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Queries for k-th smallest in given ranges

Last Updated : 27 Apr, 2025
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Given ranges of the form [l, r] and an integer denoting the number of queries. The task is to return the kth smallest element for each query (assume k>1) after combining all the ranges. In case the kth smallest element doesn't exist, return -1. 

Examples : 

Input: n = 2, q = 3, range[] = {{1, 4}, {6, 8}}, queries[] = {2, 6, 10}
Output: 2 7 -1
Explanation: After combining the given ranges, the numbers become 1 2 3 4 6 7 8. As here 2nd smallest element is 2, 6th smallest element is 7, and as 10th element doesn't exist, so we return -1.

Input : arr[] = {{2, 6}, {5, 7}} queries[] = {5, 8};
Output : 6, -1
Explanation: After combining the given ranges, the numbers become 2 3 4 5 6 7. As here 5th element is 6, 8th element doesn't exist, so we return -1.

[Naive Approach] - Using Linear Search - O(n log n + qn) Time and O(n) Space

The idea is to Merge Overlapping Intervals and keep all intervals sorted in ascending order of start time. After merging in an array merged[], we use linear search to find the kth smallest element.

C++
#include <bits/stdc++.h>
using namespace std;

// Structure to store the
// start and end point
struct Interval
{
    int s;
    int e;
};

// Comparison function for sorting
bool comp(Interval a, Interval b)
{
    return a.s < b.s;
}

// Function to find Kth smallest number in a vector
// of merged intervals
int kthSmallestNum(vector<Interval> merged, int k)
{
    int n = merged.size();

    // Traverse merged[] to find
    // Kth smallest element using Linear search.
    for (int j = 0; j < n; j++)
    {
        if (k <= abs(merged[j].e -
                     merged[j].s + 1))
            return (merged[j].s + k - 1);

        k = k - abs(merged[j].e -
                     merged[j].s + 1);
    }

    if (k)
        return -1;
}

// To combined both type of ranges,
// overlapping as well as non-overlapping.
void mergeIntervals(vector<Interval> &merged,
                 Interval arr[], int n)
{
    // Sorting intervals according to start
    // time
    sort(arr, arr + n, comp);

    // Merging all intervals into merged
    merged.push_back(arr[0]);
    for (int i = 1; i < n; i++)
    {
        // To check if starting point of next
        // range is lying between the previous
        // range and ending point of next range
        // is greater than the Ending point
        // of previous range then update ending
        // point of previous range by ending
        // point of next range.
        Interval prev = merged.back();
        Interval curr = arr[i];
        if ((curr.s >= prev.s &&
             curr.s <= prev.e) &&
            (curr.e > prev.e))

            merged.back().e = curr.e;

        else
        {
            // If starting point of next range
            // is greater than the ending point
            // of previous range then store next range
            // in merged[].
            if (curr.s > prev.e)
                merged.push_back(curr);
        }
    }
}

int main()
{
    Interval arr[] = {{2, 6}, {4, 7}};
    int n = sizeof(arr)/sizeof(arr[0]);
    int query[] = {5, 8};
    int q = sizeof(query)/sizeof(query[0]);

    // Merge all intervals into merged[]
    vector<Interval>merged;
    mergeIntervals(merged, arr, n);

    // Processing all queries on merged
    // intervals
    for (int i = 0; i < q; i++)
        cout << kthSmallestNum(merged, query[i])
             << endl;

    return 0;
}
Java
import java.util.*;

class GFG
{

// Structure to store the
// start and end point
static class Interval
{
    int s;
    int e;
    Interval(int a,int b)
    {
        s = a;
        e = b;
    }
};
static class Sortby implements Comparator<Interval> 
{ 
    // Comparison function for sorting
    public int compare(Interval a, Interval b)
    {
        return a.s - b.s;
    }
} 

// Function to find Kth smallest number in a Vector
// of merged intervals
static int kthSmallestNum(Vector<Interval> merged, int k)
{
    int n = merged.size();

