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前言 何為PostgreSQL? PostgreSQL簡(jiǎn)史 格式約定 更多信息 臭蟲匯報(bào)指導(dǎo) I. 教程 章1. 從頭開始 1.1. 安裝 1.2. 體系基本概念 1.3. 創(chuàng)建一個(gè)數(shù)據(jù)庫(kù) 1.4. 訪問數(shù)據(jù)庫(kù) 章2. SQL語(yǔ)言 2.1. 介紹 2.2. 概念 2.3. 創(chuàng)建新表 2.4. 向表中添加行 2.5. 查詢一個(gè)表 2.6. 表間鏈接 2.7. 聚集函數(shù) 2.8. 更新 2.9. 刪除 章3. 高級(jí)特性 3.1. 介紹 3.2. 視圖 3.3. 外鍵 3.4. 事務(wù) 3.5. 窗口函數(shù) 3.6. 繼承 3.7. 結(jié)論 II. SQL語(yǔ)言 章4. SQL語(yǔ)法 4.1. 詞法結(jié)構(gòu) 4.2. 值表達(dá)式 4.3. 調(diào)用函數(shù) 章5. 數(shù)據(jù)定義 5.1. 表的基本概念 5.2. 缺省值 5.3. 約束 5.4. 系統(tǒng)字段 5.5. 修改表 5.6. 權(quán)限 5.7. 模式 5.8. 繼承 5.9. 分區(qū) 5.10. 其它數(shù)據(jù)庫(kù)對(duì)象 5.11. 依賴性跟蹤 章 6. 數(shù)據(jù)操作 6.1. 插入數(shù)據(jù) 6.2. 更新數(shù)據(jù) 6.3. 刪除數(shù)據(jù) 章7. 查詢 7.1. 概述 7.2. 表表達(dá)式 7.3. 選擇列表 7.4. 組合查詢 7.5. 行排序 7.6. LIMIT和OFFSET 7.7. VALUES列表 7.8. WITH的查詢(公用表表達(dá)式) 章8. 數(shù)據(jù)類型 8.1. 數(shù)值類型 8.2. 貨幣類型 8.3. 字符類型 8.4. 二進(jìn)制數(shù)據(jù)類型 8.5. 日期/時(shí)間類型 8.6. 布爾類型 8.7. 枚舉類型 8.8. 幾何類型 8.9. 網(wǎng)絡(luò)地址類型 8.10. 位串類型 8.11. 文本搜索類型 8.12. UUID類型 8.13. XML類型 8.14. 數(shù)組 8.15. 復(fù)合類型 8.16. 對(duì)象標(biāo)識(shí)符類型 8.17. 偽類型 章 9. 函數(shù)和操作符 9.1. 邏輯操作符 9.2. 比較操作符 9.3. 數(shù)學(xué)函數(shù)和操作符 9.4. 字符串函數(shù)和操作符 9.5. 二進(jìn)制字符串函數(shù)和操作符 9.6. 位串函數(shù)和操作符 9.7. 模式匹配 9.8. 數(shù)據(jù)類型格式化函數(shù) 9.9. 時(shí)間/日期函數(shù)和操作符 9.10. 支持枚舉函數(shù) 9.11. 幾何函數(shù)和操作符 9.12. 網(wǎng)絡(luò)地址函數(shù)和操作符 9.13. 文本檢索函數(shù)和操作符 9.14. XML函數(shù) 9.15. 序列操作函數(shù) 9.16. 條件表達(dá)式 9.17. 數(shù)組函數(shù)和操作符 9.18. 聚合函數(shù) 9.19. 窗口函數(shù) 9.20. 子查詢表達(dá)式 9.21. 行和數(shù)組比較 9.22. 返回集合的函數(shù) 9.23. 系統(tǒng)信息函數(shù) 9.24. 系統(tǒng)管理函數(shù) 9.25. 觸發(fā)器函數(shù) 章10. 類型轉(zhuǎn)換 10.3. 函數(shù) 10.2. 操作符 10.1. 概述 10.4. 值存儲(chǔ) 10.5. UNION 章11. 索引 11.1. 介紹 11.2. 索引類型 11.3. 多字段索引 11.4. 索引和ORDER BY 11.5. 組合多個(gè)索引 11.6. 唯一索引 11.7. 表達(dá)式上的索引 11.8. 部分索引 11.9. 操作類和操作簇 11.10. 檢查索引的使用 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. 并發(fā)控制 13.1. 介紹 13.2. 事務(wù)隔離 13.3. 明確鎖定 13.4. 應(yīng)用層數(shù)據(jù)完整性檢查 13.5. 鎖和索引 章14. 性能提升技巧 14.1. 使用EXPLAIN 14.2. 規(guī)劃器使用的統(tǒng)計(jì)信息 14.3. 用明確的JOIN語(yǔ)句控制規(guī)劃器 14.4. 向數(shù)據(jù)庫(kù)中添加記錄 14.5. 非持久性設(shè)置 III. 服務(wù)器管理 章15. 安裝指導(dǎo) 15.1. 簡(jiǎn)版 15.2. 要求 15.3. 獲取源碼 15.4. 升級(jí) 15.5. 安裝過(guò)程 15.6. 安裝后的設(shè)置 15.7. 支持的平臺(tái) 15.8. 特殊平臺(tái)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. 