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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OFFSET 7.7. 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 BY 11.5. 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 Search 12.1. Introduction 12.2. Tables and Indexes 12.3. Controlling Text Search 12.4. Additional Features 12.5. Parsers 12.6. Dictionaries 12.7. Configuration Example 12.8. Testing and Debugging Text Search 12.9. GiST and GIN Index Types 12.10. psql Support 12.11. Limitations 12.12. 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EXPLAIN 14.2. 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 Windows 16.1. Building with Visual C++ or the Platform SDK 16.2. 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 Tests 30.1. Running the Tests 30.2. Test Evaluation 30.3. Variant Comparison Files 30.4. Test Coverage Examination IV. 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 C 33.1. The Concept 33.2. Connecting to the Database Server 33.3. Closing a Connection 33.4. Running SQL Commands 33.5. Choosing a Connection 33.6. Using Host Variables 33.7. Dynamic SQL 33.8. pgtypes library 33.9. Using Descriptor Areas 33.10. Informix compatibility mode 33.11. Error Handling 33.12. Preprocessor directives 33.13. Processing Embedded SQL Programs 33.14. Library Functions 33.15. 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_name 34.4. administrable_role_authorizations 34.5. applicable_roles 34.6. attributes 34.7. check_constraint_routine_usage 34.8. check_constraints 34.9. column_domain_usage 34.10. column_privileges 34.11. column_udt_usage 34.12. 字段 34.13. constraint_column_usage 34.14. constraint_table_usage 34.15. data_type_privileges 34.16. domain_constraints 34.18. domains 34.17. domain_udt_usage 34.19. element_types 34.20. enabled_roles 34.21. foreign_data_wrapper_options 34.22. foreign_data_wrappers 34.23. foreign_server_options 34.24. foreign_servers 34.25. key_column_usage 34.26. parameters 34.27. referential_constraints 34.28. role_column_grants 34.29. role_routine_grants 34.30. role_table_grants 34.31. role_usage_grants 34.32. routine_privileges 34.33. routines 34.34. schemata 34.35. sequences 34.36. sql_features 34.37. sql_implementation_info 34.38. sql_languages 34.39. sql_packages 34.40. sql_parts 34.41. sql_sizing 34.42. sql_sizing_profiles 34.43. table_constraints 34.44. table_privileges 34.45. tables 34.46. triggered_update_columns 34.47. 触发器 34.48. usage_privileges 34.49. user_mapping_options 34.50. user_mappings 34.51. view_column_usage 34.52. view_routine_usage 34.53. view_table_usage 34.54. 视图 V. 服务器端编程 章35. 扩展SQL 35.1. 扩展性是如何实现的 35.2. PostgreSQL类型系统 35.3. User-Defined Functions 35.4. Query Language (SQL) Functions 35.5. Function Overloading 35.6. Function Volatility Categories 35.7. Procedural Language Functions 35.8. Internal Functions 35.9. C-Language Functions 35.10. User-Defined Aggregates 35.11. User-Defined Types 35.12. User-Defined Operators 35.13. Operator Optimization Information 35.14. Interfacing Extensions To Indexes 35.15. 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 Tree 37.2. 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 Languages 38.1. 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 Hood 39.11. 开发PL/pgSQL的一些提示 39.12. 