Shubha-accenture/dataproc-jupyter-plugin-fork
Aug 2025 – Aug 2025
1 Month active
Languages Used
CSSJavaScriptTypeScript
Technical Skills
Front End DevelopmentFrontend DevelopmentReact
srinivasan-acn
PROFILE
Srinivasan-acn
During August 2025, Srganesan focused on stabilizing Spark dynamic allocation property handling in the Shubha-accenture/dataproc-jupyter-plugin-fork repository. He addressed a bug by reverting recent changes to the Spark properties configuration, restoring the previous stable logic for dynamic allocation and auto-scaling. This involved removing a filtering hook and related CSS adjustments, ensuring that all necessary Spark properties are available when dynamic allocation is enabled. Working primarily with React, JavaScript, and CSS, Srganesan’s approach prioritized backward compatibility and reliability, reducing the risk of misconfiguration for users of the dataproc Jupyter plugin. The work demonstrated careful attention to stability.
Overall Statistics
Feature vs Bugs
0%Features
Repository Contributions
2Total
Bugs
1
Commits
2
Features
0
Lines of code
52
Activity Months1
Your Network
4169 people
Work History
August 2025
2 Commits
Aug 1, 2025August 2025: Focused on stabilizing Spark dynamic allocation property handling in the Shubha-accenture/dataproc-jupyter-plugin-fork repository. Delivered a revert-based fix that restores the previous, stable Spark property configuration for dynamic allocation and auto-scaling, and removed the filtering hook and related CSS adjustments. This work reduces misconfigurations, preserves backward compatibility, and enhances reliability for users relying on dynamic allocation in the dataproc Jupyter plugin.
2 Commits
Aug 1, 2025August 2025: Focused on stabilizing Spark dynamic allocation property handling in the Shubha-accenture/dataproc-jupyter-plugin-fork repository. Delivered a revert-based fix that restores the previous, stable Spark property configuration for dynamic allocation and auto-scaling, and removed the filtering hook and related CSS adjustments. This work reduces misconfigurations, preserves backward compatibility, and enhances reliability for users relying on dynamic allocation in the dataproc Jupyter plugin.
August 2025
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture70.0%
Performance70.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
CSSJavaScriptTypeScript
Technical Skills
Front End DevelopmentFrontend DevelopmentReact
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