apache/spark
Sep 2025 – Sep 2025
1 Month active
Languages Used
PythonScala
Technical Skills
Apache SparkData EngineeringData ProcessingDataFrame APIPySparkPython
Shujing Yang
PROFILE
Shujing Yang
Shujing Yang developed three core features for the apache/spark repository, focusing on data distribution and cross-language compatibility. She implemented the DataFrame repartitionById API for PySpark, enabling users to specify partition IDs directly and improving control over data repartitioning. Her work also enhanced Arrow UDTF support by introducing automatic return type coercion and preparing df.asTable() for Spark Connect testing, aligning Python and Scala behaviors. Additionally, she delivered a direct passthrough partitioning API for Spark Connect, including protobuf integration and comprehensive unit tests. Yang’s contributions demonstrated depth in data engineering, leveraging Python, Scala, and Spark SQL to address connector parity.
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
524 people
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
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