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前言何为PostgreSQL?PostgreSQL简史格式约定更多信息臭虫汇报指导I. 教程章1. 从头开始1.1. 安装1.2. 体系基本概念1.3. 创建一个数据库1.4. 访问数据库章2. SQL语言2.1. 介绍2.2. 概念2.3. 创建新表2.4. 向表中添加行2.5. 查询一个表2.6. 表间链接2.7. 聚集函数2.8. 更新2.9. 删除章3. 高级特性3.1. 介绍3.2. 视图3.3. 外键3.4. 事务3.5. 窗口函数3.6. 继承3.7. 结论II. SQL语言章4. SQL语法4.1. 词法结构4.2. 值表达式4.3. 调用函数章5. 数据定义5.1. 表的基本概念5.2. 缺省值5.3. 约束5.4. 系统字段5.5. 修改表5.6. 权限5.7. 模式5.8. 继承5.9. 分区5.10. 其它数据库对象5.11. 依赖性跟踪章 6. 数据操作6.1. 插入数据6.2. 更新数据6.3. 删除数据章7. 查询7.1. 概述7.2. 表表达式7.3. 选择列表7.4. 组合查询7.5. 行排序7.6. LIMIT和OFFSET7.7. VALUES列表7.8. WITH的查询(公用表表达式)章8. 数据类型8.1. 数值类型8.2. 货币类型8.3. 字符类型8.4. 二进制数据类型8.5. 日期/时间类型8.6. 布尔类型8.7. 枚举类型8.8. 几何类型8.9. 网络地址类型8.10. 位串类型8.11. 文本搜索类型8.12. UUID类型8.13. XML类型8.14. 数组8.15. 复合类型8.16. 对象标识符类型8.17. 伪类型章 9. 函数和操作符9.1. 逻辑操作符9.2. 比较操作符9.3. 数学函数和操作符9.4. 字符串函数和操作符9.5. 二进制字符串函数和操作符9.6. 位串函数和操作符9.7. 模式匹配9.8. 数据类型格式化函数9.9. 时间/日期函数和操作符9.10. 支持枚举函数9.11. 几何函数和操作符9.12. 网络地址函数和操作符9.13. 文本检索函数和操作符9.14. XML函数9.15. 序列操作函数9.16. 条件表达式9.17. 数组函数和操作符9.18. 聚合函数9.19. 窗口函数9.20. 子查询表达式9.21. 行和数组比较9.22. 返回集合的函数9.23. 系统信息函数9.24. 系统管理函数9.25. 触发器函数章10. 类型转换10.3. 函数10.2. 操作符10.1. 概述10.4. 值存储10.5. UNION章11. 索引11.1. 介绍11.2. 索引类型11.3. 多字段索引11.4. 索引和ORDER BY11.5. 组合多个索引11.6. 唯一索引11.7. 表达式上的索引11.8. 部分索引11.9. 操作类和操作簇11.10. 检查索引的使用章12. Full Text Search12.1. Introduction12.2. Tables and Indexes12.3. Controlling Text Search12.4. Additional Features12.5. Parsers12.6. Dictionaries12.7. Configuration Example12.8. Testing and Debugging Text Search12.9. GiST and GIN Index Types12.10. psql Support12.11. Limitations12.12. Migration from Pre-8.3 Text Search章13. 并发控制13.1. 介绍13.2. 事务隔离13.3. 明确锁定13.4. 应用层数据完整性检查13.5. 锁和索引章14. 性能提升技巧14.1. 使用EXPLAIN14.2. 规划器使用的统计信息14.3. 用明确的JOIN语句控制规划器14.4. 向数据库中添加记录14.5. 非持久性设置III. 服务器管理章15. 安装指导15.1. 简版15.2. 要求15.3. 获取源码15.4. 升级15.5. 安装过程15.6. 安装后的设置15.7. 支持的平台15.8. 特殊平台的要求章16. Installation from Source Code on Windows16.1. Building with Visual C++ or the Platform SDK16.2. Building libpq with Visual C++ or Borland C++章17. 服务器安装和操作17.1. PostgreSQL用户帐户17.2. 创建数据库集群17.3. 启动数据库服务器17.4. 管理内核资源17.5. 关闭服务17.6. 防止服务器欺骗17.7. 加密选项17.8. 用SSL进行安全的TCP/IP连接17.9. Secure TCP/IP Connections with SSH Tunnels章18. 服务器配置18.1. 设置参数18.2. 文件位置18.3. 连接和认证18.4. 资源消耗18.5. 预写式日志18.6. 查询规划18.7. 错误报告和日志18.8. 运行时统计18.9. 自动清理18.10. 客户端连接缺省18.12. 版本和平台兼容性18.11. 锁管理18.13. 预置选项18.14. 自定义的选项18.15. 开发人员选项18.16. 短选项章19. 用户认证19.1. pg_hba.conf 文件19.2. 用户名映射19.3. 认证方法19.4. 用户认证章20. 数据库角色和权限20.1. 数据库角色20.2. 角色属性20.3. 权限20.4. 角色成员20.5. 函数和触发器章21. 管理数据库21.1. 概述21.2. 创建一个数据库21.3. 临时库21.4. 数据库配置21.5. 删除数据库21.6. 表空间章22. 本土化22.1. 区域支持22.2. 字符集支持章23. 日常数据库维护工作23.1. Routine Vacuuming日常清理23.2. 经常重建索引23.3. 日志文件维护章24. 备份和恢复24.1. SQL转储24.2. 文件系统级别的备份24.3. 在线备份以及即时恢复(PITR)24.4. 版本间迁移章25. 高可用性与负载均衡,复制25.1. 不同解决方案的比较25.2. 日志传送备份服务器25.3. 失效切换25.4. 日志传送的替代方法25.5. 热备章26. 恢复配置26.1. 归档恢复设置26.2. 恢复目标设置26.3. 备服务器设置章27. 监控数据库的活动27.1. 标准Unix工具27.2. 统计收集器27.3. 查看锁27.4. 动态跟踪章28. 监控磁盘使用情况28.1. 判断磁盘的使用量28.2. 磁盘满导致的失效章29. 可靠性和预写式日志29.1. 可靠性29.2. 预写式日志(WAL)29.3. 异步提交29.4. WAL配置29.5. WAL内部章30. Regression Tests30.1. Running the Tests30.2. Test Evaluation30.3. Variant Comparison Files30.4. Test Coverage ExaminationIV. 客户端接口章31. libpq-C库31.1. 数据库联接函数31.2. 连接状态函数31.3. 命令执行函数31.4. 异步命令处理31.5. 取消正在处理的查询31.6. 捷径接口31.7. 异步通知31.8. 与COPY命令相关的函数31.9. Control Functions 控制函数31.10. 其他函数31.11. 注意信息处理31.12. 事件系统31.13. 环境变量31.14. 口令文件31.15. 连接服务的文件31.16. LDAP查找连接参数31.17. SSL支持31.18. 在多线程程序里的行为31.19. 制作libpq程序31.20. 例子程序章32. 大对象32.1. 介绍32.2. 实现特点32.3. 客户端接口32.4. 服务器端函数32.5. 例子程序章33. ECPG - Embedded SQL in C33.1. The Concept33.2. Connecting to the Database Server33.3. Closing a Connection33.4. Running SQL Commands33.5. Choosing a Connection33.6. Using Host Variables33.7. Dynamic SQL33.8. pgtypes library33.9. Using Descriptor Areas33.10. Informix compatibility mode33.11. Error Handling33.12. Preprocessor directives33.13. Processing Embedded SQL Programs33.14. Library Functions33.15. Internals章34. 信息模式34.1. 关于这个模式34.2. 数据类型34.3. information_schema_catalog_name34.4. administrable_role_authorizations34.5. applicable_roles34.6. attributes34.7. check_constraint_routine_usage34.8. check_constraints34.9. column_domain_usage34.10. column_privileges34.11. column_udt_usage34.12. 