}
Whenever an element is to be searched, compute the hash code of the key passed and locate the element using that hash code as index in the array. Use linear probing to get the element ahead if the element is not found at the computed hash code.
struct DataItem *search(int key) {
//get the hash
int hashIndex = hashCode(key);
//move in array until an empty
while(hashArray[hashIndex] != NULL) {
if(hashArray[hashIndex]->key == key)
return hashArray[hashIndex];
//go to next cell
++hashIndex;
//wrap around the table
hashIndex %= SIZE;
}
return NULL;
}
Whenever an element is to be inserted, compute the hash code of the key passed and locate the index using that hash code as an index in the array. Use linear probing for empty location, if an element is found at the computed hash code.
void insert(int key,int data) {
struct DataItem *item = (struct DataItem*) malloc(sizeof(struct DataItem));
item->data = data;
item->key = key;
//get the hash
int hashIndex = hashCode(key);
//move in array until an empty or deleted cell
while(hashArray[hashIndex] != NULL && hashArray[hashIndex]->key != -1) {
//go to next cell
++hashIndex;
//wrap around the table
hashIndex %= SIZE;
}
hashArray[hashIndex] = item;
}
Whenever an element is to be deleted, compute the hash code of the key passed and locate the index using that hash code as an index in the array. Use linear probing to get the element ahead if an element is not found at the computed hash code. When found, store a dummy item there to keep the performance of the hash table intact.
struct DataItem* delete(struct DataItem* item) {
int key = item->key;
//get the hash
int hashIndex = hashCode(key);
//move in array until an empty
while(hashArray[hashIndex] !=NULL) {
if(hashArray[hashIndex]->key == key) {
struct DataItem* temp = hashArray[hashIndex];
//assign a dummy item at deleted position
hashArray[hashIndex] = dummyItem;
return temp;
}
//go to next cell
++hashIndex;
//wrap around the table
hashIndex %= SIZE;
}
return NULL;
}
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1. What is hashing in computer science engineering (CSE)? |
2. How does hashing work in computer science engineering (CSE)? |
3. What are the advantages of using hashing in computer science engineering (CSE)? |
4. What are the different types of hash functions used in computer science engineering (CSE)? |
5. How is collision resolution handled in hashing in computer science engineering (CSE)? |
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