Readwrite-splitting

Background

Read/write splitting YAML configuration is highly readable. The YAML format enables you to quickly understand the dependencies between read/write sharding rules. ShardingSphere automatically creates the ShardingSphereDataSource object according to the YAML configuration, which reduces unnecessary coding for users.

Parameters

Readwrite-splitting

rules:
- !READWRITE_SPLITTING
  dataSources:
    <data_source_name> (+): # Logic data source name of readwrite-splitting, which uses Groovy's Row Value Expressions SPI implementation to parse by default
      write_data_source_name: # Write data source name, which uses Groovy's Row Value Expressions SPI implementation to parse by default
      read_data_source_names: # Read data source names, multiple data source names separated with comma, which uses Groovy's Row Value Expressions SPI implementation to parse by default
      transactionalReadQueryStrategy (?): # Routing strategy for read query within a transaction, values include: PRIMARY (to primary), FIXED (to fixed data source), DYNAMIC (to any data source), default value: DYNAMIC
      loadBalancerName: # Load balance algorithm name
  # Load balance algorithm configuration
  loadBalancers:
    <load_balancer_name> (+): # Load balance algorithm name
      type: # Load balance algorithm type
      props: # Load balance algorithm properties
        # ...

Please refer to Built-in Load Balance Algorithm List for more details about type of algorithm.

Procedure

1. Add read/write splitting data source.
2. Set the load balancer algorithm.
3. Use read/write data source.

Sample

rules:
- !READWRITE_SPLITTING
  dataSources:
    readwrite_ds:
      writeDataSourceName: write_ds
      readDataSourceNames:
        - read_ds_0
        - read_ds_1
      transactionalReadQueryStrategy: PRIMARY
      loadBalancerName: random
  loadBalancers:
    random:
      type: RANDOM

Related References

• Read-write splitting-Core features
• Java API: read-write splitting