Hadoop has come a long way since its inception. Powered by a community of open source enthusiasts, it has seen three major version releases. The version 1 release saw the light of day six years after the first release of Hadoop. With this release, the Hadoop platform had full capabilities that can run MapReduce-distributed computing on Hadoop Distributed File System (HDFS) distributed storage. It had some of the most major performance improvements ever done, along with full support for security. This release also enjoyed a lot of improvements with respect to HBASE.

The version 2 release made significant leaps compared to version 1 of Hadoop. It introduced YARN, a sophisticated general-purpose resource manager and job scheduling component. HDFS high availability, HDFS federations, and HDFS snapshots were some other prominent features introduced in version 2 releases.

The latest major release of Hadoop is version 3. This version has seen some significant features such as HDFS erasure encoding, a new YARN Timeline service (with new architecture), YARN opportunistic containers and distributed scheduling, support for three name nodes, and intra-data-node load balancers. Apart from major feature additions, version 3 has performance improvements and bug fixes. As this book is about mastering Hadoop 3, we'll mostly talk about this version.

In this chapter, we will take a look at Hadoop's history and how the Hadoop evolution timeline looks. We will look at the features of Hadoop 3 and get a logical view of the Hadoop ecosystem along with different Hadoop distributions. 

In particular, we will cover the following topics: