This document provides an introduction to Hadoop, including:
- An overview of big data and the challenges it poses for data storage and processing.
- How Hadoop addresses these challenges through its distributed, scalable architecture based on MapReduce and HDFS.
- Descriptions of key Hadoop components like MapReduce, HDFS, Hive, and Sqoop.
- Examples of how to perform common data processing tasks like word counting and friend recommendations using MapReduce.
- Some best practices, limitations, and other tools in the Hadoop ecosystem.