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. 集合回傳函式
      • 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(MVCC)
      • 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. 特別注意
      • 13.6. 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. Installation from Binaries
    • 17. 用原始碼安裝
      • 16.1. Short Version
      • 16.2. Requirements
      • 16.3. Getting The Source
      • 16.4. 安裝流程
      • 16.5. Post-Installation Setup
      • 16.6. Supported Platforms
      • 16.7. 平台相關的注意事項
    • 18. 用原始碼在 Windows 上安裝
      • 17.1. Building with Visual C++ or the Microsoft Windows SDK
    • 19. 服務配置與維運
      • 18.1. PostgreSQL 使用者帳號
      • 18.2. Creating a Database Cluster
      • 18.3. Starting the Database Server
      • 18.4. 核心資源管理
      • 18.5. Shutting Down the Server
      • 18.6. Upgrading a PostgreSQL Cluster
      • 18.7. Preventing Server Spoofing
      • 18.8. Encryption Options
      • 18.9. Secure TCP/IP Connections with SSL
      • 18.10. Secure TCP/IP Connections with GSSAPI Encryption
      • 18.11. Secure TCP/IP Connections with SSH Tunnels
      • 18.12. 在 Windows 註冊事件日誌
    • 20. 服務組態設定
      • 19.1. Setting Parameters
      • 19.2. File Locations
      • 19.3. 連線與認證
      • 19.4. 資源配置
      • 19.5. Write Ahead Log
      • 19.6. 複寫(Replication)
      • 19.7. 查詢規畫
      • 19.8. 錯誤回報與日誌記錄
      • 19.9. 執行階段統計資訊
      • 19.10. 自動資料庫清理
      • 20.11. 用戶端連線預設參數
      • 19.12. 交易鎖定管理
      • 19.13. 版本與平台的相容性
      • 19.14. Error Handling
      • 19.15. 預先配置的參數
      • 19.16. Customized Options
      • 19.17. Developer Options
      • 19.18. Short Options
    • 21. 使用者認證
      • 20.1. 設定檔:pg_hba.conf
      • 20.2. User Name Maps
      • 20.3. Authentication Methods
      • 20.4. Trust Authentication
      • 20.5. Password Authentication
      • 20.6. GSSAPI Authentication
      • 20.7. SSPI Authentication
      • 20.8. Ident Authentication
      • 20.9. Peer Authentication
      • 20.10. LDAP Authentication
      • 20.11. RADIUS Authentication
      • 20.12. Certificate Authentication
      • 20.13. PAM Authentication
    • 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. Managing Databases
      • 22.1. Overview
      • 22.2. Creating a Database
      • 22.3. 樣版資料庫
      • 22.4. Database Configuration
      • 22.5. Destroying a Database
      • 22.6. Tablespaces
    • 24. 語系
      • 23.1. 語系支援
      • 23.2. Collation Support
      • 23.3. 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
      • 25.1. SQL Dump
      • 25.2. 檔案系統層級備份
      • 25.3. Continuous Archiving and Point-in-Time Recovery (PITR)
    • 27. High Availability, Load Balancing, and Replication
      • 26.1. 比較不同的解決方案
      • 26.2. 日誌轉送備用伺服器 Log-Shipping Standby Servers
      • 26.3. Failover
      • 26.4. Alternative Method for Log Shipping
      • 26.5. Hot Standby
    • 28. 監控資料庫活動
      • 27.1. Standard Unix Tools
      • 27.2. 統計資訊收集器
      • 27.3. Viewing Locks
      • 27.4. Progress Reporting
      • 27.5. Dynamic Tracing
    • 29. 監控磁碟使用情況
      • 28.1. 瞭解磁碟使用情形
      • 28.2. 磁碟空間不足錯誤
    • 30. 高可靠度及預寫日誌
      • 29.1. 可靠度
      • 29.2. Write-Ahead Logging(WAL)
      • 29.3. Asynchronous Commit
      • 29.4. WAL Configuration
      • 29.5. WAL Internals
    • 31. 邏輯複寫(Logical Replication)
      • 30.1. 發佈(Publication)
      • 30.2. 訂閱(Subscription)
      • 30.3. 衝突處理
      • 30.4. 限制
      • 30.5. 架構
      • 30.6. 監控
      • 30.7. 安全性
      • 30.8. 系統設定
      • 30.9. 快速設定
    • 32. Just-in-Time Compilation(JIT)
      • 31.1. What is JIT compilation?
      • 31.2. When to JIT?
      • 31.3. Configuration
      • 31.4. Extensibility
    • 33. 迴歸測試
      • 32.1. Running the Tests
      • 32.2. Test Evaluation
      • 32.3. Variant Comparison Files
      • 32.4. TAP Tests
      • 32.5. Test Coverage Examination
  • IV. 用戶端介面
    • 33. 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
      • 33.15. 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
    • 34. Large Objects
      • 35.1. Introduction
      • 35.2. Implementation Features
      • 35.3. Client Interfaces
      • 35.4. Server-side Functions
      • 35.5. Example Program
    • 35. 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
    • 36. The Information Schema
      • 36.1. The Schema
      • 36.2. Data Types
      • 36.3. information_schema_catalog_name
      • 36.4. administrable_role_authorizations
      • 36.5. applicable_roles
      • 36.6. attributes
      • 36.7. character_sets
      • 36.8. check_constraint_routine_usage
      • 36.9. check_constraints
      • 36.10. collations
      • 36.11. collation_character_set_applicability
      • 36.12. column_domain_usage
      • 36.13. column_options
      • 36.14. column_privileges
      • 36.16. column_udt_usage
      • 36.17. columns
      • 36.18. constraint_column_usage
      • 37.18. constraint_table_usage
      • 37.19. data_type_privileges
      • 37.20. 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
      • 36.33. parameters
      • 36.34. referential_constraints
      • 37.34. role_column_grants
      • 37.35. role_routine_grants
      • 36.37. role_table_grants
      • 37.37. role_udt_grants
      • 37.38. role_usage_grants
      • 37.39. routine_privileges
      • 37.40. routines
      • 36.42. schemata
      • 37.42. sequences
      • 37.43. sql_features
      • 37.44. sql_implementation_info
      • 37.45. sql_languages
      • 37.46. sql_packages
      • 37.47. sql_parts
      • 37.48. sql_sizing
      • 37.49. sql_sizing_profiles
      • 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
      • 37.61. view_column_usage
      • 37.62. view_routine_usage