字段34.13. constraint_column_usage34.14. constraint_table_usage34.15. data_type_privileges34.16. domain_constraints34.18. domains34.17. domain_udt_usage34.19. element_types34.20. enabled_roles34.21. foreign_data_wrapper_options34.22. foreign_data_wrappers34.23. foreign_server_options34.24. foreign_servers34.25. key_column_usage34.26. parameters34.27. referential_constraints34.28. role_column_grants34.29. role_routine_grants34.30. role_table_grants34.31. role_usage_grants34.32. routine_privileges34.33. routines34.34. schemata34.35. sequences34.36. sql_features34.37. sql_implementation_info34.38. sql_languages34.39. sql_packages34.40. sql_parts34.41. sql_sizing34.42. sql_sizing_profiles34.43. table_constraints34.44. table_privileges34.45. tables34.46. triggered_update_columns34.47. 触发器34.48. usage_privileges34.49. user_mapping_options34.50. user_mappings34.51. view_column_usage34.52. view_routine_usage34.53. view_table_usage34.54. 视图V. 服务器端编程章35. 扩展SQL35.1. 扩展性是如何实现的35.2. PostgreSQL类型系统35.3. User-Defined Functions35.4. Query Language (SQL) Functions35.5. Function Overloading35.6. Function Volatility Categories35.7. Procedural Language Functions35.8. Internal Functions35.9. C-Language Functions35.10. User-Defined Aggregates35.11. User-Defined Types35.12. User-Defined Operators35.13. Operator Optimization Information35.14. Interfacing Extensions To Indexes35.15. 用C++扩展章36. 触发器36.1. 触发器行为概述36.3. 用 C 写触发器36.2. 数据改变的可视性36.4. 一个完整的例子章37. 规则系统37.1. The Query Tree37.2. 视图和规则系统37.3. 在INSERT,UPDATE和DELETE上的规则37.4. 规则和权限37.5. 规则和命令状态37.6. 规则与触发器得比较章38. Procedural Languages38.1. Installing Procedural Languages章39. PL/pgSQL - SQL过程语言39.1. 概述39.2. PL/pgSQL的结构39.3. 声明39.4. 表达式39.5. 基本语句39.6. 控制结构39.7. 游标39.8. 错误和消息39.9. 触发器过程39.10. PL/pgSQL Under the Hood39.11. 开发PL/pgSQL的一些提示39.12. 从OraclePL/SQL 进行移植章40. PL/Tcl - Tcl Procedural Language40.1. Overview40.2. PL/Tcl Functions and Arguments40.3. Data Values in PL/Tcl40.4. Global Data in PL/Tcl40.5. Database Access from PL/Tcl40.6. Trigger Procedures in PL/Tcl40.7. Modules and the unknown command40.8. Tcl Procedure Names章41. PL/Perl - Perl Procedural Language41.1. PL/Perl Functions and Arguments41.2. Data Values in PL/Perl41.3. Built-in Functions41.4. Global Values in PL/Perl41.6. PL/Perl Triggers41.5. Trusted and Untrusted PL/Perl41.7. PL/Perl Under the Hood章42. PL/Python - Python Procedural Language42.1. Python 2 vs. Python 342.2. PL/Python Functions42.3. Data Values42.4. Sharing Data42.5. Anonymous Code Blocks42.6. Trigger Functions42.7. Database Access42.8. Utility Functions42.9. Environment Variables章43. Server Programming Interface43.1. Interface FunctionsSpi-spi-connectSpi-spi-finishSpi-spi-pushSpi-spi-popSpi-spi-executeSpi-spi-execSpi-spi-execute-with-argsSpi-spi-prepareSpi-spi-prepare-cursorSpi-spi-prepare-paramsSpi-spi-getargcountSpi-spi-getargtypeidSpi-spi-is-cursor-planSpi-spi-execute-planSpi-spi-execute-plan-with-paramlistSpi-spi-execpSpi-spi-cursor-openSpi-spi-cursor-open-with-argsSpi-spi-cursor-open-with-paramlistSpi-spi-cursor-findSpi-spi-cursor-fetchSpi-spi-cursor-moveSpi-spi-scroll-cursor-fetchSpi-spi-scroll-cursor-moveSpi-spi-cursor-closeSpi-spi-saveplan43.2. Interface Support FunctionsSpi-spi-fnameSpi-spi-fnumberSpi-spi-getvalueSpi-spi-getbinvalSpi-spi-gettypeSpi-spi-gettypeidSpi-spi-getrelnameSpi-spi-getnspname43.3. Memory ManagementSpi-spi-pallocSpi-reallocSpi-spi-pfreeSpi-spi-copytupleSpi-spi-returntupleSpi-spi-modifytupleSpi-spi-freetupleSpi-spi-freetupletableSpi-spi-freeplan43.4. Visibility of Data Changes43.5. ExamplesVI. 