# Sort elements by frequency | Set 1

• Difficulty Level : Medium
• Last Updated : 18 Jul, 2022

Print the elements of an array in the decreasing frequency if 2 numbers have same frequency then print the one which came first.

Examples:

Input:  arr[] = {2, 5, 2, 8, 5, 6, 8, 8}
Output: arr[] = {8, 8, 8, 2, 2, 5, 5, 6}

Input: arr[] = {2, 5, 2, 6, -1, 9999999, 5, 8, 8, 8}
Output: arr[] = {8, 8, 8, 2, 2, 5, 5, 6, -1, 9999999} METHOD 1 (Use Sorting)

• Use a sorting algorithm to sort the elements O(nlogn)
• Iterate the sorted array and construct a 2D array of element and count O(n).
• Sort the 2D array according to count O(nlogn).

Example:

Input 2 5 2 8 5 6 8 8
After sorting we get
2 2 5 5 6 8 8 8
Now construct the 2D array as
2, 2
5, 2
6, 1
8, 3
Sort by count
8, 3
2, 2
5, 2
6, 1

How to maintain the order of elements if the frequency is the same?

The above approach doesn’t make sure the order of elements if the frequency is the same. To handle this, we should use indexes in step 3, if two counts are the same then we should first process(or print) the element with a lower index. In step 1, we should store the indexes instead of elements.

Input   2  5  2  8  5  6  8  8
After sorting we get
Element 2 2 5 5 6 8 8 8
Index   0 2 1 4 5 3 6 7
Now construct the 2D array as
Index, Count
0,      2
1,      2
5,      1
3,      3
Sort by count (consider indexes in case of tie)
3, 3
0, 2
1, 2
5, 1
Print the elements using indexes in the above 2D array. Below is the implementation of the above approach –

## CPP

 `// Sort elements by frequency. If two elements have same``// count, then put the elements that appears first``#include ``using` `namespace` `std;` `// Used for sorting``struct` `ele {``    ``int` `count, index, val;``};` `// Used for sorting by value``bool` `mycomp(``struct` `ele a, ``struct` `ele b)``{``    ``return` `(a.val < b.val);``}` `// Used for sorting by frequency. And if frequency is same,``// then by appearance``bool` `mycomp2(``struct` `ele a, ``struct` `ele b)``{``    ``if` `(a.count != b.count)``        ``return` `(a.count < b.count);``    ``else``        ``return` `a.index > b.index;``}` `void` `sortByFrequency(``int` `arr[], ``int` `n)``{``    ``struct` `ele element[n];``    ``for` `(``int` `i = 0; i < n; i++) {` `        ``// Fill Indexes``        ``element[i].index = i;` `        ``// Initialize counts as 0``        ``element[i].count = 0;` `        ``// Fill values in structure``        ``// elements``        ``element[i].val = arr[i];``    ``}` `    ``/* Sort the structure elements according to value,``       ``we used stable sort so relative order is maintained.``     ``*/``    ``stable_sort(element, element + n, mycomp);` `    ``/* initialize count of first element as 1 */``    ``element.count = 1;` `    ``/* Count occurrences of remaining elements */``    ``for` `(``int` `i = 1; i < n; i++) {` `        ``if` `(element[i].val == element[i - 1].val) {``            ``element[i].count += element[i - 1].count + 1;` `            ``/* Set count of previous element as -1, we are``               ``doing this because we'll again sort on the``               ``basis of counts (if counts are equal than on``               ``the basis of index)*/``            ``element[i - 1].count = -1;` `            ``/* Retain the first index (Remember first index``               ``is always present in the first duplicate we``               ``used stable sort. */``            ``element[i].index = element[i - 1].index;``        ``}` `        ``/* Else If previous element is not equal to current``          ``so set the count to 1 */``        ``else``            ``element[i].count = 1;``    ``}` `    ``/* Now we have counts and first index for each element``       ``so now sort on the basis of count and in case of tie``       ``use index to sort.*/``    ``stable_sort(element, element + n, mycomp2);``    ``for` `(``int` `i = n - 1, index = 0; i >= 0; i--)``        ``if` `(element[i].count != -1)``            ``for` `(``int` `j = 0; j < element[i].count; j++)``                ``arr[index++] = element[i].val;``}` `// Driver program``int` `main()``{``    ``int` `arr[] = { 2, 5, 2, 6, -1, 9999999, 5, 8, 8, 8 };``    ``int` `n = ``sizeof``(arr) / ``sizeof``(arr);` `    ``sortByFrequency(arr, n);` `    ``for` `(``int` `i = 0; i < n; i++)``        ``cout << arr[i] << ``" "``;``    ``return` `0;``}`

