PostgreSQL 正體中文使用手冊
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  • 簡介
  • 前言
    • 1. 什麼是 PostgreSQL?
    • 2. PostgreSQL 沿革
    • 3. 慣例
    • 4. 其他參考資訊
    • 5. 問題回報指南
  • I. 新手教學
    • 1. 入門指南
      • 1.1. 安裝
      • 1.2. 基礎架構
      • 1.3. 建立一個資料庫
      • 1.4. 存取一個資料庫
    • 2. SQL 查詢語言
      • 2.1. 簡介
      • 2.2. 概念
      • 2.3. 創建一個新的資料表
      • 2.4. 資料列是資料表的組成單位
      • 2.5. 資料表的查詢
      • 2.6. 交叉查詢
      • 2.7. 彙總查詢
      • 2.8. 更新資料
      • 2.9. 刪除資料
    • 3. 先進功能
      • 3.1. 簡介
      • 3.2. 檢視表(View)
      • 3.3. 外部索引鍵
      • 3.4. 交易安全
      • 3.5. 窗函數
      • 3.6. 繼承
      • 3.7. 結論
  • II. SQL 查詢語言
    • 4. SQL 語法
      • 4.1. 語法結構
      • 4.2. 參數表示式
      • 4.3. 函數呼叫
    • 5. 定義資料結構
      • 5.1. 認識資料表
      • 5.2. 預設值
      • 5.3. Generated Columns
      • 5.4. 限制條件
      • 5.5. 系統欄位
      • 5.6. 表格變更
      • 5.7. 權限
      • 5.8. 資料列安全原則
      • 5.9. Schemas
      • 5.10. 繼承
      • 5.11. 分割資料表
      • 5.12. 外部資料
      • 5.13. 其他資料庫物件
      • 5.14. 相依性追蹤
    • 6. 資料處理
      • 6.1. 新增資料
      • 6.2. 更新資料
      • 6.3. 刪除資料
      • 6.4. 修改並回傳資料
    • 7. 資料查詢
      • 7.1. 概觀
      • 7.2. 資料表表示式
      • 7.3. 取得資料列表
      • 7.4. 合併查詢結果
      • 7.5. 資料排序
      • 7.6. LIMIT 和 OFFSET
      • 7.7. VALUES 列舉資料
      • 7.8. WITH Querys(Common Table Expressions)
    • 8. 資料型別
      • 8.1. 數字型別
      • 8.2. 貨幣型別
      • 8.3. 字串型別
      • 8.4. 位元組型別(bytea)
      • 8.5. 日期時間型別
      • 8.6. 布林型別
      • 8.7. 列舉型別
      • 8.8. 地理資訊型別
      • 8.9. 網路資訊型別
      • 8.10. 位元字串型別
      • 8.11. 全文檢索型別
      • 8.12. UUID 型別
      • 8.13. XML 型別
      • 8.14. JSON 型別
      • 8.15. 陣列
      • 8.16. 複合型別
      • 8.17. 範圍型別
      • 8.18. Domain Types
      • 8.19. 物件指標型別
      • 8.20. pg_lsn 型別
      • 8.21. 概念型別
    • 9. 函式及運算子
      • 9.1. 邏輯運算子
      • 9.2. 比較函式及運算子
      • 9.3. 數學函式及運算子
      • 9.4. 字串函式及運算子
      • 9.5. 位元字串函式及運算子
      • 9.6. 二元字串函式及運算子
      • 9.7. 特徵比對
      • 9.8. 型別轉換函式
      • 9.9 日期時間函式及運算子
      • 9.10. 列舉型別函式
      • 9.11. 地理資訊函式及運算子
      • 9.12. 網路位址函式及運算子
      • 9.13. 文字檢索函式及運算子
      • 9.14. UUID Functions
      • 9.15. XML 函式
      • 9.16. JSON 函式及運算子
      • 9.17. 序列函式
      • 9.18. 條件表示式
      • 9.19. 陣列函式及運算子
      • 9.20. 範圍函式及運算子
      • 9.21. 彙總函數
      • 9.22. Window 函式
      • 9.23. 子查詢
      • 9.24. 資料列與陣列的比較運算
      • 9.25. 集合回傳函數
      • 9.26. 系統資訊函數
      • 9.27. 系統管理函式
      • 9.28. 觸發函式
      • 9.29. 事件觸發函式
      • 9.30. Statistics Information Functions
    • 10. 型別轉換
      • 10.1. 概觀
      • 10.2. 運算子
      • 10.3. 函式
      • 10.4. 資料儲存轉換規則
      • 10.5. UNION、CASE 等相關結構
      • 10.6. SELECT 輸出規則
    • 11. 索引(Index)
      • 11.1. 簡介
      • 11.2. 索引型別
      • 11.3. 多欄位索引
      • 11.4. 索引與 ORDER BY
      • 11.5. 善用多個索引
      • 11.6. 唯一值索引
      • 11.7. 表示式索引
      • 11.8. 部份索引(partial index)
      • 11.9. Index-Only Scans and Covering Indexes
      • 11.10. 運算子物件及家族
      • 11.11. 索引與排序規則
      • 11.12. 檢查索引運用
    • 12. 全文檢索
      • 12.1. 簡介
      • 12.2. 查詢與索引
      • 12.3. 細部控制
      • 12.4. 延伸功能
      • 12.5. 斷詞
      • 12.6. 字典
      • 12.7. 組態範例
      • 12.8. 測試與除錯
      • 12.9. GIN 及 GiST 索引型別
      • 12.10. psql支援
      • 12.11. 功能限制
    • 13. 一致性管理(Concurrency Control)
      • 13.1. 簡介
      • 13.2. 交易隔離
      • 13.3. 鎖定模式
      • 13.4. 在應用端檢視資料一致性
      • 13.5. Serialization Failure Handling
      • 13.6. 特別提醒
      • 13.7. 鎖定與索引
    • 14. 效能技巧
      • 14.1. 善用 EXPLAIN
      • 14.2. 統計資訊
      • 14.3. 使用確切的 JOIN 方式
      • 14.4. 快速建立資料庫內容
      • 14.5. 風險性彈性設定
    • 15. 平行查詢
      • 15.1. 如何運作?
      • 15.2. 啓用時機?
      • 15.3. 平行查詢計畫
      • 15.4. 平行查詢的安全性
  • III. 系統管理
    • 16. 以預編譯套件安裝
    • 17. 以原始碼安裝
      • 17.1. 簡要步驟
      • 17.2. 環境需求
      • 17.3. Getting The Source
      • 17.4. 安裝流程
      • 17.5. Post-Installation Setup
      • 17.6. Supported Platforms
      • 17.7. 平台相關的注意事項
    • 18. 以原始碼在 Windows 上安裝
      • 18.1. Building with Visual C++ or the Microsoft Windows SDK
    • 19. 服務配置與維運
      • 19.1. PostgreSQL 使用者帳號
      • 19.2. Creating a Database Cluster
      • 19.3. Starting the Database Server
      • 19.4. 核心資源管理
      • 19.5. Shutting Down the Server
      • 19.6. Upgrading a PostgreSQL Cluster
      • 19.7. Preventing Server Spoofing
      • 19.8. Encryption Options
      • 19.9. Secure TCP/IP Connections with SSL
      • 19.10. Secure TCP/IP Connections with GSSAPI Encryption
      • 19.11. Secure TCP/IP Connections with SSH Tunnels
      • 19.12. 在 Windows 註冊事件日誌
    • 20. 服務組態設定
      • 20.1. Setting Parameters
      • 20.2. File Locations
      • 20.3. 連線與認證
      • 20.4. 資源配置
      • 20.5. Write Ahead Log
      • 20.6. 複寫(Replication)
      • 20.7. 查詢規畫
      • 20.8. 錯誤回報與日誌記錄
      • 20.9. 執行階段統計資訊
      • 20.10. 自動資料庫清理
      • 20.11. 用戶端連線預設參數
      • 20.12. 交易鎖定管理
      • 20.13. 版本與平台的相容性
      • 20.14. Error Handling
