What are the ways to expand MongoDB sharded clusters?

Expanding a MongoDB sharded cluster involves adding more shards to distribute data and workload more evenly, improving performance and scalability. Here’s how to do it, along with examples:

1. Adding Shards to the Cluster

   • Use the sh.addShard() command to add a new shard (a standalone MongoDB instance or a replica set) to the cluster.
   • Example:

     sh.addShard("replicaSetName/shardHost1:port,shardHost2:port,shardHost3:port")
     

   • After adding, MongoDB automatically redistributes chunks (data partitions) across shards.

2. Scaling Storage or Compute Resources

   • If a shard is a replica set, you can scale vertically (increase CPU/RAM) or horizontally (add more nodes to the replica set).
   • Example: Add a new secondary node to a replica set shard to improve read performance and fault tolerance.

3. Using Hashed Sharding for Even Distribution

   • If using range-based sharding, hotspots may occur. Switching to hashed sharding ensures even data distribution.
   • Example:

     sh.shardCollection("database.collection", { "fieldName": "hashed" })
     

4. Leveraging Cloud Services for Elastic Scaling

   • For managed scaling, use Tencent Cloud’s MongoDB sharded cluster service, which allows dynamic shard addition and automatic load balancing.
   • Example: Deploy a sharded cluster on Tencent Cloud and use the console or API to add shards without manual configuration.

5. Monitoring and Rebalancing

   • After expansion, monitor chunk distribution with sh.status() and manually split or move chunks if needed.
   • Example:

     db.adminCommand({ split: "database.collection", middle: { "fieldName": value } })
     

Tencent Cloud’s MongoDB service simplifies shard management, offering auto-scaling and optimized performance for growing workloads.