    // Traverse merged.get( )o find
    // Kth smallest element using Linear search.
    for (int j = 0; j < n; j++)
    {
        if (k <= Math.abs(merged.get(j).e -
                    merged.get(j).s + 1))
            return (merged.get(j).s + k - 1);

        k = k - Math.abs(merged.get(j).e -
                    merged.get(j).s + 1);
    }

    if (k != 0)
        return -1;
    return 0;
}

// To combined both type of ranges,
// overlapping as well as non-overlapping.
static Vector<Interval> mergeIntervals(Vector<Interval> merged,
                Interval arr[], int n)
{
    // Sorting intervals according to start
    // time
    Arrays.sort(arr, new Sortby());

    // Merging all intervals into merged
    merged.add(arr[0]);
    for (int i = 1; i < n; i++)
    {
        // To check if starting point of next
        // range is lying between the previous
        // range and ending point of next range
        // is greater than the Ending point
        // of previous range then update ending
        // point of previous range by ending
        // point of next range.
        Interval prev = merged.get(merged.size() - 1);
        Interval curr = arr[i];
        if ((curr.s >= prev.s &&
            curr.s <= prev.e) &&
            (curr.e > prev.e))

            merged.get(merged.size()-1).e = curr.e;

        else
        {
            // If starting point of next range
            // is greater than the ending point
            // of previous range then store next range
            // in merged.get(.)         if (curr.s > prev.e)
                merged.add(curr);
        }
    }
    return merged;
}

public static void main(String args[])
{
    Interval arr[] = {new Interval(2, 6), new Interval(4, 7)};
    int n = arr.length;
    int query[] = {5, 8};
    int q = query.length;

    // Merge all intervals into merged.get()) 
    Vector<Interval> merged = new Vector<Interval>();
    merged=mergeIntervals(merged, arr, n);

    // Processing all queries on merged
    // intervals
    for (int i = 0; i < q; i++)
        System.out.println( kthSmallestNum(merged, query[i]));
}
}
Python
class Interval:
    def __init__(self, s, e):
        self.s = s
        self.e = e

# Function to find Kth smallest number in a vector
# of merged intervals
def kthSmallestNum(merged: list, k: int) -> int:
    n = len(merged)

    # Traverse merged[] to find
    # Kth smallest element using Linear search.
    for j in range(n):
        if k <= abs(merged[j].e - merged[j].s + 1):
            return merged[j].s + k - 1

        k = k - abs(merged[j].e - merged[j].s + 1)

    if k:
        return -1

# To combined both type of ranges,
# overlapping as well as non-overlapping.
def mergeIntervals(merged: list, arr: list, n: int):

    # Sorting intervals according to start
    # time
    arr.sort(key = lambda a: a.s)

    # Merging all intervals into merged
    merged.append(arr[0])
    for i in range(1, n):

        # To check if starting point of next
        # range is lying between the previous
        # range and ending point of next range
        # is greater than the Ending point
        # of previous range then update ending
        # point of previous range by ending
        # point of next range.
        prev = merged[-1]
        curr = arr[i]
        if curr.s >= prev.s and curr.s <= prev.e and\
          curr.e > prev.e:
            merged[-1].e = curr.e
        else:

            # If starting point of next range
            # is greater than the ending point
            # of previous range then store next range
            # in merged[].
            if curr.s > prev.e:
                merged.append(curr)

# Driver Code
if __name__ == "__main__":

    arr = [Interval(2, 6), Interval(4, 7)]
    n = len(arr)
    query = [5, 8]
    q = len(query)

    # Merge all intervals into merged[]
    merged = []
    mergeIntervals(merged, arr, n)

    # Processing all queries on merged
    # intervals
    for i in range(q):
        print(kthSmallestNum(merged, query[i]))
C#
using System;
using System.Collections;
using System.Collections.Generic;
 
class GFG{
 
// Structure to store the
// start and end point
public class Interval
{
    public int s;
    public int e;
    
    public Interval(int a, int b)
    {
        s = a;
        e = b;
    }
};

class sortHelper : IComparer
{
    int IComparer.Compare(object a, object b)
    {
        Interval first = (Interval)a;
        Interval second = (Interval)b;
        return first.s - second.s;
    }
}

// Function to find Kth smallest number in 
// a Vector of merged intervals
static int kthSmallestNum(ArrayList merged, int k)
{
    int n = merged.Count;
    
