Apache Hadoop 3 Quick Start Guide: Learn about big data processing and analytics

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 Description

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.

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 for

Aspiring 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.

Table of Contents

1. Hadoop 3.0 - Background and Introduction
2. Planning and Setting Up Hadoop Clusters
3. Deep Dive into the Hadoop Distributed File System
4. Developing MapReduce Applications
5. Building Rich YARN Applications
6. Monitoring and Administration of a Hadoop Cluster
7. Demystifying Hadoop Ecosystem Components
8. Advanced Topics in Apache Hadoop

一本快節奏的指南，將幫助您了解Apache Hadoop 3及其生態系統

主要特點:
- 設置、配置和開始使用Hadoop，以從大型數據集中獲取有用的洞察力
- 使用Hadoop的不同組件，如MapReduce、HDFS和YARN進行工作
- 了解Hadoop 3中引入的新功能

書籍描述:
Apache Hadoop是一個廣泛使用的分佈式數據平台。它使得大型數據集能夠高效處理，而不是使用一台大型計算機來存儲和處理數據。本書將帶您入門Hadoop生態系統，並介紹主要的技術主題，包括MapReduce、YARN和HDFS。

本書首先概述了大數據和Apache Hadoop。然後，您將設置一個虛擬Hadoop開發環境和一個多節點企業Hadoop集群。您將看到並行編程範式（如MapReduce）如何解決許多複雜的數據處理問題。

本書還涵蓋了大數據軟件開發生命周期的重要方面，包括質量保證和控制、性能、管理和監控。

然後，您將學習Hadoop生態系統以及Kafka、Sqoop、Flume、Pig、Hive和HBase等工具。最後，您將研究高級主題，包括使用Apache Storm進行實時流式處理和使用Apache Spark進行數據分析。

通過閱讀本書，您將熟悉Hadoop 3集群的不同配置。

您將學到:
- 使用HDFS、MapReduce和YARN存儲和分析大規模數據
- 在不同模式下安裝和配置Hadoop 3
- 有效使用YARN在Hadoop平台上運行不同的應用程序
- 了解和監控Hadoop集群的管理方式
- 使用Storm消耗流式數據，然後使用Spark進行分析
- 探索Apache Hadoop生態系統組件，如Flume、Sqoop、HBase、Hive和Kafka

本書適合對Hadoop 3的基本知識感興趣的大數據專業人士。現有的Hadoop用戶也可以從本書中了解Hadoop 3引入的新功能。具備Java編程知識將是一個額外的優勢。

目錄:
1. Hadoop 3.0 - 背景和介紹
2. 計劃和設置Hadoop集群
3. 深入研究Hadoop分佈式文件系統
4. 開發MapReduce應用程序
5. 構建豐富的YARN應用程序
6. 監控和管理Hadoop集群
7. 解密Hadoop生態系統組件
8. Apache Hadoop的高級主題