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Hash tables and red-black trees in Java collection framework

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2024-04-12 14:42:01404browse

Hash tables and red-black trees are the two major data structures in the Java collection framework: Hash tables use hash functions to quickly insert and search, but may produce hash conflicts. The red-black tree is a balanced binary search tree that provides balanced logarithmic complexity operations and can automatically sort.

Hash tables and red-black trees in Java collection framework

Hash table and red-black tree in Java collection framework

Hash table and red-black tree are Java collection framework A vital data structure for storing and retrieving data. This article will introduce these two data structures and provide practical examples to illustrate their uses.

Hash table

  • A hash table is a data structure based on a hash function that maps an object to an index by calculating its hash code. .
  • The hash function converts an object into a unique integer that is used to determine the object's position in the hash table.
  • Hash tables provide fast insert and lookup operations, but there is a risk of hash collisions, where different objects are mapped to the same index.

Code Example:

HashMap<String, Integer> phoneBook = new HashMap<>();
phoneBook.put("John Doe", 1234567890);
int johnDoePhoneNumber = phoneBook.get("John Doe");

In this example, we create a hash table to store the mapping between names and phone numbers. When looking up John Doe's phone number, we simply calculate the hash code for his name and use it to locate his entry in the hash table.

Red-black tree

  • The red-black tree is a balanced binary search tree that ensures logarithmic complexity in the worst case Insertion, deletion and search operations.
  • Red-black trees are balanced, which means that the depth difference from each leaf node to the root node is at most 2.
  • Red-black trees are usually used in scenarios that require efficient insertion, deletion and sorting operations.

Code Example:

TreeSet<Integer> sortedNumbers = new TreeSet<>();
sortedNumbers.add(10);
sortedNumbers.add(5);
sortedNumbers.add(15);
int lowestNumber = sortedNumbers.first();

In this example, we create a red-black tree to store a set of integers and automatically sort them. When we need to find the smallest number in a set, we just use the first() method.

When choosing a hash table and a red-black tree, you need to consider the following factors:

  • Hash table: Fast insertion and search, but prone to collisions .
  • Red-black tree: Balanced operation of logarithmic complexity, able to maintain sorting.

Based on the specific requirements of your application, informed choices can be made to optimize performance and ease of use.

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