distributed systems, such as horizontal scaling of computing capability and high availability. Clustered environments need to store metadata and coordinate nodes’ status through a separately deployed and more of them require to include multiple accesses to services and the corresponding database resources in the same transaction. As a result, distributed transactions appear. Though the relational database high access cost, soft transactions require developers to transform the application and realize resources lock and backward compensa‐ tion. 3.2.3 Goal The main design goal of the distributed transaction

distributed systems, such as horizontal scaling of computing capability and high availability. Clustered environments need to store metadata and coordinate nodes’ status through a separately deployed and more of them require to include multiple accesses to services and the corresponding database resources in the same transaction. As a result, distributed transactions appear. Though the relational database high access cost, soft transactions require developers to transform the application and realize resources lock and backward compensa‐ tion. 3.2.3 Goal The main design goal of the distributed transaction

distributed systems, such as horizontal scaling of computing capability and high availability. Clustered environments need to store metadata and coordinate nodes’ status through a separately deployed and more of them require to include multiple accesses to services and the corresponding database resources in the same transaction. As a result, distributed transactions appear. Though the relational database 33 Apache ShardingSphere document require developers to transform the application and realize resources lock and backward compensa‐ tion. 8.2.3 Goal The main design goal of the distributed transaction

distributed systems, such as horizontal scaling of computing capability and high availability. Clustered environments need to store metadata and coordinate nodes’ status through a separately deployed and more of them require to include multiple accesses to services and the corresponding database resources in the same transaction. As a result, distributed transactions appear. Though the relational database 33 Apache ShardingSphere document require developers to transform the application and realize resources lock and backward compensa‐ tion. 8.2.3 Goal The main design goal of the distributed transaction

ShardingSphere‐Proxy, developers can operate data just like using database, but they need to configure resources and rules through YAML file (or registry center). However, the format of YAML and habits changed Definition Language) responsible for the definition of resources and rules; • RQL (Resource & Rule Query Language) responsible for the query of resources and rules; • RAL (Resource & Rule Administration Language) the max load, stop the node’s access to the database, so that the database can ensure sufficient resources to provide services for other Apache ShardingSphere nodes. Request Limit In the face of overload

（可选）引入自定义算法 当用户需要使用自定义的算法类时，可通过以下方式配置使用自定义算法，以分片为例： 1. 实现 `ShardingAlgorithm` 接口定义的算法实现类。 2. 在项目 `resources` 目录下创建 `META-INF/services` 目录。 3. 在 `META-INF/services` 目录下新建文件 `org.apache.shardingsphere.sharding overnance.zookeeper .persistence.size 持久卷（PersistentVolume）大小 ‘ 8Gi‘ g overnance.zookeeper .resources.limits ZooKeeper 容器的资源限制 {} governance .zookeeper. resource s.requests. memory ZooKeeper 容器申请的内存 compute.image.tag ShardingSphere‐Proxy 镜像标签 5.1.2 compu te.imagePullSecrets 拉取私有仓库的凭证 [] compu te.resources.limits ShardingSphere‐Proxy 容器的资 源限制 {} compute.resour ces. requests.memory ShardingSphere‐Proxy

ShardingSphere‐Proxy, developers can operate data just like using database, but they need to configure resources and rules through YAML file (or registry center). However, the format of YAML and habits changed Definition Language) responsible for the definition of resources and rules; • RQL (Resource & Rule Query Language) responsible for the query of resources and rules; • RAL (Resource & Rule Administration Language) the max load, stop the node’s access to the database, so that the database can ensure sufficient resources to provide services for other Apache ShardingSphere nodes. Request Limit In the face of overload

ShardingSphere‐Proxy, developers can operate data just like using database, but they need to configure resources and rules through YAML file (or registry center). However, the format of YAML and habits changed Definition Language) responsible for the definition of resources and rules; • RQL (Resource & Rule Query Language) responsible for the query of resources and rules; • RAL (Resource & Rule Administration Language) and more of them require to include multiple accesses to services and the corresponding database resources in the same transaction. As a result, distributed transactions appear. Though the relational database

interfaces and APIs that help the rest of the application remain independent of any persistence-related resources. Open source− MyBatis is free and an open source software. Advantages of MYBATIS MYBATIS offers shown below − import java.io.IOException; import java.io.Reader; import org.apache.ibatis.io.Resources; import org.apache.ibatis.session.SqlSession; import org.apache.ibatis.session.SqlSessionFactory; { public static void main(String args[]) throws IOException{ Reader reader = Resources.getResourceAsReader("SqlMapConfig.xml"); SqlSessionFactory sqlSessionFactory = new SqlSes

使用自定义算法 当用户需要使用自定义的算法类时，可通过以下方式配置使用自定义算法，以分片为例： 1. 实现 ShardingAlgorithm 接口定义的算法实现类。 2. 在项目 resources 目录下创建 META-INF/services 目录。 3. 在 META-INF/services 目录下新建文件 org.apache.shardingsphere.sharding.spi governance.zookeep er. persistence.size 持久卷（PersistentVolume）大小 8Gi governance.zookeep er. resources.limits ZooKeeper 容器的资源限制 {} govern ance.zookeeper. resour ces.requests. memory ZooKeeper 容器申请的内存 compute.image.tag ShardingSphere‐Proxy 镜像标签 5.1.2 comp ute.imagePullSecrets 拉取私有仓库的凭证 [] comp ute.resources.limits ShardingSphere‐Proxy 容器的资 源限制 {} compute.resou rces. requests.memory ShardingSphere‐Proxy