Databricks DCAD : Databricks Certified Associate Developer for Apache Spark 3.0 Exam Dumps

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Latest 2024 Updated Databricks Databricks Certified Associate Developer for Apache Spark 3.0 Syllabus
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Exam Number : DCAD
Exam Name : Databricks Certified Associate Developer for Apache Spark 3.0
Vendor Name : Databricks
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DCAD Exam Format | DCAD Course Contents | DCAD Course Outline | DCAD Exam Syllabus | DCAD Exam Objectives

Exam Details for DCAD Databricks Certified Associate Developer for Apache Spark 3.0:

Number of Questions: The exam consists of approximately 60 multiple-choice and multiple-select questions.

Time Limit: The total time allocated for the exam is 90 minutes (1 hour and 30 minutes).

Passing Score: To pass the exam, you must achieve a minimum score of 70%.

Exam Format: The exam is conducted online and is proctored. You will be required to answer the questions within the allocated time frame.

Course Outline:

1. Spark Basics:
- Understanding Apache Spark architecture and components
- Working with RDDs (Resilient Distributed Datasets)
- Transformations and actions in Spark

2. Spark SQL:
- Working with structured data using Spark SQL
- Writing and executing SQL queries in Spark
- DataFrame operations and optimizations

3. Spark Streaming:
- Real-time data processing with Spark Streaming
- Windowed operations and time-based transformations
- Integration with external systems and sources

4. Spark Machine Learning (MLlib):
- Introduction to machine learning with Spark MLlib
- Feature extraction and transformation in Spark MLlib
- Model training and evaluation using Spark MLlib

5. Spark Graph Processing (GraphX):
- Working with graph data in Spark using GraphX
- Graph processing algorithms and operations
- Analyzing and visualizing graph data in Spark

6. Spark Performance Tuning and Optimization:
- Identifying and resolving performance bottlenecks in Spark applications
- Spark configuration and tuning techniques
- Optimization strategies for Spark data processing

Exam Objectives:

1. Understand the fundamentals of Apache Spark and its components.
2. Perform data processing and transformations using RDDs.
3. Utilize Spark SQL for structured data processing and querying.
4. Implement real-time data processing using Spark Streaming.
5. Apply machine learning techniques with Spark MLlib.
6. Analyze and process graph data using Spark GraphX.
7. Optimize and tune Spark applications for improved performance.

Exam Syllabus:

The exam syllabus covers the following topics:

1. Spark Basics
- Apache Spark architecture and components
- RDDs (Resilient Distributed Datasets)
- Transformations and actions in Spark

2. Spark SQL
- Spark SQL and structured data processing
- SQL queries and DataFrame operations
- Spark SQL optimizations

3. Spark Streaming
- Real-time data processing with Spark Streaming
- Windowed operations and time-based transformations
- Integration with external systems

4. Spark Machine Learning (MLlib)
- Introduction to machine learning with Spark MLlib
- Feature extraction and transformation
- Model training and evaluation

5. Spark Graph Processing (GraphX)
- Graph data processing in Spark using GraphX
- Graph algorithms and operations
- Graph analysis and visualization

6. Spark Performance Tuning and Optimization
- Performance bottlenecks and optimization techniques
- Spark configuration and tuning
- Optimization strategies for data processing

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Databricks 3.0 outline

SD Times news digest: Core WCF joins .NET Foundation, Databricks and Booz Allen team up, and Javalin 3.0

The .NET Foundation has announced support for Core WCF, an OSS project whose initial code donated from a WCF team member at Microsoft. Core WCP is a por of the Windows Communication Framework. According to its GitHub page, its goal is to move existing WCF projects to .NET Core.

“I think this is a great example of how the .NET Foundation can help coordinate .NET open source projects in a way that benefits the broader community,” the team wrote in a post.

The project will first be for HTTP and TCP SOAP services on-top of Kestrel, which are the most commonly used transports on .NET Framework. The team said the project is not yet ready for production and is reaching out for developer support.

