airbnb/chronon
Jan 2025 – Aug 2025
4 Months active
Languages Used
ScalaPython
Technical Skills
Scalabuild configurationsoftware architectureAirflowbackend developmentdata engineering
mickjermsurawong-openai
PROFILE
Mickjermsurawong-openai
Mick Jermsurawong contributed to the airbnb/chronon repository by building scalable data aggregation and publishing workflows, integrating Flink as a core build component to support real-time analytics. He enhanced reliability in scheduled data pipelines by implementing deterministic Airflow execution dates, improving data correctness for joins and group-by operations. Mick also developed query-level custom partition column support, increasing flexibility in data partitioning strategies while maintaining backward compatibility. Using Scala, Python, and Spark, he addressed complex backend and data engineering challenges, such as fixing over-counting in the Sawtooth Mutation Aggregator, and consistently delivered well-tested, compatibility-focused solutions that improved system stability.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
4Total
Bugs
2
Commits
4
Features
2
Lines of code
999
Activity Months4
Your Network
231 people
Work History
August 2025
1 Commits
Aug 1, 2025August 2025 monthly summary for airbnb/chronon. Focused on correctness and reliability of the Sawtooth Mutation Aggregator under caching. Delivered a bug fix that prevents over-counting by cloning the first relevant hop during aggregation, and added a regression test to ensure batch IR is not mutated during aggregation. Result: more accurate mutation counting, reduced risk of incorrect analytics, and improved stability in the cache-enabled path.
1 Commits
Aug 1, 2025August 2025 monthly summary for airbnb/chronon. Focused on correctness and reliability of the Sawtooth Mutation Aggregator under caching. Delivered a bug fix that prevents over-counting by cloning the first relevant hop during aggregation, and added a regression test to ensure batch IR is not mutated during aggregation. Result: more accurate mutation counting, reduced risk of incorrect analytics, and improved stability in the cache-enabled path.
August 2025
March 2025
1 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary for airbnb/chronon: Delivered a new feature to support query-level custom partition columns, with full test coverage and backward-compatible changes. The work enhances data partitioning flexibility and lays groundwork for more dynamic partitioning strategies. No critical issues introduced; compatibility-focused fixes were applied during integration.
March 2025
1 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary for airbnb/chronon: Delivered a new feature to support query-level custom partition columns, with full test coverage and backward-compatible changes. The work enhances data partitioning flexibility and lays groundwork for more dynamic partitioning strategies. No critical issues introduced; compatibility-focused fixes were applied during integration.
February 2025
1 Commits
Feb 1, 2025February 2025 (2025-02) monthly summary highlighting work on airbnb/chronon with a focus on reliability and data correctness of scheduled tasks.
1 Commits
Feb 1, 2025February 2025 (2025-02) monthly summary highlighting work on airbnb/chronon with a focus on reliability and data correctness of scheduled tasks.
February 2025
January 2025
1 Commits • 1 Features
Jan 1, 2025In January 2025, delivered Flink-based aggregate publishing for the airbnb/chronon project by integrating Flink into the root build and updating the configuration to treat Flink as a core component. This establishes a scalable foundation for data aggregation and publish workflows, supporting future real-time analytics and more reliable batch processing.
January 2025
1 Commits • 1 Features
Jan 1, 2025In January 2025, delivered Flink-based aggregate publishing for the airbnb/chronon project by integrating Flink into the root build and updating the configuration to treat Flink as a core component. This establishes a scalable foundation for data aggregation and publish workflows, supporting future real-time analytics and more reliable batch processing.
Activity
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Quality Metrics
Correctness100.0%
Maintainability85.0%
Architecture90.0%
Performance85.0%
AI Usage80.0%
Skills & Technologies
Programming Languages
PythonScala
Technical Skills
AirflowData EngineeringDatabase ManagementPythonScalaSparkbackend developmentbuild configurationdata aggregationdata engineeringsoftware architectureunit testing
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