      • 20.15. 預先配置的參數
      • 20.16. Customized Options
      • 20.17. Developer Options
      • 20.18. Short Options
    • 21. 使用者認證
      • 21.1. 設定檔:pg_hba.conf
      • 21.2. User Name Maps
      • 21.3. Authentication Methods
      • 21.4. Trust Authentication
      • 21.5. Password Authentication
      • 21.6. GSSAPI Authentication
      • 21.7. SSPI Authentication
      • 21.8. Ident Authentication
      • 21.9. Peer Authentication
      • 21.10. LDAP Authentication
      • 21.11. RADIUS Authentication
      • 21.12. Certificate Authentication
      • 21.13. PAM Authentication
      • 21.14. BSD Authentication
      • 21.15. Authentication Problems
    • 22. 資料庫角色
      • 22.1. Database Roles
      • 22.2. Role Attributes
      • 22.3. Role Membership
      • 22.4. 移除角色
      • 22.5. Default Roles
      • 22.6. Function Security
    • 23. 管理資料庫
      • 23.1. Overview
      • 23.2. Creating a Database
      • 23.3. 樣版資料庫
      • 23.4. Database Configuration
      • 23.5. Destroying a Database
      • 23.6. Tablespaces
    • 24. 語系
      • 24.1. 語系支援
      • 24.2. Collation Support
      • 24.3. 字元集支援
    • 25. 例行性資料庫維護工作
      • 25.1. 例行性資料清理
      • 25.2. 定期重建索引
      • 25.3. Log 檔案維護
    • 26. 備份及還原
      • 26.1. SQL Dump
      • 26.2. 檔案系統層級備份
      • 26.3. 持續封存及 Point-in-Time Recovery (PITR)
    • 27. High Availability, Load Balancing, and Replication
      • 27.1. 比較不同的解決方案
      • 27.2. 日誌轉送備用伺服器 Log-Shipping Standby Servers
      • 27.3. Failover
      • 27.4. Hot Standby
    • 28. 監控資料庫活動
      • 28.1. 標準的 Unix 工具
      • 28.2. 統計資訊收集器
      • 28.3. Viewing Locks
      • 28.4. Progress Reporting
      • 28.5. Dynamic Tracing
    • 29. 監控磁碟使用情況
      • 29.1. 瞭解磁碟使用情形
      • 29.2. 磁碟空間不足錯誤
    • 30. 高可靠度及預寫日誌
      • 30.1. 可靠度
      • 30.2. Data Checksums
      • 30.3. Write-Ahead Logging(WAL)
      • 30.4. Asynchronous Commit
      • 30.5. WAL Configuration
      • 30.6. WAL Internals
    • 31. 邏輯複寫(Logical Replication)
      • 31.1. 發佈(Publication)
      • 31.2. 訂閱(Subscription)
      • 31.3. Row Filters
      • 31.4. Column Lists
      • 31.5. 衝突處理
      • 31.6. 限制
      • 31.7. 架構
      • 31.8. 監控
      • 31.9. 安全性
      • 31.10. 系統設定
      • 31.11. 快速設定
    • 32. Just-in-Time Compilation(JIT)
      • 32.1. What is JIT compilation?
      • 32.2. When to JIT?
      • 32.3. Configuration
      • 32.4. Extensibility
    • 33. 迴歸測試
      • 33.1. Running the Tests
      • 33.2. Test Evaluation
      • 33.3. Variant Comparison Files
      • 33.4. TAP Tests
      • 33.5. Test Coverage Examination
  • IV. 用戶端介面
    • 34. libpq - C Library
      • 33.1. 資料庫連線控制函數
      • 33.2. 連線狀態函數
      • 33.3. Command Execution Functions
      • 33.4. Asynchronous Command Processing
      • 33.5. Retrieving Query Results Row-By-Row
      • 33.6. Canceling Queries in Progress
      • 33.7. The Fast-Path Interface
      • 33.8. Asynchronous Notification
      • 33.9. Functions Associated with the COPY Command
      • 33.10. Control Functions
      • 33.11. Miscellaneous Functions
      • 33.12. Notice Processing
      • 33.13. Event System
      • 33.14. 環境變數
      • 34.16. 密碼檔
      • 33.16. The Connection Service File
      • 33.17. LDAP Lookup of Connection Parameters
      • 33.18. SSL Support
      • 33.19. Behavior in Threaded Programs
      • 33.20. Building libpq Programs
      • 33.21. Example Programs
    • 35. Large Objects
      • 35.1. Introduction
      • 35.2. Implementation Features
      • 35.3. Client Interfaces
      • 35.4. Server-side Functions
      • 35.5. Example Program
    • 36. ECPG - Embedded SQL in C
      • 35.1. The Concept
      • 35.2. Managing Database Connections
      • 35.3. Running SQL Commands
      • 35.4. Using Host Variables
      • 35.5. Dynamic SQL
      • 35.6. pgtypes Library
      • 35.7. Using Descriptor Areas
      • 35.8. Error Handling
      • 35.9. Preprocessor Directives
      • 35.10. Processing Embedded SQL Programs
      • 35.11. Library Functions
      • 35.12. Large Objects
      • 35.13. C++ Applications
      • 35.14. Embedded SQL Commands
      • 35.15. Informix Compatibility Mode
      • 35.16. Internals
    • 37. The Information Schema
      • 37.1. The Schema
      • 37.2. Data Types
      • 37.3. information_schema_catalog_name
      • 37.4. administrable_role_authorizations
      • 37.5. applicable_roles
      • 37.7. attributes
      • 37.7. character_sets
      • 37.8. check_constraint_routine_usage
      • 37.9. check_constraints
      • 37.10. collations
      • 37.11. collation_character_set_applicability
      • 37.12. column_column_usage
      • 37.13. column_domain_usage
      • 37.14. column_options
      • 37.15. column_privileges
      • 37.16. column_udt_usage
      • 37.17. columns
      • 37.18. constraint_column_usage
      • 37.19. constraint_table_usage
