. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 8.1.8 Appendix with SQL operator . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 8.2 Distributed Transaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 8.2.9 Appendix with SQL operator . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 8.3 Readwrite‐splitting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 8.7.8 Appendix with SQL operator . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 8.8 Data Masking . . . . . . . . .

jdbcURL 的识别适配，元数据加载实现 • SQL 解析 – org.apache.shardingsphere:shardingsphere-parser-sql-clickhouse，SQL 解 析的 ClickHouse 方言实现 – org.apache.shardingsphere:shardingsphere-parser-sql-hive，SQL 解 析 的 Hive 方言实现 ShardingSphere JDBC 使用 ClickHouse 方言时，用户需要手动引入相关的可选模块和 classifier 为 http 的 ClickHouse JDBC 驱动。原则上，ShardingSphere 的 GraalVM Native Image 集成不希望使用 classifier 为 all 的 com.clickhouse:clickhouse-jdbc，因为 Uber Jar shardingsphere-parser-sql-clickhouse ${shardingsphere.version} com.clickhouse 9.1. ShardingSphere-JDBC 146

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 3.1.8 Appendix with SQL operator . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 3.2 Distributed Transaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 ii 3.2.9 Appendix with SQL operator . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 3.3 Readwrite‐splitting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 3.8.8 Appendix with SQL operator . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 3.9 Shadow . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 3.1.8 Appendix with SQL operator . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 3.2 Distributed Transaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 3.2.9 Appendix with SQL operator . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 ii 3.3 Readwrite‐splitting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 3.8.8 Appendix with SQL operator . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 3.9 Shadow . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 8.1.8 Appendix with SQL operator . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 8.2 Distributed Transaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 8.2.9 Appendix with SQL operator . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 8.3 Readwrite‐splitting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 8.7.8 Appendix with SQL operator . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 8.8 Data Masking . . . . . . . . .

provided by different database dialect, it is categorized into keyword, expression, literal value and operator. SQL is then converted into abstract syntax tree by syntactic parser. For example, the following single‐sharding route (equal mark as the operator of sharding key), multiple‐sharding route (IN as the operator of sharding key) and range sharding route (BETWEEN as the operator of sharding key). SQL without sharding not include joint query or only includes joint query between binding tables. When the sharding operator is equal mark, the route result will fall into a single database (table); when sharding operators

databases. What’s more, it also brings the same problem as data sharding, complicating developer and operator’s maintenance and operation. The following diagram has shown the complex topological rela‐ tions provided by different database dialect, it is categorized into keyword, expression, literal value and operator. SQL is then converted into abstract syntax tree by syntactic parser. For example, the following single‐sharding route (equal mark as the operator of sharding key), multiple‐sharding route (IN as the operator of sharding key) and range sharding route (BETWEEN as the operator of sharding key). SQL without sharding

databases. What’s more, it also brings the same problem as data sharding, complicating developer and operator’s maintenance and operation. The following diagram has shown the complex topological rela‐ tions provided by different database dialect, it is categorized into keyword, expression, literal value and operator. SQL is then converted into abstract syntax tree by syntactic parser. For example, the following single‐sharding route (equal mark as the operator of sharding key), multiple‐sharding route (IN as the operator of sharding key) and range sharding route (BETWEEN as the operator of sharding key). SQL without sharding

databases. What’s more, it also brings the same problem as data sharding, complicating developer and operator’s maintenance and operation. The following diagram has shown the complex topological rela‐ tions provided by different database dialect, it is categorized into keyword, expression, literal value and operator. SQL is then converted into abstract syntax tree by syntactic parser. For example, the following single‐sharding route (equal mark as the operator of sharding key), multiple‐sharding route (IN as the operator of sharding key) and range sharding route (BETWEEN as the operator of sharding key). SQL without sharding

table-name="t_order" operator= "EQUAL"> 3.10. 测试引擎 108 Apache ShardingSphere document, v5.0.0-beta operator= "EQUAL"> column-name="order_id" table-name="t_order" operator= "EQUAL"> operator= "EQUAL">

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