    // Traverse merged.get( )o find
    // Kth smallest element using Linear search.
    for(int j = 0; j < n; j++)
    {
        if (k <= Math.Abs(((Interval)merged[j]).e -
                          ((Interval)merged[j]).s + 1))
            return (((Interval)merged[j]).s + k - 1);
 
        k = k - Math.Abs(((Interval)merged[j]).e -
                         ((Interval)merged[j]).s + 1);
    }
 
    if (k != 0)
        return -1;
        
    return 0;
}
 
// To combined both type of ranges,
// overlapping as well as non-overlapping.
static ArrayList mergeIntervals(ArrayList merged,
                                Interval []arr, int n)
{
    
    // Sorting intervals according to start
    // time
    Array.Sort(arr, new sortHelper());
    
    // Merging all intervals into merged
    merged.Add((Interval)arr[0]);
    
    for(int i = 1; i < n; i++)
    {
        
        // To check if starting point of next
        // range is lying between the previous
        // range and ending point of next range
        // is greater than the Ending point
        // of previous range then update ending
        // point of previous range by ending
        // point of next range.
        Interval prev = (Interval)merged[merged.Count - 1];
        Interval curr = arr[i];
        
        if ((curr.s >= prev.s && curr.s <= prev.e) && 
            (curr.e > prev.e))
        {
            ((Interval)merged[merged.Count - 1]).e = ((Interval)curr).e;
        }
        else
        {
            
            // If starting point of next range
            // is greater than the ending point
            // of previous range then store next range
            // in merged.get(.) if (curr.s > prev.e)
            merged.Add(curr);
        }
    }
    return merged;
}

public static void Main(string []args)
{
    Interval []arr = { new Interval(2, 6), 
                       new Interval(4, 7) };
    int n = arr.Length;
    int []query = { 5, 8 };
    int q = query.Length;
    
    // Merge all intervals into merged.get()) 
    ArrayList merged = new ArrayList();
    
    merged = mergeIntervals(merged, arr, n);
    
    // Processing all queries on merged
    // intervals
    for(int i = 0; i < q; i++)
        Console.WriteLine(kthSmallestNum(
            merged, query[i]));
}
}
JavaScript
class Interval
{
    constructor(a,b)
    {
        this.s=a;
        this.e=b;
    }
}

// Function to find Kth smallest number in a Vector
// of merged intervals
function kthSmallestNum(merged,k)
{
    let n = merged.length;
 
    // Traverse merged.get( )o find
    // Kth smallest element using Linear search.
    for (let j = 0; j < n; j++)
    {
        if (k <= Math.abs(merged[j].e -
                    merged[j].s + 1))
            return (merged[j].s + k - 1);
 
        k = k - Math.abs(merged[j].e -
                    merged[j].s + 1);
    }
 
    if (k != 0)
        return -1;
    return 0;
}

// To combined both type of ranges,
// overlapping as well as non-overlapping.
function mergeIntervals(merged,arr,n)
{
    // Sorting intervals according to start
    // time
    arr.sort(function(a,b){return a.s-b.s;});
 
    // Merging all intervals into merged
    merged.push(arr[0]);
    for (let i = 1; i < n; i++)
    {
        // To check if starting point of next
        // range is lying between the previous
        // range and ending point of next range
        // is greater than the Ending point
        // of previous range then update ending
        // point of previous range by ending
        // point of next range.
        let prev = merged[merged.length - 1];
        let curr = arr[i];
        if ((curr.s >= prev.s &&
            curr.s <= prev.e) &&
            (curr.e > prev.e))
 
            merged[merged.length-1].e = curr.e;
 
        else
        {
            // If starting point of next range
            // is greater than the ending point
            // of previous range then store next range
            // in merged.get(.)         if (curr.s > prev.e)
                merged.push(curr);
        }
    }
    return merged;
}

let arr=[new Interval(2, 6), new Interval(4, 7)];
let n = arr.length;
let query = [5, 8];
let q = query.length;

// Merge all intervals into merged.get())
let merged = [];
merged=mergeIntervals(merged, arr, n);

// Processing all queries on merged
// intervals
for (let i = 0; i < q; i++)
    console.log( kthSmallestNum(merged, query[i])+"<br>");

Output
6
-1

Time Complexity : O(nlog(n) + qn) - O(nlog(n)) arises from the sorting and merging operations performed on the intervals and O(qn) is to process the q number of queries where each query taken O(n) time.
Auxiliary Space: O(n) - for storing the input intervals arr[].

