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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
Spark offers a three-dimensional perspective of your application's interface along with the capability to adjust view settings dynamically during runtime, enabling you to design exceptional applications. If your app relies on notifications, Spark's notification monitor tracks each NSNotification as it is dispatched, providing a comprehensive stack trace, a detailed list of recipients, the methods invoked, and additional relevant information. This feature allows for a quick understanding of your app's architecture while enhancing debugging efficiency. By connecting your application to the Spark Inspector, you place your app's interface in the spotlight, with real-time updates reflecting your interactions. We keep track of every alteration within your app's view hierarchy, ensuring you remain informed about ongoing changes. The visual representation of your app in Spark is not only aesthetically pleasing but also fully customizable. You have the ability to alter nearly every aspect of your views, from class-level properties to CALayer transformations, and upon making any changes, Spark triggers a method within your app to directly implement that adjustment. This seamless integration fosters a more intuitive development experience, allowing for rapid iteration and refinement.
API Access
Has API
API Access
Has API
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Free Trial
Free Version
Pricing Details
$49.99 one-time payment
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Deployment
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Windows
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Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
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Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Deequ
Website
github.com/awslabs/deequ
Vendor Details
Company Name
Spark Inspector
Website
sparkinspector.com