      • 37.20. data_type_privileges
      • 37.21. domain_constraints
      • 37.21. domain_udt_usage
      • 37.22. domains
      • 37.23. element_types
      • 37.24. enabled_roles
      • 37.25. foreign_data_wrapper_options
      • 37.26. foreign_data_wrappers
      • 37.27. foreign_server_options
      • 37.28. foreign_servers
      • 37.29. foreign_table_options
      • 37.30. foreign_tables
      • 36.32. key_column_usage
      • 37.33. parameters
      • 36.34. referential_constraints
      • 37.34. role_column_grants
      • 37.35. role_routine_grants
      • 37.37. role_table_grants
      • 37.38. role_udt_grants
      • 37.39. role_usage_grants
      • 37.40. routine_column_usage
      • 37.41. routine_privileges
      • 37.45. routines
      • 37.46. schemata
      • 37.47. sequences
      • 37.48. sql_features
      • 37.49. sql_implementation_info
      • 37.50. sql_parts
      • 37.51. sql_sizing
      • 36.51. table_constraints
      • 36.49. table_privileges
      • 37.52. tables
      • 37.53. transforms
      • 37.54. triggered_update_columns
      • 37.55. triggers
      • 37.56. udt_privileges
      • 37.57. usage_privileges
      • 37.58. user_defined_types
      • 37.59. user_mapping_options
      • 37.60. user_mappings
      • 37.63. view_column_usage
      • 37.64. view_routine_usage
      • 37.65. view_table_usage
      • 37.66. views
  • V. 資料庫程式設計
    • 38. SQL 延伸功能
      • 38.1. How Extensibility Works
      • 38.2. The PostgreSQL Type System
      • 38.3. 使用者自訂函數
      • 38.4. User-defined Procedures
      • 38.5. Query Language (SQL) Functions
      • 38.6. Function Overloading
      • 38.7. 函數易變性類別
      • 38.8. Procedural Language Functions
      • 38.9. Internal Functions
      • 38.10. C-Language Functions
      • 38.11. Function Optimization Information
      • 38.12. User-defined Aggregates
      • 38.13. User-defined Types
      • 38.14. User-defined Operators
      • 38.15. Operator Optimization Information
      • 38.16. Interfacing Extensions To Indexes
      • 38.17. 封裝相關物件到延伸功能中
      • 38.18. Extension Building Infrastructure
    • 39. Triggers
      • 39.1. Overview of Trigger Behavior
      • 39.2. Visibility of Data Changes
      • 39.3. Writing Trigger Functions in C
      • 39.4. A Complete Trigger Example
    • 40. Event Triggers (事件觸發)
      • 40.1. Overview of Event Trigger Behavior
      • 40.2. Event Trigger Firing Matrix
      • 40.3. Writing Event Trigger Functions in C
      • 40.4. A Complete Event Trigger Example
    • 41. 規則系統
      • 41.1. The Query Tree
      • 41.2. Views and the Rule System
      • 41.3. Materialized Views
      • 41.4. Rules on INSERT, UPDATE, and DELETE
      • 41.5. 規則及權限
      • 41.6. Rules and Command Status
      • 41.7. Rules Versus Triggers
    • 42. Procedural Languages(程序語言)
      • 42.1. Installing Procedural Languages
    • 43. PL/pgSQL - SQL Procedural Language
      • 43.1. Overview
      • 43.2. Structure of PL/pgSQL
      • 43.3. Declarations
      • 43.4. Expressions
      • 43.5. 基本語法
      • 43.6. Control Structures
      • 43.7. Cursors
      • 43.8. Transaction Management
      • 43.9. Errors and Messages
      • 43.10. Trigger Functions
      • 43.11. PL/pgSQL under the Hood
      • 43.12. Tips for Developing in PL/pgSQL
      • 43.13. Porting from Oracle PL/SQL
    • 44. PL/Tcl - Tcl Procedural Language
    • 45. PL/Perl — Perl Procedural Language
    • 46. PL/Python - Python Procedural Language
      • 46.1. PL/Python Functions
      • 46.2. Data Values
      • 46.3. Sharing Data
      • 46.4. Anonymous Code Blocks
      • 46.5. Trigger Functions
      • 46.6. Database Access
      • 46.7. Explicit Subtransactions
      • 46.8. Transaction Management
      • 46.9. Utility Functions
      • 46.10. Python 2 vs. Python 3
      • 46.11. Environment Variables
    • 47. Server Programming Interface
    • 48. Background Worker Processes
    • 49. Logical Decoding
      • 48.1. Logical Decoding Examples
      • 48.2. Logical Decoding Concepts
      • 48.3. Streaming Replication Protocol Interface
      • 48.4. Logical Decoding SQL Interface
      • 48.5. System Catalogs Related to Logical Decoding
      • 48.6. Logical Decoding Output Plugins
      • 48.7. Logical Decoding Output Writers
      • 48.8. Synchronous Replication Support for Logical Decoding
    • 50. Replication Progress Tracking
    • 51. Archive Modules
      • 51.1. Initialization Functions
      • 51.2. Archive Module Callbacks
  • VI. 參考資訊
    • I. SQL 指令
      • ALTER DATABASE
      • ALTER DEFAULT PRIVILEGES
      • ALTER EXTENSION
      • ALTER FUNCTION
      • ALTER INDEX
      • ALTER LANGUAGE
      • ALTER MATERIALIZED VIEW
      • ALTER POLICY
      • ALTER PUBLICATION
      • ALTER ROLE
      • ALTER RULE
      • ALTER SCHEMA