服務(wù)器安裝和操作 17.1. PostgreSQL用戶帳戶 17.2. 創(chuàng)建數(shù)據(jù)庫(kù)集群 17.3. 啟動(dòng)數(shù)據(jù)庫(kù)服務(wù)器 17.4. 管理內(nèi)核資源 17.5. 關(guān)閉服務(wù) 17.6. 防止服務(wù)器欺騙 17.7. 加密選項(xiàng) 17.8. 用SSL進(jìn)行安全的TCP/IP連接 17.9. Secure TCP/IP Connections with SSH Tunnels 章18. 服務(wù)器配置 18.1. 設(shè)置參數(shù) 18.2. 文件位置 18.3. 連接和認(rèn)證 18.4. 資源消耗 18.5. 預(yù)寫式日志 18.6. 查詢規(guī)劃 18.7. 錯(cuò)誤報(bào)告和日志 18.8. 運(yùn)行時(shí)統(tǒng)計(jì) 18.9. 自動(dòng)清理 18.10. 客戶端連接缺省 18.12. 版本和平臺(tái)兼容性 18.11. 鎖管理 18.13. 預(yù)置選項(xiàng) 18.14. 自定義的選項(xiàng) 18.15. 開發(fā)人員選項(xiàng) 18.16. 短選項(xiàng) 章19. 用戶認(rèn)證 19.1. pg_hba.conf 文件 19.2. 用戶名映射 19.3. 認(rèn)證方法 19.4. 用戶認(rèn)證 章20. 數(shù)據(jù)庫(kù)角色和權(quán)限 20.1. 數(shù)據(jù)庫(kù)角色 20.2. 角色屬性 20.3. 權(quán)限 20.4. 角色成員 20.5. 函數(shù)和觸發(fā)器 章21. 管理數(shù)據(jù)庫(kù) 21.1. 概述 21.2. 創(chuàng)建一個(gè)數(shù)據(jù)庫(kù) 21.3. 臨時(shí)庫(kù) 21.4. 數(shù)據(jù)庫(kù)配置 21.5. 刪除數(shù)據(jù)庫(kù) 21.6. 表空間 章22. 本土化 22.1. 區(qū)域支持 22.2. 字符集支持 章23. 日常數(shù)據(jù)庫(kù)維護(hù)工作 23.1. Routine Vacuuming日常清理 23.2. 經(jīng)常重建索引 23.3. 日志文件維護(hù) 章24. 備份和恢復(fù) 24.1. SQL轉(zhuǎn)儲(chǔ) 24.2. 文件系統(tǒng)級(jí)別的備份 24.3. 在線備份以及即時(shí)恢復(fù)(PITR) 24.4. 版本間遷移 章25. 高可用性與負(fù)載均衡,復(fù)制 25.1. 不同解決方案的比較 25.2. 日志傳送備份服務(wù)器 25.3. 失效切換 25.4. 日志傳送的替代方法 25.5. 熱備 章26. 恢復(fù)配置 26.1. 歸檔恢復(fù)設(shè)置 26.2. 恢復(fù)目標(biāo)設(shè)置 26.3. 備服務(wù)器設(shè)置 章27. 監(jiān)控?cái)?shù)據(jù)庫(kù)的活動(dòng) 27.1. 標(biāo)準(zhǔn)Unix工具 27.2. 統(tǒng)計(jì)收集器 27.3. 查看鎖 27.4. 動(dòng)態(tài)跟蹤 章28. 監(jiān)控磁盤使用情況 28.1. 判斷磁盤的使用量 28.2. 磁盤滿導(dǎo)致的失效 章29. 可靠性和預(yù)寫式日志 29.1. 可靠性 29.2. 預(yù)寫式日志(WAL) 29.3. 異步提交 29.4. WAL配置 29.5. WAL內(nèi)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. 客戶端接口 章31. libpq-C庫(kù) 31.1. 數(shù)據(jù)庫(kù)聯(lián)接函數(shù) 31.2. 連接狀態(tài)函數(shù) 31.3. 命令執(zhí)行函數(shù) 31.4. 異步命令處理 31.5. 取消正在處理的查詢 31.6. 捷徑接口 31.7. 異步通知 31.8. 與COPY命令相關(guān)的函數(shù) 31.9. Control Functions 控制函數(shù) 31.10. 其他函數(shù) 31.11. 注意信息處理 31.12. 事件系統(tǒng) 31.13. 環(huán)境變量 31.14. 口令文件 31.15. 連接服務(wù)的文件 31.16. LDAP查找連接參數(shù) 31.17. SSL支持 31.18. 在多線程程序里的行為 31.19. 制作libpq程序 31.20. 例子程序 章32. 大對(duì)象 32.1. 介紹 32.2. 實(shí)現(xiàn)特點(diǎn) 32.3. 客戶端接口 32.4. 服務(wù)器端函數(shù) 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. 關(guān)于這個(gè)模式 34.2. 數(shù)據(jù)類型 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. 