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This article explains why duplicate message consumption occurs in Kafka, outlines the underlying confirmation and consumer failure issues, and presents idempotent design strategies such as deduplication tables and code examples to ensure reliable processing.
This article explains the causes of duplicate message consumption in RabbitMQ, demonstrates how to reproduce the issue with a 10,000‑message test, and provides three practical solutions using unique IDs stored in Redis to ensure idempotent processing in Java Spring applications.
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