linkedin/datahub-gma
Oct 2025 – May 2026
3 Months active
Languages Used
JavaYAML
Technical Skills
Backend DevelopmentDatabase ManagementTimezone HandlingBuild AutomationContinuous IntegrationEbean ORM
Mridul Sharma
PROFILE
Mridul Sharma
Worked on the linkedin/datahub-gma repository, focusing on backend development and database management using Java, SQL, and Ebean ORM. Over three months, delivered features and fixes that improved system reliability and performance. Addressed a critical data consistency issue by standardizing timestamp handling to UTC in the Data Access Layer, reducing cross-region data misinterpretation. Migrated the codebase and CI workflows to Java 11, enabling future upgrades and resolving validation issues. Enhanced performance by optimizing listUrns queries and modernizing build automation. Implemented robust cache pre-warming and cleanup for Ebean DAO, ensuring consistent cache state and reducing latency after JVM startup.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
4Total
Bugs
2
Commits
4
Features
2
Lines of code
292
Activity Months3
Your Network
113 peopleSame Organization
@linkedin.com100
Allen AverbukhMember
Xin(Adam) ChenMember
Ahmet Alp BalkanMember
Alex HopmannMember
Alan Z.Member
Aman GuptaMember
Amaan MarfatiaMember
AMAN PANDEYMember
Abhishek NathMember
Shared Repositories
13
Work History
May 2026
1 Commits • 1 Features
May 1, 2026May 2026 performance and stability focus for linkedin/datahub-gma. Implemented robust Ebean DAO cache pre-warm in the initialization path, ensuring startup caches are populated consistently and reducing first-request latency after JVM startup, especially in environments where schema migrations run as a separate job. Introduced targeted cache cleanup and stale-entry handling to improve cache reliability across deploys. Strengthened schema-cache coherence with additional validation hooks and test hygiene to keep cache state in sync with evolving schemas. Completed code cleanup by removing dead fields and ensured test utilities invalidate caches after schema changes.
1 Commits • 1 Features
May 1, 2026May 2026 performance and stability focus for linkedin/datahub-gma. Implemented robust Ebean DAO cache pre-warm in the initialization path, ensuring startup caches are populated consistently and reducing first-request latency after JVM startup, especially in environments where schema migrations run as a separate job. Introduced targeted cache cleanup and stale-entry handling to improve cache reliability across deploys. Strengthened schema-cache coherence with additional validation hooks and test hygiene to keep cache state in sync with evolving schemas. Completed code cleanup by removing dead fields and ensured test utilities invalidate caches after schema changes.
May 2026
April 2026
2 Commits • 1 Features
Apr 1, 2026April 2026 monthly summary for linkedin/datahub-gma: Delivered platform enhancements with a Java 11 migration and a performance optimization for listUrns, delivering business value through upgrade readiness, improved transaction reliability, and faster listings.
April 2026
2 Commits • 1 Features
Apr 1, 2026April 2026 monthly summary for linkedin/datahub-gma: Delivered platform enhancements with a Java 11 migration and a performance optimization for listUrns, delivering business value through upgrade readiness, improved transaction reliability, and faster listings.
October 2025
1 Commits
Oct 1, 2025Month 2025-10 summary for linkedin/datahub-gma: Addressed a critical data consistency issue by standardizing all timestamp handling to UTC in the Data Access Layer. This involved refactoring timestamp formatting and parsing across reads and writes, ensuring consistent interpretation across time zones in distributed deployments. The change reduces data misinterpretation risks and improves reliability for cross-region analytics and data pipelines. No new features released this month; this bug fix strengthens data governance and system stability for multi-region usage. Commit fe4bc2192c5ca365e94b6abe281ae921d4014558 ("Fix timezone issue during reads and writes (#583)").
1 Commits
Oct 1, 2025Month 2025-10 summary for linkedin/datahub-gma: Addressed a critical data consistency issue by standardizing all timestamp handling to UTC in the Data Access Layer. This involved refactoring timestamp formatting and parsing across reads and writes, ensuring consistent interpretation across time zones in distributed deployments. The change reduces data misinterpretation risks and improves reliability for cross-region analytics and data pipelines. No new features released this month; this bug fix strengthens data governance and system stability for multi-region usage. Commit fe4bc2192c5ca365e94b6abe281ae921d4014558 ("Fix timezone issue during reads and writes (#583)").
October 2025
Activity
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Quality Metrics
Correctness95.0%
Maintainability85.0%
Architecture90.0%
Performance85.0%
AI Usage40.0%
Skills & Technologies
Programming Languages
JavaYAML
Technical Skills
Backend DevelopmentBuild AutomationContinuous IntegrationDatabase ManagementEbean ORMJavaJava DevelopmentSQLTimezone Handlingbackend developmentdatabase management
Repositories Contributed To
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