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

Performance Deterioration Caused by Dirty Page Flushing Efficiency During TPC-C High-Concurrency Long-Term Stable Running

Symptom

TPC-C performance deteriorates due to dirty page flushing efficiency during high-concurrency long-term stable running. The details are as follows: The initial performance is high. As the running time increases, the value of tmpTotal in the database decreases, the CPU usage of the WalWriter thread is 100%, and other CPUs are almost not loaded. In the WDR report, the waiting time for dirty page flushing accounts for the highest proportion.

Cause

Generally, you can analyze the specific cause by checking the process status and operating system resource usage (such as CPU and I/O), or further analyze the root cause based on the WDR. In this scenario, dirty page refreshing is inefficient.

Solution

Reduce the concurrency or increase the value of shared_buffers.
Adjust dirty page parameters. In scenarios where doublewrite is enabled, you can adjust parameters such as page_writer_sleep (downward adjustment) and max_io_capacity (upward adjustment) to improve dirty page elimination efficiency.
Replace high-performance disks (such as NVMe disks).

The resources occupied by the database must meet the service requirements. In a high-concurrency test, you need to add resources to ensure that database services are available.