      • 37.63. view_table_usage
      • 37.64. views
  • V. 資料庫程式設計
    • 38. SQL 延伸功能
      • 38.1. How Extensibility Works
      • 37.2. The PostgreSQL Type System
      • 37.3. 使用者自訂函數
      • 37.4. User-defined Procedures
      • 37.5. Query Language (SQL) Functions
      • 37.6. Function Overloading
      • 37.7. 函數易變性類別
      • 37.8. Procedural Language Functions
      • 37.9. Internal Functions
      • 37.10. C-Language Functions
      • 37.11. Function Optimization Information
      • 37.12. User-defined Aggregates
      • 37.13. User-defined Types
      • 37.14. User-defined Operators
      • 37.15. Operator Optimization Information
      • 38.16. Interfacing Extensions To Indexes
      • 37.17. 封裝相關物件到延伸功能中
      • 37.18. Extension Building Infrastructure
    • 38. Triggers
      • 38.1. Overview of Trigger Behavior
      • 38.2. Visibility of Data Changes
      • 38.3. Writing Trigger Functions in C
      • 38.4. A Complete Trigger Example
    • 39. Event Triggers (事件觸發)
      • 39.1. Overview of Event Trigger Behavior
      • 39.2. Event Trigger Firing Matrix
      • 39.3. Writing Event Trigger Functions in C
      • 39.4. A Complete Event Trigger Example
    • 40. 規則系統
      • 40.1. The Query Tree
      • 40.2. Views and the Rule System
      • 40.3. Materialized Views
      • 40.4. Rules on INSERT, UPDATE, and DELETE
      • 40.5. 規則及權限
      • 40.6. Rules and Command Status
      • 40.7. Rules Versus Triggers
    • 41. Procedural Languages(程序語言)
      • 41.1. Installing Procedural Languages
      • 41.2. Structure of PL/pgSQL
      • 41.5. Basic Statements
      • 41.11. 深入了解 PL/pgSQL
    • 42. PL/pgSQL - SQL Procedural Language
      • 42.1. Overview
      • 42.2. Structure of PL/pgSQL
      • 42.3. Declarations
      • 42.4. Expressions
      • 42.5. 基本語法
      • 42.6. Control Structures
    • 43. PL/Tcl - Tcl Procedural Language
    • 44. PL/Perl — Perl Procedural Language
    • 45. PL/Python - Python Procedural Language
      • 45.1. Python 2 vs. Python 3
      • 45.2. PL/Python Functions
      • 45.3. Data Values
      • 45.4. Sharing Data
      • 45.5. Anonymous Code Blocks
      • 45.6. Trigger Functions
      • 45.7. Database Access
      • 45.8. Explicit Subtransactions
      • 45.9. Transaction Management
      • 45.10. Utility Functions
      • 45.11. Environment Variables
    • 46. Server Programming Interface
    • 47. Background Worker Processes
    • 48. 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
    • 49. Replication Progress Tracking
  • 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
      • 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_timing
      • pg_upgrade
      • postgres
  • VII. 資料庫進階
    • 50. PostgreSQL 的內部架構
      • 50.1. 處理查詢語句的流程
      • 50.2. How Connections Are Established
      • 50.3. The Parser Stage
      • 50.4. The PostgreSQL Rule System
      • 50.5. Planner/Optimizer
      • 50.6. Executor
    • 51. 系統目錄
      • 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
      • 51.80. pg_replication_slots
      • 51.82 pg_roles
      • 51.85. pg_settings
      • 51.87. pg_shmem_allocations
      • 51.88. pg_stats
      • 51.90. pg_tables
      • 51.93. pg_user
      • 51.95. pg_views
    • 52. 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
    • 53. 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
    • 54. Native Language Support
      • 54.1. For the Translator
      • 54.2. For the Programmer
    • 55. 撰寫程序語言的處理程序
    • 56. 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
    • 59. 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
    • 60. Table Access Method Interface Definition
    • 61. Index Access Method Interface Definition
    • 62. Generic WAL Records
    • 64. B-Tree Indexes
      • 64.1. Introduction
      • 64.2. Behavior of B-Tree Operator Classes
      • 64.3. B-Tree Support Functions
      • 64.4. Implementation
    • 64. GiST Indexes
      • 64.1. Introduction
      • 64.2. Built-in Operator Classes
      • 64.3. Extensibility
      • 64.4. Implementation
      • 64.5. Examples
    • 65. SP-GiST Indexes
      • 65.1. Introduction
      • 65.2. Built-in Operator Classes
      • 65.3. Extensibility
      • 65.4. Implementation
      • 65.5. Examples
    • 66. GIN 索引
      • 66.1. 簡介
      • 66.2. 內建運算子類
      • 66.3. 延伸介面
      • 66.4. 實作說明
      • 66.5. GIN 小巧技
      • 66.6. 限制
      • 66.7. 範例
    • 67. BRIN Indexes
      • 67.1. Introduction
      • 67.2. Built-in Operator Classes
      • 67.3. Extensibility
    • 68. 資料庫實體儲存格式
      • 68.1. Database File Layout
      • 68.2. 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
    • 69. System Catalog Declarations and Initial Contents
    • 70. 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
    • 71. 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. 日期時間慣用字
      • B.3. 日期時間設定檔
      • B.4. 日期時間的沿革
    • 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 14
    • 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.29. pg_stat_statements
      • F.30. pgstattuple
      • F.31. pg_trgm
      • F.32. pg_visibility
      • F.33. postgres_fdw
      • F.35. sepgsql
      • F.38. tablefunc
      • F.40. test_decoding
      • F.41. tsm_system_rows
      • F.42. tsm_system_time
      • F.44. 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
    • 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
  • 參考書目
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  • 9.16.1. Processing and Creating JSON Data
  • 9.16.2. The SQL/JSON Path Language
  • 9.16.2.1. Strict And Lax Modes
  • 9.16.2.2. Regular Expressions
  • 9.16.2.3. SQL/JSON Path Operators And Methods