觸發(fā)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. 視圖 V. 服務(wù)器端編程 章35. 擴(kuò)展SQL 35.1. 擴(kuò)展性是如何實(shí)現(xiàn)的 35.2. PostgreSQL類型系統(tǒng) 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++擴(kuò)展 章36. 觸發(fā)器 36.1. 觸發(fā)器行為概述 36.3. 用 C 寫觸發(fā)器 36.2. 數(shù)據(jù)改變的可視性 36.4. 一個(gè)完整的例子 章37. 規(guī)則系統(tǒng) 37.1. The Query Tree 37.2. 視圖和規(guī)則系統(tǒng) 37.3. 在INSERT,UPDATE和DELETE上的規(guī)則 37.4. 規(guī)則和權(quán)限 37.5. 規(guī)則和命令狀態(tài) 37.6. 規(guī)則與觸發(fā)器得比較 章38. Procedural Languages 38.1. Installing Procedural Languages 章39. PL/pgSQL - SQL過(guò)程語(yǔ)言 39.1. 概述 39.2. PL/pgSQL的結(jié)構(gòu) 39.3. 聲明 39.4. 表達(dá)式 39.5. 基本語(yǔ)句 39.6. 控制結(jié)構(gòu) 39.7. 游標(biāo) 39.8. 錯(cuò)誤和消息 39.9. 觸發(fā)器過(guò)程 39.10. PL/pgSQL Under the Hood 39.11. 開發(fā)PL/pgSQL的一些提示 39.12. 從OraclePL/SQL 進(jìn)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. 參考手冊(cè) 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. 客戶端應(yīng)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服務(wù)器應(yīng)用程序 App-initdb App-pgcontroldata App-pg-ctl App-pgresetxlog App-postgres App-postmaster VII. 內(nèi)部 章44. PostgreSQL內(nèi)部概覽 44.1. 查詢路徑 44.2. 連接是如何建立起來(lái)的 44.3. 分析器階段 44.4. ThePostgreSQL規(guī)則系統(tǒng) 44.5. 規(guī)劃器/優(yōu)化器 44.6. 執(zhí)行器 章45. 系統(tǒng)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. 索引訪問方法接口定義 51.1. 索引的系統(tǒng)表記錄 51.2. 索引訪問方法函數(shù) 51.3. 索引掃描 51.4. 索引鎖的考量 51.5. 索引唯一性檢查 51.6. 索引開銷估計(jì)函數(shù) 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. 數(shù)據(jù)庫(kù)物理存儲(chǔ) 54.1. 數(shù)據(jù)庫(kù)文件布局 54.2. TOAST 54.3. 自由空間映射 54.4. 可見映射 54.5. 數(shù)據(jù)庫(kù)分頁(yè)文件 章55. BKI后端接口 55.1. BKI 文件格式 55.2. BKI命令 55.3. 系統(tǒng)初始化的BKI文件的結(jié)構(gòu) 55.4. 例子 章56. 規(guī)劃器如何使用統(tǒng)計(jì)信息 56.1. 行預(yù)期的例子 VIII. 附錄 A. PostgreSQL錯(cuò)誤代碼 B. 日期/時(shí)間支持 B.1. 日期/時(shí)間輸入解析 B.2. 日期/時(shí)間關(guān)鍵字 B.3. 日期/時(shí)間配置文件 B.4. 日期單位的歷史 C. SQL關(guān)鍵字 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. 額外提供的模塊 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. 外部項(xiàng)目 G.1. 客戶端接口 G.2. 過(guò)程語(yǔ)言 G.3. 擴(kuò)展 H. The Source Code Repository H.1. Getting The Source Via Git I. 文檔 I.1. DocBook I.2. 工具集 I.3. 制作文檔 I.4. 文檔寫作 I.5. 風(fēng)格指導(dǎo) J. 首字母縮略詞 參考書目 Bookindex Index
characters

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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