Hash Table
Hash Table Cheat Sheet
Hash tables, commonly referred to as hash maps, are a powerful data structure that pairs keys with values through a process known as hashing. By applying a hash function to a key, a hash table computes an index into an array of buckets or slots, enabling quick data retrieval. This efficiency in mapping keys to values makes hash tables an indispensable tool in software development.
Key Concepts
Hash Function: A function that processes an input element to produce a hash code, determining the index where the value is stored in the hash table.
Space-Time Tradeoff: Hash tables exemplify a tradeoff between space and time, offering rapid searches at the expense of additional memory to manage the hash table structure.
Collision Resolution: Collisions occur when multiple keys hash to the same index. Techniques such as separate chaining (linking collided items using linked lists) or open addressing (finding the next available slot) are employed to resolve these collisions.
Implementations in Different Languages
Golang: Maps.
C++: Utilizes
std::unordered_map
for hash table implementation.Java: Employs
java.util.Map
, withjava.util.HashMap
being a common choice.Python: Implements hash tables using the
dict
type.JavaScript: Offers
Object
orMap
for hash table functionalities.
Time Complexity
Access: Direct access by hash code is not typically possible, making this operation not applicable.
Search: O(1) on average, thanks to efficient hashing.
Insert: O(1) on average, allowing for quick additions to the hash table.
Remove: O(1) on average, facilitating fast removals.
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