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  1. II. SQL 查詢語言
  2. 9. 函式及運算子

9.16. JSON 函式及運算子

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本節描述的內容為:

  • 用於處理和建立 JSON 資料的函數和運算子

  • SQL/JSON 路徑語言

要了解有關 SQL/JSON 標準的更多資訊,請參閱 []。有關於 PostgreSQL 支援的 JSON 型別的詳細資訊,請參閱。

9.16.1. Processing and Creating JSON Data

列出了可用於 JSON 資料型別的運算子(請參閱)。

Table 9.44. json and jsonb Operators

Operator
Right Operand Type
Return type
Description
Example
Example Result

->

int

json or jsonb

Get JSON array element (indexed from zero, negative integers count from the end)

'[{"a":"foo"},{"b":"bar"},{"c":"baz"}]'::json->2

{"c":"baz"}

->

text

json or jsonb

Get JSON object field by key

'{"a": {"b":"foo"}}'::json->'a'

{"b":"foo"}

->>

int

text

Get JSON array element as text

'[1,2,3]'::json->>2

3

->>

text

text

Get JSON object field as text

'{"a":1,"b":2}'::json->>'b'

2

#>

text[]

json or jsonb

Get JSON object at the specified path

'{"a": {"b":{"c": "foo"}}}'::json#>'{a,b}'

{"c": "foo"}

#>>

text[]

text

Get JSON object at the specified path as text

'{"a":[1,2,3],"b":[4,5,6]}'::json#>>'{a,2}'

3

這些運算子都有 json 和 jsonb 型別共用的變形。欄位/元素/路徑提取運算子回傳與其左側輸入相同的類型(json 或 jsonb),但指定為回傳 text 的運算符除外,這些運算子將結果強制轉換為 text。如果 JSON 輸入的結構不符合要求,則欄位/元素/路徑提取運算子將回傳 NULL 而不會失敗。例如,如果不存在這樣的元素。接受整數 JSON 陣列索引的欄位/元素/路徑提取運算子均支援表示從陣列末尾開始的負數索引值。

The standard comparison operators shown in are available for jsonb, but not for json. They follow the ordering rules for B-tree operations outlined at .

Some further operators also exist only for jsonb, as shown in . Many of these operators can be indexed by jsonb operator classes. For a full description of jsonb containment and existence semantics, see . describes how these operators can be used to effectively index jsonb data.

Table 9.45. Additional jsonb Operators

Operator
Right Operand Type
Description
Example

@>

jsonb

Does the left JSON value contain the right JSON path/value entries at the top level?

'{"a":1, "b":2}'::jsonb @> '{"b":2}'::jsonb

<@

jsonb

Are the left JSON path/value entries contained at the top level within the right JSON value?

'{"b":2}'::jsonb <@ '{"a":1, "b":2}'::jsonb

?

text

Does the string exist as a top-level key within the JSON value?

'{"a":1, "b":2}'::jsonb ? 'b'

?|

text[]

Do any of these array strings exist as top-level keys?

'{"a":1, "b":2, "c":3}'::jsonb ?| array['b', 'c']

?&

text[]

Do all of these array strings exist as top-level keys?

'["a", "b"]'::jsonb ?& array['a', 'b']

||

jsonb

Concatenate two jsonb values into a new jsonb value

'["a", "b"]'::jsonb || '["c", "d"]'::jsonb

-

text

Delete key/value pair or string element from left operand. Key/value pairs are matched based on their key value.

'{"a": "b"}'::jsonb - 'a'

-

text[]

Delete multiple key/value pairs or string elements from left operand. Key/value pairs are matched based on their key value.

'{"a": "b", "c": "d"}'::jsonb - '{a,c}'::text[]

-

integer

Delete the array element with specified index (Negative integers count from the end). Throws an error if top level container is not an array.

