apache/spark
May 2025 – Jun 2025
2 Months active
Languages Used
PythonScala
Technical Skills
API developmentSparkdata processingprotobufData EngineeringGraph Theory
Aakash Japi
PROFILE
Aakash Japi
Aakash Japi developed foundational features for Apache Spark, focusing on declarative pipeline support within the apache/spark repository. Over two months, he delivered the Spark Connect API for Declarative Pipelines, introducing protocol buffers to enable remote construction and management of dataflow graphs and datasets. Using Scala, Spark, and protobuf, Aakash implemented the DataflowGraph infrastructure, supporting graph-based pipeline creation, resolution, validation, and schema inference. His work established a robust API surface and improved reliability for data pipeline execution, laying the groundwork for vendor-neutral integrations and future optimizations. The depth of his contributions reflects strong data engineering and graph theory expertise.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
2
Lines of code
13,187
Activity Months2
Your Network
524 people
Work History
June 2025
2 Commits • 1 Features
Jun 1, 2025Month: 2025-06. Delivered DataflowGraph for Declarative Pipelines in Apache Spark, enabling graph-based management of pipelines, including creation, resolution, validation, and schema determination. This work, anchored by SPARK-52283 commits, establishes a solid foundation for declarative pipeline execution, improved error detection, and more reliable data flows.
2 Commits • 1 Features
Jun 1, 2025Month: 2025-06. Delivered DataflowGraph for Declarative Pipelines in Apache Spark, enabling graph-based management of pipelines, including creation, resolution, validation, and schema determination. This work, anchored by SPARK-52283 commits, establishes a solid foundation for declarative pipeline execution, improved error detection, and more reliable data flows.
June 2025
May 2025
1 Commits • 1 Features
May 1, 2025May 2025 monthly summary for Apache Spark (apache/spark): Delivered Spark Connect API for Declarative Pipelines, introducing new protocol buffers to create and manage dataflow graphs, datasets, and flows within the Spark ecosystem. This work enables remote, declarative pipeline construction and execution via Spark Connect, paving the way for vendor-neutral integrations and more flexible data workflows. The effort centers on the SPARK-52223 commit and the addition of SDP Spark Connect Protos, establishing a solid API surface for future enhancements.
May 2025
1 Commits • 1 Features
May 1, 2025May 2025 monthly summary for Apache Spark (apache/spark): Delivered Spark Connect API for Declarative Pipelines, introducing new protocol buffers to create and manage dataflow graphs, datasets, and flows within the Spark ecosystem. This work enables remote, declarative pipeline construction and execution via Spark Connect, paving the way for vendor-neutral integrations and more flexible data workflows. The effort centers on the SPARK-52223 commit and the addition of SDP Spark Connect Protos, establishing a solid API surface for future enhancements.
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture93.4%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
PythonScala
Technical Skills
API developmentData EngineeringGraph TheoryScalaSparkSpark SQLdata processingprotobuf
Repositories Contributed To
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