PrevNext
Not Frequent
 0/15

More Operations on Sorted Sets

Authors: Darren Yao, Benjamin Qi, Andrew Wang

Contributor: Aadit Ambadkar

Finding the next element smaller or larger than a specified key in a set, and using iterators with sets.

Edit This Page

C++

Resources
IUSACO
4.4 - Sets & Maps

module is based off this

CP2
2.2.2 - Non-Linear Data Structures

see decription of BSTs and heaps

Java

Resources
IUSACO
4.3 - Sets & Maps

module is based off this

CP2
2.2.2 - Non-Linear Data Structures

see decription of BSTs and heaps


In sets and maps where keys (or elements) are stored in sorted order, accessing or removing the next key higher or lower than some input key k is supported.

Keep in mind that insertion and deletion will take O(log⁡N)\mathcal{O}(\log N) time for sorted sets, which is more than the average O(1)\mathcal{O}(1) insertion and deletion for unordered sets, but less than the worst case O(N)\mathcal{O}(N) insertion and deletion for unordered sets.

Using Iterators

In Bronze, we avoided discussion of any set operations involving iterators.

C++

Resources
CPH
4.4 - Set Iterators

Java

In Java, iterators are helpful for looping through sets.

Iterators used with HashSet would yield the elements in random order:

Set<Integer> set = new HashSet<Integer>();
set.add(1);
set.add(3);
set.add(0);
set.add(-2);
Iterator it = set.iterator();
while (it.hasNext()) {
	Integer i = (Integer)it.next();
	System.out.print(i + " ");  // returns some random order
}

But with TreeSet the elements are in sorted order:

Set<Integer> set = new TreeSet<Integer>();
set.add(1);
set.add(3);
set.add(0);
set.add(-2);
Iterator it = set.iterator();
while (it.hasNext()) {
	Integer i = (Integer)it.next();
	System.out.print(i + " ");  // returns -2 0 1 3
}

Instead of creating an iterator and looping with it like in C++, Java provides a for-each loop which creates a hidden iterator and loops with it automatically:

Set<Integer> set = new TreeSet<Integer>();
set.add(1);
set.add(3);
set.add(0);
set.add(-2);
for (int i : set) {
	System.out.print(i + " ");  // returns -2 0 1 3
}

Warning!

You shouldn't modify sets when traversing it with set iterators like in any other iterators for Collections (this INCLUDES when using a for-each loop). The only modification possible is using the iterator remove() method which can only be used once before calling the next() method.

Sorted Sets

C++

The sorted std::set also supports:

  • lower_bound: returns an iterator to the least element greater than or equal to some element k.
  • upper_bound: returns an iterator to the least element strictly greater than some element k.
set<int> s;
s.insert(1);                        // [1]
s.insert(14);                       // [1, 14]
s.insert(9);                        // [1, 9, 14]
s.insert(2);                        // [1, 2, 9, 14]
cout << *s.upper_bound(7) << '\n';  // 9
cout << *s.upper_bound(9) << '\n';  // 14
cout << *s.lower_bound(5) << '\n';  // 9
cout << *s.lower_bound(9) << '\n';  // 9
cout << *s.begin() << '\n';         // 1
auto it = s.end();
cout << *(--it) << '\n';    // 14
s.erase(s.upper_bound(6));  // [1, 2, 14]

Warning!

Suppose that we replace s.upper_bound(7) with upper_bound(begin(s),end(s),7), which was the syntax that we used for vectors in the prerequisite module. This will still output the expected results, but its time complexity is linear in the size of the set s rather than logarithmic, so make sure to avoid it!

Java

TreeSets in Java allow for a multitude of additional operations:

  • first(): returns the lowest element in the set
  • last(): returns the greatest element in the set
  • lower(E v): returns the greatest element strictly less than v
  • floor(E v): returns the greatest element less than or equal to v
  • higher(E v): returns the least element strictly greater than v
  • ceiling(E v): returns the least element greater than or equal to v
TreeSet<Integer> set = new TreeSet<Integer>();
set.add(1);                          // [1]
set.add(14);                         // [1, 14]
set.add(9);                          // [1, 9, 14]
set.add(2);                          // [1, 2, 9, 14]
System.out.println(set.higher(7));   // 9
System.out.println(set.higher(9));   // 14
System.out.println(set.lower(5));    // 2
System.out.println(set.first());     // 1
System.out.println(set.last());      // 14
set.remove(set.higher(6));           // [1, 2, 14]
System.out.println(set.higher(23));  // ERROR, no such element exists

One limitation of sorted sets is that we can't efficiently access the kthk^{th} largest element in the set, or find the number of elements in the set greater than some arbitrary xx. In C++, these operations can be handled using a data structure called an order statistic tree.