'["a", "b"]'::jsonb - 1

#-

text[]

Delete the field or element with specified path (for JSON arrays, negative integers count from the end)

'["a", {"b":1}]'::jsonb #- '{1,b}'

@?

jsonpath

Does JSON path return any item for the specified JSON value?

'{"a":[1,2,3,4,5]}'::jsonb @? '$.a[*] ? (@ > 2)'

@@

jsonpath

Returns the result of JSON path predicate check for the specified JSON value. Only the first item of the result is taken into account. If the result is not Boolean, then null is returned.

'{"a":[1,2,3,4,5]}'::jsonb @@ '$.a[*] > 2'

Note

The || operator concatenates the elements at the top level of each of its operands. It does not operate recursively. For example, if both operands are objects with a common key field name, the value of the field in the result will just be the value from the right hand operand.

Note

The @? and @@ operators suppress the following errors: lacking object field or array element, unexpected JSON item type, and numeric errors. This behavior might be helpful while searching over JSON document collections of varying structure.

Table 9.46. JSON Creation Functions

Function
Description
Example
Example Result

to_json(anyelement)

to_jsonb(anyelement)

Returns the value as json or jsonb. Arrays and composites are converted (recursively) to arrays and objects; otherwise, if there is a cast from the type to json, the cast function will be used to perform the conversion; otherwise, a scalar value is produced. For any scalar type other than a number, a Boolean, or a null value, the text representation will be used, in such a fashion that it is a valid json or jsonb value.

to_json('Fred said "Hi."'::text)

"Fred said \"Hi.\""

array_to_json(anyarray [, pretty_bool])

Returns the array as a JSON array. A PostgreSQL multidimensional array becomes a JSON array of arrays. Line feeds will be added between dimension-1 elements if pretty_bool is true.

array_to_json('{{1,5},{99,100}}'::int[])

[[1,5],[99,100]]

row_to_json(record [, pretty_bool])

Returns the row as a JSON object. Line feeds will be added between level-1 elements if pretty_bool is true.

row_to_json(row(1,'foo'))

{"f1":1,"f2":"foo"}

json_build_array(VARIADIC "any")

jsonb_build_array(VARIADIC "any")

Builds a possibly-heterogeneously-typed JSON array out of a variadic argument list.

json_build_array(1,2,'3',4,5)

[1, 2, "3", 4, 5]

json_build_object(VARIADIC "any")

jsonb_build_object(VARIADIC "any")

Builds a JSON object out of a variadic argument list. By convention, the argument list consists of alternating keys and values.

json_build_object('foo',1,'bar',2)

{"foo": 1, "bar": 2}

json_object(text[])

jsonb_object(text[])

Builds a JSON object out of a text array. The array must have either exactly one dimension with an even number of members, in which case they are taken as alternating key/value pairs, or two dimensions such that each inner array has exactly two elements, which are taken as a key/value pair.

json_object('{a, 1, b, "def", c, 3.5}')

json_object('{{a, 1},{b, "def"},{c, 3.5}}')

{"a": "1", "b": "def", "c": "3.5"}

json_object(keys text[], values text[])

jsonb_object(keys text[], values text[])

This form of json_object takes keys and values pairwise from two separate arrays. In all other respects it is identical to the one-argument form.

json_object('{a, b}', '{1,2}')

{"a": "1", "b": "2"}

Note

array_to_json and row_to_json have the same behavior as to_json except for offering a pretty-printing option. The behavior described for to_json likewise applies to each individual value converted by the other JSON creation functions.

Note

Table 9.47. JSON Processing Functions

Function
Return Type
Description
Example
Example Result

json_array_length(json)

jsonb_array_length(jsonb)

int

Returns the number of elements in the outermost JSON array.

json_array_length('[1,2,3,{"f1":1,"f2":[5,6]},4]')

5

json_each(json)

jsonb_each(jsonb)

setof key text, value json

setof key text, value jsonb

Expands the outermost JSON object into a set of key/value pairs.

select * from json_each('{"a":"foo", "b":"bar"}')

json_each_text(json)

jsonb_each_text(jsonb)

setof key text, value text

Expands the outermost JSON object into a set of key/value pairs. The returned values will be of type text.

select * from json_each_text('{"a":"foo", "b":"bar"}')

json_extract_path(from_json json, VARIADIC path_elems text[])

jsonb_extract_path(from_json jsonb, VARIADIC path_elems text[])

json

jsonb

Returns JSON value pointed to by path_elems (equivalent to #> operator).

json_extract_path('{"f2":{"f3":1},"f4":{"f5":99,"f6":"foo"}}','f4')

{"f5":99,"f6":"foo"}

json_extract_path_text(from_json json, VARIADIC path_elems text[])

jsonb_extract_path_text(from_json jsonb, VARIADIC path_elems text[])

text

Returns JSON value pointed to by path_elems as text (equivalent to #>> operator).

json_extract_path_text('{"f2":{"f3":1},"f4":{"f5":99,"f6":"foo"}}','f4', 'f6')

foo

json_object_keys(json)

jsonb_object_keys(jsonb)

setof text

Returns set of keys in the outermost JSON object.

json_object_keys('{"f1":"abc","f2":{"f3":"a", "f4":"b"}}')

json_populate_record(base anyelement, from_json json)

jsonb_populate_record(base anyelement, from_json jsonb)

anyelement

Expands the object in from_json to a row whose columns match the record type defined by base (see note below).

