apache/spark
Apr 2026 – Apr 2026
1 Month active
Languages Used
Scala
Technical Skills
Apache SparkScalabackend development
Brooks Walls
PROFILE
Brooks Walls
Contributed to the apache/spark repository by delivering an observability enhancement for structured streaming workloads. Developed and integrated the Streaming Query Scheduling Logs Enrichment feature, which surfaces streaming query and batch identifiers in scheduling logs to improve debugging in multi-query environments. Modified core components such as TaskSetManager and FairSchedulableBuilder using Scala and Apache Spark internals, ensuring that relevant identifiers are consistently logged. Added comprehensive unit tests and performed manual validation through the Spark shell to verify correct log emission without introducing user-facing changes. This work focused on backend development, emphasizing reliability, traceability, and faster issue diagnosis for streaming applications.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
819
Activity Months1
Your Network
733 peopleSame Organization
@databricks.com332
Work History
April 2026
1 Commits • 1 Features
Apr 1, 2026April 2026 monthly summary for apache/spark focusing on streaming observability enhancements. Delivered Streaming Query Scheduling Logs Enrichment to include streaming query Id and batch Id in scheduling logs, significantly improving debugging of structured streaming queries in multi-query environments. Implemented changes across critical components (TaskSetManager and FairSchedulableBuilder) to surface queryId and batchId in logs. Added unit tests and performed manual validation to ensure correct log emission without user-facing changes. No major user-facing bugs fixed this month; the work emphasizes observability, reliability, and faster issue diagnosis. Demonstrated strong proficiency with Spark internals, logging, testing, and collaborative development. Key points: - Feature delivered: Streaming Query Scheduling Logs Enrichment - Commit: ea8b6d61c9857b11f5503262a669f4f161beef7a - PR reference: SPARK-56326 - Testing: Unit tests added; manual validation via spark shell - Authorship: Brooks Walls; coauthored using AI tooling
1 Commits • 1 Features
Apr 1, 2026April 2026 monthly summary for apache/spark focusing on streaming observability enhancements. Delivered Streaming Query Scheduling Logs Enrichment to include streaming query Id and batch Id in scheduling logs, significantly improving debugging of structured streaming queries in multi-query environments. Implemented changes across critical components (TaskSetManager and FairSchedulableBuilder) to surface queryId and batchId in logs. Added unit tests and performed manual validation to ensure correct log emission without user-facing changes. No major user-facing bugs fixed this month; the work emphasizes observability, reliability, and faster issue diagnosis. Demonstrated strong proficiency with Spark internals, logging, testing, and collaborative development. Key points: - Feature delivered: Streaming Query Scheduling Logs Enrichment - Commit: ea8b6d61c9857b11f5503262a669f4f161beef7a - PR reference: SPARK-56326 - Testing: Unit tests added; manual validation via spark shell - Authorship: Brooks Walls; coauthored using AI tooling
April 2026
Activity
Loading activity data...
Quality Metrics
Correctness100.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage80.0%
Skills & Technologies
Programming Languages
Scala
Technical Skills
Apache SparkScalabackend development
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline