When opting for Redis in your system, it's likely due to its outstanding performance capabilities.

A single-node Redis instance can support an impressive traffic volume of up to 100,000 queries per second (QPS). However, this level of performance also means that any latency can significantly impact user experience.

Thus, maintaining Redis's high performance and minimizing latency during operations is crucial. Here are 11 strategies to help you achieve that:

1. Avoid Storing Large Keys

   Storing large keys can consume excessive memory and severely affect Redis's performance. Since Redis operates on a single-threaded model, writing a large key can lead to significant delays during memory allocation, increasing operation latency. Similarly, deleting or reading large keys can create bottlenecks, queuing subsequent requests and degrading overall performance. Therefore, it's advisable for your application to refrain from storing large keys.

2. Limit Use of Complex Commands

   Redis processes requests using a single-threaded approach. High-complexity commands can monopolize CPU resources, resulting in queuing delays for other requests. To prevent this, avoid commands that require extensive computation, such as SORT, SINTER, and ZUNIONSTORE. Instead, consider performing these operations on the client side.

3. Be Mindful of DEL Command Complexity

   When removing keys, the DEL command's performance can be affected by the type of key being deleted. While deleting a String key has a time complexity of O(1), List/Hash/Set/ZSet keys have a complexity of O(N), where N is the number of elements. This means that more elements will slow down the deletion process, as each element's memory must be freed sequentially. To manage keys with many elements, delete them in batches.

   • For Lists, repeatedly use LPOP or RPOP until all elements are removed.
   • For Hashes, Sets, or ZSets, first use HSCAN, SSCAN, or SCAN to identify elements, then delete them one by one.

4. Enable Lazy-Free Mechanism

   If large keys are unavoidable, consider enabling Redis's lazy-free mechanism (available in version 4.0 and above). This feature allows Redis to release memory in the background when deleting large keys, minimizing the impact on the main thread.

5. Monitor Size of N in O(N) Commands

   Avoid complacency after steering clear of highly complex commands. When executing O(N) commands, be aware of how large N is. Querying too many elements at once can lead to prolonged network transmission times and increased latency. Always check the number of elements before executing commands like LRANGE or HGETALL, and query in batches when necessary.

6. Utilize Batch Commands

   When performing multiple operations, leverage batch commands to enhance efficiency. Batch processing reduces network I/O round-trips between the client and server, thus improving performance. For instance, use MGET/MSET for Strings and HMGET/HMSET for Hashes, or utilize Pipeline for other data types.

7. Prevent Bulk Key Expiration

   Redis clears expired keys in a timed and lazy fashion, which can block the main thread if numerous keys expire simultaneously. To mitigate this, stagger expiration times by adding randomness when setting them, reducing the risk of concentrated expiration.

8. Establish Long Connections and Optimize Connection Pools

   Opt for long-lived connections to Redis instead of short ones, as the latter incurs the overhead of TCP handshakes with each request. Additionally, implement a connection pool with reasonable parameters to manage resources effectively.

9. Stick to db 0

   Although Redis offers 16 databases, it's advisable to only use db 0 for several reasons:

   • Switching databases requires executing SELECT commands, adding extra load.
   • Multiple instances can be deployed for different business lines, enhancing performance.
   • Redis Cluster only supports db 0, simplifying future migrations.

10. Implement Read-Write Separation with Sharding

For businesses with high read demands, deploying multiple slave databases can distribute read pressure and improve overall performance. If your write load is substantial, consider using a sharded cluster to share the write burden.

11. Reconsider AOF Usage

If data loss isn't a concern, avoid enabling AOF to prevent performance degradation from disk writes. If AOF is necessary, configure it with appendfsync every second and allow disk flushing to occur in a background thread to minimize performance impact.

These are actionable optimizations to enhance Redis's high performance. If performance is a priority for your Redis usage, these recommendations can help you optimize effectively.

For more insights on Redis, feel free to check out my other articles.