## Python3

 `# Python3 program that performs the following``# operations: Sort elements by frequency. If two elements``# have same count, then put the elements that appears first` `# Used for sorting`  `class` `ele:``    ``def` `__init__(``self``):` `        ``self``.count ``=` `0``        ``self``.index ``=` `0``        ``self``.val ``=` `0`  `def` `mycomp(a):``    ``return` `a.val` `# Used for sorting by frequency. And if frequency is same,``# then by appearance`  `def` `mycomp2(a):``    ``# using negative value for a.index``    ``# since the sorting should be in``    ``# descending order``    ``return` `(a.count, ``-``a.index)`  `def` `sortByFrequency(arr, n):``    ``element ``=` `[``None` `for` `_ ``in` `range``(n)]``    ``for` `i ``in` `range``(n):` `        ``element[i] ``=` `ele()` `        ``# Fill Indexes``        ``element[i].index ``=` `i` `        ``# Initialize counts as 0``        ``element[i].count ``=` `0` `        ``# Fill values in structure``        ``# elements``        ``element[i].val ``=` `arr[i]` `    ``# Sort the structure elements according to value,``    ``# we used stable sort so relative order is maintained.``    ``#``    ``element.sort(key``=``mycomp)` `    ``# initialize count of first element as 1``    ``element[``0``].count ``=` `1` `    ``# Count occurrences of remaining elements``    ``for` `i ``in` `range``(``1``, n):` `        ``if` `(element[i].val ``=``=` `element[i ``-` `1``].val):``            ``element[i].count ``+``=` `element[i ``-` `1``].count ``+` `1` `            ``# Set count of previous element as -1, we are``            ``#  doing this because we'll again sort on the``            ``#  basis of counts (if counts are equal than on``            ``# the basis of index)*/``            ``element[i ``-` `1``].count ``=` `-``1` `            ``# Retain the first index (Remember first index``            ``#  is always present in the first duplicate we``            ``#  used stable sort. */``            ``element[i].index ``=` `element[i ``-` `1``].index` `        ``# Else If previous element is not equal to current``        ``#  so set the count to 1``        ``else``:``            ``element[i].count ``=` `1` `    ``# Now we have counts and first index for each element``    ``# so now sort on the basis of count and in case of tie``    ``# use index to sort.*/``    ``element.sort(key``=``mycomp2)` `    ``index ``=` `0``    ``for` `i ``in` `range``(n ``-` `1``, ``-``1``, ``-``1``):``        ``if` `(element[i].count !``=` `-``1``):``            ``for` `j ``in` `range``(element[i].count):``                ``arr[index] ``=` `element[i].val``                ``index ``+``=` `1`  `# Driver program``arr ``=` `[``2``, ``5``, ``2``, ``6``, ``-``1``, ``9999999``, ``5``, ``8``, ``8``, ``8``]``n ``=` `len``(arr)` `sortByFrequency(arr, n)` `print``(``*``arr)` `# This code is contributed by phasing17`

