Show Menu
Cheatography
  1. Home >
  2. Programming >

Types of Tests in Pyspark Cheat Sheet (DRAFT) by

In PySpark testing, clarity and confidence come from validating each layer of your data pipeline. This cheat sheet outlines four essential test types Unit, Integration, Data Quality, and Regression each serving a unique purpose in ensuring your transformations are correct, your data is clean, and your logic remains stable over time.

This is a draft cheat sheet. It is a work in progress and is not finished yet.

Unit Test

Validate the correc­tness of individual transf­orm­ation logic (e.g., filters, mappings, UDFs)

Regression Test

Confirm that new changes haven’t broken existing logic or outputs
 

Integr­ation Test

Ensure multiple components (e.g., joins, aggreg­ations, pipelines) work together as expected

Business Rule Test

Enforce domain­-sp­ecific rules
 

Data Quality Test

Check for data hygiene issues like nulls, duplic­ates, schema mismat­ches, and format violations

Perfor­mance Test

Measure speed, memory, partit­ioning