Hash tables are a powerful data structure that can help you perform fast searches and insertions in your algorithms. In this article, you will learn what hash tables are, how they work, and how to use them in some common scenarios.
A hash table is a data structure that stores key-value pairs in an array. The key is a unique identifier that can be any data type, such as a string, a number, or an object. The value is the data associated with the key, such as a name, a score, or a record. To store or retrieve a key-value pair, the hash table uses a hash function that maps the key to an index in the array. The hash function should be fast, consistent, and distribute the keys evenly across the array.
A hash table works by applying the hash function to the key and using the result as the index to access the array. For example, if the hash function is h(key) = key mod 10, then the key 35 will map to the index 5 in the array. This means that the value associated with the key 35 will be stored or retrieved from the array at index 5. This process is very fast, as it only involves one calculation and one array access.
One of the main benefits of using a hash table is that it can perform searches and insertions in constant time, O(1), on average. This means that the time it takes to find or add a key-value pair does not depend on the size of the data set, but only on the quality of the hash function and the array size. This makes hash tables ideal for scenarios where you need to store and access large amounts of data quickly and efficiently.
One of the main challenges of using a hash table is that it can suffer from collisions. A collision occurs when two different keys map to the same index in the array. This can cause problems, such as overwriting or losing data, or slowing down the performance of the hash table. To avoid or resolve collisions, there are different strategies, such as chaining, linear probing, or double hashing. These strategies involve creating linked lists, finding alternative indexes, or using another hash function to handle the collisions.
Hash tables can be used in a variety of algorithms, depending on the problem and goal. For instance, they can be used to count frequencies, find duplicates, cache results, and create mappings. Counting frequencies helps you uncover the most or least common elements in a data set, while finding duplicates helps you prevent or identify anomalies. Caching helps improve performance and efficiency by avoiding unnecessary work, and mapping makes lookups, translations, and conversions faster and easier.