apache/spark
May 2025 – Sep 2025
3 Months active
Languages Used
JavaScala
Technical Skills
API DevelopmentJavaSQLScalaDatabase ManagementSoftware Development
Uros Stankovic
PROFILE
Uros Stankovic
Over a three-month period, this developer contributed to the apache/spark repository by delivering three features and addressing one bug, focusing on backend and data infrastructure improvements. They introduced a new API for listing table summaries in the Data Source V2 Table Catalog, streamlining metadata retrieval and enhancing efficiency for large-scale Spark SQL deployments. Their work also included deprecating JdbcRDD in favor of a modern JDBC data source and enhancing error messaging for JDBC queries, improving both integration and debuggability. Throughout these projects, they applied skills in Java, Scala, SQL, and Spark, demonstrating careful alignment with repository standards and collaborative development practices.
Overall Statistics
Feature vs Bugs
75%Features
Repository Contributions
4Total
Bugs
1
Commits
4
Features
3
Lines of code
262
Activity Months3
Your Network
735 peopleSame Organization
@databricks.com334
Work History
September 2025
1 Commits • 1 Features
Sep 1, 2025September 2025 monthly summary for apache/spark. Delivered a JDBC Data Source Error Messaging Enhancement to improve debuggability and user experience when syntax errors occur in JDBC-based queries. This work reduces debugging time and enhances reliability of Spark's JDBC integration, aligning with SPARK-53677. No major bug fixes documented this month. The effort demonstrates end-to-end ownership from code changes to user impact and showcases collaboration with the Spark community.
1 Commits • 1 Features
Sep 1, 2025September 2025 monthly summary for apache/spark. Delivered a JDBC Data Source Error Messaging Enhancement to improve debuggability and user experience when syntax errors occur in JDBC-based queries. This work reduces debugging time and enhances reliability of Spark's JDBC integration, aligning with SPARK-53677. No major bug fixes documented this month. The effort demonstrates end-to-end ownership from code changes to user impact and showcases collaboration with the Spark community.
September 2025
July 2025
2 Commits • 1 Features
Jul 1, 2025Month: 2025-07 — concise monthly summary focusing on business value and technical achievements for the Spark repository.
July 2025
2 Commits • 1 Features
Jul 1, 2025Month: 2025-07 — concise monthly summary focusing on business value and technical achievements for the Spark repository.
May 2025
1 Commits • 1 Features
May 1, 2025May 2025 monthly summary for apache/spark. Key feature delivered: Data Source V2 Table Catalog: List Table Summaries API. This API provides a new listTableSummaries endpoint to fetch table metadata summaries, reducing the number of operations needed to retrieve information and improving efficiency for large catalogs. Commit reference: 810a547e20e616bc3bd89e1caa8e2062818b5971 (SPARK-52109). No major bugs fixed this month. Impact: faster metadata discovery, improved developer productivity, and a foundation for further Data Source V2 catalog optimizations. Technologies demonstrated: Spark SQL, Data Source V2 API design, Java/Scala development, code review and version control discipline. Business value: reduces metadata fetch overhead, enabling quicker data discovery and more responsive data pipelines.
1 Commits • 1 Features
May 1, 2025May 2025 monthly summary for apache/spark. Key feature delivered: Data Source V2 Table Catalog: List Table Summaries API. This API provides a new listTableSummaries endpoint to fetch table metadata summaries, reducing the number of operations needed to retrieve information and improving efficiency for large catalogs. Commit reference: 810a547e20e616bc3bd89e1caa8e2062818b5971 (SPARK-52109). No major bugs fixed this month. Impact: faster metadata discovery, improved developer productivity, and a foundation for further Data Source V2 catalog optimizations. Technologies demonstrated: Spark SQL, Data Source V2 API design, Java/Scala development, code review and version control discipline. Business value: reduces metadata fetch overhead, enabling quicker data discovery and more responsive data pipelines.
May 2025
Activity
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Quality Metrics
Correctness100.0%
Maintainability85.0%
Architecture90.0%
Performance90.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
JavaScala
Technical Skills
API DevelopmentDatabase ManagementJavaSQLScalaSoftware DevelopmentSparkbackend development
Repositories Contributed To
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