Since already lots of libraries in most of the programming languages offer pre-built Heaps, knowing how it works and how to use the implementations to get our desired output often suffice. We can now implement Priority Queue requirements with the help of a Binary heap but in extreme rare occasions, we will need to write the entire implementation from scratch by ourselves. To distinguish between Leaf and internal nodes, we have : if n is the length of the array, then any node at index i is internal if 2*i+2 <= n. Here we can clearly see that for each node at index i, the children nodes are at (2*i + 1, 2*i +2) Now some points to note from the array implementation: The root node of a Heap always contains the element with highest priority or greatest value in case of Max heap or lowest value in case of Min heap, which is removed first when popped from the Heap.Ī Heap can be typically represented with an array.Min Heap - In this, nodes are ordered from smaller values in top levels to larger values in lower levels.Max Heap - In this, nodes are ordered from larger values in the top levels to smaller values in the lower levels.In case of violation of the Heap Property after insertion, swapping must takes place to satisfy it.įor example, if we try to insert 4 to the above valid heap: Insertion of new Node always happens from left to right and only in the last level (or new next level when the last level is complete).Every heap is a complete binary tree, meaning each level in the tree should have the maximum number of nodes, except the last level.In the below diagram, the red coloured numbers represent the priorities of the nodes. Each Node has higher priority than its children’s.Sounds similar to Binary Tree? Well, Binary heap is a special kind of binary tree where the ordering of every nodes matter. That is, it should be possible to order the data from least to highest priority or highest to least priority.Ī classic implementation of Priority Queue can be with Binary Heap.Īs the name suggests, in a binary heap, every node has at most two children. Note: Priority queue only supports the data which can be compared with each other. So far, priority queue is just like an Abstract Data Type which has to be implemented separately to get the desired order. This is a priority queue where each data in the queue has a certain priority and the data with highest priority goes out first and then the second and so on.įrom the above example, it can be seen that a simple queue cannot be used to implement a priority queue, where each data is associated with some weight. Now imagine, what if in that same queue, a celebrity joins in? Or may be the President of your country? Would that person be standing at the end of the queue now to wait for his turn? Well, in this circumstances, you might want them to go before you, despite the fact they joined last. Hence, a FIFO (or First In First Out) linear data structure. A simple queue, where the first person who joined it, will be the first one to leave it too.
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