Similar Questions : K way Merge

Prerequsites : 🌇kth smallest element in an array, Merge K sorted Arrays

These questions may involve merging multiple sorted arrays to obtain the Kth item or the desired answer from a set of multiple sorted arrays. It is a prerequisite to have multiple sorted arrays for this method. Multiple sorted arrays allow us to operate on the greedy principle of choosing the smallest element first from each array as we move across the arrays. During the merging process, the minimum values across all arrays are processed first and merged through a heap to obtain the final value.

Prerequisite: Multiple sorted arrays

Similar Questions

1. Kth Smallest Element in a Sorted Matrix | Solution
1. Treat each row in a matrix as a separate sorted array. Merge the values from the arrays until k elements and return the last element popped from the heap.
Copy

matrix = 
[
  [ 2,  6,  8],
  [11, 12, 14],
  [15, 16, 18]
],

2. Design Twitter | Solution
1. This is similar K way merge to get the  10 most recent tweets in the user's news feed. The feed of each user is in ascending order, representing the time the tweet was posted. To get the 10 most recent tweets we need to run K way merge in reverse. Talked in detail in Design twitter.

2. To find the Kth largest element in a set of sorted arrays, we can merge them in reverse order and return the last element popped from the heap when the array is of size K.
3. Median of two Sorted arrays | Solution
1. However, finding the median still requires O(n) time, where n is the size of both arrays. While there are more efficient methods for solving this problem at log(n), using the K-way merge pattern can help clarify things around looking for similar questions.
4. Merge k Sorted Lists | Solution
1. Similar to Merge K sorted Arrays, but with a linked list representation instead of an array.
5. Smallest Range Covering Elements from K Lists | Solution
1. A slight variation of K-way merge involves merging all the arrays as usual while keeping track of the upper and lower bounds across all the elements in the heap. With every merge, the difference between the upper bound and the lower bound changes. We only reduce the lower bound through the heap. This ties into the greedy principle of shortening the range. At the end, we simply return the smallest range between the upper and lower bounds.
6. Here are some more examples that were done better by another person on LeetCode.

See similar questions, Help people out by submitting them.