Developing Spark Applications Using Scala & Cloudera from Pluralsight

Apache Spark is one of the fastest and most efficient general engines for large-scale data processing. In this course, you'll learn how to develop Spark applications for your Big Data using Scala and a stable Hadoop distribution, Cloudera CDH.

At the core of working with large-scale datasets is a thorough knowledge of Big Data platforms like Apache Spark and Hadoop. In this course, Developing Spark Applications Using Scala & Cloudera, you’ll learn how to process data at scales you previously thought were out of your reach. First, you’ll learn all the technical details of how Spark works. Next, you’ll explore the RDD API, the original core abstraction of Spark. Then, you’ll discover how to become more proficient using Spark SQL and DataFrames. Finally, you'll learn to work with Spark's typed API: Datasets. When you’re finished with this course, you’ll have a foundational knowledge of Apache Spark with Scala and Cloudera that will help you as you move forward to develop large-scale data applications that enable you to work with Big Data in an efficient and performant way.

What's inside

Syllabus

Course Overview

Why Spark with Scala and Cloudera?

Getting an Environment and Data: CDH + StackOverflow

Refreshing Your Knowledge: Scala Fundamentals for This Course

Understanding Spark: An Overview

Getting Technical with Spark

Learning the Core of Spark: RDDs

Going Deeper into Spark Core

Increasing Proficiency with Spark: DataFrames and Spark SQL

Continuing the Journey on DataFrames and Spark SQL

Working with a Typed API: Datasets

Final Takeaway and Continuing the Journey with Spark

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Strong foundation for beginners to develop working knowledge of big data applications using Spark, Scala, and Hadoop distribution

Provides hands-on labs and interactive materials to enhance understanding and application of concepts

Taught by Xavier Morera, an experienced instructor in Apache Spark and big data applications

Examines technical details and core abstractions of Spark, such as RDDs and DataFrames

Develops proficiency in working with Spark's typed API, Datasets

Course material is relevant to big data processing in industry and academia

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Developing Spark Applications Using Scala & Cloudera with these activities:

Review Spark

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Refresh your knowledge of Apache Spark before starting this course to strengthen your foundation.

Browse courses on Apache Spark

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Review Spark documentation
Work through Spark tutorials

Find a Spark Mentor

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Enhance your learning by finding an experienced Spark mentor who can provide valuable insights and guidance.

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Identify potential mentors
Reach out and connect with mentors

Hello Spark App

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Put your Spark skills to practice by building a simple Spark application.

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Create a new Spark project
Write Spark code to read and process data
Run your Spark application

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Practice Spark RDDs

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Strengthen your understanding of Spark RDDs through repetitive exercises.

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Work through RDD exercises
Implement RDD operations in your own code

Practice Spark DataFrames and Spark SQL

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Solidify your knowledge of Spark DataFrames and Spark SQL through targeted exercises.

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Work through DataFrames and Spark SQL exercises
Apply DataFrames and Spark SQL in your own code

Mentor Junior Spark Developers

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Expand your knowledge by mentoring others and reinforcing your understanding of Spark concepts.

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Identify opportunities to mentor
Provide guidance and support to mentees

Create a Spark Tutorial

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Deepen your understanding of Spark by creating a tutorial that explains a specific aspect of the framework.

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Choose a topic
Research and gather information
Write and record your tutorial
Publish your tutorial

Participate in Spark Hackathons

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Challenge yourself and test your Spark skills by participating in hackathons.

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Identify Spark hackathons
Form a team or participate individually
Develop and submit your Spark project

Career center

Learners who complete Developing Spark Applications Using Scala & Cloudera will develop knowledge and skills that may be useful to these careers:

Big Data Engineer

A Big Data Engineer designs, builds, and maintains systems for managing and processing large volumes of data. This course may be useful in learning the core concepts of Apache Spark, Scala, and Cloudera, which are essential tools for Big Data engineering tasks.

See salaries and explore the career path for Big Data Engineer

Data Engineer

A Data Engineer designs, builds, tests, and maintains data management systems and databases. This course can help build a foundation for working with Apache Spark, Scala, and Cloudera, which are popular tools and technologies used for data engineering tasks.

See salaries and explore the career path for Data Engineer

Data Scientist

A Data Scientist uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured. This course can help build a foundation in Apache Spark, Scala, and Cloudera, which are widely used for data science tasks.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

A Machine Learning Engineer designs, develops, and maintains machine learning models and systems. This course can help build a foundation in Apache Spark, Scala, and Cloudera, which are widely used for machine learning tasks.

See salaries and explore the career path for Machine Learning Engineer

Data Integration Engineer

A Data Integration Engineer designs and implements data integration solutions to combine data from multiple sources. This course can help build a foundation in Apache Spark, Scala, and Cloudera, which are commonly used for data integration tasks.

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Analytics Engineer

An Analytics Engineer designs, builds, and maintains data analytics systems and tools. This course can help build a foundation in Apache Spark, Scala, and Cloudera, which are widely used for data analytics tasks.

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Software Architect

A Software Architect designs and oversees the development of software systems and ensures their scalability, reliability, and performance. This course can help build a foundation in Apache Spark, Scala, and Cloudera, which are essential tools for designing and developing large-scale software systems.

See salaries and explore the career path for Software Architect

Cloud Architect

A Cloud Architect designs and manages cloud computing systems and infrastructure. This course can help build a foundation in Apache Spark, Scala, and Cloudera, which are widely used in cloud computing environments.

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Database Administrator

A Database Administrator manages and maintains database systems and ensures their optimal performance. This course can help build a foundation in Apache Spark, Scala, and Cloudera, which can be beneficial when working with large-scale databases.

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Enterprise Architect

An Enterprise Architect designs and manages the overall architecture of an organization's IT systems and infrastructure. This course may be useful in learning the basics of Apache Spark, Scala, and Cloudera, which can be beneficial when working on projects that involve designing and implementing IT solutions for large organizations.

See salaries and explore the career path for Enterprise Architect

DevOps Engineer

A DevOps Engineer collaborates with software developers and IT operations professionals to ensure the smooth development and deployment of software systems. This course may be useful in learning about Apache Spark, Scala, and Cloudera, which are used in DevOps pipelines for building, testing, and deploying software applications.

See salaries and explore the career path for DevOps Engineer

Data Visualization Engineer

A Data Visualization Engineer designs and creates data visualizations to communicate data insights effectively. This course may be useful in learning about Apache Spark, Scala, and Cloudera, which can be beneficial when working on projects that involve visualizing large datasets.

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Chief Data Officer

A Chief Data Officer is responsible for managing and governing an organization's data assets. This course may be useful in gaining knowledge about Apache Spark, Scala, and Cloudera, which can be beneficial when working on projects that involve managing and analyzing large datasets.

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Data Analyst

A Data Analyst collects, analyzes, and interprets data to help organizations make informed decisions. This course may be useful in gaining knowledge about Apache Spark, Scala, and Cloudera, which can be helpful when working on data analysis and visualization projects.

See salaries and explore the career path for Data Analyst

Software Engineer

A Software Engineer develops, maintains, and analyzes software in computer systems and applications. This course may be useful in learning the basics of Apache Spark, Scala, and Cloudera, which can be beneficial when working on projects that involve designing, developing, testing, and implementing software solutions.

See salaries and explore the career path for Software Engineer

Developing Spark Applications Using Scala & Cloudera

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