linkedin/venice
Jun 2025 – Aug 2025
2 Months active
Languages Used
Java
Technical Skills
Data EngineeringData ProcessingJavaKafkaSparkbackend development
Ali Poursamadi
PROFILE
Ali Poursamadi
Arash Poursamady contributed to the linkedin/venice repository by developing a Spark-based data ingestion module that enables real-time analytics through Pub/Sub integration. He implemented a native Spark input source to consume Pub/Sub messages, supporting raw Kafka input and converting streams into Spark DataFrames according to the Venice Pub/Sub Version-Topic Schema. This work established a foundation for scalable, end-to-end streaming pipelines using Java, Kafka, and Spark. Additionally, Arash improved observability by refactoring router metrics, replacing an obsolete metric with a streamlined gauge to enhance dashboard clarity and monitoring reliability. His contributions reflect depth in backend development and data engineering practices.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
2
Lines of code
1,553
Activity Months2
Work History
August 2025
1 Commits • 1 Features
Aug 1, 2025Monthly summary for 2025-08: Focused on observability and metrics hygiene in linkedin/venice. Delivered a targeted metrics cleanup by removing the obsolete active_ssl_connection metric and introducing connection_count_gauge. The change simplified dashboards, reduced metric surface, and improved router-level visibility with minimal risk, contributing to more reliable monitoring and faster troubleshooting.
1 Commits • 1 Features
Aug 1, 2025Monthly summary for 2025-08: Focused on observability and metrics hygiene in linkedin/venice. Delivered a targeted metrics cleanup by removing the obsolete active_ssl_connection metric and introducing connection_count_gauge. The change simplified dashboards, reduced metric surface, and improved router-level visibility with minimal risk, contributing to more reliable monitoring and faster troubleshooting.
August 2025
June 2025
2 Commits • 1 Features
Jun 1, 2025June 2025 monthly summary for linkedin/venice focused on expanding Spark-based data ingestion via Pub/Sub to enable real-time analytics and scalable data processing. Delivered Spark Pub/Sub Ingestion and DataFrame Support, introducing a Spark module to consume Pub/Sub messages, support raw Kafka input handling, and convert streams into Spark DataFrames following the Venice Pub/Sub Version-Topic Schema. This work lays groundwork for end-to-end streaming pipelines and improves data freshness for downstream analytics.
June 2025
2 Commits • 1 Features
Jun 1, 2025June 2025 monthly summary for linkedin/venice focused on expanding Spark-based data ingestion via Pub/Sub to enable real-time analytics and scalable data processing. Delivered Spark Pub/Sub Ingestion and DataFrame Support, introducing a Spark module to consume Pub/Sub messages, support raw Kafka input handling, and convert streams into Spark DataFrames following the Venice Pub/Sub Version-Topic Schema. This work lays groundwork for end-to-end streaming pipelines and improves data freshness for downstream analytics.
Activity
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Quality Metrics
Correctness93.4%
Maintainability93.4%
Architecture93.4%
Performance93.4%
AI Usage80.0%
Skills & Technologies
Programming Languages
Java
Technical Skills
Data EngineeringData ProcessingJavaKafkaSparkbackend developmentmetrics management
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