What's New
Function Overview
Product Bulletin
- Product Notice
- Version Support Notes
Service Overview
- GaussDB(DWS) Infographics
- What Is GaussDB(DWS)?
- Data Warehouse Types
- Data Warehouse Flavors
- Advantages
- Application Scenarios
- Functions
- Concepts
- Related Services
- Security
- GaussDB(DWS) Permissions Management
- GaussDB(DWS) Access
- Restrictions
- Technical Support
- Service Quotas
- GaussDB(DWS) Technical Specifications
Billing
- GaussDB(DWS) Billing Overview
- Billing Modes
- Item
- Billing Examples
- Billing Mode Change
- Renewal
  - Overview
  - Manual Renewal
- Bills
- Arrears
- Stopping Billing
- Cost Management
- Billing FAQs
Getting Started
- Checkpoint Vehicle Analysis
- Supply Chain Requirement Analysis of a Company
- Operations Status Analysis of a Retail Department Store
- Creating a Time Series Table
- Best Practices of Hot and Cold Data Management
- Best Practices for Automatic Partition Management
- Creating a Cluster and Connecting to It
- Using CDM to Migrate MySQL Data to the GaussDB(DWS) Cluster
- Using DLI Flink Jobs to Write Kafka Data to GaussDB(DWS) in Real Time
- Basic SQL Operations
- Database Quick Start
- Getting Started with Common Practices
User Guide
- Using GaussDB(DWS)
- Preparations
- Creating a GaussDB(DWS) Cluster
- Connecting to a GaussDB(DWS) Cluster
- Creating a GaussDB(DWS) Database and User
- Migrating Service Data to a GaussDB(DWS) Cluster
  - Migrating Data to a GaussDB(DWS) Cluster Using GDS-Kafka
  - Data Source Management
- GaussDB(DWS) Cluster Data Security and Encryption
- GaussDB(DWS) Cluster Management
- GaussDB(DWS) Cluster O&M
Best Practices
- Import and Export
- Data Migration
- Data Analytics
- Decoupled Storage and Compute
  - DWS 3.0 Decoupled Storage and Compute Usage Suggestions and Performance Optimization
- Data Development
- Database Management
- Performance Tuning
  - Optimizing Table Structure Design to Enhance GaussDB(DWS) Query Performance
  - Analyzing SQL Statements That Are Being Executed to Handle GaussDB(DWS) Performance Issues
- Cluster Management
  - Binding Different Resource Pools to Two Types of Jobs to Balance Load for GaussDB(DWS)
  - Scaling Options for GaussDB(DWS) with a Coupled Storage-Compute Architecture
Data Migration and Synchronization
- Data Migration to GaussDB(DWS)
- Importing Data
- Full Database Migration
  - Using CDM to Migrate Data to GaussDB(DWS)
  - Using DSC to Migrate SQL Scripts
- Real-time Import
  - Using DRS to Import Data to GaussDB(DWS)
  - Real-time Data Import From Kafka GaussDB(DWS)
- Metadata Migration
  - Using gs_dump and gs_dumpall to Export Metadata
  - Using gs_restore to Import Data
- Exporting Data
- Other Operations
Developer Guide
- Standard data warehouse (9.1.0.x)
- Standard data warehouse (8.1.3.x)
- Hybrid Data Warehouse (9.1.0.x）
- Hybrid Data Warehouse (8.1.3.x）
- Historical Versions
SQL Syntax Reference
- SQL Syntax Reference (9.1.0.x)
- SQL Syntax Reference (8.1.3.x)
- Historical Versions
Performance Tuning
- Overview of Query Performance Optimization
- Query Execution Process
- SQL Execution Plan
- SQL Optimization Guide
- Optimization Cases
- SQL Execution Troubleshooting
- query_band Load Identification
- Common Performance Parameter Optimization Design
Tool Guide
- Overview
- Downloading Related Tools
- gsql
- Data Studio
- GDS
- DSC
- DataCheck
- DWS-Connector
- Server Tool
API Reference
- Before You Start
- API Overview
- Calling APIs
- Getting Started
- API Description
- Application Cases
  - Using Postman to Call the API for Creating a Cluster
  - Using Postman to Call the API for Creating a Snapshot
- Introduction
- Appendix
SDK Reference
- SDK Overview
FAQs
- Top FAQs
- Product Consulting
- Database Connections
- Data Migration
- Database Usage
- Cluster Management
- Account Permissions
- Database Performance
- Backup and Restoration
  1. Why Does It Take a Long Time to Create an Automated Snapshot in GaussDB(DWS)?
  2. Does a GaussDB(DWS) Snapshot Have the Same Function as an EVS Snapshot?
Troubleshooting
- Database Connections
- JDBC/ODBC
- Data Import and Export
- Database Parameter Modification
- Account/Permission/Password
- Cluster Performance
- Cluster Exceptions
  - The Disk Usage Alarm Is Frequently Generated
- Database Use
Videos
Performance White Paper
- Overview
- Test Result
  - TPC-H Single Query Test
  - TPC-DS Single Query Test
- Test Methods
- Appendixes
  - TPC-H Test Sets
  - TPC-DS Test Sets
Technical White Paper
- GaussDB(DWS)
- Platforms and Technical Specifications Supported by GaussDB(DWS)
  - Technical Specifications
- GaussDB(DWS) Core Technologies
- GaussDB(DWS) Tools
  - Client Tools
  - Database Monitoring Tool
- External APIs
Error Code Reference
- 8.2.0 and earlier versions
  - Management Console Error Code
  - Data Warehouse Service Error Codes
- 8.2.1 or later versions
Glossary
More Documents
- User Guide
- API Reference (ME-Abu Dhabi Region)
- Developer Guide (ME-Abu Dhabi Region)
- SQL Syntax Reference (ME-Abu Dhabi Region)
- Tool Guide (ME-Abu Dhabi Region)
- Error Code Reference (ME-Abu Dhabi Region)
  - Management Console Error Code
- User Guide (Paris Region)
- API Reference (Paris Region)
- Developer Guide (Paris Region)
- SQL Syntax Reference (Paris Region)
- Tool Guide (Paris Region)
- Error Code Reference (Paris Region)
  - Management Console Error Code
- User Guide (Kuala Lumpur Region)
- API Reference (Kuala Lumpur Region)
- Developer Guide (Kuala Lumpur Region)
- SQL Syntax Reference (Kuala Lumpur Region)
- Tool Guide (Kuala Lumpur Region)
- Error Code Reference (Kuala Lumpur Region)
  - Management Console Error Code
General Reference
- Glossary
- Service Level Agreement
- White Papers
- Endpoints
- Permissions