从OraclePL/SQL 进行移植 章40. PL/Tcl - Tcl Procedural Language 40.1. Overview 40.2. PL/Tcl Functions and Arguments 40.3. Data Values in PL/Tcl 40.4. Global Data in PL/Tcl 40.5. Database Access from PL/Tcl 40.6. Trigger Procedures in PL/Tcl 40.7. Modules and the unknown command 40.8. Tcl Procedure Names 章41. PL/Perl - Perl Procedural Language 41.1. PL/Perl Functions and Arguments 41.2. Data Values in PL/Perl 41.3. Built-in Functions 41.4. Global Values in PL/Perl 41.6. PL/Perl Triggers 41.5. Trusted and Untrusted PL/Perl 41.7. PL/Perl Under the Hood 章42. PL/Python - Python Procedural Language 42.1. Python 2 vs. Python 3 42.2. PL/Python Functions 42.3. Data Values 42.4. Sharing Data 42.5. Anonymous Code Blocks 42.6. Trigger Functions 42.7. Database Access 42.8. Utility Functions 42.9. Environment Variables 章43. Server Programming Interface 43.1. Interface Functions Spi-spi-connect Spi-spi-finish Spi-spi-push Spi-spi-pop Spi-spi-execute Spi-spi-exec Spi-spi-execute-with-args Spi-spi-prepare Spi-spi-prepare-cursor Spi-spi-prepare-params Spi-spi-getargcount Spi-spi-getargtypeid Spi-spi-is-cursor-plan Spi-spi-execute-plan Spi-spi-execute-plan-with-paramlist Spi-spi-execp Spi-spi-cursor-open Spi-spi-cursor-open-with-args Spi-spi-cursor-open-with-paramlist Spi-spi-cursor-find Spi-spi-cursor-fetch Spi-spi-cursor-move Spi-spi-scroll-cursor-fetch Spi-spi-scroll-cursor-move Spi-spi-cursor-close Spi-spi-saveplan 43.2. Interface Support Functions Spi-spi-fname Spi-spi-fnumber Spi-spi-getvalue Spi-spi-getbinval Spi-spi-gettype Spi-spi-gettypeid Spi-spi-getrelname Spi-spi-getnspname 43.3. Memory Management Spi-spi-palloc Spi-realloc Spi-spi-pfree Spi-spi-copytuple Spi-spi-returntuple Spi-spi-modifytuple Spi-spi-freetuple Spi-spi-freetupletable Spi-spi-freeplan 43.4. Visibility of Data Changes 43.5. Examples VI. 参考手册 I. SQL命令 Sql-abort Sql-alteraggregate Sql-alterconversion Sql-alterdatabase Sql-alterdefaultprivileges Sql-alterdomain Sql-alterforeigndatawrapper Sql-alterfunction Sql-altergroup Sql-alterindex Sql-alterlanguage Sql-alterlargeobject Sql-alteroperator Sql-alteropclass Sql-alteropfamily Sql-alterrole Sql-alterschema Sql-altersequence Sql-alterserver Sql-altertable Sql-altertablespace Sql-altertsconfig Sql-altertsdictionary Sql-altertsparser Sql-altertstemplate Sql-altertrigger Sql-altertype Sql-alteruser Sql-alterusermapping Sql-alterview Sql-analyze Sql-begin Sql-checkpoint Sql-close Sql-cluster Sql-comment Sql-commit Sql-commit-prepared Sql-copy Sql-createaggregate Sql-createcast Sql-createconstraint Sql-createconversion Sql-createdatabase Sql-createdomain Sql-createforeigndatawrapper Sql-createfunction Sql-creategroup Sql-createindex Sql-createlanguage Sql-createoperator Sql-createopclass Sql-createopfamily Sql-createrole Sql-createrule Sql-createschema Sql-createsequence Sql-createserver Sql-createtable Sql-createtableas Sql-createtablespace Sql-createtsconfig Sql-createtsdictionary Sql-createtsparser Sql-createtstemplate Sql-createtrigger Sql-createtype Sql-createuser Sql-createusermapping Sql-createview Sql-deallocate Sql-declare Sql-delete Sql-discard Sql-do Sql-dropaggregate Sql-dropcast Sql-dropconversion Sql-dropdatabase Sql-dropdomain Sql-dropforeigndatawrapper Sql-dropfunction Sql-dropgroup Sql-dropindex Sql-droplanguage Sql-dropoperator Sql-dropopclass Sql-dropopfamily Sql-drop-owned Sql-droprole Sql-droprule Sql-dropschema Sql-dropsequence Sql-dropserver Sql-droptable Sql-droptablespace Sql-droptsconfig Sql-droptsdictionary Sql-droptsparser Sql-droptstemplate Sql-droptrigger Sql-droptype Sql-dropuser Sql-dropusermapping Sql-dropview Sql-end Sql-execute Sql-explain Sql-fetch Sql-grant Sql-insert Sql-listen Sql-load Sql-lock Sql-move Sql-notify Sql-prepare Sql-prepare-transaction Sql-reassign-owned Sql-reindex Sql-release-savepoint Sql-reset Sql-revoke Sql-rollback Sql-rollback-prepared Sql-rollback-to Sql-savepoint Sql-select Sql-selectinto Sql-set Sql-set-constraints Sql-set-role Sql-set-session-authorization Sql-set-transaction Sql-show Sql-start-transaction Sql-truncate Sql-unlisten Sql-update Sql-vacuum Sql-values II. 