v3.1

About MogDB
- MogDB Introduction
- Comparison Between MogDB and openGauss
- MogDB Release Notes
  - MogDB Release Notes
  - MogDB 3.1.0
- Open Source Components
- Usage Limitations
- Terms of Use
Quick Start
- MogDB Playground
- Container-based MogDB Installation
- Installation on a Single Node
- MogDB Access
  - Use CLI to Access MogDB
    - gsql
    - pgcli
  - Use GUI to Access MogDB
  - Use Middleware to Access MogDB
    - Use WebLogic to Configure MogDB Data Sources
    - Use WebSphere to Configure MogDB Data Sources
  - Use Programming Language to Access MogDB
    - Java
    - C/C++
    - Python
    - Go
    - Rust
    - NodeJS
    - .Net
- Using Sample Dataset Mogila
Characteristic Description
Installation Guide
- Installation Preparation
  - Environment Requirement
  - Operating System Configuration
- Container Installation
- PTK-based Installation
- OM-based Installation
- Manual Installation
- Recommended Parameter Settings
Administrator Guide
AI Features Guide
- AI Features Overview
- AI4DB: Autonomous Database O&M
  - DBMind Mode
  - Components that Support DBMind
    - Prometheus Exporter
  - AI Sub-functions of the DBMind
    - X-Tuner: Parameter Tuning and Diagnosis
    - Index-advisor: Index Recommendation
    - Slow Query Diagnosis: Root Cause Analysis for Slow SQL Statements
    - Forecast: Trend Prediction
    - SQLdiag: Slow SQL Discovery
    - SQL Rewriter
    - Anomaly Detection
- DB4AI: Database-driven AI
  - Native DB4AI Engine
  - Full-process AI
    - PLPython Fenced Mode
    - DB4AI-Snapshots for Data Version Management
- AI in DB
  - Intelligence Explain: SQL Statement Query Time Prediction
- ABO Optimizer
  - Intelligent Cardinality Estimation
  - Adaptive Plan Selection
Security Guide
- Database Security Management
Developer Guide
- Application Development Guide
  - Development Specifications
  - Development Based on JDBC
  - Development Based on ODBC
  - Development Based on libpq
    - Dependent Header Files of libpq
    - Development Process
    - Example
    - Link Parameters
    - libpq API Reference
      - Database Connection Control Functions
        Description
        PQconnectdbParams
        PQconnectdb
        PQconninfoParse
        PQconnectStart
        PQerrorMessage
        PQsetdbLogin
        PQfinish
        PQreset
        PQstatus
      - Database Statement Execution Functions
        PQclear
        PQexec
        PQexecParams
        PQexecParamsBatch
        PQexecPrepared
        PQexecPreparedBatch
        PQfname
        PQgetvalue
        PQnfields
        PQntuples
        PQprepare
        PQresultStatus
      - Functions for Asynchronous Command Processing
        Description
        PQsendQuery
        PQsendQueryParams
        PQsendPrepare
        PQsendQueryPrepared
        PQflush
      - Functions for Canceling Queries in Progress
        PQgetCancel
        PQfreeCancel
        PQcancel
  - Psycopg-Based Development
  - Commissioning
- Stored Procedure
- User Defined Functions
- PL/pgSQL-SQL Procedural Language
  - Overview of PL/pgSQL Functions
  - Data Types
  - Data Type Conversion
  - Arrays and Records
  - DECLARE Syntax
  - Basic Statements
  - Dynamic Statements
  - Control Statements
  - Transaction Management
  - Other Statements
  - Cursors
  - Advanced Packages
    - Basic Interfaces
      - PKG_SERVICE
  - Retry Management
  - Debugging
  - package
- Scheduled Jobs
  - PKG_SERVICE API
- Autonomous Transaction
- Logical Replication
  - Logical Decoding
    - Overview
    - Logical Decoding by SQL Function Interfaces
  - Publication-Subscription
- Extension
  - PostGIS Extension
  - Foreign Data Wrapper
  - orafce
  - pg_bulkload
  - pg_prewarm
  - pg_repack
  - pg_trgm
  - wal2json
  - whale
- Materialized View
  - Materialized View Overview
  - Full Materialized View
  - Incremental Materialized View
- Partition Management
  - Partition Pruning
  - Recommendations For Choosing A Partitioning Strategy
Performance Tuning Guide
Reference Guide
Common Faults and Identification
- Common Fault Locating Methods
- Common Fault Locating Cases
  - Core Fault Locating
  - Permission/Session/Data Type Fault Location
  - Service/High Availability/Concurrency Fault Location
  - Table/Partition Table Fault Location
    - Table Size Does not Change After VACUUM FULL Is Executed on the Table
    - An Error Is Reported When the Table Partition Is Modified
  - File System/Disk/Memory Fault Location
  - SQL Fault Location
  - Index Fault Location
  - CM Two-Node Fault Location
    - Manual Failover
    - Manual Failover for Brain Split
Source Code Parsing
FAQs
Glossary
Communication Matrix
Mogeaver
- Overview
- Release Notes

Data Type Used by the Ledger Database

The ledger database uses the hash16 data type to store row-level hash digests or table-level hash digests, and uses the hash32 data type to store global hash digests or history table verification hashes.

Table 1 Hash type of the ledger database

Name	Description	Storage Space	Value Range
HASH16	Stored as an unsigned 64-bit integer	8 bytes	0 to +18446744073709551615
HASH32	Stored as a group of 16 unsigned integer elements	16 bytes	Value range of an unsigned integer array of 16 elements

The hash16 data type is used to store row-level or table-level hash digests in the ledger database. After obtaining the hash sequence of a 16-character hexadecimal string, the system invokes the hash16in function to convert the sequence into an unsigned 64-bit integer and stores the integer in a hash16 variable. For example:

Hexadecimal string: e697da2eaa3a775b; 64-bit unsigned integer: 16615989244166043483
Hexadecimal string: ffffffffffffffff; 64-bit unsigned integer: 18446744073709551615

The hash32 data type is used to store the global hash digest or history table verification hash in the ledger database. After obtaining the hash sequence of a 32-character hexadecimal string, the system invokes the hash32in function to convert the sequence to an array containing 16 unsigned integer elements. For example:

Hexadecimal string: 685847ed1fe38e18f6b0e2b18c00edee
Hash32 array: [104,88,71,237,31,227,142,24,246,176,226,177,140,0,237,238]