Distributed Request Cache for Idempotency in Multi-Server Systems
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Solution Overview
Problem
In a multi-client, multi-server environment, existing idempotency features that rely on a central data store create bottlenecks and overhead, especially as the number of clients and servers increases, due to the complexity of duplicate request detection and the risk of duplicate processing when resending requests.
Innovation Solution
A system that reduces reliance on a central data store by using a request-cache local to each server, where requests with an idempotence-risk flag are processed and stored, and client identifiers are managed to ensure uniqueness, allowing asynchronous storage and eviction of requests, thereby minimizing the need for central data store access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a central data store is used for duplicate request detection, then idempotency is maintained across multiple servers, but system scalability is hindered due to bottlenecks
Solution Approach 1:
The patent divides the centralized duplicate detection mechanism into distributed local caches at each server instance. Each server maintains its own request history in local memory, eliminating the need for a centralized data store and allowing independent processing without inter-server coordination bottlenecks.
Solution Approach 2:
The patent extracts the duplicate detection functionality from the central data store and implements it locally at each server using in-memory caching. This removes the central coordination bottleneck while maintaining idempotency through local request tracking.
2Reliability
If duplicate detection is implemented across all clients and servers, then request uniqueness is ensured, but system complexity increases significantly
Solution Approach 1:
Each server instance independently manages its own request tracking through local caching, without requiring complex inter-server communication or centralized coordination. The system serves itself by distributing the detection logic across all server instances.
Solution Approach 2:
The patent creates copies of the request tracking mechanism at each server instance rather than using a single centralized store. Each server maintains a local copy of request history, enabling independent duplicate detection without complex synchronization.
3Reliability
If a central data store is locked for request tracking, then duplicate requests are prevented, but processing speed decreases due to locking overhead
Solution Approach 1:
The patent extracts the request tracking data from persistent storage and holds it in volatile memory at each server instance. This eliminates I/O operations and locking overhead associated with centralized data stores, dramatically improving processing speed.
Solution Approach 2:
The patent uses transient in-memory caches that are automatically discarded when server instances stop. These short-lived objects eliminate the need for persistent storage and complex locking mechanisms, providing fast duplicate detection without the overhead of centralized data management.
Data Source
AI summary
One embodiment of the present invention provides a system for reducing reliance on a central data store while maintaining idempotency in a multi-client, multi-server environment. During operation, the system receives a request to perform a transaction from a client at a server, wherein the request includes a request identifier and an idempotence-risk flag. The system then determines if the idempotence-risk flag is set. If not, the system: processes the request at the server to produce a result, and stores the request in a request-cache local to the server. The system also stores the request in the central data store, and returns the result to the client.