Low High Supported Languages 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 sharding tables can also lead to the full use of local transactions when single‐table data amount de‐ creases. Troubles brought by distributed transactions can be avoided by the wise use of different Less More Supported Languages Java Only Any Any Performance Low loss Relatively High loss Low loss De centralization Yes No No Static Entry No Yes No ShardingSphere‐JDBC is suitable for java application

Low High Supported Languages 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 sharding tables can also lead to the full use of local transactions when single‐table data amount de‐ creases. Troubles brought by distributed transactions can be avoided by the wise use of different NOT NULL,runoob_test NATIONAL CH AR(40),submission_date DATE,PRIMARY KEY ( runoob_id))ENGINE=InnoDB DE‐ FAULT CHARSET=utf8; CREATE TABLE IF NOT EXISTS runoob_tbl ( runoob_id INT UNSIGNED AUTO_INCREMENT

Low High Supported Languages 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 sharding tables can also lead to the full use of local transactions when single‐table data amount de‐ creases. Troubles brought by distributed transactions can be avoided by the wise use of different Please refer to Built‐in Sharding Algorithm List and Built‐in Key Generate Algorithm List for more de‐ tails about type of algorithm. Attention Inline expression identifier can use ${...} or $->{..

Full support for DML, DDL, DCL, TCL, and common DALs. Support for complex queries such as paging, de‐duplication, sorting, grouping, aggregation, table association, etc. Support SCHEMA DDL and DML statements DynamicReadwriteSplittingStrategyConfiguration Configurable Properties: Name • D a t a T y p e * Description De fault V alue aut oAwareData SourceName S t r i n g Database discovery logic data source name • shad owAlgorithms Map shadow algorithm name and configu‐ ration de faultShadowA lgo‐ rithmName String default shadow algorithm name Shadow Data Source Configuration

Low High Supported Languages 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 sharding tables can also lead to the full use of local transactions when single‐table data amount de‐ creases. Troubles brought by distributed transactions can be avoided by the wise use of different Please refer to Built‐in Sharding Algorithm List and Built‐in Key Generate Algorithm List for more de‐ tails about type of algorithm. Attention Inline expression identifier can use ${...} or $->{..

migrate the data from other data sources, while simul‐ taneously performing data sharding. Q ue ry Fe de ra ti on Federated queries are effective in utilizing data in a complex data environment. Sharding‐ Full support for DML, DDL, DCL, TCL, and common DALs. Support for complex queries such as pag‐ ing, de‐duplication, sorting, grouping, aggregation, table association, etc. Support SCHEMA DDL and DML statements rdingStrategy (?) ShardingSt rategyCon‐ figuration Default database sharding strategy Not sharding de faultTableSha rd‐ ingStrategy (?) ShardingSt rategyCon‐ figuration Default table sharding strategy

Full support for DML, DDL, DCL, TCL, and common DALs. Support for complex queries such as paging, de‐duplication, sorting, grouping, aggregation, table association, etc. Support SCHEMA DDL and DML statements dingStrategy (?) ShardingStr ategyCon‐ figuration Default table sharding strategy Not sharding de faultKeyGene rateS‐ trategy (?) KeyGene ratorConfig‐ uration Default key generator S nowflake DynamicReadwriteSplittingStrategyConfiguration Configurable Properties: Name • D a t a T y p e * Description De fault V alue aut oAwareData SourceName S t r i n g Database discovery logic data source name •

migrate the data from other data sources, while simul‐ taneously performing data sharding. Q ue ry Fe de ra ti on Federated queries are effective in utilizing data in a complex data environment. Sharding‐ Full support for DML, DDL, DCL, TCL, and common DALs. Support for complex queries such as pag‐ ing, de‐duplication, sorting, grouping, aggregation, table association, etc. Support SCHEMA DDL and DML statements rdingStrategy (?) ShardingSt rategyCon‐ figuration Default database sharding strategy Not sharding de faultTableSha rd‐ ingStrategy (?) ShardingSt rategyCon‐ figuration Default table sharding strategy

attention to this node. 5.2. Elastic Schedule 12 Apache ShardingSphere ElasticJob document C hi ld no de na me E p h e m e r a l n o d e Description el ec ti on :r aw ‐l at ex :ˋ i ns ta nc eˋ Y E S The error handling strategies can be used. Error handler strat- egy name Description • Bui lt- in* • De fa ul t* • Extra co nfig* Log Strategy Log error and do not interrupt job Yes Y es Throw Strategy Java API ElasticJob currently provides TracingConfiguration based on database in the configuration. De‐ velopers can also extend it through SPI. // init DataSource DataSource dataSource = ...; // define

connection(%d) have re‐ leased. Please consider increasing the ‘maxPoolSize’of the data sources or de‐ creasing the ‘max‐connections‐size‐per‐query’in properties. 1 3 0 0 1 0 8 0 0 0 SQL execution Illegal username or password. 9.4. 错误码 436 Apache ShardingSphere document 功能异常 数据分片 Ve nd or Co de S QL S ta te 错误信息 2 00 00 4 2S 02 %s configuration does not exist in database ‘%s’. 2 00 01 4 2S configured data sources ‘%s’. 续下页 9.4. 错误码 437 Apache ShardingSphere document 表 2 – 接上页 Ve nd or Co de S QL S ta te 错误信息 2 00 56 4 40 00 Please check your sharding conditions ‘%s’to avoid same record in