A priority queue can efficiently implemented using which of the following data structures? Assume that the number of insert and peek (operation to see the current highest priority item) and extraction (remove the highest priority item) operations are almost same.ArrayLinkedListHeap Data Structures like Binary Heap, Fibonacci HeapAll of the above
Question
A priority queue can efficiently implemented using which of the following data structures? Assume that the number of insert and peek (operation to see the current highest priority item) and extraction (remove the highest priority item) operations are almost same.ArrayLinkedListHeap Data Structures like Binary Heap, Fibonacci HeapAll of the above
Solution
A priority queue can be efficiently implemented using Heap Data Structures like Binary Heap, Fibonacci Heap.
Here's why:
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Array and LinkedList: While these data structures can be used to implement a priority queue, they are not the most efficient. For an array or linked list, insertion operation would be O(1) but removal and peek operations would be O(n) in worst case as we have to search for the highest priority element.
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Heap Data Structures: Heap data structures like Binary Heap, Fibonacci Heap etc. are designed in such a way that they always maintain their heap property (i.e., the parent node has higher priority than its child nodes). This makes them ideal for implementing priority queues as they can perform insert, peek and extract operations in less time complexity. For a Binary Heap, these operations would take O(log n) time. Fibonacci Heap can perform insert and peek operations in O(1) amortized time and extract operation in O(log n) amortized time.
So, the most efficient data structure for implementing a priority queue, given the conditions in the question, would be Heap Data Structures like Binary Heap, Fibonacci Heap.
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