参考手册I. SQL命令Sql-abortSql-alteraggregateSql-alterconversionSql-alterdatabaseSql-alterdefaultprivilegesSql-alterdomainSql-alterforeigndatawrapperSql-alterfunctionSql-altergroupSql-alterindexSql-alterlanguageSql-alterlargeobjectSql-alteroperatorSql-alteropclassSql-alteropfamilySql-alterroleSql-alterschemaSql-altersequenceSql-alterserverSql-altertableSql-altertablespaceSql-altertsconfigSql-altertsdictionarySql-altertsparserSql-altertstemplateSql-altertriggerSql-altertypeSql-alteruserSql-alterusermappingSql-alterviewSql-analyzeSql-beginSql-checkpointSql-closeSql-clusterSql-commentSql-commitSql-commit-preparedSql-copySql-createaggregateSql-createcastSql-createconstraintSql-createconversionSql-createdatabaseSql-createdomainSql-createforeigndatawrapperSql-createfunctionSql-creategroupSql-createindexSql-createlanguageSql-createoperatorSql-createopclassSql-createopfamilySql-createroleSql-createruleSql-createschemaSql-createsequenceSql-createserverSql-createtableSql-createtableasSql-createtablespaceSql-createtsconfigSql-createtsdictionarySql-createtsparserSql-createtstemplateSql-createtriggerSql-createtypeSql-createuserSql-createusermappingSql-createviewSql-deallocateSql-declareSql-deleteSql-discardSql-doSql-dropaggregateSql-dropcastSql-dropconversionSql-dropdatabaseSql-dropdomainSql-dropforeigndatawrapperSql-dropfunctionSql-dropgroupSql-dropindexSql-droplanguageSql-dropoperatorSql-dropopclassSql-dropopfamilySql-drop-ownedSql-droproleSql-dropruleSql-dropschemaSql-dropsequenceSql-dropserverSql-droptableSql-droptablespaceSql-droptsconfigSql-droptsdictionarySql-droptsparserSql-droptstemplateSql-droptriggerSql-droptypeSql-dropuserSql-dropusermappingSql-dropviewSql-endSql-executeSql-explainSql-fetchSql-grantSql-insertSql-listenSql-loadSql-lockSql-moveSql-notifySql-prepareSql-prepare-transactionSql-reassign-ownedSql-reindexSql-release-savepointSql-resetSql-revokeSql-rollbackSql-rollback-preparedSql-rollback-toSql-savepointSql-selectSql-selectintoSql-setSql-set-constraintsSql-set-roleSql-set-session-authorizationSql-set-transactionSql-showSql-start-transactionSql-truncateSql-unlistenSql-updateSql-vacuumSql-valuesII. 客户端应用程序App-clusterdbApp-createdbApp-createlangApp-createuserApp-dropdbApp-droplangApp-dropuserApp-ecpgApp-pgconfigApp-pgdumpApp-pg-dumpallApp-pgrestoreApp-psqlApp-reindexdbApp-vacuumdbIII. PostgreSQL服务器应用程序App-initdbApp-pgcontroldataApp-pg-ctlApp-pgresetxlogApp-postgresApp-postmasterVII. 内部章44. PostgreSQL内部概览44.1. 查询路径44.2. 连接是如何建立起来的44.3. 分析器阶段44.4. ThePostgreSQL规则系统44.5. 规划器/优化器44.6. 执行器章45. 系统表45.1. 概述45.2. pg_aggregate45.3. pg_am45.4. pg_amop45.5. pg_amproc45.6. pg_attrdef45.7. pg_attribute45.8. pg_authid45.9. pg_auth_members45.10. pg_cast45.11. pg_class45.12. pg_constraint45.13. pg_conversion45.14. pg_database45.15. pg_db_role_setting45.16. pg_default_acl45.17. pg_depend45.18. pg_description45.19. pg_enum45.20. pg_foreign_data_wrapper45.21. pg_foreign_server45.22. pg_index45.23. pg_inherits45.24. pg_language45.25. pg_largeobject45.26. pg_largeobject_metadata45.27. pg_namespace45.28. pg_opclass45.29. pg_operator45.30. pg_opfamily45.31. pg_pltemplate45.32. pg_proc45.33. pg_rewrite45.34. pg_shdepend45.35. pg_shdescription45.36. pg_statistic45.37. pg_tablespace45.38. pg_trigger45.39. pg_ts_config45.40. pg_ts_config_map45.41. pg_ts_dict45.42. pg_ts_parser45.43. pg_ts_template45.44. pg_type45.45. pg_user_mapping45.46. System Views45.47. pg_cursors45.48. pg_group45.49. pg_indexes45.50. pg_locks45.51. pg_prepared_statements45.52. pg_prepared_xacts45.53. pg_roles45.54. pg_rules45.55. pg_settings45.56. pg_shadow45.57. pg_stats45.58. pg_tables45.59. pg_timezone_abbrevs45.60. pg_timezone_names45.61. pg_user45.62. pg_user_mappings45.63. pg_views章46. Frontend/Backend Protocol46.1. Overview46.2. Message Flow46.3. Streaming Replication Protocol46.4. Message Data Types46.5. Message Formats46.6. Error and Notice Message Fields46.7. Summary of Changes since Protocol 2.047. PostgreSQL Coding Conventions47.1. Formatting47.2. Reporting Errors Within the Server47.3. Error Message Style Guide章48. Native Language Support48.1. For the Translator48.2. For the Programmer章49. Writing A Procedural Language Handler章50. Genetic Query Optimizer50.1. Query Handling as a Complex Optimization Problem50.2. Genetic Algorithms50.3. Genetic Query Optimization (GEQO) in PostgreSQL50.4. Further Reading章51. 索引访问方法接口定义51.1. 索引的系统表记录51.2. 索引访问方法函数51.3. 索引扫描51.4. 索引锁的考量51.5. 索引唯一性检查51.6. 索引开销估计函数章52. GiST Indexes52.1. Introduction52.2. Extensibility52.3. Implementation52.4. Examples52.5. Crash Recovery章53. GIN Indexes53.1. Introduction53.2. Extensibility53.3. Implementation53.4. GIN tips and tricks53.5. Limitations53.6. Examples章54. 数据库物理存储54.1. 数据库文件布局54.2. TOAST54.3. 