SESSION
Best Practices for Unit Testing PySpark
OVERVIEW
| EXPERIENCE | In Person |
|---|---|
| TYPE | Lightning Talk |
| TRACK | Data Engineering and Streaming |
| TECHNOLOGIES | Apache Spark, Developer Experience, ETL |
| SKILL LEVEL | Intermediate |
| DURATION | 20 min |
This talk shows you best practices for unit testing PySpark code. Unit tests help you reduce production bugs and make your codebase easy to refactor. You will learn how to create PySpark unit tests that run locally and in CI via GitHub actions. You will learn best practices for structuring PySpark code so it’s easy to unit test. You’ll also see how to run integration tests with a cluster for staging datasets. Integration tests provide an additional level of safety.
SESSION SPEAKERS
Matthew Powers
/Staff Developer Advocate
Databricks