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HomeJavajavaTutorialWhat are the commonly used data structures in Java and what are their implementation principles?

What are the commonly used data structures in Java and what are their implementation principles?

Deepening Java Data Structure: Principles and Applications

Efficient Java programs are inseparable from the clever use of suitable data structures. This article will discuss several commonly used data structures in Java and briefly explain its underlying implementation mechanism.

Commonly used data structures in Java include:

  1. Array: Array is the most basic data structure, used to store continuous sequences of elements of the same type. The advantage is that it has a fast access speed (O(1)), but the insertion and deletion of elements are less efficient (O(n)) because subsequent elements need to be moved.

  2. LinkedList: A linked list consists of nodes, each node stores data and a pointer to the next node. The insertion and deletion of linked lists are efficient (O(1)), but the random access elements are inefficient (O(n)).

  3. Stack: The stack follows the principle of last in first out (LIFO). Java's java.util.Stack class or Deque interface (such as ArrayDeque ) can implement the stack. Commonly used in function call stack, expression evaluation, etc.

  4. Queue: Queue follows the first-in-first-out (FIFO) principle. Java's java.util.Queue interface and LinkedList class can implement queues and be applied to task scheduling, buffering and other scenarios.

  5. Tree: A tree is a hierarchical structure used to represent hierarchical relationships. Common trees include binary trees, balanced binary trees (AVL trees, red and black trees), etc. They are often used to search, sort and organize data.

  6. Graph: A graph consists of a node (vertex) and an edge connecting the node. For representation of networks, relationships, etc., the algorithm includes depth-first search (DFS) and breadth-first search (BFS).

  7. Set: The set stores non-duplicate elements. Java provides HashSet (based on hash table), TreeSet (based on red and black trees) and LinkedHashSet (combining the features of hash table and linked lists).

  8. Map: Map stores key-value pairs. Java provides HashMap (based on hash table), TreeMap (based on red and black tree), and LinkedHashMap (combining the features of hash table and linked list).

  9. Heap: Heap is a special completely binary tree that satisfies the properties of the heap (for example, the minimum heap: the parent node is less than or equal to the child node). Java's PriorityQueue class is based on a heap implementation and is used for priority queues.

  10. Hash Table: Hash Table uses a hash function to map keys to an array index, enabling quick search, insertion and deletion (average O(1)). Java's HashMap is the implementation of hash tables.

Implementation principle and code example:

The specific implementation of each data structure is relatively complex, here is a brief overview:

  • Array: Use Java built-in array types directly.
  • Linked list: Custom node classes are required, including data domains and pointer domains. LinkedList provides encapsulation of linked lists.
  • Stack/queue: Usually implemented based on arrays or linked lists. Stack and LinkedList provide corresponding interfaces.
  • Tree/graph: Custom node classes and related operation methods are required, such as traversal, insertion, deletion, etc. Many libraries provide tree and graph implementations.
  • Collection/mapping: HashSet , TreeSet , HashMap , TreeMap , etc. are all implemented based on hash tables or red and black trees. The internal implementation details involve hash functions, conflict processing, tree balance, etc.
  • Heap: PriorityQueue uses arrays internally to simulate the heap structure and maintain the heap properties.

Choosing the right data structure is critical to optimizing program performance. Understanding its underlying principles helps developers write more efficient and robust Java code. For more in-depth learning, you need to refer to Java API documents and related data structures and algorithm books.

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