## C#

 `// Sort elements by frequency. If two elements have same``// count, then put the elements that appears first``using` `System;``using` `System.Collections.Generic;` `// Used for sorting``class` `ele {``    ``public` `int` `count, index, val;``};` `// Used for sorting by value``class` `mycomp : Comparer {``    ``public` `override` `int` `Compare(ele a, ele b)``    ``{``        ``return` `(a.val.CompareTo(b.val));``    ``}``};` `// Used for sorting by frequency. And if frequency is same,``// then by appearance``class` `mycomp2 : Comparer {``    ``public` `override` `int` `Compare(ele a, ele b)``    ``{``        ``if` `(a.count != b.count)``            ``return` `(a.count).CompareTo(b.count);``        ``return` `(b.index).CompareTo(a.index);``    ``}``};` `class` `GFG {` `    ``static` `void` `sortByFrequency(``int``[] arr, ``int` `n)``    ``{``        ``ele[] element = ``new` `ele[n];``        ``for` `(``int` `i = 0; i < n; i++) {` `            ``element[i] = ``new` `ele();``            ``// Fill Indexes``            ``element[i].index = i;` `            ``// Initialize counts as 0``            ``element[i].count = 0;` `            ``// Fill values in structure``            ``// elements``            ``element[i].val = arr[i];``        ``}` `        ``/* Sort the structure elements according to value,``           ``we used stable sort so relative order is``           ``maintained.``         ``*/``        ``Array.Sort(element, ``new` `mycomp());` `        ``/* initialize count of first element as 1 */``        ``element.count = 1;` `        ``/* Count occurrences of remaining elements */``        ``for` `(``int` `i = 1; i < n; i++) {` `            ``if` `(element[i].val == element[i - 1].val) {``                ``element[i].count``                    ``+= element[i - 1].count + 1;` `                ``/* Set count of previous element as -1, we``                   ``are doing this because we'll again sort``                   ``on the basis of counts (if counts are``                   ``equal than on the basis of index)*/``                ``element[i - 1].count = -1;` `                ``/* Retain the first index (Remember first``                   ``index is always present in the first``                   ``duplicate we used stable sort. */``                ``element[i].index = element[i - 1].index;``            ``}` `            ``/* Else If previous element is not equal to``              ``current so set the count to 1 */``            ``else``                ``element[i].count = 1;``        ``}` `        ``/* Now we have counts and first index for each``           ``element so now sort on the basis of count and in``           ``case of tie use index to sort.*/``        ``Array.Sort(element, ``new` `mycomp2());``        ``for` `(``int` `i = n - 1, index = 0; i >= 0; i--)``            ``if` `(element[i].count != -1)``                ``for` `(``int` `j = 0; j < element[i].count; j++)``                    ``arr[index++] = element[i].val;``    ``}` `    ``// Driver program``    ``public` `static` `void` `Main(``string``[] args)``    ``{``        ``int``[] arr = { 2, 5, 2, 6, -1, 9999999, 5, 8, 8, 8 };``        ``int` `n = arr.Length;` `        ``sortByFrequency(arr, n);` `        ``for` `(``int` `i = 0; i < n; i++)``            ``Console.Write(arr[i] + ``" "``);``    ``}``}` `// This code is contributed by phasing17`

## Javascript

 `// JavaScript program that performs the following``// operations: Sort elements by frequency. If two elements``// have same count, then put the elements that appears first` `// Used for sorting``class ele {``    ``constructor()``    ``{``        ``this``.count;``        ``this``.index;``        ``this``.val;``    ``}``};` `// Used for sorting by value``function` `mycomp(a, b) { ``return` `(a.val > b.val); }` `// Used for sorting by frequency. And if frequency is same,``// then by appearance``function` `mycomp2(a, b)``{``    ``if` `(a.count != b.count)``        ``return` `(a.count > b.count);``    ``else``        ``return` `a.index < b.index;``}` `function` `sortByFrequency(arr, n)``{``    ``let element = ``new` `Array(n);``    ``for` `(``var` `i = 0; i < n; i++) {` `        ``element[i] = ``new` `ele();` `        ``// Fill Indexes``        ``element[i].index = i;` `        ``// Initialize counts as 0``        ``element[i].count = 0;` `        ``// Fill values in structure``        ``// elements``        ``element[i].val = arr[i];``    ``}` `    ``/* Sort the structure elements according to value,``       ``we used stable sort so relative order is maintained.``     ``*/``    ``element.sort(mycomp);` `    ``/* initialize count of first element as 1 */``    ``element.count = 1;` `    ``/* Count occurrences of remaining elements */``    ``for` `(``var` `i = 1; i < n; i++) {` `        ``if` `(element[i].val == element[i - 1].val) {``            ``element[i].count += element[i - 1].count + 1;` `            ``/* Set count of previous element as -1, we are``               ``doing this because we'll again sort on the``               ``basis of counts (if counts are equal than on``               ``the basis of index)*/``            ``element[i - 1].count = -1;` `            ``/* Retain the first index (Remember first index``               ``is always present in the first duplicate we``               ``used stable sort. */``            ``element[i].index = element[i - 1].index;``        ``}` `        ``/* Else If previous element is not equal to current``          ``so set the count to 1 */``        ``else``            ``element[i].count = 1;``    ``}` `    ``/* Now we have counts and first index for each element``       ``so now sort on the basis of count and in case of tie``       ``use index to sort.*/``    ``element.sort(mycomp2);``    ``for` `(``var` `i = n - 1, index = 0; i >= 0; i--)``        ``if` `(element[i].count != -1)``            ``for` `(``var` `j = 0; j < element[i].count; j++)``                ``arr[index++] = element[i].val;``}` `// Driver program``let arr = [ 2, 5, 2, 6, -1, 9999999, 5, 8, 8, 8 ];``let n = arr.length;` `sortByFrequency(arr, n);` `for` `(``var` `i = 0; i < n; i++)``    ``process.stdout.write(arr[i] + ``" "``);`  `// This code is contributed by phasing17`

