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Difference between Min Heap and Max Heap
A heap is a data structure which is based on tree. This tree is a complete binary tree which consists of N nodes and log N height. The elements whose priority is highest or lowest can be easily removed. This heap structure is displayed in the form of an array. The heaps can be used to derive maximum and minimum values.
Types of Heaps
Heaps are of two types and we will discuss them here.
Min Heap
The key in the Min Heap is available at the root node. It must be less than or equal to the number of keys in the child nodes. This rule has to be followed in all the trees present in the binary tree. The root is the place where the minimum key element can be found.
Max Heap
The key in the Max Heap is greater than or equal to the keys present in the keys of the child nodes. This rule is followed by all the trees present in the binary tree. The root is the place where the maximum key element can be found.
Operations performed by Min Heap and Max Heap
The operations performed on the min heap and max heap are extracting the values, getting the values, and inserting the values. Let us know about these operations in detail.
- Getting an element − Maximum or minimum value can be extracted from the heaps when the highest priority is given to the O(1) element. This element is available at the top of the tree heap.
- Inserting an element − An element can be inserted in the max and min heap by using the logarithmic time which is O(log(N)).
- Deleting an element − In order to delete an element a logarithmic time that is O(log(N)) is used.
Applications of Heap Data Structure
The heap data structure has many applications which are as follows −
- The main usage of the heap is the implementation of the priority queues. The elements can be extracted on the basis of priority which can be maximum or minimum value.
- Arrays can be sorted into descending or ascending order with the help of s sorting algorithm called heapsort.
- Heaps can be used to find shortest paths and minimum spanning trees with the help of Dijkstra’s algorithm and Prim’s algorithm.
- Heap data is used for the allocation and deallocation of memory dynamically. Memory blocks are stored in the heap which are easily managed by the heap data structure.
- Heap data structure is also used in job scheduling algorithms which helps in task scheduling on the basis of deadline or priority.
Advantages of Heap Data Structure
The heap data structure has many advantages and some of them are listed below −
- Elements can be inserted or deleted easily. When a new element is added, it is placed at the bottom of the heap and later moved on to the correct position. An element can be removed after it is replaced by the bottom element. After that heapify operation is done to restructure the heap.
- The usage of heap data structure is done to implement a priority queue. In this case, the element with the highest priority is placed at the top.
- Maximum and minimum elements can be found easily as the top element in the max heap is the maximum element and the top element in the min heap is the minimum element.
- The memory used by heap data structures is less in comparison to other data structures.
Disadvantages of Heap Structure
Heap structure has a few disadvantages which are listed below −
- There is no flexibility in the heap data because the elements are arranged in a specific order.
- A specific element cannot be easily searched in a heap.
- The heap data structure is not stable as modifications can lead to disturb the relative order.
- The dynamic memory system is used by a heap data structure which may not be good for systems with less memory.
Difference between Min Heap and Max Heap
Min Heap and Max Heap have a lot of differences which we can find in the table below −
| Min Heap | Max Heap |
|---|---|
| Min heap is a tree structure in which the key with the lowest value is present at the root node. | Max heap is a tree structure in which the key with the highest value is present at the root node. |
| The minimum key element can be found at the root node. | The maximum key element can be found at the root node. |
| The ascending order of the priorities can be found in the min heap. | The descending order of the priorities can be found in the max heap. |
| Priority is given to the smallest element in the min heap. | Priority is given to the largest element in the max heap. |
| The smallest element pops up when needed. | The largest element pops up when needed. |
| Min heap is used for the implementation of the Dijkstra Graph algorithm and Minimum Spanning trees. | Max heap is used for the implementation of priority queues. |
There are different operations performed on the min heap which include −
|
There are different operations performed on the max heap which include −
|
Conclusion
The heap data structure is based on tree and is of two types which are max heap and min heap. The Min heap has the root element with the smallest value while the max heap has the root element with the largest value. Priority is given to the smallest element in the min heap and the largest element in the max heap. The heap data structure is not flexible as modifications can disturb the relative order.
FAQs on Min Heap and Max Heap
1. What are the two types of heaps in the heap data structure?
The two types of heaps in the heap data structure are max heap and min heap.
2. What are the operations performed on the heaps?
The operations performed on the heaps are insertion, deletion, and retrieving an element.
3. What is the main aim of the heap data structure?
The main aim of the heap data structure is to implement priority queues.
4. Is heap data structure flexible?
No! The heap data structure is not flexible as the elements are arranged in specific order.
5. How memory is allocated for the heap data structure?
Memory is allocated dynamically.
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