Skip to content
Related Articles

Related Articles

Improve Article
Optimal File Merge Patterns
  • Difficulty Level : Medium
  • Last Updated : 27 Aug, 2020

Given n number of sorted files, the task is to find the minimum computations done to reach Optimal Merge Pattern.

When two or more sorted files are to be merged all together to form a single file, the minimum computations done to reach this file are known as Optimal Merge Pattern.

If more than 2 files need to be merged then it can be done in pairs. For example, if need to merge 4 files A, B, C, D. First Merge A with B to get X1, merge X1 with C to get X2, merge X2 with D to get X3 as the output file.

If we have two files of sizes m and n, the total computation time will be m+n. Here, we use greedy strategy by merging two smallest size files among all the files present.

Examples:
Given 3 files with size 2, 3, 4 units.Find optimal way to combine these files



Input: n = 3, size = {2, 3, 4}
Output: 14
Explanation: There are different ways to combine these files:
Method 1: Optimal method

Method 2:

Method 3:

Input: n = 6, size = {2, 3, 4, 5, 6, 7}
Output: 68
Explanation: Optimal way to combine these files

Approach:

Node represents a file with a given size also given nodes are greater than 2

  1. Add all the nodes in a priority queue (Min Heap).{node.weight = file size}
  2. Initialize count = 0 // variable to store file computations.
  3. Repeat while (size of priority Queue is greater than 1)
    1. create a new node
    2. new node = pq.poll().weight+pq.poll().weight;//pq denotes priority queue, remove 1st smallest and 2nd smallest element and add their weights to get a new node
    3. count += node.wight
    4. add this new node to priority queue;
  4. count is the final answer

Below is the implementation of the above approach:

C++




// C++ program to implement
// Optimal File Merge Pattern
#include<bits/stdc++.h>
using namespace std;
  
// Function to find minimum computation 
int minComputation(int size, int files[])
{
      
    // Create a min heap
    priority_queue<int, vector<int>, 
           greater<int>> pq;
  
    for(int i = 0; i < size; i++)
    {
          
        // Add sizes to priorityQueue
        pq.push(files[i]);
    }
      
    // Variable to count total Computation
    int count = 0;
  
    while(pq.size() > 1)
    {
          
        // pop two smallest size element
        // from the min heap
        int first_smallest = pq.top();
        pq.pop();
        int second_smallest = pq.top();
        pq.pop();
          
        int temp = first_smallest + second_smallest;
  
        // Add the current computations
        // with the previous one's
        count += temp;
  
        // Add new combined file size
        // to priority queue or min heap
        pq.push(temp);
    }
    return count;
}
  
// Driver code
int main()
{
      
    // No of files
    int n = 6;
      
    // 6 files with their sizes
    int files[] = { 2, 3, 4, 5, 6, 7 };
      
    // Total no of computations
    // do be done final answer
    cout << "Minimum Computations = "
         << minComputation(n, files);
  
    return 0;
}
  
// This code is contributed by jaigoyal1328

Java




// Java program to implement
// Optimal File Merge Pattern
  
import java.util.Scanner;
import java.util.PriorityQueue;
  
public class OptimalMergePatterns {
  
    // Function to find minimum computation
    static int minComputation(int size, int files[])
    {
  
        // create a min heap
        PriorityQueue<Integer> pq
            = new PriorityQueue<>();
  
        for (int i = 0; i < size; i++) {
  
            // add sizes to priorityQueue
            pq.add(files[i]);
        }
  
        // variable to count total computations
        int count = 0;
  
        while (pq.size() > 1) {
  
            // pop two smallest size element
            // from the min heap
            int temp = pq.poll() + pq.poll();
  
            // add the current computations
            // with the previous one's
            count += temp;
  
            // add new combined file size
            // to priority queue or min heap
            pq.add(temp);
        }
  
        return count;
    }
  
    public static void main(String[] args)
    {
  
        // no of files
        int size = 6;
  
        // 6 files with their sizes
        int files[] = new int[] { 2, 3, 4, 5, 6, 7 };
  
        // total no of computations
        // do be done final answer
        System.out.println("Minimum Computations = "
                           + minComputation(size, files));
    }
}
Output:
Minimum Computations = 68

Attention reader! Don’t stop learning now. Get hold of all the important DSA concepts with the DSA Self Paced Course at a student-friendly price and become industry ready.  To complete your preparation from learning a language to DS Algo and many more,  please refer Complete Interview Preparation Course.

In case you wish to attend live classes with industry experts, please refer Geeks Classes Live




My Personal Notes arrow_drop_up
Recommended Articles
Page :