自由空间映射54.4. 可见映射54.5. 数据库分页文件章55. BKI后端接口55.1. BKI 文件格式55.2. BKI命令55.3. 系统初始化的BKI文件的结构55.4. 例子章56. 规划器如何使用统计信息56.1. 行预期的例子VIII. 附录A. PostgreSQL错误代码B. 日期/时间支持B.1. 日期/时间输入解析B.2. 日期/时间关键字B.3. 日期/时间配置文件B.4. 日期单位的历史C. SQL关键字D. SQL ConformanceD.1. Supported FeaturesD.2. Unsupported FeaturesE. Release NotesRelease-0-01Release-0-02Release-0-03Release-1-0Release-1-01Release-1-02Release-1-09Release-6-0Release-6-1Release-6-1-1Release-6-2Release-6-2-1Release-6-3Release-6-3-1Release-6-3-2Release-6-4Release-6-4-1Release-6-4-2Release-6-5Release-6-5-1Release-6-5-2Release-6-5-3Release-7-0Release-7-0-1Release-7-0-2Release-7-0-3Release-7-1Release-7-1-1Release-7-1-2Release-7-1-3Release-7-2Release-7-2-1Release-7-2-2Release-7-2-3Release-7-2-4Release-7-2-5Release-7-2-6Release-7-2-7Release-7-2-8Release-7-3Release-7-3-1Release-7-3-10Release-7-3-11Release-7-3-12Release-7-3-13Release-7-3-14Release-7-3-15Release-7-3-16Release-7-3-17Release-7-3-18Release-7-3-19Release-7-3-2Release-7-3-20Release-7-3-21Release-7-3-3Release-7-3-4Release-7-3-5Release-7-3-6Release-7-3-7Release-7-3-8Release-7-3-9Release-7-4Release-7-4-1Release-7-4-10Release-7-4-11Release-7-4-12Release-7-4-13Release-7-4-14Release-7-4-15Release-7-4-16Release-7-4-17Release-7-4-18Release-7-4-19Release-7-4-2Release-7-4-20Release-7-4-21Release-7-4-22Release-7-4-23Release-7-4-24Release-7-4-25Release-7-4-26Release-7-4-27Release-7-4-28Release-7-4-29Release-7-4-3Release-7-4-30Release-7-4-4Release-7-4-5Release-7-4-6Release-7-4-7Release-7-4-8Release-7-4-9Release-8-0Release-8-0-1Release-8-0-10Release-8-0-11Release-8-0-12Release-8-0-13Release-8-0-14Release-8-0-15Release-8-0-16Release-8-0-17Release-8-0-18Release-8-0-19Release-8-0-2Release-8-0-20Release-8-0-21Release-8-0-22Release-8-0-23Release-8-0-24Release-8-0-25Release-8-0-26Release-8-0-3Release-8-0-4Release-8-0-5Release-8-0-6Release-8-0-7Release-8-0-8Release-8-0-9Release-8-1Release-8-1-1Release-8-1-10Release-8-1-11Release-8-1-12Release-8-1-13Release-8-1-14Release-8-1-15Release-8-1-16Release-8-1-17Release-8-1-18Release-8-1-19Release-8-1-2Release-8-1-20Release-8-1-21Release-8-1-22Release-8-1-23Release-8-1-3Release-8-1-4Release-8-1-5Release-8-1-6Release-8-1-7Release-8-1-8Release-8-1-9Release-8-2Release-8-2-1Release-8-2-10Release-8-2-11Release-8-2-12Release-8-2-13Release-8-2-14Release-8-2-15Release-8-2-16Release-8-2-17Release-8-2-18Release-8-2-19Release-8-2-2Release-8-2-20Release-8-2-21Release-8-2-3Release-8-2-4Release-8-2-5Release-8-2-6Release-8-2-7Release-8-2-8Release-8-2-9Release-8-3Release-8-3-1Release-8-3-10Release-8-3-11Release-8-3-12Release-8-3-13Release-8-3-14Release-8-3-15Release-8-3-2Release-8-3-3Release-8-3-4Release-8-3-5Release-8-3-6Release-8-3-7Release-8-3-8Release-8-3-9Release-8-4Release-8-4-1Release-8-4-2Release-8-4-3Release-8-4-4Release-8-4-5Release-8-4-6Release-8-4-7Release-8-4-8Release-9-0Release-9-0-1Release-9-0-2Release-9-0-3Release-9-0-4F. 额外提供的模块F.1. adminpackF.2. auto_explainF.3. btree_ginF.4. btree_gistF.5. chkpassF.6. citextF.7. cubeF.8. dblinkContrib-dblink-connectContrib-dblink-connect-uContrib-dblink-disconnectContrib-dblinkContrib-dblink-execContrib-dblink-openContrib-dblink-fetchContrib-dblink-closeContrib-dblink-get-connectionsContrib-dblink-error-messageContrib-dblink-send-queryContrib-dblink-is-busyContrib-dblink-get-notifyContrib-dblink-get-resultContrib-dblink-cancel-queryContrib-dblink-get-pkeyContrib-dblink-build-sql-insertContrib-dblink-build-sql-deleteContrib-dblink-build-sql-updateF.9. dict_intF.10. dict_xsynF.11. earthdistanceF.12. fuzzystrmatchF.13. hstoreF.14. intaggF.15. intarrayF.16. isnF.17. loF.18. ltreeF.19. oid2nameF.20. pageinspectF.21. passwordcheckF.22. pg_archivecleanupF.23. pgbenchF.24. pg_buffercacheF.25. pgcryptoF.26. pg_freespacemapF.27. pgrowlocksF.28. pg_standbyF.29. pg_stat_statementsF.30. pgstattupleF.31. pg_trgmF.32. pg_upgradeF.33. segF.34. spiF.35. sslinfoF.36. tablefuncF.37. test_parserF.38. tsearch2F.39. unaccentF.40. uuid-osspF.41. vacuumloF.42. xml2G. 外部项目G.1. 客户端接口G.2. 过程语言G.3. 扩展H. The Source Code RepositoryH.1. Getting The Source Via GitI. 文档I.1. DocBookI.2. 工具集I.3. 制作文档I.4. 文档写作I.5. 风格指导J. 首字母缩略词参考书目BookindexIndex
文字

