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Besides the obvious answer of a Priority Queue, when would a heap be useful in my programming adventures?
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You should use heap when you require to allocate a large block of memory. For example, you want to create a large size array or big structure to keep that variable around a long time then you should allocate it on the heap.
Taking an example from real life —Heap Sorting can be applied to a sim card store where there are many customers in line. The customers who have to pay bills can be dealt with first because their work will take less time. This method will save time for many customers in line and avoid unnecessary waiting.
A heap is a tree-based data structure in which all the nodes of the tree are in a specific order. For example, if is the parent node of , then the value of follows a specific order with respect to the value of and the same order will be followed across the tree.
Following are some uses other than Heapsort. Priority Queues: Priority queues can be efficiently implemented using Binary Heap because it supports insert(), delete() and extractmax(), decreaseKey() operations in O(logn) time. Binomoial Heap and Fibonacci Heap are variations of Binary Heap.
Use it whenever you need quick access to the largest (or smallest) item, because that item will always be the first element in the array or at the root of the tree.
However, the remainder of the array is kept partially unsorted. Thus, instant access is only possible to the largest (smallest) item. Insertions are fast, so it's a good way to deal with incoming events or data and always have access to the earliest/biggest.
Useful for priority queues, schedulers (where the earliest item is desired), etc...
A heap is a tree where a parent node's value is larger than that of any of its descendant nodes.
If you think of a heap as a binary tree stored in linear order by depth, with the root node first (then the children of that node next, then the children of those nodes next); then the children of a node at index N are at 2N+1 and 2N+2. This property allows quick access-by-index. And since heaps are manipulated by swapping nodes, this allows for in-place sorting.
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