1. What is a hash table?
Hash Table (Hash Table) is a data structure
Hash Table (Hash Table) is a commonly used data structure, which can realize fast search and dynamic storage.
Hash tables are widely used in practical applications, such as search engines, databases, and caches.
Second, the advantages and disadvantages of the hash table
2.1 Main features/advantages of hash tables
2.1.1 Key-value store
The key-value pairs are stored in the hash table, that is, the corresponding value can be quickly found through the key.
2.1.2 Quick Find and Insert
The key is mapped to the index position of the array through the hash function, and the search can be performed directly at this position, and the time complexity is O(1).
Both lookup and insertion have low time complexity, usually O(1).
2.1.3 Dynamic storage
Hash tables can dynamically perform insertion, deletion, and lookup operations.
2.1.4 Conflict handling
Since there may be conflicts in the calculation of the hash value, that is, different keys calculate the same hash value, so the problem of hash conflict needs to be solved.
2.2 Disadvantages of hash tables
- Additional space is required to store the hash table and possible conflict resolution.
Three, the basic principle of the hash table
For a given key, an array index is calculated by a hash function, and the key-value pair is stored at the index position.
When searching, the index corresponding to the key is also calculated through the hash function, and the search is performed directly at this position, thereby greatly reducing the time complexity of the search.
Fourth, the realization of the hash table
The implementation of a hash table usually includes the following steps:
(1) Define a hash function that maps a key to an integer to determine the position of the key in the hash table.
(2) Create an array to store the elements in the hash table.
(3) Use a hash function to map the key to the corresponding position in the array and store the corresponding value.
(4) On lookup, use the same hash function to map the key to a location in the array and check if the value at that location matches the desired value.
The implementation of the hash table can be based on different data structures, such as arrays, linked lists, red-black trees, etc.
Common hash functions include modulo hash, multiplication hash, division hash, etc.
5. Hash table and hash function
Hash tables use a hash function to map keys to locations to make lookups more efficient.
A hash table maps keys to values.
A hash table maps a key (key) to a value (value) association.
The performance of the hash table depends on the choice of hash function and the load factor of the hash table.
A good hash function should map keys to positions in the array as evenly as possible to reduce collisions and lookup times.
At the same time, an appropriate load factor can ensure the efficiency and space utilization of the hash table.
The hash table calculates the hash value of the key and stores the key-value pair in a specific position of the array, thereby realizing fast lookup, insertion, and deletion operations.
6. Function construction
7. Hash conflict handling
7.1 What is a hash collision?
A hash collision is when two different keys map to the same value in a hash table.
In practical applications, an appropriate method for resolving hash collisions is usually selected according to the performance requirements of the hash table and the probability of hash collisions.
7.2 How to resolve hash collisions?
In order to resolve hash conflicts, the following methods are usually used: including open addressing method, chain address method, establishing multi-level hash table, etc.
7.2.1 Open address method
Open addressing is a method of resolving hash collisions by moving the colliding elements to the next available location.
Common open address methods include linear probing, quadratic probing, and double hashing.
7.2.1.1 Linear probing
Linear probing is the simplest open address method
It moves the colliding element to the next position until it finds an empty slot or reaches a predetermined number of times.
However, linear probing may cause the hash table to be overfilled, reducing lookup efficiency.
7.2.1.2 Double detection method
The double detection method is an improved open address method
It uses a quadratic function to choose the next position.
This method can reduce the filling rate of the hash table, but may cause uneven distribution of the hash table.
7.2.1.3 Double hashing
Double hashing is an open addressing method based on two hash functions.
It maps keys to two different locations and inserts elements into one of them.
This method can reduce the probability of hash collisions, but requires additional storage space.
7.2.2 Chain address method
The chain address method is a method for solving hash collisions,
which stores the conflicting elements in a linked list. When searching, it is necessary to traverse the entire linked list to find the corresponding element.
The chain address method can solve the hash conflict, but it will increase the time complexity of the search.
7.2.3 Building a multi-level hash table
A multi-level hash table is a method to resolve hash collisions.
It divides the hash table into multiple sub-tables and uses different hash functions to map keys to different sub-tables.
This method can reduce the probability of hash collisions, but requires additional storage space and the design of hash functions.