Output

`8 8 8 2 2 5 5 6 -1 9999999 `

Thanks to Gaurav Ahirwar for providing the above implementation.

METHOD 2 (Use Hashing and Sorting)
Using a hashing mechanism, we can store the elements (also the first index) and their counts in a hash. Finally, sort the hash elements according to their counts.
Below is the implementation of the above approach –

## CPP

 `// CPP program for above approach``#include ``using` `namespace` `std;` `// Compare function``bool` `fcompare(pair<``int``, pair<``int``, ``int``> > p,``              ``pair<``int``, pair<``int``, ``int``> > p1)``{``    ``if` `(p.second.second != p1.second.second)``        ``return` `(p.second.second > p1.second.second);``    ``else``        ``return` `(p.second.first < p1.second.first);``}``void` `sortByFrequency(``int` `arr[], ``int` `n)``{``    ``unordered_map<``int``, pair<``int``, ``int``> > hash; ``// hash map``    ``for` `(``int` `i = 0; i < n; i++) {``        ``if` `(hash.find(arr[i]) != hash.end())``            ``hash[arr[i]].second++;``        ``else``            ``hash[arr[i]] = make_pair(i, 1);``    ``} ``// store the count of all the elements in the hashmap` `    ``// Iterator to Traverse the Hashmap``    ``auto` `it = hash.begin();` `    ``// Vector to store the Final Sortted order``    ``vector > > b;``    ``for` `(it; it != hash.end(); ++it)``        ``b.push_back(make_pair(it->first, it->second));` `    ``sort(b.begin(), b.end(), fcompare);` `    ``// Printing the Sorted sequence``    ``for` `(``int` `i = 0; i < b.size(); i++) {``        ``int` `count = b[i].second.second;``        ``while` `(count--)``            ``cout << b[i].first << ``" "``;``    ``}``}` `// Driver Function``int` `main()``{``    ``int` `arr[] = { 2, 5, 2, 6, -1, 9999999, 5, 8, 8, 8 };``    ``int` `n = ``sizeof``(arr) / ``sizeof``(arr);` `    ``sortByFrequency(arr, n);` `    ``return` `0;``}`

## Java

 `/*package whatever //do not write package name here */``import` `java.util.Arrays;``import` `java.util.Collections;``import` `java.util.Comparator;``import` `java.util.HashMap;``import` `java.util.List;``class` `GFG {` `    ``static` `Integer[] arr = { ``2``, ``5``, ``2``, ``8``, ``5``, ``6``, ``8``, ``8` `};` `    ``// Driver Code``    ``public` `static` `void` `main(String[] args)``    ``{``        ``List list = Arrays.asList(arr);``        ``sortBasedOnFrequencyAndValue(list);``    ``}``  ` `    ``// Compare Function``    ``public` `static` `void``    ``sortBasedOnFrequencyAndValue(List list)``    ``{``        ``int` `n = arr.length;``        ``final` `HashMap mapCount``            ``= ``new` `HashMap();``        ``final` `HashMap mapIndex``            ``= ``new` `HashMap();``        ``for` `(``int` `i = ``0``; i < n; i++) {``            ``if` `(mapCount.containsKey(arr[i])) {``                ``mapCount.put(arr[i],``                             ``mapCount.get(arr[i]) + ``1``);``            ``}``            ``else` `{``                ``mapCount.put(arr[i],``1``); ``// Map to capture Count of elements``                ``mapIndex.put(arr[i],i); ``// Map to capture 1st occurrence of elements``            ``}``        ``}` `        ``Collections.sort(list, ``new` `Comparator() {``            ``public` `int` `compare(Integer n1, Integer n2)``            ``{``                ``int` `freq1 = mapCount.get(n1);``                ``int` `freq2 = mapCount.get(n2);``                ``if` `(freq1 != freq2) {``                    ``return` `freq2 - freq1;``                ``}``                ``else` `{``                    ``return` `mapIndex.get(n1)``                        ``- mapIndex.get(``                            ``n2); ``// Elements with Lesser``                                 ``// Index gets Higher``                                 ``// Priority``                ``}``            ``}``        ``});``        ``System.out.println(list);``    ``}``}`

