Hadoop is traditionally used as a File System with the capability to process high data volumes using distributed algorithms. However, with its growing popularity among non-programmers and business analysts, there is a need to read and manipulate high volume records using simple, well-known interfaces. SQL is always popular among non-programmers and data analysts because of its simple constructs and easy-to-understand logical syntax. Since Hadoop is used as storage for large volumes of data and because data exploration on top of Hadoop is one of the key use cases, SQL is ideal. Keeping those goals in mind, many SQL engines are developed to process and explore data stored in the Hadoop File System. There are many SQL distributions on Hadoop. Most of them are open source. We will look into those one by one in the following sections.

In this chapter, we will cover the...