Design a data structure that supports all following operations in average O(1) time.

Note: Duplicate elements are allowed.

  1. insert(val): Inserts an item val to the collection.
  2. remove(val): Removes an item val from the collection if present.
  3. getRandom: Returns a random element from current collection of elements. The probability of each element being returned is linearly related to the number of same value the collection contains.

Example:

// Init an empty collection.
RandomizedCollection collection = new RandomizedCollection(); // Inserts 1 to the collection. Returns true as the collection did not contain 1.
collection.insert(1); // Inserts another 1 to the collection. Returns false as the collection contained 1. Collection now contains [1,1].
collection.insert(1); // Inserts 2 to the collection, returns true. Collection now contains [1,1,2].
collection.insert(2); // getRandom should return 1 with the probability 2/3, and returns 2 with the probability 1/3.
collection.getRandom(); // Removes 1 from the collection, returns true. Collection now contains [1,2].
collection.remove(1); // getRandom should return 1 and 2 both equally likely.
collection.getRandom();

Approach #1: C++.

class RandomizedCollection {
public:
/** Initialize your data structure here. */
RandomizedCollection() { } /** Inserts a value to the collection. Returns true if the collection did not already contain the specified element. */
bool insert(int val) {
auto result = m.find(val) == m.end(); m[val].push_back(nums.size());
nums.push_back(pair<int, int>(val, m[val].size() - 1)); return result;
} /** Removes a value from the collection. Returns true if the collection contained the specified element. */
bool remove(int val) {
if (!m.count(val)) return false;
else {
auto last = nums.back();
m[last.first][last.second] = m[val].back();
nums[m[val].back()] = last;
m[val].pop_back();
if (m[val].empty()) m.erase(val);
nums.pop_back();
return true;
}
} /** Get a random element from the collection. */
int getRandom() {
return nums[rand() % nums.size()].first;
}
private:
vector<pair<int, int>> nums;
unordered_map<int, vector<int>> m;
}; /**
* Your RandomizedCollection object will be instantiated and called as such:
* RandomizedCollection obj = new RandomizedCollection();
* bool param_1 = obj.insert(val);
* bool param_2 = obj.remove(val);
* int param_3 = obj.getRandom();
*/

  

In this solution we use vector<pair<int, int>> nums to resoter the numbers in the set,  using the unordered_map<int, vector<int>> to restore the position of the number.

Runtime: 36 ms, faster than 82.83% of C++ online submissions for Insert Delete GetRandom O(1) - Duplicates allowed.

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