Apache Hadoop 3 Quick Start Guide - Hrishikesh Vijay Karambelkar

Apache Hadoop 3 Quick Start Guide

Learn about big data processing and analytics
Buch | Softcover
220 Seiten
2018
Packt Publishing Limited (Verlag)
978-1-78899-983-0 (ISBN)
29,90 inkl. MwSt
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 such as MapReduce, YARN and HDFS.
A fast paced guide that will help you learn about Apache Hadoop 3 and its ecosystem

Key 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

Book DescriptionApache 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.

What you will 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

Who this book is forAspiring Big Data professionals who want to learn the essentials of Hadoop 3 will find this book to be useful. Existing Hadoop users who want to get up to speed with the new features introduced in Hadoop 3 will also benefit from this book. Having knowledge of Java programming will be an added advantage.

Hrishikesh Vijay Karambelkar is an innovator and an enterprise architect with 16 years of software design and development experience, specifically in the areas of big data, enterprise search, data analytics, text mining, and databases. He is passionate about architecting new software implementations for the next generation of software solutions for various industries, including oil and gas, chemicals, manufacturing, utilities, healthcare, and government infrastructure. In the past, he has authored three books for Packt Publishing: two editions of Scaling Big Data with Hadoop and Solr and one of Scaling Apache Solr. He has also worked with graph databases, and some of his work has been published at international conferences such as VLDB and ICDE.

Table of Contents

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

Erscheinungsdatum
Verlagsort Birmingham
Sprache englisch
Maße 75 x 93 mm
Themenwelt Informatik Datenbanken Data Warehouse / Data Mining
ISBN-10 1-78899-983-5 / 1788999835
ISBN-13 978-1-78899-983-0 / 9781788999830
Zustand Neuware
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