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Apache Hadoop 3 Quick Start Guide

Apache Hadoop 3 Quick Start Guide

By : Vijay Karambelkar
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Apache Hadoop 3 Quick Start Guide

Apache Hadoop 3 Quick Start Guide

By: 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)
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Summary

In this chapter, we covered the installation and setup of Apache Hadoop. We started with the prerequisites for setting up a Hadoop cluster. We also went through different Hadoop configurations available for users, covering the development mode, pseudo distributed single nodes, and the cluster setup. We learned how each of these configurations can be set up, and we also ran an example application on the configurations. Finally, we covered how one can diagnose the Hadoop cluster by understanding the log files and different debugging tools available. In the next chapter, we will start looking at the Hadoop Distributed File System in detail.

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