What to do if Redis lacks memory leads to performance degradation?

Redis insufficient memory can lead to performance degradation. Solution: Open source: increase memory or evaluate actual requirements, shard or cluster data. Throttle: Choose the right type, clean the data regularly, and use the compression algorithm.

Redis lacks memory and performance plummets? This is an old question, let me tell you carefully. If you have no experience and start adjusting parameters directly, it is likely that the more you adjust the parameters, it will get worse and worse, and even cause the entire system to collapse.

The root cause of this problem is that Redis's architecture determines its extremely high dependence on memory. It fills all data in memory, and memory is its lifeblood. If there is not enough memory, the data must be "driven" out. This "driven" process is the culprit of performance degradation. Imagine that your living room is too small and full of things. It is difficult to find something. Can it be efficient? The same goes for Redis.

Therefore, to solve the memory shortage, we must start from both "increasing revenue and reducing expenditure".

Open source: The most direct way to increase the available memory of Redis is to add memory sticks. But this is not a panacea. Large memory means high costs, and it is not possible to solve the problem by adding it without limit. You have to evaluate based on the actual situation. Don’t just get a few hundred Gs as soon as you come up, that’s purely a waste. More importantly, you have to figure out what memory Redis is consuming in order to be targeted.

You can use the INFO memory command to view Redis's memory usage and see which data structures occupy the most memory. If you find that some key expiration time is unreasonable, resulting in a large amount of expired data accumulation, then quickly adjust the expiration strategy. Also, if your data volume is too large and Redis itself can't stand it, then you have to consider sharding or clustering to distribute the data to multiple Redis servers. Don’t expect single-player Redis to solve all problems. It’s like pulling a truckload of bricks with a bicycle. Can it work?

Throttle: Reduce Redis' memory consumption, this is the technical job. First, you have to carefully check your data structure to choose the most appropriate type. For example, if your data is a simple key-value pair, use string type, and don't use Hash or List, which will increase memory overhead. Secondly, you have to clean up unnecessary data regularly. Although Redis's expiration mechanism is easy to use, it must be configured reasonably, and don't expect it to automatically handle all problems. You can manually delete some unused keys, or use some automation tools to clean up expired data. Finally, don't forget to compress the data. Redis supports a variety of data compression algorithms, and choosing the right algorithm can effectively reduce memory consumption.

To put it bluntly, this is like the manager's financial management. Opening up sources is to increase revenue, and reducing expenditure is to reduce expenditure. Both must be taken into account in order to truly solve the problem.

Code Example (Python): I won't write any complicated code for you in this part, because solving Redis memory problems mainly depends on command line operations and configuration file adjustments, rather than writing any Python scripts. But I will give you a simple Python script to monitor Redis memory usage:

 <code class="python">import redis r = redis.Redis(host='localhost', port=6379, db=0) info = r.info('memory') print(f"Used memory: {info['used_memory']}") print(f"Used memory human-readable: {info['used_memory_human']}") print(f"Memory peak: {info['used_memory_peak']}") print(f"Memory peak human-readable: {info['used_memory_peak_human']}")</code>

Remember, this script is just a monitoring tool. It cannot solve memory problems and can only help you discover problems. The real solution depends on your in-depth understanding and actual operation of Redis. Don’t forget to read more Redis’s official documents, that is the most authoritative information. Finally, don’t be afraid of getting stuck in pitfalls. Only by practicing more can you accumulate experience. Memory problems are not that easy to solve, so be patient!

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