apache/amoro
Dec 2024 – Aug 2025
3 Months active
Languages Used
Java
Technical Skills
Backend DevelopmentDatabase ManagementJavaSparkAPI DesignConfiguration Management
Marig_Weizhi
PROFILE
Marig_weizhi
Over three months, contributed to the apache/amoro repository by enhancing backend reliability, data accuracy, and operational efficiency. Focused on Java and Spark, the work included extending Spark catalog support and improving namespace management to reduce SQL setup errors and streamline developer workflows. Addressed dashboard data integrity by correcting the OverviewManager’s statistics aggregation, ensuring accurate reporting for analytics. Refactored Hive catalog initialization for more reliable startups and introduced metrics enhancements for finer-grained monitoring. Additional improvements optimized planning performance and ensured delete operations aligned with table data formats, demonstrating a strong emphasis on configuration management, database interaction, 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
637 peopleWork 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
Activity
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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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