客户端应用程序 App-clusterdb App-createdb App-createlang App-createuser App-dropdb App-droplang App-dropuser App-ecpg App-pgconfig App-pgdump App-pg-dumpall App-pgrestore App-psql App-reindexdb App-vacuumdb III. PostgreSQL服务器应用程序 App-initdb App-pgcontroldata App-pg-ctl App-pgresetxlog App-postgres App-postmaster VII. 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_aggregate 45.3. pg_am 45.4. pg_amop 45.5. pg_amproc 45.6. pg_attrdef 45.7. pg_attribute 45.8. pg_authid 45.9. pg_auth_members 45.10. pg_cast 45.11. pg_class 45.12. pg_constraint 45.13. pg_conversion 45.14. pg_database 45.15. pg_db_role_setting 45.16. pg_default_acl 45.17. pg_depend 45.18. pg_description 45.19. pg_enum 45.20. pg_foreign_data_wrapper 45.21. pg_foreign_server 45.22. pg_index 45.23. pg_inherits 45.24. pg_language 45.25. pg_largeobject 45.26. pg_largeobject_metadata 45.27. pg_namespace 45.28. pg_opclass 45.29. pg_operator 45.30. pg_opfamily 45.31. pg_pltemplate 45.32. pg_proc 45.33. pg_rewrite 45.34. pg_shdepend 45.35. pg_shdescription 45.36. pg_statistic 45.37. pg_tablespace 45.38. pg_trigger 45.39. pg_ts_config 45.40. pg_ts_config_map 45.41. pg_ts_dict 45.42. pg_ts_parser 45.43. pg_ts_template 45.44. pg_type 45.45. pg_user_mapping 45.46. System Views 45.47. pg_cursors 45.48. pg_group 45.49. pg_indexes 45.50. pg_locks 45.51. pg_prepared_statements 45.52. pg_prepared_xacts 45.53. pg_roles 45.54. pg_rules 45.55. pg_settings 45.56. pg_shadow 45.57. pg_stats 45.58. pg_tables 45.59. pg_timezone_abbrevs 45.60. pg_timezone_names 45.61. pg_user 45.62. pg_user_mappings 45.63. pg_views 章46. Frontend/Backend Protocol 46.1. Overview 46.2. Message Flow 46.3. Streaming Replication Protocol 46.4. Message Data Types 46.5. Message Formats 46.6. Error and Notice Message Fields 46.7. Summary of Changes since Protocol 2.0 47. PostgreSQL Coding Conventions 47.1. Formatting 47.2. Reporting Errors Within the Server 47.3. Error Message Style Guide 章48. Native Language Support 48.1. For the Translator 48.2. For the Programmer 章49. Writing A Procedural Language Handler 章50. Genetic Query Optimizer 50.1. Query Handling as a Complex Optimization Problem 50.2. Genetic Algorithms 50.3. Genetic Query Optimization (GEQO) in PostgreSQL 50.4. 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 Indexes 52.1. Introduction 52.2. Extensibility 52.3. Implementation 52.4. Examples 52.5. Crash Recovery 章53. GIN Indexes 53.1. Introduction 53.2. Extensibility 53.3. Implementation 53.4. GIN tips and tricks 53.5. Limitations 53.6. Examples 章54. 数据库物理存储 54.1. 数据库文件布局 54.2. TOAST 54.3. 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 Conformance D.1. Supported Features D.2. Unsupported Features E. Release Notes Release-0-01 Release-0-02 Release-0-03 Release-1-0 Release-1-01 Release-1-02 Release-1-09 Release-6-0 Release-6-1 Release-6-1-1 Release-6-2 Release-6-2-1 Release-6-3 Release-6-3-1 Release-6-3-2 Release-6-4 Release-6-4-1 Release-6-4-2 Release-6-5 Release-6-5-1 Release-6-5-2 Release-6-5-3 Release-7-0 Release-7-0-1 Release-7-0-2 Release-7-0-3 Release-7-1 Release-7-1-1 Release-7-1-2 Release-7-1-3 Release-7-2 Release-7-2-1 Release-7-2-2 Release-7-2-3 Release-7-2-4 Release-7-2-5 Release-7-2-6 Release-7-2-7 Release-7-2-8 Release-7-3 Release-7-3-1 Release-7-3-10 Release-7-3-11 