Real-World Big Data Analytics with Apache Spark

Every year we have a big increment of data that we need to store and analyze. When we want to aggregate all data about our users and analyze that data to find insights from it, terabytes of data undergo processing. To be able to process such amounts of data, we need to use a technology that can distribute multiple computations and make them more efficient. Apache Spark is a technology that allows us to process big data leading to faster and scalable processing. Ready to use statistical and Machine Learning techniques across large data sets? This course shows you how the Apache Spark and the Hadoop MapReduce ecosystem is perfect for the job.

This comprehensive 3-in-1 course takes a step-by-step practical approach to perform efficient data processing and analytics on your data in real-time! To begin with, you’ll learn basic Spark functionalities and achieve efficient task scheduling, memory management, and fault recovery with Spark components. You’ll then build Hadoop and Apache Spark jobs that process data quickly and effectively. You’ll also write programs for complex data analysis and solving to solve real real-world problems. Moving further, you’ll explore the Map/Reduce Hadoop and Spark approach for solving data analysis problems. Finally, you’ll leverage one of the most efficient and widely adopted big data processing framework: Apache Spark!

Towards the end of this course, you'll leverage one of the most efficient and widely adopted Big Data processing framework - Apache Spark. Perform efficient data processing and analytics on your data in real-time!

Contents and Overview

This training program includes 2 complete courses, carefully chosen to give you the most comprehensive training possible.

The first course, Big Data Analytics Using Apache Spark, covers efficient data processing and analytics on your data in real-time. This course will show you how to acquire structured, semi-structured, and unstructured content from different data sources. You’ll learn to query data using Spark SQL and acquire and load data via the Spark processing tool. You will learn to import structured and unstructured data from different data sources. Going further, you will learn how to use Apache Spark to perform complex processing without extensive programming knowledge and how to leverage those tools to perform data -analytics. By the end of the course, you will have learned to create real-world apps and stream high-velocity data with Spark Streaming.

The second course, Big Data Analytics Projects with Apache Spark, covers Solving real-world Big Data problems. This course contains various projects that consist of real-world examples. The first project is to find top selling products for an e-commerce business by efficiently joining data sets in the Map/Reduce paradigm. Next, a Market Basket Analysis will help you identify items likely to be purchased together and find correlations between items in a set of transactions. Moving on, you'll learn about probabilistic logistic regression by finding an author for a post. Next, you'll build a content-based recommendation system for movies to predict whether an action will happen, which we’ll do by building a trained model. Finally, we’ll use the Map/Reduce Spark program to calculate mutual friends on social network.

Towards the end of this course, you'll leverage one of the most efficient and widely adopted Big Data processing framework - Apache Spark. Perform efficient data processing and analytics on your data in real-time!

About the Authors

• Arokia Armel has been working in the Big Data and Analytics domain. Also, he studies and deploys cutting -edge technologies to tackle challenges with complex datasets. Currently, he is doing research on real-time sentiment analysis. He is passionate about empirical research, corporate training, and answering hard questions with data. On the other hand, he is a strategic thinker with fluent written and verbal communication skills. Moreover, he has the ability to learn cutting-edge technologies and processes quickly, with a high level of ownership. Also, he takes an innovative approach to tackle and solving business problems. In addition, he can analyze complex, high-volume, high-dimensional data from different sources.

• Tomasz Lelek is a Software Engineer who programs mostly in Java and Scala. He is a fan of microservices architecture and functional programming. He is passionate about nearly everything associated with software development. Recently, he was invited as a speaker at conferences in Poland - Confitura and JDD (Java Developers Day) and also at Krakow Scala User Group. He has also conducted a live coding session at Geecon Conference. He is a co-founder of the initlearn - e-learning platform that was built with the Java language. He also writes articles about everything related to the Java word: baeldung