Data Engineering using Spark Structured API
What you’ll learn
Apache Spark Foundation and Spark Architecture
Data Engineering and Data Processing in Spark
Working with Data Sources and Sinks
Working with Data Frames, Data Sets and Spark SQL
Using IntelliJ Idea for Spark Development and Debugging
Unit Testing, Managing Application Logs and Cluster Deployment
This Free does not require any prior knowledge of Apache Spark or Hadoop. We have taken enough care to explain Spark Architecture and fundamental concepts to help you come up to speed and grasp the content of this Free.
About the Free
I am creating Apache Spark 3 – Spark Programming in Scala for Beginners Free to help you understand the Spark programming and apply that knowledge to build data engineering solutions. This Free is example-driven and follows a working session like approach. We will be taking a live coding approach and explain all the needed concepts along the way.
Who should take this Free?
I designed this Free for software engineers willing to develop a Data Engineering pipeline and application using the Apache Spark. I am also creating this Free for data architects and data engineers who are responsible for designing and building the organization’s data-centric infrastructure. Another group of people is the managers and architects who do not directly work with Spark implementation. Still, they work with the people who implement Apache Spark at the ground level.
Spark Version used in the Free
This Free is using the Apache Spark 3.x. I have tested all the source code and examples used in this Free on Apache Spark 3.0.0 open-source distribution.
Who this Free is for:
- Software Engineers and Architects who are willing to design and develop a Bigdata Engineering Projects using Apache Spark
- Programmers and developers who are aspiring to grow and learn Data Engineering using Apache Spark