      • ALTER SEQUENCE
      • ALTER STATISTICS
      • ALTER SUBSCRIPTION
      • ALTER SYSTEM
      • ALTER TABLE
      • ALTER TABLESPACE
      • ALTER TRIGGER
      • ALTER TYPE
      • ALTER USER
      • ALTER VIEW
      • ANALYZE
      • CLUSTER
      • COMMENT
      • COMMIT PREPARED
      • COPY
      • CREATE ACCESS METHOD
      • CREATE CAST
      • CREATE DATABASE
      • CREATE EVENT TRIGGER
      • CREATE EXTENSION
      • CREATE FOREIGN TABLE
      • CREATE FOREIGN DATA WRAPPER
      • CREATE FUNCTION
      • CREATE INDEX
      • CREATE LANGUAGE
      • CREATE MATERIALIZED VIEW
      • CREATE DOMAIN
      • CREATE POLICY
      • CREATE PROCEDURE
      • CREATE PUBLICATION
      • CREATE ROLE
      • CREATE RULE
      • CREATE SCHEMA
      • CREATE SEQUENCE
      • CREATE SERVER
      • CREATE STATISTICS
      • CREATE SUBSCRIPTION
      • CREATE TABLE
      • CREATE TABLE AS
      • CREATE TABLESPACE
      • CREATE TRANSFORM
      • CREATE TRIGGER
      • CREATE TYPE
      • CREATE USER
      • CREATE USER MAPPING
      • CREATE VIEW
      • DEALLOCATE
      • DELETE
      • DO
      • DROP ACCESS METHOD
      • DROP DATABASE
      • DROP EXTENSION
      • DROP FUNCTION
      • DROP INDEX
      • DROP LANGUAGE
      • DROP MATERIALIZED VIEW
      • DROP OWNED
      • DROP POLICY
      • DROP PUBLICATION
      • DROP ROLE
      • DROP RULE
      • DROP SCHEMA
      • DROP SEQUENCE
      • DROP STATISTICS
      • DROP SUBSCRIPTION
      • DROP TABLE
      • DROP TABLESPACE
      • DROP TRANSFORM
      • DROP TRIGGER
      • DROP TYPE
      • DROP USER
      • DROP VIEW
      • EXECUTE
      • EXPLAIN
      • GRANT
      • IMPORT FOREIGN SCHEMA
      • INSERT
      • LISTEN
      • LOAD
      • MERGE
      • NOTIFY
      • PREPARE
      • PREPARE TRANSACTION
      • REASSIGN OWNED
      • REFRESH MATERIALIZED VIEW
      • REINDEX
      • RESET
      • REVOKE
      • ROLLBACK PREPARED
      • SECURITY LABEL
      • SELECT
      • SELECT INTO
      • SET
      • SET CONSTRAINTS
      • SET ROLE
      • SET SESSION AUTHORIZATION
      • SET TRANSACTION
      • SHOW
      • TRUNCATE
      • UNLISTEN
      • UPDATE
      • VACUUM
      • VALUES
    • II. PostgreSQL 用戶端工具
      • createdb
      • createuser
      • dropdb
      • dropuser
      • oid2name
      • pgbench
      • pg_basebackup
      • pg_dump
      • pg_dumpall
      • pg_isready
      • pg_receivewal
      • pg_recvlogical
      • pg_restore
      • pg_verifybackup
      • psql
      • vacuumdb
    • III. PostgreSQL 伺服器應用程式
      • initdb
      • pg_archivecleanup
      • pg_ctl
      • pg_standby
      • pg_test_fsync
      • pg_test_timing
      • pg_upgrade
      • postgres
  • VII. 資料庫進階
    • 52. PostgreSQL 的內部架構
      • 52.1. 處理查詢語句的流程
      • 52.2. How Connections Are Established
      • 52.3. The Parser Stage
      • 52.4. The PostgreSQL Rule System
      • 52.5. Planner/Optimizer
      • 52.6. Executor
    • 53. 系統資訊目錄
      • 51.3. pg_am
      • 51.7. pg_attribute
      • 51.8. pg_authid
      • 51.9. pg_auth_members
      • 51.10. pg_cast
      • 51.11 pg_class
      • 51.12. pg_collation
      • 51.13. pg_constraint
      • 51.15 pg_database
      • 51.21. pg_event_trigger
      • 51.22. pg_extension
      • 51.26 pg_index
      • 51.29. pg_language
      • 51.32. pg_namespace
      • 51.33. pg_opclass
      • 51.38. pg_policy
      • 51.39. pg_proc
      • 51.44. pg_rewrite
      • 51.49. pg_statistic
      • 51.50. pg_statistic_ext
      • 51.52. pg_subscription
      • 51.53. pg_subscription_rel
      • 51.54. pg_tablespace
      • 51.56. pg_trigger
      • 51.62. pg_type
      • 51.66. pg_available_extensions
      • 51.67. pg_available_extension_versions
      • 51.71. pg_hba_file_rules
      • 51.72. pg_indexes
      • 51.73. pg_locks
      • 51.77. pg_prepared_xacts
      • 51.79. pg_replication_origin_status
    • 54. System Views
      • 54.1. Overview
      • 54.19. pg_replication_slots
      • 54.20 pg_roles
      • 54.24. pg_settings
      • 54.25. pg_shadow
      • 54.26. pg_shmem_allocations
      • 54.27. pg_stats
      • 54.30. pg_tables
      • 54.31. pg_timezone_abbrevs
      • 54.32. pg_timezone_names
      • 54.33. pg_user
      • 54.35. pg_views
    • 55. Frontend/Backend Protocol
      • 52.1. Overview
      • 52.2. Message Flow
      • 52.3. SASL Authentication
      • 52.4. Streaming Replication Protocol
      • 52.5. Logical Streaming Replication Protocol
      • 52.6. Message Data Types
      • 52.7. Message Formats
      • 52.8. Error and Notice Message Fields
      • 52.9. Logical Replication Message Formats
      • 52.10. Summary of Changes since Protocol 2.0
    • 56. PostgreSQL 程式撰寫慣例
      • 53.1. Formatting
      • 53.2. Reporting Errors Within the Server
      • 53.3. Error Message Style Guide