[Expected Approach] Using Binary Search - O(n log n + q log n) Time and O(n) Space

We first sort and merge the range intervals. Then, by storing the prefix sum of element counts in each range, we can use binary search to quickly find the kth smallest element.

For Example: For the range { {1 4}, {6 8}, {9 10} }  the number of elements in each range are : 4, 3, 2 respectively. Hence, prefix sum set would store {4 7 9}.

For kth smallest element we just have to find the lower_bound of k in set. the corresponding index will give us the index of the merged interval in which the required element is stored.

This reduces the search time for each query from O(n) to O(log n), making it much faster for large datasets.

C++
#include <bits/stdc++.h>
using namespace std;

vector<vector<int>> mergeIntervals(vector<vector<int>> &range)
{
    int n = range.size();
    vector<vector<int>> fin;
    for (int i = 0; i < n - 1; i++)
    {
        if (range[i][1] >= range[i + 1][0])
        {
            range[i + 1][0] = min(range[i][0], range[i + 1][0]);
            range[i + 1][1] = max(range[i][1], range[i + 1][1]);
        }
        else
        {
            fin.push_back(range[i]);
        }
    }
    fin.push_back(range[n - 1]);
    return fin;
}

vector<int> kthSmallestNum(vector<vector<int>> &range, vector<int> queries)
{

    // sort the ranges accoring to first value
    sort(range.begin(), range.end());

    // merge the overlapping intervals
    vector<vector<int>> merged = mergeIntervals(range);

    // set to store the cumulative sum of number of elements in each range
    // eg {1 4} {6 8} {9 10} would store {4 7 9} in set.
    set<int> s;
    int cumsum = 0;
    for (auto cur_range : merged)
    {
        int num_ele = cur_range[1] - cur_range[0] + 1;
        cumsum += num_ele;
        s.insert(cumsum);
    }

    // final vector to store the result of each query
    vector<int> fin;

    // for each query get the lower bound of required kth smallest element.
    // go to the index returned by lower_bound and get the required element
    for (auto q : queries)
    {
        auto it = s.lower_bound(q);
        if (it == s.end())
            fin.push_back(-1);

        // if the required element is in first range
        else if (it == s.begin())
        {
            fin.push_back(merged[0][0] + q - 1);
        }

        // if the required element is in ith range. then discard previous range elements
        // if previous elements are prevele. then look for k=q-prevele in the current range
        else
        {
            int prevele = *prev(it);
            int kth = q - prevele;
            int idx = distance(s.begin(), it);
            fin.push_back(merged[idx][0] + kth - 1);
        }
    }

    return fin;
}

int main()
{
    vector<vector<int>> range = {{1, 4}, {6, 8}};
    int n = range.size();
    vector<int> queries = {2, 6, 10};
    int q = queries.size();

    vector<int> ans = kthSmallestNum(range, queries);
    for (auto it : ans)
        cout << it << " ";
    return 0;
}
Java
import java.util.*;

public class Main {

    public static List<Integer>
    kthSmallestNum(List<List<Integer> > range,
                   List<Integer> queries)
    {
        // sort the ranges
        Collections.sort(
            range, Comparator.comparingInt(a -> a.get(0)));

        // merge the overlapping intervals
        List<List<Integer> > merged = mergeIntervals(range);

        // set to store the cumulative sum of number of
        // elements in each range
        // eg {1 4} {6 8} {9 10} would store {4 7 9} in set.
        NavigableSet<Integer> s = new TreeSet<>();
        int cumsum = 0;
        for (List<Integer> cur_range : merged) {
            int num_ele
                = cur_range.get(1) - cur_range.get(0) + 1;
            cumsum += num_ele;
            s.add(cumsum);
        }

        // final vector to store the result of each query
        List<Integer> fin = new ArrayList<>();