select * from json_populate_record(null::myrowtype, '{"a": 1, "b": ["2", "a b"], "c": {"d": 4, "e": "a b c"}}')

json_populate_recordset(base anyelement, from_json json)

jsonb_populate_recordset(base anyelement, from_json jsonb)

setof anyelement

Expands the outermost array of objects in from_json to a set of rows whose columns match the record type defined by base (see note below).

select * from json_populate_recordset(null::myrowtype, '[{"a":1,"b":2},{"a":3,"b":4}]')

json_array_elements(json)

jsonb_array_elements(jsonb)

setof json

setof jsonb

Expands a JSON array to a set of JSON values.

select * from json_array_elements('[1,true, [2,false]]')

json_array_elements_text(json)

jsonb_array_elements_text(jsonb)

setof text

Expands a JSON array to a set of text values.

select * from json_array_elements_text('["foo", "bar"]')

json_typeof(json)

jsonb_typeof(jsonb)

text

Returns the type of the outermost JSON value as a text string. Possible types are object, array, string, number, boolean, and null.

json_typeof('-123.4')

number

json_to_record(json)

jsonb_to_record(jsonb)

record

Builds an arbitrary record from a JSON object (see note below). As with all functions returning record, the caller must explicitly define the structure of the record with an AS clause.

select * from json_to_record('{"a":1,"b":[1,2,3],"c":[1,2,3],"e":"bar","r": {"a": 123, "b": "a b c"}}') as x(a int, b text, c int[], d text, r myrowtype)

json_to_recordset(json)

jsonb_to_recordset(jsonb)

setof record

Builds an arbitrary set of records from a JSON array of objects (see note below). As with all functions returning record, the caller must explicitly define the structure of the record with an AS clause.

select * from json_to_recordset('[{"a":1,"b":"foo"},{"a":"2","c":"bar"}]') as x(a int, b text);

json_strip_nulls(from_json json)

jsonb_strip_nulls(from_json jsonb)

json

jsonb

Returns from_json with all object fields that have null values omitted. Other null values are untouched.

json_strip_nulls('[{"f1":1,"f2":null},2,null,3]')

[{"f1":1},2,null,3]

jsonb_set(target jsonb, path text[], new_value jsonb [, create_missing boolean])

jsonb

Returns target with the section designated by path replaced by new_value, or with new_value added if create_missing is true (default is true) and the item designated by path does not exist. As with the path oriented operators, negative integers that appear in path count from the end of JSON arrays.

jsonb_set('[{"f1":1,"f2":null},2,null,3]', '{0,f1}','[2,3,4]', false)

jsonb_set('[{"f1":1,"f2":null},2]', '{0,f3}','[2,3,4]')

[{"f1":[2,3,4],"f2":null},2,null,3]

[{"f1": 1, "f2": null, "f3": [2, 3, 4]}, 2]

jsonb_insert(target jsonb, path text[], new_value jsonb [, insert_after boolean])

jsonb

Returns target with new_value inserted. If target section designated by path is in a JSONB array, new_value will be inserted before target or after if insert_after is true (default is false). If target section designated by path is in JSONB object, new_value will be inserted only if target does not exist. As with the path oriented operators, negative integers that appear in path count from the end of JSON arrays.

jsonb_insert('{"a": [0,1,2]}', '{a, 1}', '"new_value"')

jsonb_insert('{"a": [0,1,2]}', '{a, 1}', '"new_value"', true)

{"a": [0, "new_value", 1, 2]}

{"a": [0, 1, "new_value", 2]}

jsonb_pretty(from_json jsonb)

text

Returns from_json as indented JSON text.

jsonb_pretty('[{"f1":1,"f2":null},2,null,3]')

jsonb_path_exists(target jsonb, path jsonpath [, vars jsonb [, silent bool]])

boolean

Checks whether JSON path returns any item for the specified JSON value.

jsonb_path_exists('{"a":[1,2,3,4,5]}', '$.a[*] ? (@ >= $min && @ <= $max)', '{"min":2,"max":4}')

true

jsonb_path_match(target jsonb, path jsonpath [, vars jsonb [, silent bool]])

boolean

Returns the result of JSON path predicate check for the specified JSON value. Only the first item of the result is taken into account. If the result is not Boolean, then null is returned.

jsonb_path_match('{"a":[1,2,3,4,5]}', 'exists($.a[*] ? (@ >= $min && @ <= $max))', '{"min":2,"max":4}')

true

jsonb_path_query(target jsonb, path jsonpath [, vars jsonb [, silent bool]])

setof jsonb

Gets all JSON items returned by JSON path for the specified JSON value.

select * from jsonb_path_query('{"a":[1,2,3,4,5]}', '$.a[*] ? (@ >= $min && @ <= $max)', '{"min":2,"max":4}');

jsonb_path_query_array(target jsonb, path jsonpath [, vars jsonb [, silent bool]])

jsonb

Gets all JSON items returned by JSON path for the specified JSON value and wraps result into an array.

jsonb_path_query_array('{"a":[1,2,3,4,5]}', '$.a[*] ? (@ >= $min && @ <= $max)', '{"min":2,"max":4}')

[2, 3, 4]

jsonb_path_query_first(target jsonb, path jsonpath [, vars jsonb [, silent bool]])

jsonb

Gets the first JSON item returned by JSON path for the specified JSON value. Returns NULL on no results.

jsonb_path_query_first('{"a":[1,2,3,4,5]}', '$.a[*] ? (@ >= $min && @ <= $max)', '{"min":2,"max":4}')

2

Note

Note

The functions json[b]_populate_record, json[b]_populate_recordset, json[b]_to_record and json[b]_to_recordset operate on a JSON object, or array of objects, and extract the values associated with keys whose names match column names of the output row type. Object fields that do not correspond to any output column name are ignored, and output columns that do not match any object field will be filled with nulls. To convert a JSON value to the SQL type of an output column, the following rules are applied in sequence:

  • A JSON null value is converted to a SQL null in all cases.

