apache/amoro
Dec 2024 – Aug 2025
3 Months active
Languages Used
Java
Technical Skills
Backend DevelopmentDatabase ManagementJavaSparkAPI DesignConfiguration Management
Marig_Weizhi
PROFILE
Marig_weizhi
Marig Weizhi contributed to the apache/amoro repository by enhancing backend reliability and data correctness through targeted improvements in Spark and Hive catalog management, dashboard analytics, and planning efficiency. Using Java and Spark, Marig extended catalog type support and introduced robust namespace management to reduce SQL errors and streamline developer workflows. They refactored Hive catalog initialization for more reliable startups and improved dashboard accuracy by correcting data aggregation in the OverviewManager. Marig also optimized planning logic to skip blocked tables and ensured delete operations defaulted to the correct file format, demonstrating depth in backend development, database management, and performance optimization.
Overall Statistics
Feature vs Bugs
43%Features
Repository Contributions
7Total
Bugs
4
Commits
7
Features
3
Lines of code
310
Activity Months3
Your Network
491 people
Work History
August 2025
4 Commits • 2 Features
Aug 1, 2025August 2025: Delivered reliability, performance, and correctness improvements for apache/amoro. Key outcomes include: (1) Hive catalog initialization refactor to set catalog properties earlier, boosting startup reliability; (2) optimizerGroup metric tag added for finer analytics and updated docs; (3) planning optimization skipping blocked tables and blockers check to speed up planning; (4) Default Delete File Format Fallback ensures delete uses the table's primary data format when DELETE_DEFAULT_FILE_FORMAT is not set, improving correctness. These changes improve startup stability, planning efficiency, observability, and data correctness, delivering tangible business value.
4 Commits • 2 Features
Aug 1, 2025August 2025: Delivered reliability, performance, and correctness improvements for apache/amoro. Key outcomes include: (1) Hive catalog initialization refactor to set catalog properties earlier, boosting startup reliability; (2) optimizerGroup metric tag added for finer analytics and updated docs; (3) planning optimization skipping blocked tables and blockers check to speed up planning; (4) Default Delete File Format Fallback ensures delete uses the table's primary data format when DELETE_DEFAULT_FILE_FORMAT is not set, improving correctness. These changes improve startup stability, planning efficiency, observability, and data correctness, delivering tangible business value.
August 2025
April 2025
1 Commits
Apr 1, 2025In 2025-04, focus remained on data accuracy and reliability for Apache Amoro. No new user-facing features were shipped this month; the primary work centered on stabilizing analytics dashboards by fixing the Overview Table Statistics data source. This fix ensures correct aggregation for table size, file count, and health score in the OverviewManager, improving trust in dashboards and downstream analytics. The change was implemented in apache/amoro with commit daa6bc91d6b7a3fd3c6aa1bedb0780cbe3cfb946 ([AMORO-3500] Fix Overview table data statistics (#3501)).
April 2025
1 Commits
Apr 1, 2025In 2025-04, focus remained on data accuracy and reliability for Apache Amoro. No new user-facing features were shipped this month; the primary work centered on stabilizing analytics dashboards by fixing the Overview Table Statistics data source. This fix ensures correct aggregation for table size, file count, and health score in the OverviewManager, improving trust in dashboards and downstream analytics. The change was implemented in apache/amoro with commit daa6bc91d6b7a3fd3c6aa1bedb0780cbe3cfb946 ([AMORO-3500] Fix Overview table data statistics (#3501)).
December 2024
2 Commits • 1 Features
Dec 1, 2024Month: 2024-12. Apache Amoro – Focused on improving Spark catalog robustness and namespace management to reduce runtime errors and improve developer productivity. Key features delivered: 1) Extend Spark catalog type support to include mixed_iceberg and mixed_hive in addition to arctic, preventing SQL catalog setup errors. 2) Add dropNamespace with cascade and proper non-empty namespace handling, with tests covering namespace creation and deletion.
2 Commits • 1 Features
Dec 1, 2024Month: 2024-12. Apache Amoro – Focused on improving Spark catalog robustness and namespace management to reduce runtime errors and improve developer productivity. Key features delivered: 1) Extend Spark catalog type support to include mixed_iceberg and mixed_hive in addition to arctic, preventing SQL catalog setup errors. 2) Add dropNamespace with cascade and proper non-empty namespace handling, with tests covering namespace creation and deletion.
December 2024
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Quality Metrics
Correctness84.2%
Maintainability82.8%
Architecture80.0%
Performance77.2%
AI Usage20.0%
Skills & Technologies
Programming Languages
Java
Technical Skills
API DesignBackend DevelopmentConfiguration ManagementData EngineeringDatabase InteractionDatabase ManagementJavaMetrics and MonitoringPerformance OptimizationSpark
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