35.4. Query Language (SQL) Functions

SQL functions execute an arbitrary list of SQL statements, returning the result of the last query in the list. In the simple (non-set) case, the first row of the last query's result will be returned. (Bear in mind that "the first row" of a multirow result is not well-defined unless you use ORDER BY.) If the last query happens to return no rows at all, the null value will be returned.

Alternatively, an SQL function can be declared to return a set, by specifying the function's return type as SETOF sometype, or equivalently by declaring it as RETURNS TABLE(columns). In this case all rows of the last query's result are returned. Further details appear below.

The body of an SQL function must be a list of SQL statements separated by semicolons. A semicolon after the last statement is optional. Unless the function is declared to return void, the last statement must be a SELECT, or an INSERT, UPDATE, or DELETE that has a RETURNING clause.

Any collection of commands in the SQL language can be packaged together and defined as a function. Besides SELECT queries, the commands can include data modification queries (INSERT, UPDATE, and DELETE), as well as other SQL commands. (The only exception is that you cannot put BEGIN, COMMIT, ROLLBACK, or SAVEPOINT commands into a SQL function.) However, the final command must be a SELECT or have a RETURNING clause that returns whatever is specified as the function's return type. Alternatively, if you want to define a SQL function that performs actions but has no useful value to return, you can define it as returning void. For example, this function removes rows with negative salaries from the emp table:

CREATE FUNCTION clean_emp() RETURNS void AS '
    DELETE FROM emp
        WHERE salary < 0;
' LANGUAGE SQL;

SELECT clean_emp();

 clean_emp
-----------

(1 row)

The syntax of the CREATE FUNCTION command requires the function body to be written as a string constant. It is usually most convenient to use dollar quoting (see Section 4.1.2.4) for the string constant. If you choose to use regular single-quoted string constant syntax, you must double single quote marks (') and backslashes (\) (assuming escape string syntax) in the body of the function (see Section 4.1.2.1).

Arguments to the SQL function are referenced in the function body using the syntax $n: $1 refers to the first argument, $2 to the second, and so on. If an argument is of a composite type, then the dot notation, e.g., $1.name, can be used to access attributes of the argument. The arguments can only be used as data values, not as identifiers. Thus for example this is reasonable:

INSERT INTO mytable VALUES ($1);

but this will not work:

INSERT INTO $1 VALUES (42);

35.4.1. SQL Functions on Base Types

The simplest possible SQL function has no arguments and simply returns a base type, such as integer:

CREATE FUNCTION one() RETURNS integer AS $$
    SELECT 1 AS result;
$$ LANGUAGE SQL;

-- Alternative syntax for string literal:
CREATE FUNCTION one() RETURNS integer AS '
    SELECT 1 AS result;
' LANGUAGE SQL;

SELECT one();

 one
-----
   1

Notice that we defined a column alias within the function body for the result of the function (with the name result), but this column alias is not visible outside the function. Hence, the result is labeled one instead of result.

It is almost as easy to define SQL functions that take base types as arguments. In the example below, notice how we refer to the arguments within the function as $1 and $2.

CREATE FUNCTION add_em(integer, integer) RETURNS integer AS $$
    SELECT $1 + $2;
$$ LANGUAGE SQL;

SELECT add_em(1, 2) AS answer;

 answer
--------
      3

Here is a more useful function, which might be used to debit a bank account:

CREATE FUNCTION tf1 (integer, numeric) RETURNS integer AS $$
    UPDATE bank
        SET balance = balance - $2
        WHERE accountno = $1;
    SELECT 1;
$$ LANGUAGE SQL;

A user could execute this function to debit account 17 by $100.00 as follows:

SELECT tf1(17, 100.0);

In practice one would probably like a more useful result from the function than a constant 1, so a more likely definition is:

CREATE FUNCTION tf1 (integer, numeric) RETURNS numeric AS $$
    UPDATE bank
        SET balance = balance - $2
        WHERE accountno = $1;
    SELECT balance FROM bank WHERE accountno = $1;
$$ LANGUAGE SQL;

which adjusts the balance and returns the new balance. The same thing could be done in one command using RETURNING:

