Spark Programming in Scala for Beginners with Apache Spark 3

Apache Spark is a lightning-fast unified analytics engine for big data and machine learning. Since its release, Apache Spark has seen rapid adoption by enterprises across a wide range of industries. Internet powerhouses such as Netflix, Yahoo, and eBay have deployed Spark at a massive scale. It has quickly become the largest open-source community in big data. So, mastering Apache Spark opens a wide range of professional opportunities.

This course starts with an introduction to Apache Spark where you see what Apache Spark is in brief. Then, you will be installing and using Apache Spark. After that, you will look at the Spark execution model and architecture in detail. Next, you will learn the Spark programming model and developer experience. Following that, you will look at the Spark Structured API foundation, and Spark data sources and sinks. Then, you will explore Spark Data frame and dataset transformations along with aggregations in Apache Spark. Finally, you will look at the Spark Data frame joins in detail.

By the end of this course, you will understand Spark programming and apply that knowledge to build data engineering solutions.

All the resource files are uploaded on the GitHub repository at https://github.com/PacktPublishing/Spark-Programming-in-Scala-for-Begin…

Type
video
Category
Data
publication date
2022-03-24
what you will learn

Learn Apache Spark and Spark architecture
Look at data engineering and data processing in Spark
Work with data sources and sinks
Work with data frames, datasets, and Spark SQL
Use IntelliJ IDEA for Spark development and debugging
Understand unit testing, managing application logs, and cluster deployment

duration
407
key features
A comprehensive course designed for the beginner-level for Spark programming in Scala * Deep dive into Spark 3 architecture and data engineering * Complete tested source code and examples used on Apache Spark 3.0.0 open-source distribution from the author’s end
approach
This is a hands-on and well-balanced course with theoretical and practical content. The course is example-driven and follows a working session-like approach. The author will be taking a live coding approach and explaining all the concepts needed along the way. The section will have a summary video at the end to revise the learned concepts.
audience
This course is designed for software engineers willing to develop a data engineering pipeline and application using Apache Spark. It is also for data architects and data engineers who are responsible for designing and building the organization’s data-centric infrastructure. It will also be beneficial for the managers and architects who do not directly work with Spark implementation, and still, they work with the people who implement Apache Spark at the ground level.

Before proceeding with the course, you will need basic knowledge of the Scala programming language.
meta description
A carefully designed and error-free tested course on Spark programming in Scala for beginners using Apache Spark 3. Reinforce your journey with hands-on and practical content throughout.
short description
This course does not require any prior knowledge of Apache Spark or Hadoop. The author explains Spark architecture and fundamental concepts to help you come up to speed and grasp the content of this course.

The course will help you understand Spark programming and apply that knowledge to build data engineering solutions.
subtitle
Data Engineering Using Spark Structured API
keywords
Spark 3, Apache Spark, Hadoop, Big Data, Databricks, Spark 3 Architecture, Scala, Apache Hadoop, IntelliJ IDEA, Scala Plugin, Databricks Community Edition, Apache Zeppelin
Product ISBN
9781803239538