  • If the output column is of type json or jsonb, the JSON value is just reproduced exactly.

  • If the output column is a composite (row) type, and the JSON value is a JSON object, the fields of the object are converted to columns of the output row type by recursive application of these rules.

  • Likewise, if the output column is an array type and the JSON value is a JSON array, the elements of the JSON array are converted to elements of the output array by recursive application of these rules.

  • Otherwise, if the JSON value is a string literal, the contents of the string are fed to the input conversion function for the column's data type.

  • Otherwise, the ordinary text representation of the JSON value is fed to the input conversion function for the column's data type.

While the examples for these functions use constants, the typical use would be to reference a table in the FROM clause and use one of its json or jsonb columns as an argument to the function. Extracted key values can then be referenced in other parts of the query, like WHERE clauses and target lists. Extracting multiple values in this way can improve performance over extracting them separately with per-key operators.

Note

All the items of the path parameter of jsonb_set as well as jsonb_insert except the last item must be present in the target. If create_missing is false, all items of the path parameter of jsonb_set must be present. If these conditions are not met the target is returned unchanged.

If the last path item is an object key, it will be created if it is absent and given the new value. If the last path item is an array index, if it is positive the item to set is found by counting from the left, and if negative by counting from the right - -1 designates the rightmost element, and so on. If the item is out of the range -array_length .. array_length -1, and create_missing is true, the new value is added at the beginning of the array if the item is negative, and at the end of the array if it is positive.

Note

The json_typeof function's null return value should not be confused with a SQL NULL. While calling json_typeof('null'::json) will return null, calling json_typeof(NULL::json) will return a SQL NULL.

Note

If the argument to json_strip_nulls contains duplicate field names in any object, the result could be semantically somewhat different, depending on the order in which they occur. This is not an issue for jsonb_strip_nulls since jsonb values never have duplicate object field names.

Note

The jsonb_path_exists, jsonb_path_match, jsonb_path_query, jsonb_path_query_array, and jsonb_path_query_first functions have optional vars and silent arguments.

If the vars argument is specified, it provides an object containing named variables to be substituted into a jsonpath expression.

If the silent argument is specified and has the true value, these functions suppress the same errors as the @? and @@ operators.

9.16.2. The SQL/JSON Path Language

JSON query functions and operators pass the provided path expression to the path engine for evaluation. If the expression matches the queried JSON data, the corresponding SQL/JSON item is returned. Path expressions are written in the SQL/JSON path language and can also include arithmetic expressions and functions. Query functions treat the provided expression as a text string, so it must be enclosed in single quotes.

A path expression consists of a sequence of elements allowed by the jsonpath data type. The path expression is evaluated from left to right, but you can use parentheses to change the order of operations. If the evaluation is successful, a sequence of SQL/JSON items (SQL/JSON sequence) is produced, and the evaluation result is returned to the JSON query function that completes the specified computation.

For example, suppose you have some JSON data from a GPS tracker that you would like to parse, such as:

{
  "track": {
    "segments": [
      {
        "location":   [ 47.763, 13.4034 ],
        "start time": "2018-10-14 10:05:14",
        "HR": 73
      },
      {
        "location":   [ 47.706, 13.2635 ],
        "start time": "2018-10-14 10:39:21",
        "HR": 135
      }
    ]
  }
}

To retrieve the available track segments, you need to use the .key accessor operator for all the preceding JSON objects:

'$.track.segments'

If the item to retrieve is an element of an array, you have to unnest this array using the [*] operator. For example, the following path will return location coordinates for all the available track segments:

'$.track.segments[*].location'

To return the coordinates of the first segment only, you can specify the corresponding subscript in the [] accessor operator. Note that the SQL/JSON arrays are 0-relative:

'$.track.segments[0].location'
'$.track.segments.size()'

When defining the path, you can also use one or more filter expressions that work similar to the WHERE clause in SQL. A filter expression begins with a question mark and provides a condition in parentheses:

? (condition)

Filter expressions must be specified right after the path evaluation step to which they are applied. The result of this step is filtered to include only those items that satisfy the provided condition. SQL/JSON defines three-valued logic, so the condition can be true, false, or unknown. The unknown value plays the same role as SQL NULL and can be tested for with the is unknown predicate. Further path evaluation steps use only those items for which filter expressions return true.