CREATE FUNCTION tf1 (integer, numeric) RETURNS numeric AS $$
    UPDATE bank
        SET balance = balance - $2
        WHERE accountno = $1
    RETURNING balance;
$$ LANGUAGE SQL;

35.4.2. SQL Functions on Composite Types

When writing functions with arguments of composite types, we must not only specify which argument we want (as we did above with $1 and $2) but also the desired attribute (field) of that argument. For example, suppose that emp is a table containing employee data, and therefore also the name of the composite type of each row of the table. Here is a function double_salary that computes what someone's salary would be if it were doubled:

CREATE TABLE emp (
    name        text,
    salary      numeric,
    age         integer,
    cubicle     point
);

INSERT INTO emp VALUES ('Bill', 4200, 45, '(2,1)');

CREATE FUNCTION double_salary(emp) RETURNS numeric AS $$
    SELECT $1.salary * 2 AS salary;
$$ LANGUAGE SQL;

SELECT name, double_salary(emp.*) AS dream
    FROM emp
    WHERE emp.cubicle ~= point '(2,1)';

 name | dream
------+-------
 Bill |  8400

Notice the use of the syntax $1.salary to select one field of the argument row value. Also notice how the calling SELECT command uses * to select the entire current row of a table as a composite value. The table row can alternatively be referenced using just the table name, like this:

SELECT name, double_salary(emp) AS dream
    FROM emp
    WHERE emp.cubicle ~= point '(2,1)';

but this usage is deprecated since it's easy to get confused.

Sometimes it is handy to construct a composite argument value on-the-fly. This can be done with the ROW construct. For example, we could adjust the data being passed to the function:

SELECT name, double_salary(ROW(name, salary*1.1, age, cubicle)) AS dream
    FROM emp;

It is also possible to build a function that returns a composite type. This is an example of a function that returns a single emp row:

CREATE FUNCTION new_emp() RETURNS emp AS $$
    SELECT text 'None' AS name,
        1000.0 AS salary,
        25 AS age,
        point '(2,2)' AS cubicle;
$$ LANGUAGE SQL;

In this example we have specified each of the attributes with a constant value, but any computation could have been substituted for these constants.

Note two important things about defining the function:

  • The select list order in the query must be exactly the same as that in which the columns appear in the table associated with the composite type. (Naming the columns, as we did above, is irrelevant to the system.)

  • You must typecast the expressions to match the definition of the composite type, or you will get errors like this:

    ERROR:  function declared to return emp returns varchar instead of text at column 1

A different way to define the same function is:

CREATE FUNCTION new_emp() RETURNS emp AS $$
    SELECT ROW('None', 1000.0, 25, '(2,2)')::emp;
$$ LANGUAGE SQL;

Here we wrote a SELECT that returns just a single column of the correct composite type. This isn't really better in this situation, but it is a handy alternative in some cases — for example, if we need to compute the result by calling another function that returns the desired composite value.

We could call this function directly in either of two ways:

SELECT new_emp();

         new_emp
--------------------------
 (None,1000.0,25,"(2,2)")

SELECT * FROM new_emp();

 name | salary | age | cubicle
------+--------+-----+---------
 None | 1000.0 |  25 | (2,2)

The second way is described more fully in Section 35.4.7.

When you use a function that returns a composite type, you might want only one field (attribute) from its result. You can do that with syntax like this:

SELECT (new_emp()).name;

 name
------
 None

The extra parentheses are needed to keep the parser from getting confused. If you try to do it without them, you get something like this:

SELECT new_emp().name;
ERROR:  syntax error at or near "."
LINE 1: SELECT new_emp().name;
                        ^

Another option is to use functional notation for extracting an attribute. The simple way to explain this is that we can use the notations attribute(table) and table.attribute interchangeably.

SELECT name(new_emp());

 name
------
 None

-- This is the same as:
-- SELECT emp.name AS youngster FROM emp WHERE emp.age < 30;

SELECT name(emp) AS youngster FROM emp WHERE age(emp) < 30;

 youngster
-----------
 Sam
 Andy

Tip: The equivalence between functional notation and attribute notation makes it possible to use functions on composite types to emulate "computed fields". For example, using the previous definition for double_salary(emp), we can write

SELECT emp.name, emp.double_salary FROM emp;

An application using this wouldn't need to be directly aware that double_salary isn't a real column of the table. (You can also emulate computed fields with views.)

Another way to use a function returning a composite type is to pass the result to another function that accepts the correct row type as input:

CREATE FUNCTION getname(emp) RETURNS text AS $$
    SELECT $1.name;
$$ LANGUAGE SQL;

SELECT getname(new_emp());
 getname
---------
 None
(1 row)

Still another way to use a function that returns a composite type is to call it as a table function, as described in Section 35.4.7.

35.4.3. SQL Functions with Parameter Names

It is possible to attach names to a function's parameters, for example

CREATE FUNCTION tf1 (acct_no integer, debit numeric) RETURNS numeric AS $$
    UPDATE bank
        SET balance = balance - $2
        WHERE accountno = $1
    RETURNING balance;
$$ LANGUAGE SQL;

Here the first parameter has been given the name acct_no, and the second parameter the name debit. So far as the SQL function itself is concerned, these names are just decoration; you must still refer to the parameters as $1, $2, etc within the function body. (Some procedural languages let you use the parameter names instead.) However, attaching names to the parameters is useful for documentation purposes. When a function has many parameters, it is also useful to use the names while calling the function, as described in Section 4.3.