Sorted Maps

C++

The ordered map also allows:

  • lower_bound: returns the iterator pointing to the lowest entry not less than the specified key
  • upper_bound: returns the iterator pointing to the lowest entry strictly greater than the specified key respectively.
map<int, int> m;
m[3] = 5;     // [(3, 5)]
m[11] = 4;    // [(3, 5); (11, 4)]
m[10] = 491;  // [(3, 5); (10, 491); (11, 4)]
cout << m.lower_bound(10)->first << " " << m.lower_bound(10)->second
     << '\n';  // 10 491
cout << m.upper_bound(10)->first << " " << m.upper_bound(10)->second
     << '\n';  // 11 4
m.erase(11);   // [(3, 5); (10, 491)]
if (m.upper_bound(10) == m.end()) {
	cout << "end" << endl;  // Prints end
}

Java

The ordered map additionally supports firstKey / firstEntry and lastKey / lastEntry, returning the lowest key/entry and the highest key/entry, as well as higherKey / higherEntry and lowerKey / lowerEntry, returning the lowest key/entry strictly higher than the specified key, or the highest key/entry strictly lower than the specified key.

TreeMap<Integer, Integer> map = new TreeMap<Integer, Integer>();
map.put(3, 5);                           // [(3, 5)]
map.put(11, 4);                          // [(3, 5); (11, 4)]
map.put(10, 491);                        // [(3, 5); (10, 491); (11, 4)]
System.out.println(map.firstKey());      // 3
System.out.println(map.firstEntry());    // (3, 5)
System.out.println(map.lastEntry());     // (11, 4)
System.out.println(map.higherEntry(4));  // (10, 491)
map.remove(11);                          // [(3, 5); (10, 491)]
System.out.println(map.lowerKey(4));     // 3
System.out.println(map.lowerKey(3));     // ERROR

Multisets

A multiset is a sorted set that allows multiple copies of the same element.

C++

In addition to all of the regular set operations,

  • the count() method returns the number of times an element is present in the multiset. However, this method takes time linear in the number of matches so you shouldn't use it in a contest.
  • To remove a value once, use ms.erase(ms.find(val)).
  • To remove all occurrences of a value, use ms.erase(val).

Warning!

Using ms.erase(val) erases all instances of val from the multiset. To remove one instance of val, use ms.erase(ms.find(val))!

multiset<int> ms;
ms.insert(1);                  // [1]
ms.insert(14);                 // [1, 14]
ms.insert(9);                  // [1, 9, 14]
ms.insert(2);                  // [1, 2, 9, 14]
ms.insert(9);                  // [1, 2, 9, 9, 14]
ms.insert(9);                  // [1, 2, 9, 9, 9, 14]
cout << ms.count(4) << '\n';   // 0
cout << ms.count(9) << '\n';   // 3
cout << ms.count(14) << '\n';  // 1
ms.erase(ms.find(9));
cout << ms.count(9) << '\n';  // 2
ms.erase(9);
cout << ms.count(9) << '\n';  // 0

Java

While there is no multiset in Java, we can implement one using the TreeMap from values to their respective frequencies. We declare the TreeMap implementation globally so that we can write functions for adding and removing elements from it. The first, last, higher, and lower operations still function as intended; just use firstKey, lastKey, higherKey, and lowerKey respectively.

static TreeMap<Integer, Integer> multiset = new TreeMap<Integer, Integer>();


public static void main(String[] args) { ... }


static void add(int x) {
	if (multiset.containsKey(x)) {
		multiset.put(x, multiset.get(x) + 1);
	} else {
		multiset.put(x, 1);
	}

Priority Queues

Warning!

Priority queues are not implemented in the same way as sets and multisets, but they are included in this section because the operations that they perform can also be performed with sets.

Resources
CSA
Heaps

A priority queue (or heap) supports the following operations: insertion of elements, deletion of the element considered highest priority, and retrieval of the highest priority element, all in O(log⁡N)\mathcal{O}(\log N) time according to the number of elements in the priority queue. Priority queues are simpler and faster than sets, so you should use them instead whenever possible.

