for(Student st : student ){ System.out.println(st.getId()); System.out.println(st.getName()); System.out.println(st.getBranch()); System.out.println(st.getPercentage()); getPercentage()); System.out.println(st.getEmail()); System.out.println(st.getPhone()); } System.out.println("Records Read Successfully "); List student = session.selectList("getRecByName_Id",stud); for(Student st : student ){ System.out.println("++++++++++++++details of the student named

HA R( 25 5) Y e s Collection of sharding item, multiple sharding items are separated by commas. st ate V AR CH AR (2 0) Y e s State of job execution, the value options are TASK_STAGING, TASK_RUNNING ault V alue Description jobName St ri ng Job name shar dingTotalCount i nt Sharding total count cron St ri ng CRON expression, control the job trigger time timeZone St ri ng time zone of CRON sharding sharding ItemParame‐ ters St ri ng Sharding item param‐ eters jobParameter St ri ng Job parameter mo nitorExecution b oo le an true Monitor job execution status failover b oo le an f alse Enable or

List student = session.selectList("getRecByName_Id",stud); for(Student st : student ){ System.out.println("++++++++++++++details of the student named println("Id : "+st.getId()); System.out.println("Name : "+st.getName()); System.out.println("Branch : "+st.getBranch()); System.out.println("Percentage : "+st.getPercentage()); getPercentage()); System.out.println("Email : "+st.getEmail()); System.out.println("Phone : "+st.getPhone()); } System.out.println("Records

au lt Va lu e t y p e String Type of mode configu‐ rationValues could be: Standalone or Cluster St an da lo ne r e p o s i t o r y Pe rsistRe positor yConfig uration Persist repository configurationStan‐ createDataSources() { Map dataSourceMap = new HashMap<>(); // Configure the 1st data source HikariDataSource dataSource1 = new HikariDataSource(); dataSource1.setDriverClassName("com jdbc_ state‐ ment_execu te_errors_total G AU GE Total number of statement execution errors jdbc_st ate‐ ment_execute _la‐ tency_millis H IS TO GR AM Statement execution latency jdbc_tra nsac‐

au lt Va lu e t y p e String Type of mode configu‐ rationValues could be: Standalone or Cluster St an da lo ne r e p o s i t o r y Pe rsistRe positor yConfig uration Persist repository configurationStan‐ createDataSources() { Map dataSourceMap = new HashMap<>(); // Configure the 1st data source HikariDataSource dataSource1 = new HikariDataSource(); dataSource1.setDriverClassName("com jdbc_ state‐ ment_execu te_errors_total G AU GE Total number of statement execution errors jdbc_st ate‐ ment_execute _la‐ tency_millis H IS TO GR AM Statement execution latency jdbc_tra nsac‐

approximately equal to 69.73 years. Apache ShardingSphere snowflake algorithm starts from November 1st, 2016, and can be used until 2086, which we believe can satisfy the requirement of most systems. Description t ype St ri ng Cluster mode typ, such as: Zookeeper, Etcd nam esp ace St ri ng Cluster mode instance namespace, such as: cluster‐ sharding‐mode ser ver ‐li sts St ri ng Zookeeper or Etcd Apache ShardingSphere document, v5.0.0 Name • Data T ype* Description Default Value digest (?) St ring Connect to authority tokens in registry cen‐ ter No need for authority operationTi meoutMil‐

ovi der St ri ng 元数据存储类型，可选 值为 H2，MySQL H2 jd bc_ url St ri ng JDBC URL jdbc:h2:mem:config ;DB_CLOSE_ DELAY=‐ 1;DATABASE_TO_UPPER=false;MODE=MYSQL us ern ame St ri ng 账号 sa pa ssw ord St ri ng 密码 自动时间段分片算法 类型：AUTO_INTERVAL 可配置属性： 属性名称 数 据 类型 说明 d atetime‐ lower St ring 分片的起始时间范围，时间戳格式：yyyy‐MM‐dd HH:mm:ss d atetime‐ upper St ring 分片的结束时间范围，时间戳格式：yyyy‐MM‐dd HH:mm:ss sha rding‐ seconds long 张表，表名称 为 t_user_0 到 t_user_7。详情请参见行表达式。 类型：INLINE 可配置属性： 属性名称 数据类型 说明 • 默认值 * algorithm‐expression St ring 分片算法的行表达式 allow‐r ange‐query‐ with‐inline‐sharding (?) boo lean 是否允许范围查询。注 意：范围查询会无视分 片策略，进行全路由

ovi der St ri ng 元数据存储类型，可选 值为 H2，MySQL H2 jd bc_ url St ri ng JDBC URL jdbc:h2:mem:config ;DB_CLOSE_ DELAY=‐ 1;DATABASE_TO_UPPER=false;MODE=MYSQL us ern ame St ri ng 账号 sa pa ssw ord St ri ng 密码 自动时间段分片算法 类型：AUTO_INTERVAL 可配置属性： 属性名称 数 据 类型 说明 d atetime‐ lower St ring 分片的起始时间范围，时间戳格式：yyyy‐MM‐dd HH:mm:ss d atetime‐ upper St ring 分片的结束时间范围，时间戳格式：yyyy‐MM‐dd HH:mm:ss sha rding‐ seconds long 张表，表名称为 t_user_0 到 t_user_7。详情请参见行表达式。 类型：INLINE 可配置属性： 属性名称 数据类型 说明 • 默认值 * algorithm‐expression St ring 分片算法的行表达式 allow‐r ange‐query‐ with‐inline‐sharding (?) boo lean 是否允许范围查询。注 意：范围查询会无视分 片策略，进行全路由

approximately equal to 69.73 years. Apache ShardingSphere snowflake algorithm starts from November 1st, 2016, and can be used until 2086, which we believe can satisfy the requirement of most systems. and connection pools. Map dataSourceMap = new HashMap<>(); // Configure the 1st data source HikariDataSource dataSource1 = new HikariDataSource(); dataSource1.setDriverClassName("com # Configure actual data sources spring.shardingsphere.datasource.names=ds1,ds2 # Configure the 1st data source spring.shardingsphere.datasource.ds1.type=com.zaxxer.hikari.HikariDataSource spring.shardingsphere

ovi der St ri ng 元数据存储类型，可选 值为 H2，MySQL H2 jd bc_ url St ri ng JDBC URL jdbc:h2:mem:config ;DB_CLOSE_ DELAY=‐ 1;DATABASE_TO_UPPER=false;MODE=MYSQL us ern ame St ri ng 账号 sa pa ssw ord St ri ng 密码 自动时间段分片算法 类型：AUTO_INTERVAL 可配置属性： 属性名称 数 据 类型 说明 d atetime‐ lower St ring 分片的起始时间范围，时间戳格式：yyyy‐MM‐dd HH:mm:ss d atetime‐ upper St ring 分片的结束时间范围，时间戳格式：yyyy‐MM‐dd HH:mm:ss sha rding‐ seconds long 张表，表名称 为 t_user_0 到 t_user_7。详情请参见行表达式。 类型：INLINE 可配置属性： 属性名称 数据类型 说明 • 默认值 * algorithm‐expression St ring 分片算法的行表达式 allow‐r ange‐query‐ with‐inline‐sharding (?) boo lean 是否允许范围查询。注 意：范围查询会无视分 片策略，进行全路由