Suppose you would like to retrieve all heart rate values higher than 130. You can achieve this using the following expression:

'$.track.segments[*].HR ? (@ > 130)'

To get the start time of segments with such values instead, you have to filter out irrelevant segments before returning the start time, so the filter expression is applied to the previous step, and the path used in the condition is different:

'$.track.segments[*] ? (@.HR > 130)."start time"'

You can use several filter expressions on the same nesting level, if required. For example, the following expression selects all segments that contain locations with relevant coordinates and high heart rate values:

'$.track.segments[*] ? (@.location[1] < 13.4) ? (@.HR > 130)."start time"'

Using filter expressions at different nesting levels is also allowed. The following example first filters all segments by location, and then returns high heart rate values for these segments, if available:

'$.track.segments[*] ? (@.location[1] < 13.4).HR ? (@ > 130)'

You can also nest filter expressions within each other:

'$.track ? (exists(@.segments[*] ? (@.HR > 130))).segments.size()'

This expression returns the size of the track if it contains any segments with high heart rate values, or an empty sequence otherwise.

PostgreSQL's implementation of SQL/JSON path language has the following deviations from the SQL/JSON standard:

  • .datetime() item method is not implemented yet mainly because immutable jsonpath functions and operators cannot reference session timezone, which is used in some datetime operations. Datetime support will be added to jsonpath in future versions of PostgreSQL.

  • A path expression can be a Boolean predicate, although the SQL/JSON standard allows predicates only in filters. This is necessary for implementation of the @@ operator. For example, the following jsonpath expression is valid in PostgreSQL:

    '$.track.segments[*].HR < 70'

9.16.2.1. Strict And Lax Modes

When you query JSON data, the path expression may not match the actual JSON data structure. An attempt to access a non-existent member of an object or element of an array results in a structural error. SQL/JSON path expressions have two modes of handling structural errors:

  • lax (default) — the path engine implicitly adapts the queried data to the specified path. Any remaining structural errors are suppressed and converted to empty SQL/JSON sequences.

  • strict — if a structural error occurs, an error is raised.

The lax mode facilitates matching of a JSON document structure and path expression if the JSON data does not conform to the expected schema. If an operand does not match the requirements of a particular operation, it can be automatically wrapped as an SQL/JSON array or unwrapped by converting its elements into an SQL/JSON sequence before performing this operation. Besides, comparison operators automatically unwrap their operands in the lax mode, so you can compare SQL/JSON arrays out-of-the-box. An array of size 1 is considered equal to its sole element. Automatic unwrapping is not performed only when:

  • The path expression contains type() or size() methods that return the type and the number of elements in the array, respectively.

  • The queried JSON data contain nested arrays. In this case, only the outermost array is unwrapped, while all the inner arrays remain unchanged. Thus, implicit unwrapping can only go one level down within each path evaluation step.

For example, when querying the GPS data listed above, you can abstract from the fact that it stores an array of segments when using the lax mode:

'lax $.track.segments.location'

In the strict mode, the specified path must exactly match the structure of the queried JSON document to return an SQL/JSON item, so using this path expression will cause an error. To get the same result as in the lax mode, you have to explicitly unwrap the segments array:

'strict $.track.segments[*].location'

9.16.2.2. Regular Expressions

SQL/JSON path expressions allow matching text to a regular expression with the like_regex filter. For example, the following SQL/JSON path query would case-insensitively match all strings in an array that start with an English vowel:

'$[*] ? (@ like_regex "^[aeiou]" flag "i")'

The optional flag string may include one or more of the characters i for case-insensitive match, m to allow ^ and $ to match at newlines, s to allow . to match a newline, and q to quote the whole pattern (reducing the behavior to a simple substring match).

'$ ? (@ like_regex "^\\d+$")'

9.16.2.3. SQL/JSON Path Operators And Methods

Table 9.48. jsonpath Operators and Methods

Operator/Method
Description
Example JSON
Example Query
Result

+ (unary)

Plus operator that iterates over the SQL/JSON sequence

{"x": [2.85, -14.7, -9.4]}

+ $.x.floor()

2, -15, -10

- (unary)

Minus operator that iterates over the SQL/JSON sequence

{"x": [2.85, -14.7, -9.4]}

- $.x.floor()

-2, 15, 10

+ (binary)

Addition

[2]

2 + $[0]

4

- (binary)

Subtraction

[2]

4 - $[0]

2

*

Multiplication

[4]

2 * $[0]

8

/

Division

[8]

$[0] / 2

4

%

Modulus

[32]

$[0] % 10

2

type()

Type of the SQL/JSON item

[1, "2", {}]

$[*].type()

"number", "string", "object"

size()

Size of the SQL/JSON item

{"m": [11, 15]}

$.m.size()

2

double()

Approximate floating-point number converted from an SQL/JSON number or a string

{"len": "1.9"}

$.len.double() * 2

3.8

ceiling()

Nearest integer greater than or equal to the SQL/JSON number

{"h": 1.3}

$.h.ceiling()

2

floor()

Nearest integer less than or equal to the SQL/JSON number

{"h": 1.3}

$.h.floor()

1

abs()

Absolute value of the SQL/JSON number

{"z": -0.3}

$.z.abs()

0.3

keyvalue()

Sequence of object's key-value pairs represented as array of items containing three fields ("key", "value", and "id"). "id" is a unique identifier of the object key-value pair belongs to.

