What this book covers
Chapter 1, Introduction to Big Data and Hadoop, covers an overview of big data and Hadoop, plus different use case patterns with advantages and features of Hadoop.
Chapter 2, Hadoop Ecosystem, explores the different phases or layers of Hadoop project development and some components that can be used in each layer.
Chapter 3, Pillars of Hadoop – HDFS, MapReduce, and YARN, is about the three key basic components of Hadoop, which are HDFS, MapReduce, and YARN.
Chapter 4, Data Access Components – Hive and Pig, covers the data access components Hive and Pig, which are abstract layers of the SQL-like and Pig Latin procedural languages, respectively, on top of the MapReduce framework.
Chapter 5, Storage Components – HBase, is about the NoSQL component database HBase in detail.
Chapter 6, Data Ingestion in Hadoop – Sqoop and Flume, covers the data ingestion library tools Sqoop and Flume.
Chapter 7, Streaming and Real-time Analysis – Storm and Spark, is about the streaming and real-time frameworks Storm and Spark built on top of YARN.
