Comparison of Redis queues and MySQL stability: Why is Redis prone to data loss?

Comparison of Redis and MySQL queue stability: Exploring the reasons for Redis data loss

Under the PHP7.2 and ThinkPHP frameworks, it is crucial to choose the right data storage and processing solution. This paper compares the two queue architectures based on MySQL and Redis, and analyzes the reasons why Redis queues are prone to data loss.

Architecture comparison

1. MySQL architecture:

• Producer: Data is written to MySQL intermediate table, and data uniqueness is guaranteed using unique indexes.
• Consumer: Multiple consumers read data from the intermediate table loop, and then write it to the MySQL result table after processing.

2. Redis architecture:

• Producer: The data first enters the Redis collection (deduplication), and then enters the Redis queue.
• Consumer: Multiple consumers read data from the Redis queue, delete data from the Redis collection after reading, and write it to the MySQL result table after processing.

Practical application observation

The pure MySQL architecture runs stably and no data loss was found. However, the Redis architecture often has missing result data, and even if exception handling and log monitoring are added, it is difficult to locate the root cause of the problem.

Analysis of the causes of Redis data loss

Redis data loss usually occurs at restarts and is related to RDB and AOF persistence mechanisms. But even if it works properly, the Redis architecture may experience data loss:

1. Consistency difference: MySQL supports ACID characteristics to ensure strong consistency; Redis operations are carried out in steps, and errors may occur at each step.
2. Redis operation steps: data enters the Redis collection, enters the Redis queue, reads the consumer, deletes from the collection, processs data, and writes to the MySQL result table. Any error in any step may lead to data loss. For example, data has been deleted from the collection but processing fails, resulting in data loss.

Solution

The most effective way to solve the problem of Redis data loss is to strengthen logging. Record the start and end times of each operation step in detail to facilitate tracking the specific links of data loss.

Summary: The instability and data loss problems of Redis queues need to be solved through meticulous log analysis and code review. In the absence of code details, it is difficult to accurately locate the problem outside. It is recommended that developers add detailed logs at each step to quickly troubleshoot problems.

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