Hadoop Essentials - Tackling the Challenges of Big Data with Hadoop
暫譯: Hadoop 基礎 - 解決大數據挑戰的 Hadoop 實務指南

Key Features

• Get to grips with the most powerful tools in the Hadoop ecosystem, including Storm and Spark
• Learn everything you need to take control of Big Data
• A fast-paced journey through the key features of Hadoop

Book Description

This book jumps into the world of Hadoop and its tools, to help you learn how to use them effectively to optimize and improve the way you handle Big Data.

Starting with the fundamentals Hadoop YARN, MapReduce, HDFS, and other vital elements in the Hadoop ecosystem, you will soon learn many exciting topics such as MapReduce patterns, data management, and real-time data analysis using Hadoop. You will also explore a number of the leading data processing tools including Hive and Pig, and learn how to use Sqoop and Flume, two of the most powerful technologies used for data ingestion. With further guidance on data streaming and real-time analytics with Storm and Spark, Hadoop Essentials is a reliable and relevant resource for anyone who understands the difficulties - and opportunities - presented by Big Data today.

With this guide, you'll develop your confidence with Hadoop, and be able to use the knowledge and skills you learn to successfully harness its unparalleled capabilities.

What you will learn

• Get to grips with the fundamentals of Hadoop, and tools such as HDFS, MapReduce, and YARN
• Learn how to use Hadoop for real-world Big Data projects
• Improve the performance of your Big Data architecture
• Find out how to get the most from data processing tools such as Hive and Pig
• Learn how to unlock real-time Big Data analytics with Apache Spark

About the Author

Shiva Achari has more than 8 years of extensive industry experience and is currently working as a Big Data Architect consultant with companies such as Oracle and Teradata. Over the years, he has architected, designed, and developed multiple innovative and high-performance large-scale solutions, such as distributed systems, data centers, big data management tools, SaaS cloud applications, Internet applications, and Data Analytics solutions.

Table of Contents

1. Introduction to Big Data and Hadoop
2. Hadoop Ecosystem
3. Pillars of Hadoop HDFS, MapReduce, and YARN
4. Data Access Components Hive and Pig
5. Storage Component HBase
6. Data Ingestion in Hadoop Sqoop and Flume
7. Streaming and Real-time Analysis Storm and Spark