      • 53.4. Miscellaneous Coding Conventions
    • 57. Native Language Support
      • 54.1. For the Translator
      • 54.2. For the Programmer
    • 58. 撰寫程序語言的處理程序
    • 59. Writing a Foreign Data Wrapper
      • 56.1. Foreign Data Wrapper Functions
      • 56.2. Foreign Data Wrapper Callback Routines
      • 56.3. Foreign Data Wrapper Helper Functions
      • 56.4. Foreign Data Wrapper Query Planning
      • 56.5. Row Locking in Foreign Data Wrappers
    • 60. Writing a Table Sampling Method
    • 61. Writing a Custom Scan Provider
    • 62. Genetic Query Optimizer
      • 59.1. Query Handling as a Complex Optimization Problem
      • 59.2. Genetic Algorithms
      • 59.3. Genetic Query Optimization (GEQO) in PostgreSQL
      • 59.4. Further Reading
    • 63. Table Access Method Interface Definition
    • 64. Index Access Method Interface Definition
    • 65. Generic WAL Records
    • 66. Custom WAL Resource Managers
    • 67. B-Tree Indexes
      • 67.1. Introduction
      • 67.2. Behavior of B-Tree Operator Classes
      • 67.3. B-Tree Support Functions
      • 67.4. Implementation
    • 68. GiST Indexes
      • 64.1. Introduction
      • 64.2. Built-in Operator Classes
      • 64.3. Extensibility
      • 64.4. Implementation
      • 64.5. Examples
    • 69. SP-GiST Indexes
      • 65.1. Introduction
      • 65.2. Built-in Operator Classes
      • 65.3. Extensibility
      • 65.4. Implementation
      • 65.5. Examples
    • 70. GIN 索引
      • 70.1. 簡介
      • 70.2. 內建運算子類
      • 70.3. 延伸介面
      • 70.4. 實作說明
      • 70.5. GIN 小技巧
      • 70.6. 限制
      • 70.7. 範例
    • 71. BRIN Indexes
      • 67.1. Introduction
      • 67.2. Built-in Operator Classes
      • 67.3. Extensibility
    • 72. Hash Indexes
    • 73. 資料庫實體儲存格式
      • 73.1. Database File Layout
      • 73.3. TOAST
      • 68.3. Free Space Map
      • 68.4 可視性映射表(Visibility Map)
      • 68.5. The Initialization Fork
      • 68.6. Database Page Layout
    • 74. System Catalog Declarations and Initial Contents
    • 75. 查詢計畫如何使用統計資訊
      • 70.1. Row Estimation Examples
      • 70.2. 多元統計資訊範例
      • 70.3. Planner Statistics and Security
    • 76. Backup Manifest Format
  • VIII. 附錄
    • A. PostgreSQL 錯誤代碼
    • B. 日期時間格式支援
      • B.1. 日期時間解譯流程
      • B.2. Handling of Invalid or Ambiguous Timestamps
      • B.3. 日期時間慣用字
      • B.4. 日期時間設定檔
      • B.5. POSIX Time Zone Specifications
      • B.6. 日期時間的沿革
      • B.7. Julian Dates
    • C. SQL 關鍵字
    • D. SQL 相容性
      • D.1. Supported Features
      • D.2. Unsupported Features
      • D.3. XML Limits and Conformance to SQL/XML
    • E. 版本資訊
      • E.1. Release 15.2
      • E.2. Release 15.1
      • E.3. Release 15
      • E.4. Prior Releases
    • F. 延伸支援模組
      • F.1. adminpack
      • F.2. amcheck
      • F.3. auth_delay
      • F.4. auto_explain
      • F.5. bloom
      • F.6. btree_gin
      • F.10. dblink
        • dblink_connect
        • dblink_connect_u
        • dblink_disconnect
        • dblink
        • dblink_exec
        • dblink_open
        • dblink_fetch
        • dblink_close
        • dblink_get_connections
        • dblink_error_message
        • dblink_send_query
        • dblink_is_busy
        • dblink_get_notify
        • dblink_get_result
        • dblink_cancel_query
        • dblink_get_pkey
        • dblink_build_sql_insert
        • dblink_build_sql_delete
        • dblink_build_sql_update
      • F.13. earthdistance
      • F.14. file_fdw
      • F.16. hstore
      • F.24. pg_buffercache
      • F.26. passwordcheck
      • F.29. pg_stat_statements
      • F.30. pgstattuple
      • F.31. pg_trgm
      • F.32. pg_visibility
      • F.38. postgres_fdw
      • F.35. sepgsql
      • F.43. tablefunc
      • F.45. test_decoding
      • F.46. tsm_system_rows
      • F.47. tsm_system_time
      • F.49. uuid-ossp
    • G. Additional Supplied Programs
      • G.1. Client Applications
        • oid2name
        • vacuumlo
      • G.2. Server Applications
        • pg_standby
    • H. 外部專案
      • H.1. 用戶端介面
      • H.2. Administration Tools
      • H.3. Procedural Languages
      • H.4. Extensions
    • I. The Source Code Repository
      • I.1. Getting The Source via Git
    • J. 文件取得
      • J.1. DocBook
      • J.2. Tool Sets
      • J.3. Building the Documentation
      • J.4. Documentation Authoring
      • J.5. Style Guide
    • K. PostgreSQL Limits
    • L. 縮寫字
    • M. Glossary
    • N. 色彩支援
      • N.1. When Color is Used
      • N.2. Configuring the Colors
    • O. Obsolete or Renamed Features
  • 參考書目
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On this page
  • 8.15.1. Declaration of Array Types
  • 8.15.2. Array Value Input
  • 8.15.3. Accessing Arrays
  • 8.15.4. Modifying Arrays
  • 8.15.5. Searching in Arrays
  • 8.15.6. Array Input and Output Syntax

