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To estimate the scale of the online chess service, we need to consider factors such as the number of users, daily active users (DAU), number of games played per day, and average moves per game. Based on the provided assumptions of 10 million users, 1 million DAU, 2 million games played per day, and an average of 30 moves per game, we can perform the following calculations:
Now, let's calculate the scale of the system based on these numbers:
Total Games Played per Day:
Total Games Played per Day=DAU × Average Games per User per Day
Total Games Played per Day=1,000,000×2=2,000,000
Total Moves per Day:
Total Moves per Day=Total Games Played per Day × Average Moves per Game
Total Moves per Day=2,000,000 × 30=60,000,000
To estimate the size of the database required for saving moves, game outcomes, and user data, we need to consider the record size for each type of data and the total number of records generated per day. Let's break down the estimation for each type of data:
User Data:
User data typically includes information such as username, email, password hash, profile picture, and
other profile attributes.
Assuming an average record size of 1 KB per user, considering the additional overhead for indexing and metadata.
Total Size for User Data: Total Users×Average Record Size per User
=10,000,000×1 KB =10 GB
Moves and Game Outcomes:
Each move record includes information such as game ID, player ID, move details (e.g., starting and ending positions of the piece), timestamp, and move validation status.
Game outcome records include game ID, player IDs, outcome (win, lose, draw), timestamp, and other metadata.
Assuming an average record size of 1 KB per move or game outcome record.
Total Size for Moves and Game Outcomes:
Total Moves per Day×Average Record Size per Move
=60,000,000×1 KB
=60 GB
Adding the sizes for user data and moves/game outcomes, we get an estimated total size of:
Total Database Size=Size for User Data + Size for Moves and Game Outcomes
=10 GB+60 GB
=70 GB
So, the estimated size of the database required for saving moves, game outcomes, and user data is approximately 70 GB.
For the online chess service, we need to define a set of APIs to support various functionalities such as user management, game operations, move validation, and real-time updates. Below are the expected APIs from the system:
These APIs provide the necessary functionalities for users to interact with the online chess service, including managing their accounts, playing games, validating moves, receiving real-time updates, and accessing game-related information.
User and Game Data
In the context of the online chess service, we can partition the data efficiently to improve performance, scalability, and manageability. Here's how we can approach partitioning for the entities in the SQL database:
For scaling the online chess service, we can employ the following scaling strategies:
By combining vertical and horizontal scaling strategies and implementing efficient partitioning techniques, we can ensure that the online chess service can handle increased load, maintain performance, and provide a seamless gaming experience for users.
Explain how the request flows from end to end in your high level design. Also you could draw a sequence diagram using the diagramming tool to enhance your explanation...
Dig deeper into 2-3 components and explain in detail how they work. For example, how well does each component scale? Any relevant algorithm or data structure you like to use for a component? Also you could draw a diagram using the diagramming tool to enhance your design...
Explain any trade offs you have made and why you made certain tech choices...
Try to discuss as many failure scenarios/bottlenecks as possible.
What are some future improvements you would make? How would you mitigate the failure scenario(s) you described above?