        // for each query get the lower bound of required
        // kth smallest element.
        // go to the index returned by lower_bound and get
        // the required element
        for (int q : queries) {
            Integer tail = s.ceiling(q);
            if (tail == null) {
                fin.add(-1);

                // if the required element is in ith range.
                // then discard previous range elements
                // if previous elements are prevele. then
                // look for k=q-prevele in the current range
            }
            else {
                int idx = s.headSet(tail, true).size() - 1;
                int prevele
                    = idx == 0
                          ? 0
                          : s.headSet(tail, false).last();
                int kth = q - prevele;
                fin.add(merged.get(idx).get(0) + kth - 1);
            }
        }
        return fin;
    }

    private static List<List<Integer> >
    mergeIntervals(List<List<Integer> > range)
    {
        int n = range.size();
        List<List<Integer> > fin = new ArrayList<>();
        for (int i = 0; i < n - 1; i++) {
            if (range.get(i).get(1)
                >= range.get(i + 1).get(0)) {
                range.get(i + 1).set(
                    0, Math.min(range.get(i).get(0),
                                range.get(i + 1).get(0)));
                range.get(i + 1).set(
                    1, Math.max(range.get(i).get(1),
                                range.get(i + 1).get(1)));
            }
            else {
                fin.add(range.get(i));
            }
        }
        fin.add(range.get(n - 1));
        return fin;
    }

    public static void main(String[] args)
    {
        List<List<Integer> > range = Arrays.asList(
            Arrays.asList(1, 4), Arrays.asList(6, 8));
        List<Integer> queries = Arrays.asList(2, 6, 10);
        List<Integer> ans = kthSmallestNum(range, queries);
        for (int it : ans) {
            System.out.print(it + " ");
        }
    }
}
Python
from bisect import bisect_left
from typing import List


def merge_intervals(intervals: List[List[int]]) -> List[List[int]]:
    n = len(intervals)
    fin = []
    for i in range(n - 1):
        if intervals[i][1] >= intervals[i + 1][0]:
            intervals[i + 1][0] = min(intervals[i][0], intervals[i + 1][0])
            intervals[i + 1][1] = max(intervals[i][1], intervals[i + 1][1])
        else:
            fin.append(intervals[i])
    fin.append(intervals[n - 1])
    return fin


def kth_smallest_num(intervals: List[List[int]], queries: List[int]) -> List[int]:
    # sort the ranges
    intervals.sort()
    
    # merge the overlapping intervals
    merged = merge_intervals(intervals)
    
    # set to store the cumulative sum of number of elements in each range
    # eg {1 4} {6 8} {9 10} would store {4 7 9} in set.
    s = set()
    cumsum = 0
    for cur_range in merged:
        num_ele = cur_range[1] - cur_range[0] + 1
        cumsum += num_ele
        s.add(cumsum)
    
    # final list to store the result of each query
    ans = []
    
    # for each query get the lower bound of required kth smallest element.
    # go to the index returned by lower_bound and get the required element
    for q in queries:
        it = bisect_left(sorted(s), q)
        if it == len(s):
            ans.append(-1)
        elif it == 0:
            ans.append(merged[0][0] + q - 1)
        else:
            prevele = sorted(s)[it - 1]
            kth = q - prevele
            idx = sorted(s).index(prevele)
            ans.append(merged[idx + 1][0] + kth - 1)
    
    return ans


if __name__ == '__main__':
    intervals = [[1, 4], [6, 8]]
    queries = [2, 6, 10]
    ans = kth_smallest_num(intervals, queries)
    print(ans)
C#
using System;
using System.Collections.Generic;

class Program
{
    static List<List<int>> MergeIntervals(List<List<int>> intervals)
    {
        int n = intervals.Count;
        List<List<int>> fin = new List<List<int>>();
        for (int i = 0; i < n - 1; i++)
        {
            if (intervals[i][1] >= intervals[i + 1][0])
            {
                intervals[i + 1][0] = Math.Min(intervals[i][0], intervals[i + 1][0]);
                intervals[i + 1][1] = Math.Max(intervals[i][1], intervals[i + 1][1]);
            }
            else
            {
                fin.Add(intervals[i]);
            }
        }
        fin.Add(intervals[n - 1]);
        return fin;
    }

    static List<int> KthSmallestNum(List<List<int>> intervals, List<int> queries)
    {
        // sort the ranges
        intervals.Sort((x, y) => x[0].CompareTo(y[0]));

