{"id":8636,"date":"2022-06-29T12:43:39","date_gmt":"2022-06-29T12:43:39","guid":{"rendered":"https:\/\/www.prepbytes.com\/blog\/?p=8636"},"modified":"2022-06-29T12:44:51","modified_gmt":"2022-06-29T12:44:51","slug":"merge-two-binary-max-heaps","status":"publish","type":"post","link":"https:\/\/prepbytes.com\/blog\/merge-two-binary-max-heaps\/","title":{"rendered":"Merge two Binary Max-Heaps"},"content":{"rendered":"
<\/p>\n
Binary Max – Heap<\/h3>\n
A binary max – heap follows two conditions:<\/p>\n
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The given tree must be a complete binary tree (All levels are completely filled except the last level which can have nodes as left as possible. It will help in storing the Binary Heap in an array. <\/li>\n
All the nodes must have values greater than or equal to their children nodes. The parent will always have the maximum value in the sub-heap. <\/li>\n<\/ul>\n
<\/p>\n
Algorithm:<\/h3>\n\n
Initialize an array of size (n + m), where n is the size of given array1 and m is the size of given array2.<\/li>\n
Then, firstly add all the elements from array1 and then add all the elements from array2.<\/li>\n
At last, Apply the MaxHeapify method on the resultant array, to convert the resultant array into max – heap.<\/li>\n<\/ol>\n
![\"\"](\"https:\/\/prepbytes-misc-images.s3.ap-south-1.amazonaws.com\/assets\/1656506668167-Article%20%282%29.jpg\")
<\/p>\n![\"\"](\"https:\/\/prepbytes-misc-images.s3.ap-south-1.amazonaws.com\/assets\/1656062983497-Image-01.png\")
<\/p>\n![\"\"](\"https:\/\/prepbytes-misc-images.s3.ap-south-1.amazonaws.com\/assets\/1656506560746-Image-02%20%283%29.png\")
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