Big Data Using Hadoop and Hive

Key Features

Provides comprehensive coverage of Hadoop 3 and Hive 3.x

Offers practical examples and sample code for real-world applications

Covers advanced topics like YARN, MapReduce, and data compression

Book Description

This book is a guide for developers and engineers to use Hadoop and Hive for scalable big data applications. It covers reading, writing, and managing large datasets with Hive and provides a concise introduction to Apache Hadoop and Hive, detailing their collaboration to simplify development. Through clear examples, the book explains the logic, code, and configurations needed for building successful distributed applications.

The course starts with an introduction to big data and Apache Hadoop fundamentals. It then covers the Hadoop Distributed Filesystem and how to get started with Hadoop. The journey continues with interfaces to access HDFS files, resource management with Yet Another Resource Negotiator, and MapReduce for data processing. The book also explores Hive architecture, storage types, and the Hive query language.

Mastering these concepts is vital for creating scalable big data solutions. This book ensures a smooth transition from novice to proficient Hadoop and Hive user, providing practical skills and comprehensive knowledge. By the end, readers will be able to set up, configure, and optimize Hadoop, utilize Hive for data management, and effectively solve big data challenges.

What you will learn

Understand the fundamentals of big data and its challenges

Learn the architecture and components of Apache Hadoop

Configure and optimize Hadoop for your needs

Master HDFS for effective data storage and retrieval

Develop and run MapReduce programs

Utilize Hive for advanced data querying and management

Who this book is for

This book is designed for developers and data architects who want to harness the power of Hadoop and Hive for big data applications. Readers should have a basic understanding of programming and data management concepts. Prior experience with Java and SQL will be beneficial but is not mandatory.