apache/spark
Sep 2025 – Sep 2025
1 Month active
Languages Used
PythonScala
Technical Skills
Apache SparkData EngineeringData ProcessingDataFrame APIPySparkPython
Shujing Yang
PROFILE
Shujing Yang
During September 2025, contributed to the apache/spark repository by developing three core features focused on data partitioning and cross-language compatibility. Built and integrated the DataFrame repartitionById API for PySpark, enabling users to specify partition IDs for more precise data distribution. Enhanced Arrow UDTF support by implementing automatic return type coercion and preparing Spark Connect tests for df.asTable(), aligning behavior with Arrow UDFs. Developed a direct passthrough partitioning API for Spark Connect, including Scala API methods, protobuf integration, and unit tests. Work emphasized robust data engineering practices using Python, Scala, and Spark SQL, with a focus on feature completeness and testability.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
5Total
Bugs
0
Commits
5
Features
3
Lines of code
1,148
Activity Months1
Your Network
735 peopleSame Organization
@databricks.com334
Work History
September 2025
5 Commits • 3 Features
Sep 1, 2025September 2025 monthly summary for apache/spark focusing on delivering core repartitioning APIs, Arrow UDTF enhancements, and Spark Connect direct passthrough partitioning. The month emphasized business value through improved data distribution control, cross-language compatibility, and connector parity. No major bug fixes were documented in the input data; the primary work centered on feature development and test readiness.
5 Commits • 3 Features
Sep 1, 2025September 2025 monthly summary for apache/spark focusing on delivering core repartitioning APIs, Arrow UDTF enhancements, and Spark Connect direct passthrough partitioning. The month emphasized business value through improved data distribution control, cross-language compatibility, and connector parity. No major bug fixes were documented in the input data; the primary work centered on feature development and test readiness.
September 2025
Activity
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Quality Metrics
Correctness100.0%
Maintainability84.0%
Architecture96.0%
Performance84.0%
AI Usage28.0%
Skills & Technologies
Programming Languages
PythonScala
Technical Skills
Apache SparkData EngineeringData ProcessingDataFrame APIPySparkPythonScalaSparkSpark SQLUnit Testingunit testing
Repositories Contributed To
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