How to adjust Redis memory configuration parameters?

The following steps are required to adjust the Redis memory configuration parameters: Set the maxmemory parameter and limit the maximum memory available to Redis. Select maxmemory-policy based on the data type and access mode, specifying the processing policy when the memory reaches the upper limit. Monitor memory usage to ensure that Redis will not be abnormal due to insufficient memory. Selecting the appropriate data type, such as using string type instead of hash type, can save memory. Clean out expired data regularly. Consider using Redis Cluster to slice data to handle large amounts of data.

How to adjust Redis memory configuration parameters? This question is good, but it is not that simple. Just knowing that changing the maxmemory parameter in redis.conf is not enough. Let’s talk about this article in depth, not only to tell you how to change it, but more importantly, to tell you why it is changed like this and what will happen if it is corrected wrongly. After reading it, you will have a deeper understanding of Redis memory management, and it is no longer just a simple parameter change.

The core of Redis's memory management is maxmemory parameter, which limits the maximum memory available to Redis. But just setting this parameter is like building a roof for your house without considering the layout and use of the house. You have to consider your data type, your access pattern, and how you want Redis to handle memory outages.

maxmemory itself is just an upper limit. What really determines Redis memory is your data. A simple example, if you save millions of small keys, the memory usage is completely different from saving several huge hashs. So, before setting up maxmemory , you have to carefully evaluate your data size and type. This is not a matter of slapping the head, it requires monitoring and analysis. I've seen too many people, and I set up a huge maxmemory when I came up, but the server memory exploded and Redis just fell to his knees.

Next, let’s talk about maxmemory-policy . This parameter specifies how Redis should handle it when the memory reaches maxmemory upper limit. There are many options, such as noeviction (reject new writes), allkeys-lru (eliminate the least used data recently), volatile-lru allkeys-random (eliminate the least used data recently, which sets the expiration time), volatile-random (eliminate the key that sets the expiration time), volatile-ttl (eliminate the key that eliminates the most recent expiration time), etc. Which strategy to choose depends on your application scenario.

If your data is short-term and you can tolerate data loss, volatile-lru or volatile-random may be a good choice. But if your data is very important and cannot be lost, then noeviction is the only option, but this may cause Redis to reject new write requests. You need to do a corresponding processing mechanism, such as queues or other cache policies. Don't think that noeviction is all good. It just delays the problem. When the memory is really full, Redis will still have problems or even crash. Therefore, monitoring memory usage is crucial.

I used to be in a project, because of the allkeys-lru policy that mistakenly selected, some important cached data was wrongly phased out, causing serious business problems. Ultimately, we had to use volatile-lru instead and manage the data more granularly. This lesson I still remember.

Finally, share some tips:

• Monitor memory usage: Use Redis's own monitoring tools or third-party monitoring systems to monitor memory usage in real time.
• Data type selection: Choose the appropriate data type, for example, if your data is a simple key-value pair, using string type is more memory-saving than hash type.
• Regularly clean data: For keys that have set expiration time, regularly clean out expiration data.
• Sharding: If your data volume is very large, you can consider using Redis Cluster to spread the data on multiple Redis instances.

Remember, adjusting Redis memory configuration parameters is not achieved overnight, and requires continuous monitoring, adjustment and optimization. Don’t blindly set up a large maxmemory , but choose the appropriate parameters and strategies based on the actual situation. Remember, prevention is better than treatment. Only by observing and thinking more can your Redis run stably.

Here is an example, assuming that you want Redis to use up to 2GB of memory and use the LRU strategy to eliminate the least recently used data:

 <code class="redis">maxmemory 2gb maxmemory-policy allkeys-lru</code>

This is just a simple example. In actual application, you need to adjust it according to your specific situation. Don't copy it, understand it!

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