Solving 10 Hadoop'able Problems

The Apache Hadoop ecosystem is a popular and powerful tool to solve big data problems. With so many competing tools to process data, many users want to know which particular problems are well suited to Hadoop, and how to implement those solutions.

To know what types of problems are Hadoop-able it is good to start with a basic understanding of the core components of Hadoop. You will learn about the ecosystem designed to run on top of Hadoop as well as software that is deployed alongside it. These tools give us the building blocks to build data processing applications. This course covers the core parts of the Hadoop ecosystem, helping to give a broad understanding and get you up-and-running fast. Next, it describes a number of common problems as case-study projects Hadoop is able to solve. These sections are broken down into sections by different projects, each serving as a specific use case for solving big data problems.

By the end of this course, you will have been exposed to a wide variety of Hadoop software and examples of how it is used to solve common big data problems.

About the Author

Tomasz Lelek is a Software Engineer who programs mostly in Java and Scala. He is a fan of microservice architectures and functional programming. He dedicates considerable time and effort to be better every day. Recently, he's been delving into big data technologies such as Apache Spark and Hadoop. He is passionate about nearly everything associated with software development.

Tomasz thinks that we should always try to consider different solutions and approaches to solving a problem. Recently, he was a speaker at several conferences in Poland - Confitura and JDD (Java Developer's Day) and also at Krakow Scala User Group.

He also conducted a live coding session at Geecon Conference.