35.4.4. SQL Functions with Output Parameters

An alternative way of describing a function's results is to define it with output parameters, as in this example:

CREATE FUNCTION add_em (IN x int, IN y int, OUT sum int)
AS 'SELECT $1 + $2'
LANGUAGE SQL;

SELECT add_em(3,7);
 add_em
--------
     10
(1 row)

This is not essentially different from the version of add_em shown in Section 35.4.1. The real value of output parameters is that they provide a convenient way of defining functions that return several columns. For example,

CREATE FUNCTION sum_n_product (x int, y int, OUT sum int, OUT product int)
AS 'SELECT $1 + $2, $1 * $2'
LANGUAGE SQL;

 SELECT * FROM sum_n_product(11,42);
 sum | product
-----+---------
  53 |     462
(1 row)

What has essentially happened here is that we have created an anonymous composite type for the result of the function. The above example has the same end result as

CREATE TYPE sum_prod AS (sum int, product int);

CREATE FUNCTION sum_n_product (int, int) RETURNS sum_prod
AS 'SELECT $1 + $2, $1 * $2'
LANGUAGE SQL;

but not having to bother with the separate composite type definition is often handy. Notice that the names attached to the output parameters are not just decoration, but determine the column names of the anonymous composite type. (If you omit a name for an output parameter, the system will choose a name on its own.)

Notice that output parameters are not included in the calling argument list when invoking such a function from SQL. This is because PostgreSQL considers only the input parameters to define the function's calling signature. That means also that only the input parameters matter when referencing the function for purposes such as dropping it. We could drop the above function with either of

DROP FUNCTION sum_n_product (x int, y int, OUT sum int, OUT product int);
DROP FUNCTION sum_n_product (int, int);

Parameters can be marked as IN (the default), OUT, INOUT, or VARIADIC. An INOUT parameter serves as both an input parameter (part of the calling argument list) and an output parameter (part of the result record type). VARIADIC parameters are input parameters, but are treated specially as described next.

35.4.5. SQL Functions with Variable Numbers of Arguments

SQL functions can be declared to accept variable numbers of arguments, so long as all the "optional" arguments are of the same data type. The optional arguments will be passed to the function as an array. The function is declared by marking the last parameter as VARIADIC; this parameter must be declared as being of an array type. For example:

CREATE FUNCTION mleast(VARIADIC arr numeric[]) RETURNS numeric AS $$
    SELECT min($1[i]) FROM generate_subscripts($1, 1) g(i);
$$ LANGUAGE SQL;

SELECT mleast(10, -1, 5, 4.4);
 mleast 
--------
     -1
(1 row)

Effectively, all the actual arguments at or beyond the VARIADIC position are gathered up into a one-dimensional array, as if you had written

SELECT mleast(ARRAY[10, -1, 5, 4.4]);    -- doesn't work

You can't actually write that, though — or at least, it will not match this function definition. A parameter marked VARIADIC matches one or more occurrences of its element type, not of its own type.

Sometimes it is useful to be able to pass an already-constructed array to a variadic function; this is particularly handy when one variadic function wants to pass on its array parameter to another one. You can do that by specifying VARIADIC in the call:

SELECT mleast(VARIADIC ARRAY[10, -1, 5, 4.4]);

This prevents expansion of the function's variadic parameter into its element type, thereby allowing the array argument value to match normally. VARIADIC can only be attached to the last actual argument of a function call.

The array element parameters generated from a variadic parameter are treated as not having any names of their own. This means it is not possible to call a variadic function using named arguments (Section 4.3), except when you specify VARIADIC. For example, this will work:

SELECT mleast(VARIADIC arr := ARRAY[10, -1, 5, 4.4]);

but not these:

SELECT mleast(arr := 10);
SELECT mleast(arr := ARRAY[10, -1, 5, 4.4]);

35.4.6. SQL Functions with Default Values for Arguments

Functions can be declared with default values for some or all input arguments. The default values are inserted whenever the function is called with insufficiently many actual arguments. Since arguments can only be omitted from the end of the actual argument list, all parameters after a parameter with a default value have to have default values as well. (Although the use of named argument notation could allow this restriction to be relaxed, it's still enforced so that positional argument notation works sensibly.)

For example:

CREATE FUNCTION foo(a int, b int DEFAULT 2, c int DEFAULT 3)
RETURNS int
LANGUAGE SQL
AS $$
    SELECT $1 + $2 + $3;
$$;

SELECT foo(10, 20, 30);
 foo 
-----
  60
(1 row)

SELECT foo(10, 20);
 foo 
-----
  33
(1 row)

SELECT foo(10);
 foo 
-----
  15
(1 row)

SELECT foo();  -- fails since there is no default for the first argument
ERROR:  function foo() does not exist

The = sign can also be used in place of the key word DEFAULT.

35.4.7. SQL Functions as Table Sources

All SQL functions can be used in the FROM clause of a query, but it is particularly useful for functions returning composite types. If the function is defined to return a base type, the table function produces a one-column table. If the function is defined to return a composite type, the table function produces a column for each attribute of the composite type.

Here is an example:

CREATE TABLE foo (fooid int, foosubid int, fooname text);
INSERT INTO foo VALUES (1, 1, 'Joe');
INSERT INTO foo VALUES (1, 2, 'Ed');
INSERT INTO foo VALUES (2, 1, 'Mary');

CREATE FUNCTION getfoo(int) RETURNS foo AS $$
    SELECT * FROM foo WHERE fooid = $1;
$$ LANGUAGE SQL;

SELECT *, upper(fooname) FROM getfoo(1) AS t1;

 fooid | foosubid | fooname | upper
-------+----------+---------+-------
     1 |        1 | Joe     | JOE
(1 row)

As the example shows, we can work with the columns of the function's result just the same as if they were columns of a regular table.

Note that we only got one row out of the function. This is because we did not use SETOF. That is described in the next section.

35.4.8. SQL Functions Returning Sets

When an SQL function is declared as returning SETOF sometype, the function's final query is executed to completion, and each row it outputs is returned as an element of the result set.