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  1. II. SQL 查詢語言
  2. 8. 資料型別

8.15. 陣列

PostgreSQL allows columns of a table to be defined as variable-length multidimensional arrays. Arrays of any built-in or user-defined base type, enum type, composite type, range type, or domain can be created.

8.15.1. Declaration of Array Types

To illustrate the use of array types, we create this table:

CREATE TABLE sal_emp (
    name            text,
    pay_by_quarter  integer[],
    schedule        text[][]
);

As shown, an array data type is named by appending square brackets ([]) to the data type name of the array elements. The above command will create a table named sal_emp with a column of type text (name), a one-dimensional array of type integer (pay_by_quarter), which represents the employee's salary by quarter, and a two-dimensional array of text (schedule), which represents the employee's weekly schedule.

The syntax for CREATE TABLE allows the exact size of arrays to be specified, for example:

CREATE TABLE tictactoe (
    squares   integer[3][3]
);

However, the current implementation ignores any supplied array size limits, i.e., the behavior is the same as for arrays of unspecified length.

The current implementation does not enforce the declared number of dimensions either. Arrays of a particular element type are all considered to be of the same type, regardless of size or number of dimensions. So, declaring the array size or number of dimensions in CREATE TABLE is simply documentation; it does not affect run-time behavior.

An alternative syntax, which conforms to the SQL standard by using the keyword ARRAY, can be used for one-dimensional arrays. pay_by_quarter could have been defined as:

    pay_by_quarter  integer ARRAY[4],

Or, if no array size is to be specified:

    pay_by_quarter  integer ARRAY,

As before, however, PostgreSQL does not enforce the size restriction in any case.

8.15.2. Array Value Input

To write an array value as a literal constant, enclose the element values within curly braces and separate them by commas. (If you know C, this is not unlike the C syntax for initializing structures.) You can put double quotes around any element value, and must do so if it contains commas or curly braces. (More details appear below.) Thus, the general format of an array constant is the following:

'{ val1 delim val2 delim ... }'

where delim is the delimiter character for the type, as recorded in its pg_type entry. Among the standard data types provided in the PostgreSQL distribution, all use a comma (,), except for type box which uses a semicolon (;). Each val is either a constant of the array element type, or a subarray. An example of an array constant is:

'{{1,2,3},{4,5,6},{7,8,9}}'

This constant is a two-dimensional, 3-by-3 array consisting of three subarrays of integers.

To set an element of an array constant to NULL, write NULL for the element value. (Any upper- or lower-case variant of NULL will do.) If you want an actual string value “NULL”, you must put double quotes around it.

Now we can show some INSERT statements:

INSERT INTO sal_emp
    VALUES ('Bill',
    '{10000, 10000, 10000, 10000}',
    '{{"meeting", "lunch"}, {"training", "presentation"}}');

INSERT INTO sal_emp
    VALUES ('Carol',
    '{20000, 25000, 25000, 25000}',
    '{{"breakfast", "consulting"}, {"meeting", "lunch"}}');

The result of the previous two inserts looks like this:

SELECT * FROM sal_emp;
 name  |      pay_by_quarter       |                 schedule
-------+---------------------------+-------------------------------------------
 Bill  | {10000,10000,10000,10000} | {{meeting,lunch},{training,presentation}}
 Carol | {20000,25000,25000,25000} | {{breakfast,consulting},{meeting,lunch}}
(2 rows)

Multidimensional arrays must have matching extents for each dimension. A mismatch causes an error, for example:

INSERT INTO sal_emp
    VALUES ('Bill',
    '{10000, 10000, 10000, 10000}',
    '{{"meeting", "lunch"}, {"meeting"}}');
ERROR:  multidimensional arrays must have array expressions with matching dimensions

The ARRAY constructor syntax can also be used:

INSERT INTO sal_emp
    VALUES ('Bill',
    ARRAY[10000, 10000, 10000, 10000],
    ARRAY[['meeting', 'lunch'], ['training', 'presentation']]);

INSERT INTO sal_emp
    VALUES ('Carol',
    ARRAY[20000, 25000, 25000, 25000],
    ARRAY[['breakfast', 'consulting'], ['meeting', 'lunch']]);

8.15.3. Accessing Arrays

Now, we can run some queries on the table. First, we show how to access a single element of an array. This query retrieves the names of the employees whose pay changed in the second quarter:

SELECT name FROM sal_emp WHERE pay_by_quarter[1] <> pay_by_quarter[2];

 name
-------
 Carol
(1 row)

The array subscript numbers are written within square brackets. By default PostgreSQL uses a one-based numbering convention for arrays, that is, an array of n elements starts with array[1] and ends with array[n].

This query retrieves the third quarter pay of all employees:

SELECT pay_by_quarter[3] FROM sal_emp;

 pay_by_quarter
----------------
          10000
          25000
(2 rows)

We can also access arbitrary rectangular slices of an array, or subarrays. An array slice is denoted by writing lower-bound:upper-bound for one or more array dimensions. For example, this query retrieves the first item on Bill's schedule for the first two days of the week:

SELECT schedule[1:2][1:1] FROM sal_emp WHERE name = 'Bill';

        schedule
------------------------
 {{meeting},{training}}
(1 row)

If any dimension is written as a slice, i.e., contains a colon, then all dimensions are treated as slices. Any dimension that has only a single number (no colon) is treated as being from 1 to the number specified. For example, [2] is treated as [1:2], as in this example:

SELECT schedule[1:2][2] FROM sal_emp WHERE name = 'Bill';

                 schedule
-------------------------------------------
 {{meeting,lunch},{training,presentation}}
(1 row)

To avoid confusion with the non-slice case, it's best to use slice syntax for all dimensions, e.g., [1:2][1:1], not [2][1:1].