## Python3

 `# Python program for above approach` `from` `collections ``import` `defaultdict` `# Sort by Frequency`  `def` `sortByFreq(arr, n):``    ``# arr -> Array to be sorted``    ``# n   -> Length of Array` `    ``# d is a hashmap(referred as dictionary in python)``    ``d ``=` `defaultdict(``lambda``: ``0``)``    ``for` `i ``in` `range``(n):``        ``d[arr[i]] ``+``=` `1` `    ``# Sorting the array 'arr' where key``    ``# is the function based on which``    ``# the array is sorted``    ``# While sorting we want to give``    ``# first priority to Frequency``    ``# Then to value of item``    ``arr.sort(key``=``lambda` `x: (``-``d[x], x))` `    ``return` `(arr)`  `# Driver Function``if` `__name__ ``=``=` `"__main__"``:``    ``arr ``=` `[``2``, ``5``, ``2``, ``6``, ``-``1``, ``9999999``, ``5``, ``8``, ``8``, ``8``]``    ``n ``=` `len``(arr)``    ``solution ``=` `sortByFreq(arr, n)``    ``print``(``*``solution)`

## C#

 `// C# program to implement the approach``using` `System;``using` `System.Collections.Generic;` `public` `class` `GFG {` `  ``static` `int``[] arr;` `  ``// Compare Function``  ``public` `static` `void``    ``sortBasedOnFrequencyAndValue(List<``int``> list)``  ``{``    ``int` `n = arr.Length;``    ``Dictionary<``int``, ``int``> mapCount``      ``= ``new` `Dictionary<``int``, ``int``>();``    ``Dictionary<``int``, ``int``> mapIndex``      ``= ``new` `Dictionary<``int``, ``int``>();``    ``for` `(``int` `i = 0; i < n; i++) {``      ``if` `(mapCount.ContainsKey(arr[i])) {``        ``mapCount[arr[i]]++;``      ``}``      ``else` `{``        ``mapCount[arr[i]]``          ``= 1; ``// Map to capture Count of elements``        ``mapIndex[arr[i]]``          ``= i; ``// Map to capture 1st occurrence of``        ``// elements``      ``}``    ``}` `    ``list.Sort(``      ``(``int` `n1, ``int` `n2) =>``      ``mapCount[n1] != mapCount[n2]``      ``? mapCount[n2].CompareTo(mapCount[n1])``      ``: mapIndex[n1].CompareTo(mapIndex[n2])``      ``// Elements with Lesser``      ``// Index gets Higher``      ``// Priority``    ``);` `    ``foreach``(``var` `i ``in` `list) Console.Write(i + ``" "``);``  ``}` `  ``// Driver Code``  ``public` `static` `void` `Main(``string``[] args)``  ``{``    ``arr = ``new` `int``[] { 2,       5, 2, 6, -1,``                     ``9999999, 5, 8, 8, 8 };``    ``List<``int``> list = ``new` `List<``int``>(arr);``    ``sortBasedOnFrequencyAndValue(list);``  ``}``}` `// This code is contributed by phasing17`

## Javascript

 ``

Output

`8 8 8 2 2 5 5 6 -1 9999999 `

This can also be solved by Using two maps, one for array element as an index and after this second map whose keys are frequency and value are array elements.

METHOD 3(Use BST and Sorting)

• Insert elements in BST one by one and if an element is already present then increment the count of the node. The node of the Binary Search Tree (used in this approach) will be as follows.