C++

C++

priority_queue<int> pq;
pq.push(7);                // [7]
pq.push(2);                // [2, 7]
pq.push(1);                // [1, 2, 7]
pq.push(5);                // [1, 2, 5, 7]
cout << pq.top() << endl;  // 7
pq.pop();                  // [1, 2, 5]
pq.pop();                  // [1, 2]
pq.push(6);                // [1, 2, 6]

Java

Java

In Java, we delete and retrieve the element of lowest rather than highest priority.

PriorityQueue<Integer> pq = new PriorityQueue<Integer>();
pq.add(7);                      // [7]
pq.add(2);                      // [7, 2]
pq.add(1);                      // [7, 2, 1]
pq.add(5);                      // [7, 5, 2, 1]
System.out.println(pq.peek());  // 1
pq.poll();                      // [7, 5, 2]
pq.poll();                      // [7, 5]
pq.add(6);                      // [7, 6, 5]

Introductory Problems

StatusSourceProblem NameDifficultyTags
CSES
Concert Tickets
Easy
Show TagsSorted Set
CF
Cellular Network
Easy
Show TagsSorted Set
CSES
Traffic Lights
Normal
Show TagsSorted Set
CSES
Room Allocation
Normal
Show TagsSorted Set

Harder Example - Bit Inversions

Warning!

Problems marked as "Hard" or beyond in this module would likely be too difficult to appear on a USACO Silver contest.

Bit Inversions
CSES - Hard

Focus Problem – try your best to solve this problem before continuing!

View Internal Solution

Solution

We'll use iterators extensively.

Let the bit string be s=s0s1s2…,sn−1s=s_0s_1s_2\ldots,s_{n-1}. In the set dif, we store all indices ii such that si≠si−1s_i\neq s_{i-1} (including i=0i=0 and i=ni=n). If the elements of dif are 0=dif1<dif2<⋯<difk=n0=dif_1<dif_2<\cdots<dif_k=n, then the longest length is equal to

max⁡(dif2−dif1,dif3−dif2,…,difk−difk−1).\max(dif_2-dif_1,dif_3-dif_2,\ldots,dif_k-dif_{k-1}).

We can store each of these differences in a multiset ret; after each inversion, we'll need to output the maximum element of ret.

Inverting a bit at a 0-indexed position x corresponds to inserting x into dif if it not currently present or removing x if it is, and then doing the same with x+1. Whenever we insert or remove an element of dif, we should update ret accordingly.

C++

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


#define sz(x) (x).size()


string s;
int m;
set<int> dif;
multiset<int> ret;

Java

Warning!

Java solutions are too slow for the CSES. Use C++ instead to get AC.

import java.io.*;
import java.util.*;


class BitInversion {
	public static TreeMap<Integer, Integer> ret =
	    new TreeMap<Integer, Integer>();
	public static String s;
	public static int m;
	public static Set<Integer> dif = new TreeSet<Integer>();

Note that multiset has a high constant factor, so replacing ret with a priority queue and an array that stores the number of times each integer occurs in the priority queue reduces the runtime by a factor of 2.

C++

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


#define sz(x) (int)(x).size()


string s;
int m;
set<int> dif;
priority_queue<int> ret;
int cnt[200005];

Java

import java.io.*;
import java.util.*;


class BitInversion {
	public static PriorityQueue<Integer> pq =
	    new PriorityQueue<Integer>(Collections.reverseOrder());
	public static String s;
	public static int m;
	public static TreeSet<Integer> dif = new TreeSet<Integer>();
	public static int cnt[];

Harder Problems

StatusSourceProblem NameDifficultyTags
Silver
Milk Measurement
Normal
Show TagsSorted Set
Silver
Convention II
Normal
Show TagsSorted Set
CF
William and Robot
Normal
Show TagsGreedy, Sorted Set, Sorting
CF
Array Destruction
Normal
Show TagsGreedy, Multiset, Sorting
CF
Covered Points Count
Normal
Show TagsCoordinate Compression, Prefix Sums, Sorted Set, Sorting
CF
Survival of the Weakest (easy version)
Hard
Show TagsBinary Search, Sorted Set
Gold
Snow Boots
Hard
Show TagsLinked List, Sorted Set
AC
Packing Under Range Regulations
Hard
Show TagsGreedy, Sorted Set
CF
Mahmoud & Ehab & Function
Very Hard
Show TagsSorted Set
CF
Tournament
Insane
Show TagsSorted Set

Module Progress:

Join the USACO Forum!

Stuck on a problem, or don't understand a module? Join the USACO Forum and get help from other competitive programmers!

Join Forum
PrevNext