databases according to business, and the pressure is also separated into different databases. The diagram below has presented the solution to assign user tables and order tables to different databases by odd primary keys are put into the 1 database (or table), which is illustrated as the following diagram. 4.2. Sharding 22 Apache ShardingSphere document, v5.0.0 Theoretically, horizontal sharding has sharding, it consists of data source name and actual table name, e.g. ds_0. t_order_0. Mapping relationship between logic tables and actual tables and can be divided into two kinds: uniform topology and

databases according to business, and the pressure is also separated into different databases. The diagram below has presented the solution to assign user tables and order tables to different databases by odd primary keys are put into the 1 database (or table), which is illustrated as the following diagram. Theoretically, horizontal sharding has overcome the limitation of data processing volume in single table sharding rules. Data Node Configuration It is used in the configurations of the mapping relationship between logic tables and actual tables and can be divided into two kinds: uniform distribution

databases according to business, and the pressure is also separated into different databases. The diagram below has presented the solution to assign user tables and order tables to different databases by odd primary keys are put into the 1 database (or table), which is illustrated as the following diagram. Theoretically, horizontal sharding has overcome the limitation of data processing volume in single sharding, it consists of data source name and actual table name, e.g. ds_0. t_order_0. Mapping relationship between logic tables and actual tables and can be divided into two kinds: uniform topology and

databases according to business, and the pressure is also separated into different databases. The diagram below has presented the solution to assign user tables and order tables to different databases by odd primary keys are put into the 1 database (or table), which is illustrated as the following diagram. Theoretically, horizontal sharding has overcome the limitation of data processing volume in single sharding, it consists of data source name and actual table name, e.g. ds_0. t_order_0. Mapping relationship between logic tables and actual tables and can be divided into two kinds: uniform topology and

databases according to business, and the pressure is also separated into different databases. The diagram below has presented the solution to assign user tables and order tables to different databases by odd primary keys are put into the 1 database (or table), which is illustrated as the following diagram. Theoretically, horizontal sharding has overcome the limitation of data processing volume in single shard, consists of the data source name and the real table. Example: ds_0.t_order_0. The mapping relationship between the logical table and the real table can be classified into two forms: uniform distribution

databases according to business, and the pressure is also separated into different databases. The diagram below has presented the solution to assign user tables and order tables to different databases by odd primary keys are put into the 1 database (or table), which is illustrated as the following diagram. Theoretically, horizontal sharding has overcome the limitation of data processing volume in single shard, consists of the data source name and the real table. Example: ds_0.t_order_0. The mapping relationship between the logical table and the real table can be classified into two forms: uniform distribution

databases according to business, and the pressure is also separated into different databases. The diagram below has presented the solution to assign user tables and order tables to different databases by odd primary keys are put into the 1 database (or table), which is illustrated as the following diagram. Theoretically, horizontal sharding has overcome the limitation of data processing volume in single shard, consists of the data source name and the real table. Example: ds_0.t_order_0. The mapping relationship between the logical table and the real table can be classified into two forms: uniform distribution

databases according to business, and the pressure is also separated into different databases. The diagram below has presented the solution to assign user tables and order tables to different databases by odd primary keys are put into the 1 database (or table), which is illustrated as the following diagram. Theoretically, horizontal sharding has overcome the limitation of data processing volume in single shard, consists of the data source name and the real table. Example: ds_0.t_order_0. The mapping relationship between the logical table and the real table can be classified into two forms: uniform distribution

of [0, size(slices) ‐ 1]. Customized sharding options Customized sharding options can build a relationship with the sharding items, converting the sharding items’numbers to more readable business codes ShardingSphere ElasticJob document Design concept The operation and maintenance platform has no direct relationship with ElasticJob. It displays the job status by reading the job registration center data, or updating

org.hibernate.dialect 由于数据加密的 DDL 尚未开发完成，因此对于自动生成 DDL 语句的 JPA 与数据加密一起使用时，会导 致 JPA 的实体类 (Entity) 无法同时满足 DDL 和 DML 的情况。 解决方案如下： 1. 以需要加密的逻辑列名编写 JPA 的实体类 (Entity)。 2. 关闭 JPA 的 auto‐ddl，如 auto‐ddl=none。 3. 手 动 建 表， 建 表 时 应 使