Pages on DuckDB Lab — Independent DuckDB Technical Blog

About the Author

Sat, 12 Sep 2026 00:00:00 +0000

About the Author

Ross Zhang

Founder and primary author of DuckDB Lab.

Professional Background

18+ years in enterprise budget management and digital transformation
Led financial systems, budget systems, and data integration projects at major enterprises
Deep experience with Oracle, Hyperion, Kingdee and other enterprise data systems
Long-term practice in enterprise data analysis, budget systems, data integration, and digitalization

Technical Expertise

Area	Experience
DuckDB	Production deployment, performance tuning, extension development
Python Analytics	Pandas, Polars, DuckDB integration
SQL Optimization	Complex query rewriting, execution plan analysis
Data Engineering	ETL/ELT pipelines, data lake architecture
Cloud Services	AWS, AliCloud, Vercel deployment
Enterprise Software	Oracle, Hyperion, Kingdee ERP

Why DuckDB Lab

DuckDB Lab is a personal platform for recording my practical research and experiments with DuckDB, data analytics, and modern data tools.

Site content is based on:

DuckDB official documentation and technical announcements
My own practical testing and experiments
Enterprise production environment deployment experience

Contact

GitHub: pengzz9527
Email: admin@duckdblab.org

DuckDB Lab is an independent DuckDB Chinese-language technical community and experimental blog. It is not affiliated with or endorsed by the DuckDB official project.

Correction Policy

Sat, 12 Sep 2026 00:00:00 +0000

Correction Policy

DuckDB Lab is committed to maintaining technical accuracy. If you find errors in our articles, we welcome and actively address them through the following mechanism.

Scope of Corrections

The following types of errors will be actively corrected:

Technical factual errors: Incorrect DuckDB API, configuration parameters, or syntax descriptions
Code errors: Code examples that don’t run or produce expected results
Version information errors: Inaccurate DuckDB version numbers or feature availability descriptions
Benchmark data errors: Incorrect test environment, methodology, or results
Outdated information: Features that have changed after DuckDB upgrades

How to Report Errors

Method	Description
GitHub Issue	Submit an issue at duckdb-blog with the article link and error description
Email	Send to admin@duckdblab.org with subject format: `[Correction] Article Title`
Pull Request	If you have accurate corrections, you can submit a PR directly

Correction Process

Receive Report — We acknowledge error reports within 48 hours
Verify Issue — Reproduce the problem in a test environment to confirm the error
Execute Correction — Update the article content, fix code or data
Record Changes — Add a correction note at the bottom of the article (see format below)
Notify Reporter — Inform the reporter via Issue or email of the correction result

Correction Record Format

Corrected articles will include the following note at the bottom:

---
## Correction History

| Date | Correction | Reporter |
|------|-----------|----------|
| 2026-09-12 | Fixed incorrect XXX description | @username |

Our Commitment

All confirmed technical errors will be corrected
Corrected articles retain correction history for transparency
We regularly review and update existing articles to ensure timeliness
We encourage community participation in content quality improvement

Thank you for helping DuckDB Lab maintain high content quality.

Last updated: 2026-09-12

Editorial Policy

Sat, 12 Sep 2026 00:00:00 +0000

Editorial Policy

DuckDB Lab is committed to providing accurate, practical, and reproducible DuckDB technical content for the Chinese-language tech community.

Content Standards

1. Technical Accuracy

All technical articles are based on DuckDB official documentation and hands-on testing
Code examples are verified in a test environment where applicable
DuckDB version information is clearly noted at the bottom of each article

2. Version Annotation

Each technical article includes:

Article Info
DuckDB Version: v1.x / v2.x (Alpha/Preview/Release)
Last Verified: YYYY-MM-DD
Test Environment: OS / CPU / RAM / Storage
Code Repository: GitHub (if applicable)
Official Docs: https://duckdb.org/docs/

3. Benchmark Standards

Articles involving performance testing follow these guidelines:

Item	Requirement
DuckDB Version	Must be explicitly stated
Test Environment	CPU, RAM, OS, Storage must be documented
Dataset	Source, size, row count must be documented
Methodology	Query statements, run count, cache state must be documented
Results	Median, P95, baseline comparison must be reported
Reproducibility	GitHub code repository link provided (where applicable)

4. Alpha/Beta Feature Disclosure

DuckDB v2.0 Alpha/Preview features are explicitly labeled as experimental
No verified production-environment code examples are provided for alpha features
Alpha features are not described as stable, production-ready capabilities

Content Categories

Type	Description	Annotation Required
Technical Tutorial	Based on official docs + practical examples	DuckDB version required
Performance Test	Includes benchmark data	Full environment + GitHub required
Practical Case Study	Production environment experience	Applicable scenarios and limitations required
News Analysis	Technical interpretation of official announcements	Official source citation required
Commercial Speculation	Business analysis based on tech trends	Clearly labeled as author opinion

Originality and Attribution

Original content prioritized: based on hands-on testing and personal experience
Official documentation cited: with clear source links
Third-party work attributed: with author and source credits
Test data: generation scripts provided for public datasets where applicable

Correction Mechanism

If you find errors in any article, please see our Correction Policy.

Contact Us

For editorial questions or suggestions, please contact us via GitHub Issues or email contact@duckdblab.org.

Last updated: 2026-09-12

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