Binary heap<\/a> is a complete tree i.e. All the levels of the tree are completely filled except the leaf nodes or last level and have all keys on the left. Due to this property, Binary heaps are suitable to be stored in an array.
\nA binary heap is either a min-heap or a max heap.
\nIn the min-heap, the value at the root node is smaller than all the nodes present in the binary heap, and in the max heap, the value at the root node is greater than all the nodes present in the binary heap.<\/p>\n![](\"https:\/\/prepbytes-misc-images.s3.ap-south-1.amazonaws.com\/assets\/1658223779559-Image-02.png\")
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Implementation of Priority Queue<\/h3>\n
We can implement priority queues by using different data structures like an array, a linked list, a heap data structure, or a binary search tree. But Heap data structure provides an efficient implementation of priority queues.<\/p>\n
Hence, we will use a heap data structure for implementing the priority queue in this article. We will use max-heap to implement the operations of the priority queue.<\/p>\n
A time analysis of different implementations of priority queue is given below.<\/p>\n
![\"\"](\"https:\/\/prepbytes-misc-images.s3.ap-south-1.amazonaws.com\/assets\/1658223739975-Article.jpg\")
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