Book Image

Apache Hadoop 3 Quick Start Guide

By : Hrishikesh Vijay Karambelkar
Book Image

Apache Hadoop 3 Quick Start Guide

By: Hrishikesh Vijay Karambelkar

Overview of this book

Apache Hadoop is a widely used distributed data platform. It enables large datasets to be efficiently processed instead of using one large computer to store and process the data. This book will get you started with the Hadoop ecosystem, and introduce you to the main technical topics, including MapReduce, YARN, and HDFS. The book begins with an overview of big data and Apache Hadoop. Then, you will set up a pseudo Hadoop development environment and a multi-node enterprise Hadoop cluster. You will see how the parallel programming paradigm, such as MapReduce, can solve many complex data processing problems. The book also covers the important aspects of the big data software development lifecycle, including quality assurance and control, performance, administration, and monitoring. You will then learn about the Hadoop ecosystem, and tools such as Kafka, Sqoop, Flume, Pig, Hive, and HBase. Finally, you will look at advanced topics, including real time streaming using Apache Storm, and data analytics using Apache Spark. By the end of the book, you will be well versed with different configurations of the Hadoop 3 cluster.
Table of Contents (10 chapters)

Understanding Hadoop's Ecosystem

Hadoop is often used for historical data analytics, although a new trend is emerging where it is used for real-time data streaming as well. Considering the offerings of Hadoop's ecosystem, we have broadly categorized them into the following categories:

  • Data flow: This includes components that can transfer data to and from different subsystems to and from Hadoop including real-time, batch, micro-batching, and event-driven data processing.
  • Data engine and frameworks: This provides programming capabilities on top of Hadoop YARN or MapReduce.
  • Data storage: This category covers all types of data storage on top of HDFS.
  • Machine learning and analytics: This category covers big data analytics and machine learning on top of Apache Hadoop.
  • Search engine: This category covers search engines in both structured and unstructured Hadoop data.
  • Management...