Designing a system for high frequency rank computation such as a leaderboard system in gaming involves dealing with lots of real-time data. The right choice of data structure and correct usage of caching and indexing are crucial in such a scenario.
Key points to consider:
1. Real Time Update: The data needs to update in real time as it is a gaming environment.
2. Data Scaling: With an increasing number of players and games, the data handling should scale proportionally.
Here’s a suggestion on how to design such a system:
1. **Data Structure:**
To handle the data, a Binary Search Tree (BST) would be fit. In BSTs, each node contains players with score less than itself in the left subtree and with score bigger than itself in the right subtree.
Let’s assume the BST holds players where each node is:
[playerID, playerScore, Rank, leftSubTreeSize, rightSubTreeSize]; the data structure itself will intrinsically have the ranking information.
2. **Real-Time Update:**
Any time a player’s score updates, we delete that player’s node and reinsert the node with the new score. To ensure the process is efficient, we need to maintain a Hash Map which will map playerID to the respective TreeNode.
3. **Rank Calculation:**
Once the BST is ready, you can compute the rank of a player in O(log n) time. When you search for a player (starting at the root), at each node:
- If the node score is equal to the player score, return the size of right subtree + 1 (Rank starts from 1 and not 0)
- If the node score is greater than the player score, go left in the tree 1. If the node score is less than the player score, go right and add the size of the right subtree along with the root; to a RankCounter.
Furthermore, consider the following:
4. **Use of Caching:**
Cache the top players and ranks so that it doesn’t need to compute again and again. This will reduce the computation time drastically.
5. **Database and Indexing:**
Use a database like MongoDB to store player scores and their data. Use indexing on scores to make the operation faster.
6. **Concurrency Controls:**
As it’s a high frequency system, there should be appropriate locks in place to handle multiple players updating their scores at the same time.
Note: This solution assumes scores are unique for simplicity. If the scores are not unique, each node of the BST can be modified to store a list of players with the same score, or use some kind of tie-breaking rule.