Databricks and Booz Allen team up on unified analytics for government agenciesUnified analytics provider Databricks and machine learning services provider Booz Allen are teaming up to help federal agencies scale their data analytics and accelerate AI initiatives.

“Booz Allen and Databricks recognize Federal customers are at varying levels of adoption when it comes to cloud adoption. Together we are providing a solution that is ready now and future proof,” said Michael Hoff, senior vice president of business development and partners at Databricks.

In the new joint solution, Booz Allen can integrate Databricks’ product and Delta Lake with ODP and offer U.S. Government clients the unique ability to deploy it on-premises or onto hybrid infrastructure.

Javalin 3.0 releasedThe 3.0 version Javalin web framework for Kotlin and Java is now available. The latest release priorities simplicity and first class interoperability between the languages. It supports WebSockets, HTTP2 and async requests.

The release offers several new features such as revamped validation for parameters, WebSockets, standalone mode and event setup as well as added OpenAPI (Swagger) support. ‘Extension’ has been renamed to ‘Plugin’ the configuration has been moved from the ‘Javalin” class to JavalinConfig.’

A detailed list of Javalin 3.0 improvements can be viewed here.

Crank Software releases Storyboard 6.0Crank Software, which provides embedded user interface (UI) software, released Storyboard 6.0 this month.

The new release focuses on resource management with a newly integrated Storyboard Lite engine that reduces resource footprint and an optimized OpenGL scene graph renderer. It also includes the ability to manage resources with the new Project Metrics view during development and a new option to visualize screen modalities at design time.

“We built Storyboard 6.0 to help embedded development teams rise to the challenge of creating experiences that exceed those expectations regardless of the target platform, by simplifying the workflow, providing actionable resource data at design time, and reducing the application footprint,” said Brian Edmond, president of Crank Software.

Innovation Lab now supports full Chatbot developmentExadel announced that its cloud-based mobile development platform now supports full Chatbot development.

“Chatbots are helping businesses everywhere connect with customers efficiently and the use cases for chatbots are endless. We are looking forward to helping Innovation Lab users determine the strategic fit for chatbots in their organizations,” said Dmitry Binunksy, VP Products and Platforms at Exadel.

The chatbot can be developed with no code written and its fully integrated with the rest of the platform.

MindNode 3.1 Adds Redesigned Outline, Markdown Export

MindNode is an elegant and powerful mindmapping app that I use on all my devices to visualize thoughts and topics before writing an article or preparing research for a podcast episode. I’ve been a fan of MindNode for years, and I was particularly impressed with version 3.0, which brought a new iOS 7 design alongside more intuitive interactions, better iCloud sync, and keyboard shortcuts.

Today’s 3.1 update, available on the App Store, features an entirely new sidebar for your mindmap outline that replaces the app’s old popover. The advantage of the sidebar approach is immediately clear on the iPad, and especially in landscape mode: with the new version, you can keep the map and sidebar open at the same time, tapping on items in the outline to select the respective node on the map (and vice versa).

This change makes for a fantastic experience when navigating large documents that branch in different directions: nodes can be folded and unfolded directly in the outline, with changes reflected on the map; you can pan around while the sidebar is shown, and double-tap a line in the outline to select the item on the map and edit it. Basic font formatting like bold and underline is shown in the sidebar as well, and animations for folding sections and reopening them are smooth. At the top of the sidebar, you can search for any string of text and results will be highlighted as you tap in the outline.

Another addition that I’m happy to see in MindNode is Markdown export, available from the app’s sharing menu.

Because I tend to prepare longer articles as maps in MindNode, I find value in being able to export from the app directly to my text editor of choice. In the screenshot above, you can see a MindNode document exported to Editorial 1.1.

MindNode continues to strike a great balance between good looks and advanced features, and the new outline mode in version 3.1 lets you browse and edit large maps without losing MindNode’s ease of use.

MindNode is available at $9.99 on the App Store.

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