This book is a quick-start guide for learning Apache Hadoop version 3. It is targeted at readers with no prior knowledge of Apache Hadoop, and covers key big data concepts, such as data manipulation using MapReduce, flexible model utilization with YARN, and storing different datasets with Hadoop Distributed File System (HDFS). This book will teach you about different configurations of Hadoop version 3 clusters, from a lightweight developer edition to an enterprise-ready deployment. Throughout your journey, this guide will demonstrate how parallel programming paradigms such as MapReduce can be used to solve many complex data processing problems, using case studies and code to do so. Along with development, the book will also cover the important aspects of the big data software development life cycle, such as quality assurance and control, performance, administration, and monitoring. This book serves as a starting point for those who wish to master the Apache Hadoop ecosystem.
Apache Hadoop 3 Quick Start Guide
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Apache Hadoop 3 Quick Start Guide
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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.
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Current Title:
Apache Hadoop 3 Quick Start Guide
Table of Contents (10 chapters)
Preface
Free Chapter
Hadoop 3.0 - Background and Introduction
Planning and Setting Up Hadoop Clusters
Deep Dive into the Hadoop Distributed File System
Developing MapReduce Applications
Building Rich YARN Applications
Monitoring and Administration of a Hadoop Cluster
Demystifying Hadoop Ecosystem Components
Advanced Topics in Apache Hadoop
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