tencent cloud

TDSQL-C for MySQL

Release Notes and Announcements
Release Notes
Product Announcements
Beginner's Guide
Product Introduction
Overview
Strengths
Use Cases
Architecture
Product Specifications
Instance Types
Product Feature List
Database Versions
Regions and AZs
Common Concepts
Use Limits
Suggestions on Usage Specifications
Kernel Features
Kernel Overview
Kernel Version Release Notes
Optimized Kernel Version
Functionality Features
Performance Features
Security Features
Stability Feature
Analysis Engine Features
Inspection and Repair of Kernel Issues
Purchase Guide
Billing Overview
Product Pricing
Creating Cluster
Specification Adjustment Description
Renewal
Payment Overdue
Refund
Change from Pay-as-You-Go to Yearly/Monthly Subscription
Change from Pay-as-You-Go to Serverless Billing
Value-Added Services Billing Overview
Viewing Billing Statements
Getting Started
Database Audit
Overview
Viewing Audit Instance List
Enabling Audit Service
Viewing Audit Logs
Log Shipping
Post-Event Alarm Configuration
Modifying Audit Rule
Modifying Audit Service
Disabling Audit Service
Audit Rule Template
Viewing Audit Task
Authorizing Sub-User to Use Database Audit
Serverless Service
Serverless Introduction
Creating and Managing a Serverless Cluster
Elastic Scaling Management Tool
Serverless Resource Pack
Multi-AZ Deployment
Configuration Change
FAQs
Serverless Cost Estimator
Operation Guide
Operation Overview
Switching Cluster Page View in Console
Database Connection
Instance Management
Configuration Adjustment
Instance Mode Management
Cluster Management
Scaling Instance
Database Proxy
Account Management
Database Management
Database Management Tool
Parameter Configuration
Multi-AZ Deployment
GD
Backup and Restoration
Operation Log
Data Migration
Parallel Query
Columnar Storage Index (CSI)
Analysis Engine
Database Security and Encryption
Monitoring and Alarms
Basic SQL Operations
Connecting to TDSQL-C for MySQL Through SCF
Tag
Practical Tutorial
Classified Protection Practice for Database Audit of TDSQL-C for MySQL
Upgrading Database Version from MySQL 5.7 to 8.0 Through DTS
Usage Instructions for TDSQL-C MySQL
New Version of Console
Implementing Multiple RO Groups with Multiple Database Proxy Connection Addresses
Strengths of Database Proxy
Selecting Billing Mode for Storage Space
Creating Remote Disaster Recovery by DTS
Creating VPC for Cluster
Data Rollback
Solution to High CPU Utilization
How to Authorize Sub-Users to View Monitoring Data
White Paper
Security White Paper
Performance White Paper
Troubleshooting
Connection Issues
Performance Issues
API Documentation
History
Introduction
API Category
Making API Requests
Instance APIs
Multi-Availability Zone APIs
Other APIs
Audit APIs
Database Proxy APIs
Backup and Recovery APIs
Parameter Management APIs
Billing APIs
serverless APIs
Resource Package APIs
Account APIs
Performance Analysis APIs
Data Types
Error Codes
FAQs
Basic Concepts
Purchase and Billing
Compatibility and Format
Connection and Network
Features
Console Operations
Database and Table
Performance and Log
Database Audit
Between TDSQL-C for MySQL and TencentDB for MySQL
Service Agreement
Service Level Agreement
Terms of Service
TDSQL-C Policy
Privacy Policy
Data Privacy and Security Agreement
General References
Standards and Certifications
Glossary
Contact Us

Lazy Materialization

PDF
Focus Mode
Font Size
Last updated: 2024-12-11 14:45:39

What Is Lazy Materialization

If the primary key or index key cannot be hit when a SQL query is executed in a database, a full table scan (TableScan) is required. This process of scanning all data is usually costly. To optimize this process, Lazy Materialization can be adopted. This technology works by delaying data materialization until the query execution phase when necessary computation and storage are performed, thereby improving the query performance and system response speed.
In the process of executing SQL queries in a read-only analysis engine, predicate columns are read first, and the Filter operator is used to perform calculations to obtain the filtered results. Subsequently, the read-only analysis engine materializes other columns that need to be read based on these filtered results. This method effectively reduces the amount of data read from non-predicate columns during large-scale data filtering, thereby increasing the scanning speed.

Advantages of Lazy Materialization

Data is compressed in the read-only analysis engine, so the materialization process requires decompression of the data. Lazy Materialization can reduce the range of the data to be decompressed, thereby reducing the CPU overhead caused by decompression.
When a SQL query involves multiple columns, early materialization may cause the database to read and combine data from all columns, even though some of the columns may not be used in the query of the final result. In contrast, Lazy Materialization delays the data combination process, allowing the database to read and process only the columns that are really needed. This approach effectively reduces unnecessary I/O operations, thereby improving the query efficiency.
Lazy Materialization makes operations like filtering and aggregation more efficient, as these operations only need to process column data rather than the entire row. The characteristics of columnar storage (such as data compression and batch processing) can be better utilized, resulting in faster query execution.

Parameters of Lazy Materialization

Lazy Materialization can be enabled/disabled with the parameter libra_enable_late_materialization, and "ON" indicates that Lazy Materialization is enabled.
Attribute
Description
Parameter Type
BOOL.
Default Value
ON.
Value range
ON: Enable Lazy Materialization.
OFF: Disable Lazy Materialization.
Scope
Global & Session.
SET_VAR Hint supported
Yes.
#Disable Lazy Materialization at session level.
set libra_enable_late_materialization=off;
#Enable Lazy Materialization at session level.
set libra_enable_late_materialization=on;

Example of Lazy Materialization

As shown in the figure below, when Lazy Materialization is enabled, you can clearly see the COLUMN READ operator in the execution plan. This operator is an example of Lazy Materialization being enabled.


How to Set Lazy Materialization in HINT

SET_VAR Hint allows you to enable or disable Lazy Materialization in a single SQL statement. An example is as follows.
select /*+ set_var(libra_enable_late_materialization=1)*/ * from t where c1=1 and c2=1;


Help and Support

Was this page helpful?

Help us improve! Rate your documentation experience in 5 mins.

Feedback