Release-7-3-12 Release-7-3-13 Release-7-3-14 Release-7-3-15 Release-7-3-16 Release-7-3-17 Release-7-3-18 Release-7-3-19 Release-7-3-2 Release-7-3-20 Release-7-3-21 Release-7-3-3 Release-7-3-4 Release-7-3-5 Release-7-3-6 Release-7-3-7 Release-7-3-8 Release-7-3-9 Release-7-4 Release-7-4-1 Release-7-4-10 Release-7-4-11 Release-7-4-12 Release-7-4-13 Release-7-4-14 Release-7-4-15 Release-7-4-16 Release-7-4-17 Release-7-4-18 Release-7-4-19 Release-7-4-2 Release-7-4-20 Release-7-4-21 Release-7-4-22 Release-7-4-23 Release-7-4-24 Release-7-4-25 Release-7-4-26 Release-7-4-27 Release-7-4-28 Release-7-4-29 Release-7-4-3 Release-7-4-30 Release-7-4-4 Release-7-4-5 Release-7-4-6 Release-7-4-7 Release-7-4-8 Release-7-4-9 Release-8-0 Release-8-0-1 Release-8-0-10 Release-8-0-11 Release-8-0-12 Release-8-0-13 Release-8-0-14 Release-8-0-15 Release-8-0-16 Release-8-0-17 Release-8-0-18 Release-8-0-19 Release-8-0-2 Release-8-0-20 Release-8-0-21 Release-8-0-22 Release-8-0-23 Release-8-0-24 Release-8-0-25 Release-8-0-26 Release-8-0-3 Release-8-0-4 Release-8-0-5 Release-8-0-6 Release-8-0-7 Release-8-0-8 Release-8-0-9 Release-8-1 Release-8-1-1 Release-8-1-10 Release-8-1-11 Release-8-1-12 Release-8-1-13 Release-8-1-14 Release-8-1-15 Release-8-1-16 Release-8-1-17 Release-8-1-18 Release-8-1-19 Release-8-1-2 Release-8-1-20 Release-8-1-21 Release-8-1-22 Release-8-1-23 Release-8-1-3 Release-8-1-4 Release-8-1-5 Release-8-1-6 Release-8-1-7 Release-8-1-8 Release-8-1-9 Release-8-2 Release-8-2-1 Release-8-2-10 Release-8-2-11 Release-8-2-12 Release-8-2-13 Release-8-2-14 Release-8-2-15 Release-8-2-16 Release-8-2-17 Release-8-2-18 Release-8-2-19 Release-8-2-2 Release-8-2-20 Release-8-2-21 Release-8-2-3 Release-8-2-4 Release-8-2-5 Release-8-2-6 Release-8-2-7 Release-8-2-8 Release-8-2-9 Release-8-3 Release-8-3-1 Release-8-3-10 Release-8-3-11 Release-8-3-12 Release-8-3-13 Release-8-3-14 Release-8-3-15 Release-8-3-2 Release-8-3-3 Release-8-3-4 Release-8-3-5 Release-8-3-6 Release-8-3-7 Release-8-3-8 Release-8-3-9 Release-8-4 Release-8-4-1 Release-8-4-2 Release-8-4-3 Release-8-4-4 Release-8-4-5 Release-8-4-6 Release-8-4-7 Release-8-4-8 Release-9-0 Release-9-0-1 Release-9-0-2 Release-9-0-3 Release-9-0-4 F. 额外提供的模块 F.1. adminpack F.2. auto_explain F.3. btree_gin F.4. btree_gist F.5. chkpass F.6. citext F.7. cube F.8. dblink Contrib-dblink-connect Contrib-dblink-connect-u Contrib-dblink-disconnect Contrib-dblink Contrib-dblink-exec Contrib-dblink-open Contrib-dblink-fetch Contrib-dblink-close Contrib-dblink-get-connections Contrib-dblink-error-message Contrib-dblink-send-query Contrib-dblink-is-busy Contrib-dblink-get-notify Contrib-dblink-get-result Contrib-dblink-cancel-query Contrib-dblink-get-pkey Contrib-dblink-build-sql-insert Contrib-dblink-build-sql-delete Contrib-dblink-build-sql-update F.9. dict_int F.10. dict_xsyn F.11. earthdistance F.12. fuzzystrmatch F.13. hstore F.14. intagg F.15. intarray F.16. isn F.17. lo F.18. ltree F.19. oid2name F.20. pageinspect F.21. passwordcheck F.22. pg_archivecleanup F.23. pgbench F.24. pg_buffercache F.25. pgcrypto F.26. pg_freespacemap F.27. pgrowlocks F.28. pg_standby F.29. pg_stat_statements F.30. pgstattuple F.31. pg_trgm F.32. pg_upgrade F.33. seg F.34. spi F.35. sslinfo F.36. tablefunc F.37. test_parser F.38. tsearch2 F.39. unaccent F.40. uuid-ossp F.41. vacuumlo F.42. xml2 G. 外部项目 G.1. 客户端接口 G.2. 过程语言 G.3. 扩展 H. 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personnages

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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