Group Betting Cache Locking for Low-Latency, Conflict-Free Updates
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Solution Overview
Problem
Existing online betting systems face challenges in allowing collective group bets due to regulatory requirements that mandate individual bet placement, leading to inefficiencies and increased database load from repeated table access, which affects user experience and data integrity.
Innovation Solution
A group betting system utilizing a distributed cache to store draft group bet records and employing a lock mechanism to manage concurrent modifications, ensuring fast and conflict-free operations, with individual bets being placed on behalf of users post-validation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If a traditional database is used to store group bet records, then data persistence and reliability are ensured, but database load increases and latency increases due to repeated table access
Solution Approach 1:
The system segments the database access pattern by introducing a distributed cache layer that stores frequently accessed group bet records. This separates the hot data (recent group bets) from the persistent storage, allowing fast access to commonly modified records while reducing overall database load.
Solution Approach 2:
A distributed cache acts as an intermediary between the user devices and the database. The cache receives requests, serves frequently accessed group bet records from memory, and only queries the database when necessary, thereby reducing direct database access and latency.
2Ease of operation
If multiple users simultaneously modify group bet records, then user experience is improved, but data corruption occurs due to concurrent access conflicts
Solution Approach 1:
The system performs preliminary actions by acquiring a lock on the group bet record before allowing modifications. This ensures that only one user can modify the record at a time, preventing data corruption while still allowing concurrent users to access and modify different records simultaneously.
Solution Approach 2:
The lock mechanism acts as an intermediary that coordinates concurrent access to group bet records. It allows multiple users to access the system simultaneously but ensures that only one user can modify a specific record at a time, preventing data corruption while maintaining ease of operation.
3Adaptability or versatility
If individual bet placement is enforced by regulation, then compliance is ensured, but system complexity increases when implementing group bet functionality
Solution Approach 1:
The system segments the group bet functionality into distinct components: a distributed cache for storing group bet records, a lock mechanism for managing concurrent access, and an individual bet placement engine that processes bets separately for each user. This modular approach maintains compliance while managing complexity.
Solution Approach 2:
The distributed cache and lock mechanism serve as intermediaries that simplify the implementation of group bets while maintaining individual bet placement. These components handle the complexity of concurrent access and data consistency, allowing the system to provide group functionality without increasing operational complexity.
Data Source
AI summary
Techniques are disclosed comprising receiving, at a server, an action request from a first user device to perform an action in relation to a group bet record stored in a group bet distributed cache, the group bet record being associated with the first user device and at least one additional user device. The techniques may transmit, from the server, a get request to the group bet distributed cache to retrieve the group bet record. The group bet record and a lock may be received at the server from the group bet distributed cache, based on the group bet distributed cache having determined that the lock is available. The action may be performed on the group bet record according to the action request.