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Apache Hadoop 3 Quick Start Guide

Learn About Big Data Processing And Analytics - English Edition

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This fast-paced guide helps you learn about Apache Hadoop 3 and its ecosystem. It covers setting up, configuring, and starting with Hadoop to gain insights from large datasets, as well as working with its components like MapReduce, HDFS, and YARN. The book introduces the main technical topics, beginning with an overview of big data and Hadoop, before guiding you through setting up a pseudo Hadoop development environment and a multi-node enterprise cluster. You'll explore how the parallel programming paradigm, particularly MapReduce, addresses complex data processing challenges. Key aspects of the big data software development lifecycle, including quality assurance, performance, administration, and monitoring, are also discussed. Additionally, the book delves into the Hadoop ecosystem and tools such as Kafka, Sqoop, Flume, Pig, Hive, and HBase. Advanced topics include real-time streaming with Apache Storm and data analytics using Apache Spark. By the end, you'll be proficient in various Hadoop 3 cluster configurations. This book is ideal for aspiring Big Data professionals and existing Hadoop users looking to understand the new features of Hadoop 3, with Java programming knowledge being a plus.

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Apache Hadoop 3 Quick Start Guide, Hrishikesh Vijay Karambelkar

Taal
Jaar van publicatie
2018
Bindwijze
(Paperback),
Staat van het boek
Goed
Prijs
€ 17,99

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Titel
Apache Hadoop 3 Quick Start Guide
Ondertitel
Learn About Big Data Processing And Analytics - English Edition
Taal
Engels
Jaar van publicatie
2018
Formaat
Paperback
Aantal pagina's
220
ISBN10
1788999835
ISBN13
9781788999830
Reeks
Aantekening
This fast-paced guide helps you learn about Apache Hadoop 3 and its ecosystem. It covers setting up, configuring, and starting with Hadoop to gain insights from large datasets, as well as working with its components like MapReduce, HDFS, and YARN. The book introduces the main technical topics, beginning with an overview of big data and Hadoop, before guiding you through setting up a pseudo Hadoop development environment and a multi-node enterprise cluster. You'll explore how the parallel programming paradigm, particularly MapReduce, addresses complex data processing challenges. Key aspects of the big data software development lifecycle, including quality assurance, performance, administration, and monitoring, are also discussed. Additionally, the book delves into the Hadoop ecosystem and tools such as Kafka, Sqoop, Flume, Pig, Hive, and HBase. Advanced topics include real-time streaming with Apache Storm and data analytics using Apache Spark. By the end, you'll be proficient in various Hadoop 3 cluster configurations. This book is ideal for aspiring Big Data professionals and existing Hadoop users looking to understand the new features of Hadoop 3, with Java programming knowledge being a plus.