high concurrency in OLTP scenarios . . . . . . . . . . . . . . . . . . . 18 Mass data real‐time analysis in OLAP scenarios . . . . . . . . . . . . . . . . . . . 19 3.1.5 Related References . . . . . utilizing data in a complex data environment. Sharding‐ Sphere provides complex data query and analysis capabilities across data sources, simpli‐ fying the data aggregation from different data locations enhancement capabili‐ ties through traffic deformation, redirection, governance, authentication, and analysis. 1.2.3 Pluggable: Building database function ecology The pluggable architecture of Apache ShardingSphere

high concurrency in OLTP scenarios . . . . . . . . . . . . . . . . . . . 19 Mass data real‐time analysis in OLAP scenarios . . . . . . . . . . . . . . . . . . . 20 3.1.5 Related References . . . . . enhancement capabili‐ ties through traffic deformation, redirection, governance, authentication, and analysis. 1.2. Design Philosophy 5 Apache ShardingSphere document, v5.2.0 1.2.3 Pluggable: Building database Heterogeneous language Java Only Any Performance Low loss Relatively High loss Decentralization Yes No Static entry No Yes Independent ShardingSphere-Proxy ShardingSphere‐Proxy is a transparent database proxy

high concurrency in OLTP scenarios . . . . . . . . . . . . . . . . . . . 22 Mass data real‐time analysis in OLAP scenarios . . . . . . . . . . . . . . . . . . . 23 8.1.5 Related References . . . . . utilizing data in a complex data environment. Sharding‐ Sphere provides complex data query and analysis capabilities across data sources, simpli‐ fying the data aggregation from different data locations enhancement capabili‐ ties through traffic deformation, redirection, governance, authentication, and analysis. 2.3 Pluggable: Building database function ecology The pluggable architecture of Apache ShardingSphere

high concurrency in OLTP scenarios . . . . . . . . . . . . . . . . . . . 22 Mass data real‐time analysis in OLAP scenarios . . . . . . . . . . . . . . . . . . . 23 8.1.5 Related References . . . . . utilizing data in a complex data environment. Sharding‐ Sphere provides complex data query and analysis capabilities across data sources, simpli‐ fying the data aggregation from different data locations enhancement capabili‐ ties through traffic deformation, redirection, governance, authentication, and analysis. 2.3 Pluggable: Building database function ecology The pluggable architecture of Apache ShardingSphere

Java Only Any Any Performance Low loss Relatively High loss Low loss De centralization Yes No No Static Entry No Yes No 1.1.4 Hybrid Architecture ShardingSphere‐JDBC adopts a decentralized architecture high‐performance light‐weight OLTP application developed with Java. ShardingSphere‐Proxy provides static entry and all languages support, applicable for OLAP application and the sharding databases management Supported Languages Java Only Any Performance Low loss Relatively High loss Decentralization Yes No Static Entry No Yes ShardingSphere‐JDBC is suitable for java application. 3.1.2 ShardingSphere-Proxy

Java Only Any Any Performance Low loss Relatively High loss Low loss De centralization Yes No No Static Entry No Yes No 1.1.4 Hybrid Architecture ShardingSphere‐JDBC adopts a decentralized architecture high‐performance light‐weight OLTP application developed with Java. ShardingSphere‐Proxy provides static entry and all languages support, applicable for OLAP application and the sharding databases management Supported Languages Java Only Any Performance Low loss Relatively High loss Decentralization Yes No Static Entry No Yes ShardingSphere‐JDBC is suitable for java application. Source Codes: https://github

Java Only Any Any Performance Low loss Relatively High loss Low loss De centralization Yes No No Static Entry No Yes No 1.1.4 Hybrid Architecture ShardingSphere‐JDBC adopts a decentralized architecture high‐performance light‐weight OLTP application developed with Java. ShardingSphere‐Proxy provides static entry and all languages support, applicable for OLAP application and the sharding databases management Supported Languages Java Only Any Performance Low loss Relatively High loss Decentralization Yes No Static Entry No Yes ShardingSphere‐JDBC is suitable for java application. 3.1.2 ShardingSphere-Proxy

Java Only Any Any Performance Low loss Relatively High loss Low loss De centralization Yes No No Static Entry No Yes No 1.1.4 Hybrid Architecture ShardingSphere‐JDBC adopts decentralized architecture high‐performance light‐weight OLTP application developed with Java; ShardingSphere‐Proxy provides static entry and all languages support, applicable for OLAP application and the sharding databases management This kind of dichotomy solution lacks flexible coping ability to switch between two modes with static initialization. In practical situations, route results of each time may differ with different SQL

class MyJobDemo { public static void main(String[] args) { new ScheduleJobBootstrap(createRegistryCenter(), new MyJob(), createJobConfiguration()).schedule(); } private static CoordinatorRegistryCenter ZookeeperConfiguration("zk_host:2181", "my-job")); regCenter.init(); return regCenter; } private static JobConfiguration createJobConfiguration() { // create job configuration // ... } } 4.3. Configure the key is shardingContext, and the value is in json format. public class HttpJobMain { public static void main(String[] args) { new ScheduleJobBootstrap(regCenter, "HTTP", JobConfiguration.newBuilder(

class MyJobDemo { public static void main(String[] args) { new ScheduleJobBootstrap(createRegistryCenter(), new MyJob(), createJobConfiguration()).schedule(); } private static CoordinatorRegistryCenter ZookeeperConfiguration("zk_host:2181", "my-job")); regCenter.init(); return regCenter; } private static JobConfiguration createJobConfiguration() { // 创建作业配置 // ... } } 4.3. 作业配置 6 5 概念 & 功能 本章节阐述 http 信息。分片信息以 Header 形式传递，key 为 shardingContext，值为 json 格式。 public class HttpJobMain { public static void main(String[] args) { new ScheduleJobBootstrap(regCenter, "HTTP", JobConfiguration.newBuilder(