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Thang Long VU

PROFILE

Thang Long Vu

Long Vu contributed to both the xupefei/spark and apache/spark repositories, focusing on improving SQL parsing and schema evolution for Spark. He refactored the INSERT INTO parsing logic in Scala, replacing tuples with case classes in AstBuilder.scala to enhance code readability and maintainability. Later, he developed a per-statement schema evolution feature for SQL INSERT commands, introducing the WITH SCHEMA EVOLUTION syntax and integrating it with Spark’s V2 write path. This work, implemented with Scala and Spark SQL, streamlined schema management during data ingestion and ensured robust error handling, demonstrating thoughtful engineering depth in both code structure and feature design.

Overall Statistics

Feature vs Bugs

100%Features

Repository Contributions

2Total
Bugs
0
Commits
2
Features
2
Lines of code
456
Activity Months2

Work History

January 2026

1 Commits • 1 Features

Jan 1, 2026

January 2026 monthly summary: Delivered a new per-statement schema evolution capability for Spark INSERT commands, enabling automatic schema evolution via a dedicated WITH SCHEMA EVOLUTION syntax. Implemented syntax recognition and wired it to enable mergeSchema on V2 Insert commands, with tests validating behavior and ensuring users receive clear errors for unsupported formats. No major bug fixes recorded for this scope. This work reduces data ingestion friction in evolving schemas, improves reliability of inserts across formats, and aligns with MERGE schema evolution patterns. Demonstrated expertise in Spark SQL, V2 write path, analyzer integration, test-driven development, and cross-team coordination.

March 2025

1 Commits • 1 Features

Mar 1, 2025

Month: 2025-03 — xupefei/spark repository. Key feature delivered: Refactored INSERT INTO parsing logic to use case classes instead of tuples in AstBuilder.scala to improve readability and maintainability (SPARK-51370). Commit: 1ad7f31baf98dc76a6213b6f587360f38bda76b1. No major bugs fixed are recorded for this month in the provided data. Overall impact: clearer parsing code reduces cognitive load for future changes, lowers maintenance risk, and supports easier onboarding for contributors, contributing to faster delivery and more reliable parsing. Technologies/skills demonstrated: Scala case classes, refactoring for readability, AST parsing logic, commit traceability, and SPARK-51370 alignment.

Activity

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Quality Metrics

Correctness80.0%
Maintainability90.0%
Architecture80.0%
Performance80.0%
AI Usage20.0%

Skills & Technologies

Programming Languages

Scala

Technical Skills

Code RefactoringData EngineeringSQLScalaSoftware EngineeringSpark

Repositories Contributed To

2 repos

Overview of all repositories you've contributed to across your timeline

xupefei/spark

Mar 2025 Mar 2025
1 Month active

Languages Used

Scala

Technical Skills

Code RefactoringScalaSoftware Engineering

apache/spark

Jan 2026 Jan 2026
1 Month active

Languages Used

Scala

Technical Skills

Data EngineeringSQLSpark