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Description
Deequ is an innovative library that extends Apache Spark to create "unit tests for data," aiming to assess the quality of extensive datasets. We welcome any feedback and contributions from users. The library requires Java 8 for operation. It is important to note that Deequ version 2.x is compatible exclusively with Spark 3.1, and the two are interdependent. For those using earlier versions of Spark, the Deequ 1.x version should be utilized, which is maintained in the legacy-spark-3.0 branch. Additionally, we offer legacy releases that work with Apache Spark versions ranging from 2.2.x to 3.0.x. The Spark releases 2.2.x and 2.3.x are built on Scala 2.11, while the 2.4.x, 3.0.x, and 3.1.x releases require Scala 2.12. The primary goal of Deequ is to perform "unit-testing" on data to identify potential issues early on, ensuring that errors are caught before the data reaches consuming systems or machine learning models. In the sections that follow, we will provide a simple example to demonstrate the fundamental functionalities of our library, highlighting its ease of use and effectiveness in maintaining data integrity.
Description
The toolkit is available as a collection of resources distributed through the Maven Central repository. It necessitates Java version 7 or higher to run tests, which must be executed using either JUnit or TestNG. For guidance on incorporating the library into a Java project, refer to the section on Running tests with JMockit. This tutorial explores the various APIs offered by the library, illustrated through example tests that utilize Java 8. The primary API consists of a singular annotation that facilitates the automatic creation and setup of the objects intended for testing. Additionally, there exists the mocking API, commonly referred to as the "Expectations" API, which is designed for tests that engage with mocked dependencies. Furthermore, a compact faking API, known as the "Mockups" API, is provided for generating and utilizing fake implementations, thereby mitigating the full resource demands of external components. Overall, this toolkit enhances testing efficiency by streamlining the setup process and providing versatile mocking capabilities.
API Access
Has API
No
API Access
Has API
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
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Pricing Details
Free
Free Trial
No
Free Version
Yes
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Customer Support
Business Hours
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Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Deequ
Website
github.com/awslabs/deequ
Vendor Details
Company Name
JMockit
Website
jmockit.github.io