On this page

Show all

Help Center/ GaussDB(DWS)/ Troubleshooting/ Cluster Performance/ Slow Performance Caused by Too Many Small CUs in Column Storage

Slow Performance Caused by Too Many Small CUs in Column Storage

Updated on 2025-01-06 GMT+08:00

View PDF

In actual service scenarios, a large number of column-store tables are used. However, improper use of column-store tables may cause serious performance problems. The most common problem is slow performance caused by too many small CUs.

Symptom

The system I/O surges for a long time, and the query becomes slow occasionally.
After checking the execution plan information when the service is occasionally slow, it is found that the cstore scan is slow. The reason is that although the amount of data to be scanned is small, the number of CUs to be scanned is large.

As shown in the following figure, a CU can store 60,000 records, but more than 2000 CUs need to be scanned for 70,000 records. There are too many small CUs.

Troubleshooting

Check the data distribution in the table CUs. Perform the following operations on DNs:

Check the cudesc table corresponding to the column-store table.

For non-partitioned tables:

      
         SELECT 'cstore.'||relname FROM pg_class where oid = (SELECT relcudescrelid FROM pg_class c inner join pg_namespace n on c.relnamespace = n.oid where relname = 'table name' and nspname = 'schema name');

For partitioned tables:

      
         SELECT 'cstore.'||relname FROM pg_class where oid in (SELECT p.relcudescrelid FROM pg_partition p,pg_class c,pg_namespace n where c.relnamespace = n.oid and p.parentid = c.oid and c.relname = 'table name' and n.nspname = 'schema name' and p.relcudescrelid != 0);

Check the rowcount of each CU in the cudesc table.
Query the cudesc table information returned in step 1. The query result is similar to the following. Pay attention to the number of CUs whose row_count is too small (far less than 60,000). If the number is large, there are many small CUs and the CU expansion problem is serious, affecting the storage efficiency and query access efficiency.

Trigger Conditions

Column-store data is frequently imported in small batches. In scenarios where partitions are involved and the number of partitions is large, the small CU problem is more serious.

Solutions

Service Side

Import column-store tables in batches. The amount of data to be imported at a time (if there are partitions, the amount of data to be imported to a single partition at time) is close to or greater than 60,000 x Number of primary DNs.
If the data volume is small, you are advised to use row-store tables for data import.

Maintenance Portal

If the amount of data to be imported to the database cannot be adjusted on the service side, periodically perform VACUUM FULL on column-store tables to integrate small CUs. This will relieve the problem to some extent.

Parent topic: Cluster Performance

Previous topic: Performance Deterioration Due to Data Bloat

Next topic: Reducing I/O Usage