It is possible to omit the lower-bound and/or upper-bound of a slice specifier; the missing bound is replaced by the lower or upper limit of the array's subscripts. For example:

SELECT schedule[:2][2:] FROM sal_emp WHERE name = 'Bill';

        schedule
------------------------
 {{lunch},{presentation}}
(1 row)

SELECT schedule[:][1:1] FROM sal_emp WHERE name = 'Bill';

        schedule
------------------------
 {{meeting},{training}}
(1 row)

An array subscript expression will return null if either the array itself or any of the subscript expressions are null. Also, null is returned if a subscript is outside the array bounds (this case does not raise an error). For example, if schedule currently has the dimensions [1:3][1:2] then referencing schedule[3][3] yields NULL. Similarly, an array reference with the wrong number of subscripts yields a null rather than an error.

An array slice expression likewise yields null if the array itself or any of the subscript expressions are null. However, in other cases such as selecting an array slice that is completely outside the current array bounds, a slice expression yields an empty (zero-dimensional) array instead of null. (This does not match non-slice behavior and is done for historical reasons.) If the requested slice partially overlaps the array bounds, then it is silently reduced to just the overlapping region instead of returning null.

The current dimensions of any array value can be retrieved with the array_dims function:

SELECT array_dims(schedule) FROM sal_emp WHERE name = 'Carol';

 array_dims
------------
 [1:2][1:2]
(1 row)

array_dims produces a text result, which is convenient for people to read but perhaps inconvenient for programs. Dimensions can also be retrieved with array_upper and array_lower, which return the upper and lower bound of a specified array dimension, respectively:

SELECT array_upper(schedule, 1) FROM sal_emp WHERE name = 'Carol';

 array_upper
-------------
           2
(1 row)

array_length will return the length of a specified array dimension:

SELECT array_length(schedule, 1) FROM sal_emp WHERE name = 'Carol';

 array_length
--------------
            2
(1 row)

cardinality returns the total number of elements in an array across all dimensions. It is effectively the number of rows a call to unnest would yield:

SELECT cardinality(schedule) FROM sal_emp WHERE name = 'Carol';

 cardinality
-------------
           4
(1 row)

8.15.4. Modifying Arrays

An array value can be replaced completely:

UPDATE sal_emp SET pay_by_quarter = '{25000,25000,27000,27000}'
    WHERE name = 'Carol';

or using the ARRAY expression syntax:

UPDATE sal_emp SET pay_by_quarter = ARRAY[25000,25000,27000,27000]
    WHERE name = 'Carol';

An array can also be updated at a single element:

UPDATE sal_emp SET pay_by_quarter[4] = 15000
    WHERE name = 'Bill';

or updated in a slice:

UPDATE sal_emp SET pay_by_quarter[1:2] = '{27000,27000}'
    WHERE name = 'Carol';

The slice syntaxes with omitted lower-bound and/or upper-bound can be used too, but only when updating an array value that is not NULL or zero-dimensional (otherwise, there is no existing subscript limit to substitute).

A stored array value can be enlarged by assigning to elements not already present. Any positions between those previously present and the newly assigned elements will be filled with nulls. For example, if array myarray currently has 4 elements, it will have six elements after an update that assigns to myarray[6]; myarray[5] will contain null. Currently, enlargement in this fashion is only allowed for one-dimensional arrays, not multidimensional arrays.

Subscripted assignment allows creation of arrays that do not use one-based subscripts. For example one might assign to myarray[-2:7] to create an array with subscript values from -2 to 7.

New array values can also be constructed using the concatenation operator, ||:

SELECT ARRAY[1,2] || ARRAY[3,4];
 ?column?
-----------
 {1,2,3,4}
(1 row)

SELECT ARRAY[5,6] || ARRAY[[1,2],[3,4]];
      ?column?
---------------------
 {{5,6},{1,2},{3,4}}
(1 row)

The concatenation operator allows a single element to be pushed onto the beginning or end of a one-dimensional array. It also accepts two N-dimensional arrays, or an N-dimensional and an N+1-dimensional array.

When a single element is pushed onto either the beginning or end of a one-dimensional array, the result is an array with the same lower bound subscript as the array operand. For example:

SELECT array_dims(1 || '[0:1]={2,3}'::int[]);
 array_dims
------------
 [0:2]
(1 row)

SELECT array_dims(ARRAY[1,2] || 3);
 array_dims
------------
 [1:3]
(1 row)

When two arrays with an equal number of dimensions are concatenated, the result retains the lower bound subscript of the left-hand operand's outer dimension. The result is an array comprising every element of the left-hand operand followed by every element of the right-hand operand. For example:

SELECT array_dims(ARRAY[1,2] || ARRAY[3,4,5]);
 array_dims
------------
 [1:5]
(1 row)

SELECT array_dims(ARRAY[[1,2],[3,4]] || ARRAY[[5,6],[7,8],[9,0]]);
 array_dims
------------
 [1:5][1:2]
(1 row)

When an N-dimensional array is pushed onto the beginning or end of an N+1-dimensional array, the result is analogous to the element-array case above. Each N-dimensional sub-array is essentially an element of the N+1-dimensional array's outer dimension. For example:

SELECT array_dims(ARRAY[1,2] || ARRAY[[3,4],[5,6]]);
 array_dims
------------
 [1:3][1:2]
(1 row)

An array can also be constructed by using the functions array_prepend, array_append, or array_cat. The first two only support one-dimensional arrays, but array_cat supports multidimensional arrays. Some examples:

SELECT array_prepend(1, ARRAY[2,3]);
 array_prepend
---------------
 {1,2,3}
(1 row)

SELECT array_append(ARRAY[1,2], 3);
 array_append
--------------
 {1,2,3}
(1 row)

SELECT array_cat(ARRAY[1,2], ARRAY[3,4]);
 array_cat
-----------
 {1,2,3,4}
(1 row)

SELECT array_cat(ARRAY[[1,2],[3,4]], ARRAY[5,6]);
      array_cat
---------------------
 {{1,2},{3,4},{5,6}}
(1 row)

SELECT array_cat(ARRAY[5,6], ARRAY[[1,2],[3,4]]);
      array_cat
---------------------
 {{5,6},{1,2},{3,4}}

In simple cases, the concatenation operator discussed above is preferred over direct use of these functions. However, because the concatenation operator is overloaded to serve all three cases, there are situations where use of one of the functions is helpful to avoid ambiguity. For example consider:

SELECT ARRAY[1, 2] || '{3, 4}';  -- the untyped literal is taken as an array
 ?column?
-----------
 {1,2,3,4}

SELECT ARRAY[1, 2] || '7';                 -- so is this one
ERROR:  malformed array literal: "7"

SELECT ARRAY[1, 2] || NULL;                -- so is an undecorated NULL
 ?column?
----------
 {1,2}
(1 row)

SELECT array_append(ARRAY[1, 2], NULL);    -- this might have been meant
 array_append
--------------
 {1,2,NULL}

In the examples above, the parser sees an integer array on one side of the concatenation operator, and a constant of undetermined type on the other. The heuristic it uses to resolve the constant's type is to assume it's of the same type as the operator's other input — in this case, integer array. So the concatenation operator is presumed to represent array_cat, not array_append. When that's the wrong choice, it could be fixed by casting the constant to the array's element type; but explicit use of array_append might be a preferable solution.

