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

Comparison of Redis Queue and MySQL Database Stability: Exploring the Cause of Redis Data Loss

Based on the actual development experience under the PHP7.2 and ThinkPHP framework, this paper compares and analyzes the stability differences in the construction queue using MySQL and Redis. Practice shows that the MySQL-based architecture data is stable and reliable, while the Redis-based architecture has the risk of data loss.

MySQL-based architecture

Our MySQL architecture is designed as follows:

1. Producer: A large amount of data is first written to the MySQL intermediate table, and the unique index is used to ensure data uniqueness.
2. Consumer: Multiple consumers poll to read MySQL intermediate table data, and after processing, the result is written to the MySQL result table.

The architecture operates stably and no data loss was found.

Redis-based architecture

Architectural design based on Redis:

1. Producer: The data first enters the Redis collection (avoid duplicate data), and then joins the Redis queue after confirming that it is correct.
2. Consumer: The consumer reads data from the Redis queue, writes the results to the MySQL result table after processing, and deletes the processed data from the Redis collection.

However, this architecture has problems with data loss and it is difficult to locate the cause.

Analysis of the causes of Redis data loss

Redis data loss does not occur when it is running normally, but is related to the persistence mechanism (RDB and AOF) and the atomicity of the operations. Data loss is only possible when Redis restarts.

The instability of Redis queues mainly stems from the non-atomicity of their operations. Unlike the ACID feature and strong consistency transaction processing of MySQL, Redis operations are performed step by step, and any step may error.

Specifically for our Redis architecture:

• Data into Redis collection and queue: Are both steps successfully executed?
• Consumer operation: fetching data from the queue, deleting data from the collection, processing data, writing to the MySQL result table. Any failure of any step may lead to data loss. For example, after data is deleted from the collection, an error occurs during the processing process and ultimately cannot be written to MySQL.

How to troubleshoot Redis data loss?

In order to effectively locate the cause of data loss, it is recommended to add detailed logging to track the execution status of each step. For example, record data incoming, dequeuing, processing, and writing to each link of the database. In this way, even if data is lost, the root cause of the problem can be found through log analysis.

Summarize

Redis-based queue architecture is prone to data loss due to its step-by-step operation. The transaction characteristics of MySQL ensure the consistency and stability of data. To avoid Redis data loss, be sure to carefully check each operation step and monitor and troubleshoot through a complete logging system.

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