To expand the table capacity of Memcached in a cloud database, you typically need to scale the underlying infrastructure or optimize the data storage approach, as Memcached itself is an in-memory key-value store without persistent storage or table structures. However, if you're referring to scaling a caching layer that mimics table-like behavior (e.g., using namespaces or key prefixes to simulate tables), here’s how to approach it:
Scale Memcached Instances Horizontally:
Add more Memcached nodes to distribute the load and increase total memory capacity. This can be done manually or via auto-scaling groups in the cloud.
Example: If your current setup has 3 Memcached nodes with 1GB each, adding 2 more nodes (1GB each) increases total capacity to 5GB.
Use Sharding (Key-Based Partitioning):
Split data across multiple Memcached instances by hashing keys (e.g., using consistent hashing). This allows you to scale beyond single-node memory limits.
Example: Store user data with keys like user_1, user_2 and distribute them across nodes based on a hash of the key prefix (user).
Leverage Cloud-Native Solutions:
In a cloud environment, use managed services that support dynamic scaling. For instance, Tencent Cloud’s TencentDB for Memcached (or similar services) allows you to adjust node count and memory allocation via the console or API.
Optimize Data Structure:
If "table capacity" refers to storing structured data, consider compressing values or using more efficient serialization (e.g., Protocol Buffers instead of JSON).
Combine with Persistent Storage:
For data that must persist, pair Memcached with a cloud database like TencentDB for MySQL or Redis (if persistence is needed). Use Memcached for caching hot data while storing the full dataset in a persistent database.
For Tencent Cloud users, Tencent Cloud’s Elastic Memcached Service supports elastic scaling, automatic failover, and monitoring, simplifying capacity expansion. You can adjust configurations via the Tencent Cloud Console or SDKs.