What Are Priority Queues in Data Structure?


Scott Campbell

A priority queue is a data structure that stores elements with associated priority values. It follows the principle of “first in, first out,” where the element with the highest priority is dequeued first. In other words, elements are inserted into the queue with their respective priorities, and when they are removed, the element with the highest priority comes out first.

Understanding Priority Queues

Priority queues are commonly used in various applications, such as task scheduling, graph algorithms (such as Dijkstra’s algorithm), and data compression algorithms (such as Huffman coding). They allow us to efficiently manage and process elements based on their priority levels.

A priority queue can be implemented using different data structures, such as arrays, linked lists, binary heaps, or balanced search trees. Each implementation has its advantages and disadvantages in terms of time complexity for insertion and removal operations.

Operations on a Priority Queue

A priority queue typically supports the following operations:

  • Insertion: The process of adding an element to the queue while maintaining its order according to its priority.
  • Deletion: The process of removing an element from the queue based on its priority. The highest-priority element is removed first.
  • Peek/Top: Retrieving the highest-priority element from the queue without removing it.

The time complexity of these operations depends on the underlying implementation of the priority queue. For example, binary heap-based implementations provide efficient time complexities for both insertion and deletion operations (O(log n)), making them widely used in practice.

Applications of Priority Queues

The flexibility and efficiency of priority queues make them valuable in various scenarios:

  • Task Scheduling: In operating systems, priority queues are used to schedule processes or threads based on their priorities.
  • Event-driven Simulations: Priority queues are used to manage events in simulations, where each event occurs at a specific time and must be processed in a specific order.
  • Dijkstra’s Algorithm: Priority queues are crucial in finding the shortest path in a graph. They help select the next node with the minimum distance during graph traversal.
  • Huffman Coding: Priority queues are used to build efficient prefix codes for data compression. They allow us to assign shorter codes to frequently occurring characters, reducing the overall size of compressed data.


In summary, a priority queue is a valuable data structure that allows efficient management and processing of elements based on their priorities. It finds applications in various domains such as task scheduling, graph algorithms, and data compression. By understanding the underlying implementation and operations of priority queues, you can leverage this powerful tool to solve complex problems efficiently.

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