Best Unit Testing Software for Apache Spark
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Compare the Top Unit Testing Software that integrates with Apache Spark as of November 2025
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This a list of Unit Testing software that integrates with Apache Spark. Use the filters on the left to add additional filters for products that have integrations with Apache Spark. View the products that work with Apache Spark in the table below.
What is Unit Testing Software for Apache Spark?
Unit testing software is a type of software tool and/or framework that enables developers and programmers to test small and individual source code units in order to ensure that each unit of the source code functions as it should. Compare and read user reviews of the best Unit Testing software for Apache Spark currently available using the table below. This list is updated regularly.
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Deequ
Deequ
Deequ is a library built on top of Apache Spark for defining "unit tests for data", which measure data quality in large datasets. We are happy to receive feedback and contributions. Deequ depends on Java 8. Deequ version 2.x only runs with Spark 3.1, and vice versa. If you rely on a previous Spark version, please use a Deequ 1.x version (legacy version is maintained in legacy-spark-3.0 branch). We provide legacy releases compatible with Apache Spark versions 2.2.x to 3.0.x. The Spark 2.2.x and 2.3.x releases depend on Scala 2.11 and the Spark 2.4.x, 3.0.x, and 3.1.x releases depend on Scala 2.12. Deequ's purpose is to "unit-test" data to find errors early, before the data gets fed to consuming systems or machine learning algorithms. In the following, we will walk you through a toy example to showcase the most basic usage of our library.
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