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What is Spark Inspector?

Spark provides a unique three-dimensional viewpoint of your application's interface, along with the ability to modify view settings in real-time during execution, which empowers developers to create outstanding applications. For apps that depend on notifications, Spark's notification monitor meticulously tracks every NSNotification as it is sent, offering an exhaustive stack trace, a comprehensive list of recipients, the methods that were called, and other pertinent details. This functionality not only aids in quickly grasping your app's structure but also significantly improves the debugging process. By linking your application with the Spark Inspector, you bring your app's interface into focus, showcasing live updates that reflect your actions. We monitor every change in your app's view hierarchy, ensuring you are always aware of the latest modifications. The visual display of your application in Spark is both visually appealing and highly customizable, allowing you to tweak nearly all elements of your views, from class-level attributes to CALayer transformations. Each time you implement a change, Spark activates a corresponding method in your app to immediately execute that update. This smooth integration enhances the development experience, facilitating quick iterations and improvements, making the entire process more efficient and enjoyable for developers. Ultimately, Spark not only elevates the design aspect but also optimizes the functionality and usability of your applications.

What is Deequ?

Deequ is a groundbreaking library designed to enhance Apache Spark by enabling "unit tests for data," which helps evaluate the quality of large datasets. User feedback and contributions are highly encouraged as we strive to improve the library. The operation of Deequ requires Java 8, and it is crucial to recognize that version 2.x of Deequ is only compatible with Spark 3.1, creating a dependency between the two. Users of older Spark versions should opt for Deequ 1.x, which is available in the legacy-spark-3.0 branch. Moreover, we also provide legacy releases that support Apache Spark versions from 2.2.x to 3.0.x. The Spark versions 2.2.x and 2.3.x utilize Scala 2.11, while the 2.4.x, 3.0.x, and 3.1.x releases rely on Scala 2.12. Deequ's main objective is to conduct "unit-testing" on data to pinpoint possible issues at an early stage, thereby ensuring that mistakes are rectified before the data is utilized by consuming systems or machine learning algorithms. In the upcoming sections, we will illustrate a straightforward example that showcases the essential features of our library, emphasizing its user-friendly nature and its role in preserving data quality. This example will also reveal how Deequ can simplify the process of maintaining high standards in data management.

Media

Media

Integrations Supported

Apache Spark
Xcode

Integrations Supported

Apache Spark
Xcode

API Availability

Has API

API Availability

Has API

Pricing Information

$49.99 one-time payment
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Spark Inspector

Company Website

sparkinspector.com

Company Facts

Organization Name

Deequ

Company Website

github.com/awslabs/deequ

Categories and Features

Categories and Features

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