1244. Design A Leaderboard π
Description
Design a Leaderboard class, which has 3 functions:
addScore(playerId, score): Update the leaderboard by addingscoreto the given player's score. If there is no player with such id in the leaderboard, add him to the leaderboard with the givenscore.top(K): Return the score sum of the topKplayers.reset(playerId): Reset the score of the player with the given id to 0 (in other words erase it from the leaderboard). It is guaranteed that the player was added to the leaderboard before calling this function.
Initially, the leaderboard is empty.
Example 1:
Input: ["Leaderboard","addScore","addScore","addScore","addScore","addScore","top","reset","reset","addScore","top"] [[],[1,73],[2,56],[3,39],[4,51],[5,4],[1],[1],[2],[2,51],[3]] Output: [null,null,null,null,null,null,73,null,null,null,141] Explanation: Leaderboard leaderboard = new Leaderboard (); leaderboard.addScore(1,73); // leaderboard = [[1,73]]; leaderboard.addScore(2,56); // leaderboard = [[1,73],[2,56]]; leaderboard.addScore(3,39); // leaderboard = [[1,73],[2,56],[3,39]]; leaderboard.addScore(4,51); // leaderboard = [[1,73],[2,56],[3,39],[4,51]]; leaderboard.addScore(5,4); // leaderboard = [[1,73],[2,56],[3,39],[4,51],[5,4]]; leaderboard.top(1); // returns 73; leaderboard.reset(1); // leaderboard = [[2,56],[3,39],[4,51],[5,4]]; leaderboard.reset(2); // leaderboard = [[3,39],[4,51],[5,4]]; leaderboard.addScore(2,51); // leaderboard = [[2,51],[3,39],[4,51],[5,4]]; leaderboard.top(3); // returns 141 = 51 + 51 + 39;
Constraints:
1 <= playerId, K <= 10000- It's guaranteed that
Kis less than or equal to the current number of players. 1 <= score <= 100- There will be at most
1000function calls.
Solutions
Solution 1: Hash Table + Ordered List
Thinking
We update and reset a player's score and sum the top \(K\) scores. A thousand calls make a linear scan of all players unattractive. A hash map stores the score by \(playerId\); a sorted list holds the multiset of scores.
Adding a score removes the old value then inserts the new one; reset deletes symmetrically; \(top(K)\) sums the last \(K\) entries. The map locates a player in \(O(1)\); the sorted list updates in logarithmic time and exposes an ordered suffix.
We use a hash table \(d\) to record the scores of each player, and an ordered list \(rank\) to record the scores of all players.
When the addScore function is called, we first check if the player is in the hash table \(d\). If not, we add their score to the ordered list \(rank\). Otherwise, we first remove their score from the ordered list \(rank\), then add their updated score to the ordered list \(rank\), and finally update the score in the hash table \(d\). The time complexity is \(O(\log n)\).
When the top function is called, we directly return the sum of the first \(K\) elements in the ordered list \(rank\). The time complexity is \(O(K \times \log n)\).
When the reset function is called, we first remove the player from the hash table \(d\), then remove their score from the ordered list \(rank\). The time complexity is \(O(\log n)\).
The space complexity is \(O(n)\), where \(n\) is the number of players.
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