8.15.5. Searching in Arrays

To search for a value in an array, each value must be checked. This can be done manually, if you know the size of the array. For example:

SELECT * FROM sal_emp WHERE pay_by_quarter[1] = 10000 OR
                            pay_by_quarter[2] = 10000 OR
                            pay_by_quarter[3] = 10000 OR
                            pay_by_quarter[4] = 10000;
SELECT * FROM sal_emp WHERE 10000 = ANY (pay_by_quarter);

In addition, you can find rows where the array has all values equal to 10000 with:

SELECT * FROM sal_emp WHERE 10000 = ALL (pay_by_quarter);

Alternatively, the generate_subscripts function can be used. For example:

SELECT * FROM
   (SELECT pay_by_quarter,
           generate_subscripts(pay_by_quarter, 1) AS s
      FROM sal_emp) AS foo
 WHERE pay_by_quarter[s] = 10000;

You can also search an array using the && operator, which checks whether the left operand overlaps with the right operand. For instance:

SELECT * FROM sal_emp WHERE pay_by_quarter && ARRAY[10000];

You can also search for specific values in an array using the array_position and array_positions functions. The former returns the subscript of the first occurrence of a value in an array; the latter returns an array with the subscripts of all occurrences of the value in the array. For example:

SELECT array_position(ARRAY['sun','mon','tue','wed','thu','fri','sat'], 'mon');
 array_positions
-----------------
 2

SELECT array_positions(ARRAY[1, 4, 3, 1, 3, 4, 2, 1], 1);
 array_positions
-----------------
 {1,4,8}

Tip

Arrays are not sets; searching for specific array elements can be a sign of database misdesign. Consider using a separate table with a row for each item that would be an array element. This will be easier to search, and is likely to scale better for a large number of elements.

8.15.6. Array Input and Output Syntax

The external text representation of an array value consists of items that are interpreted according to the I/O conversion rules for the array's element type, plus decoration that indicates the array structure. The decoration consists of curly braces ({ and }) around the array value plus delimiter characters between adjacent items. The delimiter character is usually a comma (,) but can be something else: it is determined by the typdelim setting for the array's element type. Among the standard data types provided in the PostgreSQL distribution, all use a comma, except for type box, which uses a semicolon (;). In a multidimensional array, each dimension (row, plane, cube, etc.) gets its own level of curly braces, and delimiters must be written between adjacent curly-braced entities of the same level.

The array output routine will put double quotes around element values if they are empty strings, contain curly braces, delimiter characters, double quotes, backslashes, or white space, or match the word NULL. Double quotes and backslashes embedded in element values will be backslash-escaped. For numeric data types it is safe to assume that double quotes will never appear, but for textual data types one should be prepared to cope with either the presence or absence of quotes.

By default, the lower bound index value of an array's dimensions is set to one. To represent arrays with other lower bounds, the array subscript ranges can be specified explicitly before writing the array contents. This decoration consists of square brackets ([]) around each array dimension's lower and upper bounds, with a colon (:) delimiter character in between. The array dimension decoration is followed by an equal sign (=). For example:

SELECT f1[1][-2][3] AS e1, f1[1][-1][5] AS e2
 FROM (SELECT '[1:1][-2:-1][3:5]={{{1,2,3},{4,5,6}}}'::int[] AS f1) AS ss;

 e1 | e2
----+----
  1 |  6
(1 row)

The array output routine will include explicit dimensions in its result only when there are one or more lower bounds different from one.

As shown previously, when writing an array value you can use double quotes around any individual array element. You must do so if the element value would otherwise confuse the array-value parser. For example, elements containing curly braces, commas (or the data type's delimiter character), double quotes, backslashes, or leading or trailing whitespace must be double-quoted. Empty strings and strings matching the word NULL must be quoted, too. To put a double quote or backslash in a quoted array element value, precede it with a backslash. Alternatively, you can avoid quotes and use backslash-escaping to protect all data characters that would otherwise be taken as array syntax.

You can add whitespace before a left brace or after a right brace. You can also add whitespace before or after any individual item string. In all of these cases the whitespace will be ignored. However, whitespace within double-quoted elements, or surrounded on both sides by non-whitespace characters of an element, is not ignored.

Tip

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(These kinds of array constants are actually only a special case of the generic type constants discussed in . The constant is initially treated as a string and passed to the array input conversion routine. An explicit type specification might be necessary.)

Notice that the array elements are ordinary SQL constants or expressions; for instance, string literals are single quoted, instead of double quoted as they would be in an array literal. The ARRAY constructor syntax is discussed in more detail in .

However, this quickly becomes tedious for large arrays, and is not helpful if the size of the array is unknown. An alternative method is described in . The above query could be replaced by:

This function is described in .

This and other array operators are further described in . It can be accelerated by an appropriate index, as described in .

If the value written for an element is NULL (in any case variant), the element is taken to be NULL. The presence of any quotes or backslashes disables this and allows the literal string value “NULL” to be entered. Also, for backward compatibility with pre-8.2 versions of PostgreSQL, the configuration parameter can be turned off to suppress recognition of NULL as a NULL.

The ARRAY constructor syntax (see ) is often easier to work with than the array-literal syntax when writing array values in SQL commands. In ARRAY, individual element values are written the same way they would be written when not members of an array.\

Section 4.1.2.7
Section 4.2.12
Section 9.23
Table 9.62
Section 9.18
Section 11.2
array_nulls
Section 4.2.12