Bookbot

Apache Hadoop 3 Quick Start Guide

Learn About Big Data Processing And Analytics - English Edition

Parámetros

  • 220 páginas
  • 8 horas de lectura

Más información sobre el libro

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.

Compra de libros

Apache Hadoop 3 Quick Start Guide, Hrishikesh Vijay Karambelkar

Idioma
Publicado en
2018
Encuadernación
(Tapa blanda),
Estado del libro
Bueno
Precio
17,99 €

Métodos de pago

Nadie lo ha calificado todavía.Añadir reseña

Título
Apache Hadoop 3 Quick Start Guide
Subtítulo
Learn About Big Data Processing And Analytics - English Edition
Idioma
Inglés
Publicado en
2018
Formato
Tapa blanda
Páginas
220
ISBN10
1788999835
ISBN13
9781788999830
Serie
Descripción
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.