Optimizing Chat History Storage in MariaDB Cluster
As our chat application continues to grow, we’re facing an issue where the archived chat history is becoming increasingly small due to storage constraints. To address this challenge, we’ll implement a compression mechanism and leverage Redis-server for object caching.
Compressing Chat History
To reduce storage requirements, we’ll compress the previous chat history using a suitable compression algorithm (e.g., GZIP or Snappy). This will significantly decrease the size of archived data while maintaining its integrity.
Using Redis-server for Object Caching
We’ll utilize Redis-server to cache archived chat history in memory. By doing so, the latest chats will be stored in the memory, ensuring:
1. Fast access: No limitations on retrieving previously archived chat history.
2. Ollama LLM independence: Availability of previous chat history is not dependent on the currently used Ollama LLM.
Automated Synchronization
To maintain data consistency between Redis-server and MariaDB records, we’ll set up an automated synchronization process every x seconds:
1. Retrieve the latest chats stored in Redis-server.
2. Store them in corresponding database records in MariaDB.
3. Update Redis-server with new records.
This approach ensures that both systems stay synchronized, providing a seamless chat experience for all users.
Benefits
By implementing this compression and caching mechanism, we’ll achieve:
1. Reduced storage requirements
2. Fast access to archived chat history
3. Improved overall performance
We’re confident that this optimized solution will address our storage constraints and provide a better experience for our users.