This feature is normally used when calling the function in the FROM clause. In this case each row returned by the function becomes a row of the table seen by the query. For example, assume that table foo has the same contents as above, and we say:

CREATE FUNCTION getfoo(int) RETURNS SETOF foo AS $$
    SELECT * FROM foo WHERE fooid = $1;
$$ LANGUAGE SQL;

SELECT * FROM getfoo(1) AS t1;

Then we would get:

 fooid | foosubid | fooname
-------+----------+---------
     1 |        1 | Joe
     1 |        2 | Ed
(2 rows)

It is also possible to return multiple rows with the columns defined by output parameters, like this:

CREATE TABLE tab (y int, z int);
INSERT INTO tab VALUES (1, 2), (3, 4), (5, 6), (7, 8);

CREATE FUNCTION sum_n_product_with_tab (x int, OUT sum int, OUT product int)
RETURNS SETOF record
AS $$
    SELECT $1 + tab.y, $1 * tab.y FROM tab;
$$ LANGUAGE SQL;

SELECT * FROM sum_n_product_with_tab(10);
 sum | product
-----+---------
  11 |      10
  13 |      30
  15 |      50
  17 |      70
(4 rows)

The key point here is that you must write RETURNS SETOF record to indicate that the function returns multiple rows instead of just one. If there is only one output parameter, write that parameter's type instead of record.

Currently, functions returning sets can also be called in the select list of a query. For each row that the query generates by itself, the function returning set is invoked, and an output row is generated for each element of the function's result set. Note, however, that this capability is deprecated and might be removed in future releases. The following is an example function returning a set from the select list:

CREATE FUNCTION listchildren(text) RETURNS SETOF text AS $$
    SELECT name FROM nodes WHERE parent = $1
$$ LANGUAGE SQL;

SELECT * FROM nodes;
   name    | parent
-----------+--------
 Top       |
 Child1    | Top
 Child2    | Top
 Child3    | Top
 SubChild1 | Child1
 SubChild2 | Child1
(6 rows)

SELECT listchildren('Top');
 listchildren
--------------
 Child1
 Child2
 Child3
(3 rows)

SELECT name, listchildren(name) FROM nodes;
  name  | listchildren
--------+--------------
 Top    | Child1
 Top    | Child2
 Top    | Child3
 Child1 | SubChild1
 Child1 | SubChild2
(5 rows)

In the last SELECT, notice that no output row appears for Child2, Child3, etc. This happens because listchildren returns an empty set for those arguments, so no result rows are generated.

Note: If a function's last command is INSERT, UPDATE, or DELETE with RETURNING, that command will always be executed to completion, even if the function is not declared with SETOF or the calling query does not fetch all the result rows. Any extra rows produced by the RETURNING clause are silently dropped, but the commanded table modifications still happen (and are all completed before returning from the function).

35.4.9. SQL Functions Returning TABLE

There is another way to declare a function as returning a set, which is to use the syntax RETURNS TABLE(columns). This is equivalent to using one or more OUT parameters plus marking the function as returning SETOF record (or SETOF a single output parameter's type, as appropriate). This notation is specified in recent versions of the SQL standard, and thus may be more portable than using SETOF.

For example, the preceding sum-and-product example could also be done this way:

CREATE FUNCTION sum_n_product_with_tab (x int)
RETURNS TABLE(sum int, product int) AS $$
    SELECT $1 + tab.y, $1 * tab.y FROM tab;
$$ LANGUAGE SQL;

It is not allowed to use explicit OUT or INOUT parameters with the RETURNS TABLE notation — you must put all the output columns in the TABLE list.

35.4.10. Polymorphic SQL Functions

SQL functions can be declared to accept and return the polymorphic types anyelement, anyarray, anynonarray, and anyenum. See Section 35.2.5 for a more detailed explanation of polymorphic functions. Here is a polymorphic function make_array that builds up an array from two arbitrary data type elements:

CREATE FUNCTION make_array(anyelement, anyelement) RETURNS anyarray AS $$
    SELECT ARRAY[$1, $2];
$$ LANGUAGE SQL;

SELECT make_array(1, 2) AS intarray, make_array('a'::text, 'b') AS textarray;
 intarray | textarray
----------+-----------
 {1,2}    | {a,b}
(1 row)

Notice the use of the typecast 'a'::text to specify that the argument is of type text. This is required if the argument is just a string literal, since otherwise it would be treated as type unknown, and array of unknown is not a valid type. Without the typecast, you will get errors like this:

ERROR:  could not determine polymorphic type because input has type "unknown"

It is permitted to have polymorphic arguments with a fixed return type, but the converse is not. For example:

CREATE FUNCTION is_greater(anyelement, anyelement) RETURNS boolean AS $$
    SELECT $1 > $2;
$$ LANGUAGE SQL;

SELECT is_greater(1, 2);
 is_greater
------------
 f
(1 row)

CREATE FUNCTION invalid_func() RETURNS anyelement AS $$
    SELECT 1;
$$ LANGUAGE SQL;
ERROR:  cannot determine result data type
DETAIL:  A function returning a polymorphic type must have at least one polymorphic argument.

Polymorphism can be used with functions that have output arguments. For example:

CREATE FUNCTION dup (f1 anyelement, OUT f2 anyelement, OUT f3 anyarray)
AS 'select $1, array[$1,$1]' LANGUAGE SQL;

SELECT * FROM dup(22);
 f2 |   f3
----+---------
 22 | {22,22}
(1 row)

Polymorphism can also be used with variadic functions. For example:

CREATE FUNCTION anyleast (VARIADIC anyarray) RETURNS anyelement AS $$
    SELECT min($1[i]) FROM generate_subscripts($1, 1) g(i);
$$ LANGUAGE SQL;

SELECT anyleast(10, -1, 5, 4);
 anyleast 
----------
       -1
(1 row)

SELECT anyleast('abc'::text, 'def');
 anyleast 
----------
 abc
(1 row)

CREATE FUNCTION concat(text, VARIADIC anyarray) RETURNS text AS $$
    SELECT array_to_string($2, $1);
$$ LANGUAGE SQL;

SELECT concat('|', 1, 4, 2);
 concat 
--------
 1|4|2
(1 row)

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