        // merge the overlapping intervals
        List<List<int>> merged = MergeIntervals(intervals);

        // set to store the cumulative sum of number of elements in each range
        // eg {1 4} {6 8} {9 10} would store {4 7 9} in set.
        SortedSet<int> s = new SortedSet<int>();
        int cumsum = 0;
        foreach (List<int> cur_range in merged)
        {
            int num_ele = cur_range[1] - cur_range[0] + 1;
            cumsum += num_ele;
            s.Add(cumsum);
        }

        // final list to store the result of each query
        List<int> ans = new List<int>();

        // for each query get the lower bound of required kth smallest element.
        // go to the index returned by lower_bound and get the required element
        foreach (int q in queries)
        {
            int[] sorted_s = new List<int>(s).ToArray();
            int it = Array.BinarySearch(sorted_s, q);
            if (it < 0)
            {
                it = ~it;
            }
            if (it == s.Count)
            {
                ans.Add(-1);
            }
            else if (it == 0)
            {
                ans.Add(merged[0][0] + q - 1);
            }
            else
            {
                int prevele = sorted_s[it - 1];
                int kth = q - prevele;
                int idx = new List<int>(s).IndexOf(prevele);
                ans.Add(merged[idx + 1][0] + kth - 1);
            }
        }

        return ans;
    }

    static void Main()
    {
        List<List<int>> intervals = new List<List<int>> { new List<int> { 1, 4 }, new List<int> { 6, 8 } };
        List<int> queries = new List<int> { 2, 6, 10 };
        List<int> ans = KthSmallestNum(intervals, queries);
        foreach (int num in ans)
        {
            Console.Write(num + " ");
        }
    }
}
JavaScript
function mergeIntervals(range)
{
    const n = range.length;
    const fin = [];
    for (let i = 0; i < n - 1; i++) {
        if (range[i][1] >= range[i + 1][0]) {
            range[i + 1][0]
                = Math.min(range[i][0], range[i + 1][0]);
            range[i + 1][1]
                = Math.max(range[i][1], range[i + 1][1]);
        }
        else {
            fin.push(range[i]);
        }
    }
    fin.push(range[n - 1]);
    return fin;
}

function kthSmallestNum(range, queries)
{
    range.sort((a, b) => a[0] - b[0]);
    const merged = mergeIntervals(range);

    // set to store the cumulative sum of number of elements
    // in each range eg {1 4} {6 8} {9 10} would store {4 7
    // 9} in set.
    const s = new Set();
    let cumsum = 0;
    for (const cur_range of merged) {
        const num_ele = cur_range[1] - cur_range[0] + 1;
        cumsum += num_ele;
        s.add(cumsum);
    }

    // final vector to store the result of each query
    const fin = [];

    // for each query get the lower bound of required kth
    // smallest element.
    // go to the index returned by lower_bound and get the
    // required element
    for (const q of queries) {
        const it = s.values();
        let tail = it.next().value;
        while (tail !== undefined && tail < q) {
            tail = it.next().value;
        }
        if (tail === undefined) {
            fin.push(-1);

            // if the required element is in ith range. then
            // discard previous range elements
            // if previous elements are prevele. then look
            // for k=q-prevele in the current range
        }
        else {
            const idx
                = Array.from(s.values()).indexOf(tail) - 1;
            const prevele
                = idx === -1 ? 0
                             : Array.from(s.values())[idx];
            const kth = q - prevele;
            fin.push(merged[idx + 1][0] + kth - 1);
        }
    }
    return fin;
}

const range = [ [ 1, 4 ], [ 6, 8 ] ];
const queries = [ 2, 6, 10 ];
const ans = kthSmallestNum(range, queries);
console.log(ans.join(" "));

Output
2 7 -1 

Time Complexity : O(nlog(n) + qlog(n)) : O(nlogn) due to insertion operation in a set performed on n intervals and qlog(n) is to perform the q number of queries. Where each query taken long time.
Auxiliary Space: O(n) - to store the prefix sum of element counts.


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