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Apache Hadoop 3 Quick Start Guide

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Learn
  • Store and analyze data at scale using HDFS, MapReduce and YARN
  • Install and configure Hadoop 3 in different modes
  • Use Yarn effectively to run different applications on Hadoop based platform
  • Understand and monitor how Hadoop cluster is managed
  • Consume streaming data using Storm, and then analyze it using Spark
  • Explore Apache Hadoop ecosystem components, such as Flume, Sqoop, HBase, Hive, and Kafka
About

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.

Features
  • Set up, configure and get started with Hadoop to get useful insights from large data sets
  • Work with the different components of Hadoop such as MapReduce, HDFS and YARN
  • Learn about the new features introduced in Hadoop 3
Page Count 226
Course Length 6 hours 46 minutes
ISBN 9781788999830
Date Of Publication 31 Oct 2018

Authors

Hrishikesh Karambelkar

Hrishikesh Karambelkar is a software architect with a blend of entrepreneurial and professional experience. His core expertise involves working with multiple technologies such as Apache Hadoop and Solr, and architecting new solutions for the next generation of a product line for his organization. He has published various research papers in the domains of graph searches in databases at various international conferences in the past. On a technical note, Hrishikesh has worked on many challenging problems in the industry involving Apache Hadoop and Solr.