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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
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35.13. Operator Optimization Information

A PostgreSQL operator definition can include several optional clauses that tell the system useful things about how the operator behaves. These clauses should be provided whenever appropriate, because they can make for considerable speedups in execution of queries that use the operator. But if you provide them, you must be sure that they are right! Incorrect use of an optimization clause can result in slow queries, subtly wrong output, or other Bad Things. You can always leave out an optimization clause if you are not sure about it; the only consequence is that queries might run slower than they need to.

Additional optimization clauses might be added in future versions of PostgreSQL. The ones described here are all the ones that release 9.0.4 understands.

35.13.1. COMMUTATOR

The COMMUTATOR clause, if provided, names an operator that is the commutator of the operator being defined. We say that operator A is the commutator of operator B if (x A y) equals (y B x) for all possible input values x, y. Notice that B is also the commutator of A. For example, operators < and > for a particular data type are usually each others' commutators, and operator + is usually commutative with itself. But operator - is usually not commutative with anything.

The left operand type of a commutable operator is the same as the right operand type of its commutator, and vice versa. So the name of the commutator operator is all that PostgreSQL needs to be given to look up the commutator, and that's all that needs to be provided in the COMMUTATOR clause.

It's critical to provide commutator information for operators that will be used in indexes and join clauses, because this allows the query optimizer to "flip around" such a clause to the forms needed for different plan types. For example, consider a query with a WHERE clause like tab1.x = tab2.y, where tab1.x and tab2.y are of a user-defined type, and suppose that tab2.y is indexed. The optimizer cannot generate an index scan unless it can determine how to flip the clause around to tab2.y = tab1.x, because the index-scan machinery expects to see the indexed column on the left of the operator it is given. PostgreSQL will not simply assume that this is a valid transformation — the creator of the = operator must specify that it is valid, by marking the operator with commutator information.

When you are defining a self-commutative operator, you just do it. When you are defining a pair of commutative operators, things are a little trickier: how can the first one to be defined refer to the other one, which you haven't defined yet? There are two solutions to this problem:

  • One way is to omit the COMMUTATOR clause in the first operator that you define, and then provide one in the second operator's definition. Since PostgreSQL knows that commutative operators come in pairs, when it sees the second definition it will automatically go back and fill in the missing COMMUTATOR clause in the first definition.

  • The other, more straightforward way is just to include COMMUTATOR clauses in both definitions. When PostgreSQL processes the first definition and realizes that COMMUTATOR refers to a nonexistent operator, the system will make a dummy entry for that operator in the system catalog. This dummy entry will have valid data only for the operator name, left and right operand types, and result type, since that's all that PostgreSQL can deduce at this point. The first operator's catalog entry will link to this dummy entry. Later, when you define the second operator, the system updates the dummy entry with the additional information from the second definition. If you try to use the dummy operator before it's been filled in, you'll just get an error message.

35.13.2. NEGATOR

The NEGATOR clause, if provided, names an operator that is the negator of the operator being defined. We say that operator A is the negator of operator B if both return Boolean results and (x A y) equals NOT (x B y) for all possible inputs x, y. Notice that B is also the negator of A. For example, < and >= are a negator pair for most data types. An operator can never validly be its own negator.

Unlike commutators, a pair of unary operators could validly be marked as each others' negators; that would mean (A x) equals NOT (B x) for all x, or the equivalent for right unary operators.

An operator's negator must have the same left and/or right operand types as the operator to be defined, so just as with COMMUTATOR, only the operator name need be given in the NEGATOR clause.

Providing a negator is very helpful to the query optimizer since it allows expressions like NOT (x = y) to be simplified into x <> y. This comes up more often than you might think, because NOT operations can be inserted as a consequence of other rearrangements.

Pairs of negator operators can be defined using the same methods explained above for commutator pairs.

35.13.3. RESTRICT

The RESTRICT clause, if provided, names a restriction selectivity estimation function for the operator. (Note that this is a function name, not an operator name.) RESTRICT clauses only make sense for binary operators that return boolean. The idea behind a restriction selectivity estimator is to guess what fraction of the rows in a table will satisfy a WHERE-clause condition of the form:

column OP constant

for the current operator and a particular constant value. This assists the optimizer by giving it some idea of how many rows will be eliminated by WHERE clauses that have this form. (What happens if the constant is on the left, you might be wondering? Well, that's one of the things that COMMUTATOR is for...)

Writing new restriction selectivity estimation functions is far beyond the scope of this chapter, but fortunately you can usually just use one of the system's standard estimators for many of your own operators. These are the standard restriction estimators:

eqsel for =
neqsel for <>
scalarltsel for < or <=
scalargtsel for > or >=

It might seem a little odd that these are the categories, but they make sense if you think about it. = will typically accept only a small fraction of the rows in a table; <> will typically reject only a small fraction. < will accept a fraction that depends on where the given constant falls in the range of values for that table column (which, it just so happens, is information collected by ANALYZE and made available to the selectivity estimator). <= will accept a slightly larger fraction than < for the same comparison constant, but they're close enough to not be worth distinguishing, especially since we're not likely to do better than a rough guess anyhow. Similar remarks apply to > and >=.

You can frequently get away with using either eqsel or neqsel for operators that have very high or very low selectivity, even if they aren't really equality or inequality. For example, the approximate-equality geometric operators use eqsel on the assumption that they'll usually only match a small fraction of the entries in a table.