{"x": "20", "y": 32}

$.keyvalue()

{"key": "x", "value": "20", "id": 0}, {"key": "y", "value": 32, "id": 0}

Table 9.49. jsonpath Filter Expression Elements

Value/Predicate
Description
Example JSON
Example Query
Result

==

Equality operator

[1, 2, 1, 3]

$[*] ? (@ == 1)

1, 1

!=

Non-equality operator

[1, 2, 1, 3]

$[*] ? (@ != 1)

2, 3

<>

Non-equality operator (same as !=)

[1, 2, 1, 3]

$[*] ? (@ <> 1)

2, 3

<

Less-than operator

[1, 2, 3]

$[*] ? (@ < 2)

1

<=

Less-than-or-equal-to operator

[1, 2, 3]

$[*] ? (@ <= 2)

1, 2

>

Greater-than operator

[1, 2, 3]

$[*] ? (@ > 2)

3

>=

Greater-than-or-equal-to operator

[1, 2, 3]

$[*] ? (@ >= 2)

2, 3

true

Value used to perform comparison with JSON true literal

[{"name": "John", "parent": false}, {"name": "Chris", "parent": true}]

$[*] ? (@.parent == true)

{"name": "Chris", "parent": true}

false

Value used to perform comparison with JSON false literal

[{"name": "John", "parent": false}, {"name": "Chris", "parent": true}]

$[*] ? (@.parent == false)

{"name": "John", "parent": false}

null

Value used to perform comparison with JSON null value

[{"name": "Mary", "job": null}, {"name": "Michael", "job": "driver"}]

$[*] ? (@.job == null) .name

"Mary"

&&

Boolean AND

[1, 3, 7]

$[*] ? (@ > 1 && @ < 5)

3

||

Boolean OR

[1, 3, 7]

$[*] ? (@ < 1 || @ > 5)

7

!

Boolean NOT

[1, 3, 7]

$[*] ? (!(@ < 5))

7

like_regex

["abc", "abd", "aBdC", "abdacb", "babc"]

$[*] ? (@ like_regex "^ab.*c" flag "i")

"abc", "aBdC", "abdacb"

starts with

Tests whether the second operand is an initial substring of the first operand

["John Smith", "Mary Stone", "Bob Johnson"]

$[*] ? (@ starts with "John")

"John Smith"

exists

Tests whether a path expression matches at least one SQL/JSON item

{"x": [1, 2], "y": [2, 4]}

strict $.* ? (exists (@ ? (@[*] > 2)))

2, 4

is unknown

Tests whether a Boolean condition is unknown

[-1, 2, 7, "infinity"]

$[*] ? ((@ > 0) is unknown)

"infinity"

shows the functions that are available for creating json and jsonb values. (There are no equivalent functions for jsonb, of the row_to_json and array_to_json functions. However, the to_jsonb function supplies much the same functionality as these functions would.)

The extension has a cast from hstore to json, so that hstore values converted via the JSON creation functions will be represented as JSON objects, not as primitive string values.

shows the functions that are available for processing json and jsonb values.

Many of these functions and operators will convert Unicode escapes in JSON strings to the appropriate single character. This is a non-issue if the input is type jsonb, because the conversion was already done; but for json input, this may result in throwing an error, as noted in .

See also for the aggregate function json_agg which aggregates record values as JSON, and the aggregate function json_object_agg which aggregates pairs of values into a JSON object, and their jsonb equivalents, jsonb_agg and jsonb_object_agg.

SQL/JSON path expressions specify the items to be retrieved from the JSON data, similar to XPath expressions used for SQL access to XML. In PostgreSQL, path expressions are implemented as the jsonpath data type and can use any elements described in .

To refer to the JSON data to be queried (the context item), use the $ sign in the path expression. It can be followed by one or more , which go down the JSON structure level by level to retrieve the content of context item. Each operator that follows deals with the result of the previous evaluation step.

The result of each path evaluation step can be processed by one or more jsonpath operators and methods listed in . Each method name must be preceded by a dot. For example, you can get an array size:

For more examples of using jsonpath operators and methods within path expressions, see .

Functions and operators that can be used in filter expressions are listed in . The path evaluation result to be filtered is denoted by the @ variable. To refer to a JSON element stored at a lower nesting level, add one or more accessor operators after @.

There are minor differences in the interpretation of regular expression patterns used in like_regex filters, as described in .

The SQL/JSON standard borrows its definition for regular expressions from the LIKE_REGEX operator, which in turn uses the XQuery standard. PostgreSQL does not currently support the LIKE_REGEX operator. Therefore, the like_regex filter is implemented using the POSIX regular expression engine described in . This leads to various minor discrepancies from standard SQL/JSON behavior, which are cataloged in . Note, however, that the flag-letter incompatibilities described there do not apply to SQL/JSON, as it translates the XQuery flag letters to match what the POSIX engine expects.

Keep in mind that the pattern argument of like_regex is a JSON path string literal, written according to the rules given in . This means in particular that any backslashes you want to use in the regular expression must be doubled. For example, to match strings that contain only digits:

shows the operators and methods available in jsonpath. shows the available filter expression elements.

Tests whether the first operand matches the regular expression given by the second operand, optionally with modifications described by a string of flag characters (see )

Table 9.46
hstore
Table 9.47
Section 8.14
Section 9.20
Section 8.14.6
accessor operators
Section 9.15.2.3
Section 9.15.2.3
Table 9.49
Section 9.15.2.2
Section 9.7.3
Section 9.7.3.8
Section 8.14.6
Table 9.48
Table 9.49
Section 9.15.2.2
第 8.14 節
第 8.14 節
Table 9.1
Section 8.14.4
Table 9.45
Section 8.14.3
Section 8.14.4
Table 9.44
sqltr-19075-6