Big Data Using Hadoop and Hive / / Nitin Kumar.

• Superior document: Title is part of eBook package: De Gruyter MLI AI COLLECTION
• VerfasserIn: Kumar, Nitin,
• Place / Publishing House: Dulles, VA : : Mercury Learning and Information, , [2021]; ©2021
• Year of Publication: 2021
• Language: English
• Physical Description: 1 online resource (192 p.)

This book is the basic guide for developers, architects, engineers, and anyone who wants to start leveraging the open-source software Hadoop and Hive to build distributed, scalable concurrent big data applications. Hive will be used for reading, writing, and managing the large, data set files. The book is a concise guide on getting started with an overall understanding on Apache Hadoop and Hive and how they work together to speed up development with minimal effort. It will refer to simple concepts and examples, as they are likely to be the best teaching aids. It will explain the logic, code, and configurations needed to build a successful, distributed, concurrent application, as well as the reason behind those decisions. Features: Shows how to leverage the open-source software Hadoop and Hive to build distributed, scalable, concurrent big data applications Includes material on Hive architecture with various storage types and the Hive query language Features a chapter on big data and how Hadoop can be used to solve the changes around it Explains the basic Hadoop setup, configuration, and optimization

Table of Contents

Frontmatter -- CONTENTS -- Preface -- Chapter 1: Big Data -- Chapter 2: What is Apache Hadoop? -- Chapter 3: The Hadoop Distribution Filesystem -- Chapter 4: Getting Started with Hadoop -- Chapter 5: Interfaces to Access HDFS Files -- Chapter 6: Yet Another Resource Negotiator -- Chapter 7: MapReduce -- Chapter 8: Hive -- Chapter 9: Getting Started with Hive -- Chapter 10: File Format -- Chapter 11: Data Compression -- Index