This article explains various techniques for detecting and preventing duplicate backend requests—using unique request IDs, business parameter hashing, MD5 summaries, and Redis SETNX with expiration—providing Java code examples and a complete deduplication utility.
This article explains why duplicate requests—especially write operations—can cause serious issues, outlines common duplication scenarios, and presents a complete server‑side solution using unique request IDs with Redis as well as business‑parameter hashing with MD5 to achieve reliable idempotency in Java back‑end systems.
This article explains why duplicate requests—especially write operations—can cause serious issues, outlines common duplication scenarios, and provides a comprehensive server‑side solution using unique request IDs, parameter hashing with MD5, and Redis SETNX with expiration to reliably detect and block repeats.
The article examines why duplicate request filtering is a complex backend problem, explores various causes, discusses client‑side and server‑side strategies such as request IDs, Redis checks, distributed locks, and request signing, and highlights practical pitfalls and security considerations.
This article explains why duplicate requests—especially write operations—can cause serious issues, outlines common causes such as replay attacks and client retries, and provides a comprehensive server‑side solution using unique request IDs, Redis, and MD5‑based parameter deduplication with Java code examples.
The article explains how to prevent harmful duplicate write requests on the server side by using unique request identifiers with Redis, computing MD5 digests of sorted JSON parameters, excluding volatile fields, and provides a reusable Java helper class with example code and logs.
This guide explains the scenarios that cause duplicate HTTP requests in web applications, demonstrates two Axios cancellation techniques, and shows how to encapsulate the logic in a reusable module with request tracking, interceptor integration, npm linking, and open‑source contribution steps.
This article explains how to prevent and gracefully handle duplicate requests on the server side by using unique request IDs with Redis, generating MD5 digests of request parameters, and provides a reusable Java helper class with code examples and testing logs.
This article explains why duplicate requests occur, defines idempotency, and presents common backend strategies—such as unique indexes, optimistic locks, anti‑repeat tokens, anti‑repeat tables, and distributed locks—illustrated with an order‑processing workflow.
