Written By: Trisha Konkimalla
Apache Spark is a data processing system that can handle massive data sets easily and delegate processing functions across many devices, either on its own or in conjunction with other distributed computing resources. This article contains amazing free apache spark courses!
The course aims to close the distance between what's found in Apache Spark documentation and other courses and what developers really want. It attempts to respond to many of the commonly asked Apache Spark questions on StackOverflow and other platforms, such as why do you need Apache Spark if you already have Hadoop and what is the difference between Apache Spark and Hadoop. How is Apache Spark able to do quicker computations? What is RDD abstraction, and how does it work?
The course will show you how to set up a local programming environment by downloading Java and JDK, IntelliJ IDEA, and Apache Spark Integration with IDEA.
You'll need a machine with 4GB of RAM and a 64-bit operating system, as well as some Scala experience.
This course is for new programmers or businesspeople who want to learn about the fundamental methods for wrangling and analyzing big data. You will have the ability to walk through hands-on examples of Hadoop and Spark frameworks, two of the most common in the industry, even though you have no previous experience. You'll be able to describe the Hadoop architecture, program stack, and execution environment specific components and common processes. You will be led by the assignments on how data scientists use critical principles and strategies such as Map-Reduce to solve basic challenges in big data.
This Pluralsight course is excellent if you want to learn Apache Spark from the ground up. It explains why Hadoop is ineffective for analyzing today's Big Data and how Apache Spark's pace aids modern big data analysis. In this course, you'll learn Spark from the ground up, beginning with its history and progressing to developing a Wikipedia research framework in order to better understand the Apache Spark Core API. If you've mastered the Apache Spark Core library, you'll be able to use other Spark libraries such as Streaming and SQL APIs. Finally, you'll hear about certain pitfalls to avoid while working with Apache Spark.
Setting up your own, local growth environment is one of the most difficult aspects of studying Big Data, and this course will aid you in this endeavor. This course will show you how to set up an Apache Spark development environment on a Windows 10 laptop with 4 GB of RAM. You will go on to other Python and Apache Spark courses after you've completed this one.