You can use scalarltsel and scalargtsel for comparisons on data types that have some sensible means of being converted into numeric scalars for range comparisons. If possible, add the data type to those understood by the function convert_to_scalar() in src/backend/utils/adt/selfuncs.c. (Eventually, this function should be replaced by per-data-type functions identified through a column of the pg_type system catalog; but that hasn't happened yet.) If you do not do this, things will still work, but the optimizer's estimates won't be as good as they could be.

There are additional selectivity estimation functions designed for geometric operators in src/backend/utils/adt/geo_selfuncs.c: areasel, positionsel, and contsel. At this writing these are just stubs, but you might want to use them (or even better, improve them) anyway.

35.13.4. JOIN

The JOIN clause, if provided, names a join selectivity estimation function for the operator. (Note that this is a function name, not an operator name.) JOIN clauses only make sense for binary operators that return boolean. The idea behind a join selectivity estimator is to guess what fraction of the rows in a pair of tables will satisfy a WHERE-clause condition of the form:

table1.column1 OP table2.column2

for the current operator. As with the RESTRICT clause, this helps the optimizer very substantially by letting it figure out which of several possible join sequences is likely to take the least work.

As before, this chapter will make no attempt to explain how to write a join selectivity estimator function, but will just suggest that you use one of the standard estimators if one is applicable:

eqjoinsel for =
neqjoinsel for <>
scalarltjoinsel for < or <=
scalargtjoinsel for > or >=
areajoinsel for 2D area-based comparisons
positionjoinsel for 2D position-based comparisons
contjoinsel for 2D containment-based comparisons

35.13.5. HASHES

The HASHES clause, if present, tells the system that it is permissible to use the hash join method for a join based on this operator. HASHES only makes sense for a binary operator that returns boolean, and in practice the operator must represent equality for some data type or pair of data types.

The assumption underlying hash join is that the join operator can only return true for pairs of left and right values that hash to the same hash code. If two values get put in different hash buckets, the join will never compare them at all, implicitly assuming that the result of the join operator must be false. So it never makes sense to specify HASHES for operators that do not represent some form of equality. In most cases it is only practical to support hashing for operators that take the same data type on both sides. However, sometimes it is possible to design compatible hash functions for two or more data types; that is, functions that will generate the same hash codes for "equal" values, even though the values have different representations. For example, it's fairly simple to arrange this property when hashing integers of different widths.

To be marked HASHES, the join operator must appear in a hash index operator family. This is not enforced when you create the operator, since of course the referencing operator family couldn't exist yet. But attempts to use the operator in hash joins will fail at run time if no such operator family exists. The system needs the operator family to find the data-type-specific hash function(s) for the operator's input data type(s). Of course, you must also create suitable hash functions before you can create the operator family.

Care should be exercised when preparing a hash function, because there are machine-dependent ways in which it might fail to do the right thing. For example, if your data type is a structure in which there might be uninteresting pad bits, you cannot simply pass the whole structure to hash_any. (Unless you write your other operators and functions to ensure that the unused bits are always zero, which is the recommended strategy.) Another example is that on machines that meet the IEEE floating-point standard, negative zero and positive zero are different values (different bit patterns) but they are defined to compare equal. If a float value might contain negative zero then extra steps are needed to ensure it generates the same hash value as positive zero.

A hash-joinable operator must have a commutator (itself if the two operand data types are the same, or a related equality operator if they are different) that appears in the same operator family. If this is not the case, planner errors might occur when the operator is used. Also, it is a good idea (but not strictly required) for a hash operator family that supports multiple data types to provide equality operators for every combination of the data types; this allows better optimization.

Note: The function underlying a hash-joinable operator must be marked immutable or stable. If it is volatile, the system will never attempt to use the operator for a hash join.

Note: If a hash-joinable operator has an underlying function that is marked strict, the function must also be complete: that is, it should return true or false, never null, for any two nonnull inputs. If this rule is not followed, hash-optimization of IN operations might generate wrong results. (Specifically, IN might return false where the correct answer according to the standard would be null; or it might yield an error complaining that it wasn't prepared for a null result.)

35.13.6. MERGES

The MERGES clause, if present, tells the system that it is permissible to use the merge-join method for a join based on this operator. MERGES only makes sense for a binary operator that returns boolean, and in practice the operator must represent equality for some data type or pair of data types.

Merge join is based on the idea of sorting the left- and right-hand tables into order and then scanning them in parallel. So, both data types must be capable of being fully ordered, and the join operator must be one that can only succeed for pairs of values that fall at the "same place" in the sort order. In practice this means that the join operator must behave like equality. But it is possible to merge-join two distinct data types so long as they are logically compatible. For example, the smallint-versus-integer equality operator is merge-joinable. We only need sorting operators that will bring both data types into a logically compatible sequence.

To be marked MERGES, the join operator must appear as an equality member of a btree index operator family. This is not enforced when you create the operator, since of course the referencing operator family couldn't exist yet. But the operator will not actually be used for merge joins unless a matching operator family can be found. The MERGES flag thus acts as a hint to the planner that it's worth looking for a matching operator family.

A merge-joinable operator must have a commutator (itself if the two operand data types are the same, or a related equality operator if they are different) that appears in the same operator family. If this is not the case, planner errors might occur when the operator is used. Also, it is a good idea (but not strictly required) for a btree operator family that supports multiple data types to provide equality operators for every combination of the data types; this allows better optimization.

Note: The function underlying a merge-joinable operator must be marked immutable or stable. If it is volatile, the system will never attempt to use the operator for a merge join.

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