## C

 `struct` `tree {``    ``int` `element;``    ``int` `first_index ``/*To handle ties in counts*/``        ``int` `count;``} BST;`

## Java

 `static` `class` `tree {``    ``int` `element;``    ``int` `first_index; ``/*To handle ties in counts*/``    ``int` `count;``}``tree BST = ``new` `tree();` `// This code is contributed by gauravrajput1`

## Python3

 `# Python code to implement the approach``class` `Tree:``    ``element ``=` `None``    ` `    ``# to handle ties``    ``first_index ``=` `None``    ``count ``=` `None` `BST ``=` `Tree()` `# This code is contributed by phasing17`

## C#

 `public` `class` `tree {``    ``public` `int` `element;``    ``public` `int` `first_index; ``/* To handle ties in counts */``    ``public` `int` `count;``}``tree BST = ``new` `tree();` `// This code is contributed by gauravrajput1`

## Javascript

 `// JS code to implement the approach` `class tree {``     ``constructor()``     ``{``         ``this``.element;``         ``this``.first_index; ``//To handle ties in counts``         ``this``.count;``     ``}``     ` `};` `// This code is contributed by phasing17`

• Store the first indexes and corresponding counts of BST in a 2D array.
• Sort the 2D array according to counts (and use indexes in case of tie).

Time Complexity: O(nlogn) if a Self Balancing Binary Search Tree is used. This is implemented in Set 2.
https://youtu.be/NBXf9vCksuM

#### METHOD 4: (Heap-Based Solution)

ALGORITHM:

1. Take the arr and use unordered_map to have VALUE : FREQUENCY Table
2. Then make a HEAP such that high frequency remains at TOP and when frequency is same, just keep in ascending order (Smaller at TOP)
3. Then After full insertion into Heap.
4. Pop one by one and copy it into the Array.

WORKING CODE:

## C++

 `#include ``using` `namespace` `std;``#define ppi pair` `/*IMPORTANT: comparator works in prority_queue only if they are a class which has``operator() overloaded in it (got this from stackoverflow) */``class` `Compare {``    ``public``:``        ``bool` `operator()(pair<``int``, ``int``> a, pair<``int``, ``int``> b)``        ``{``              ``//b is at top and a is at bottom - have that in mind``            ``if``(a.first == b.first) ``//when freq same``                ``return` `a.second > b.second; ``//smaller val stays at top``            ``return` `a.first < b.first; ``// higher freq stays at top``        ``}``};` `void` `solve(vector<``int``> &arr){``    ``int` `N = arr.size();``    ``unordered_map<``int` `,``int``> mpp; ``// val, freq``    ``for``(``int` `a : arr){``        ``mpp[a]++;``    ``}``    ``//max heap - as max wise freq elements is what needed``    ``priority_queue, Compare> maxH;``    ` `    ``for``( ``auto` `m : mpp){``        ``maxH.push({m.second, m.first}); ``// freq, val``    ``}``    ``//now the max freq is at TOP of MAX heap``    ` `    ``int` `i=0; ``// to maintain index to copy``    ``while``(maxH.size()>0){``        ``int` `val = maxH.top().second; ``//val``        ``int` `freq = maxH.top().first; ``//freq``        ` `        ``while``(freq-- ){``            ``//freq - those many times make a copy``            ``arr[i] = val;``            ``i++;``        ``}``        ``maxH.pop(); ``// heapify happens and next top freq ele goes up``    ``}``    ` `}` `int` `main()``{``    ``vector<``int``> vec{ 2, 5, 2, 8, 5, 6, 8, 8 };``    ``int` `n = vec.size();`` ` `    ``solve(vec);`` ` `    ``for` `(``int` `i = 0; i < n; i++)``        ``cout << vec[i] << ``" "``;``      ``cout<<``"\n"``;``    ``return` `0;``}` `//Code done by Balakrishnan R (rbkraj000)`

Output

`8 8 8 2 2 5 5 6 `

The above implementation has passed all the test cases in the practice section of GFG.

The code and approach is done by Balakrishnan R.

Time Complexity:

O(d*log(d)) (Dominating factor O(n+ 2*d*log(d)))

Reason:  O(n) (unordered map insertion- as 1 insertion takes O(1)) + O(d*log(d)) (Heap insertion – as one insertion is log N complexity) + O(d*log(d)) (Heap Deletion – as one pop takes Log N complexity)

Here d = No. of Distinct Elements, n = Total no. of elements (size of input array). (Always d<=n  depends on array)

Extra Space Complexity:

O(d)  => As heap and map is created.

Set 2:
Sort elements by frequency | Set 2