How is data sharding used to distribute data across multiple databases?

Sharding is a method of horizontal scaling of a database, where data is distributed across multiple servers (shards) to improve performance and fault tolerance.

Data distribution occurs based on a specific key (for example, user_id), which determines which shard the data will go to. There are several sharding methods:

• Range sharding: data is split into ranges of keys (for example, users with id from 1 to 10,000 on one shard, from 10,001 to 20,000 on another).
• Hash sharding: the key is processed through a hash function, the result of which determines the shard.
• List sharding: specific key values are assigned to particular shards.

In Java, to implement sharding, you can use middleware or ORM with sharding support, or implement routing logic to direct requests to the appropriate shard server.

An example of simplified shard selection logic:

int shardCount = 4;
int shardId = userId % shardCount; // determine shard by remainder of division
// then the request is directed to the corresponding shard

Thus, sharding allows for efficient load distribution and system scaling.