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Mastering Hadoop 3: Big data processing at scale to unlock unique business insights - Softcover

 
9781788620444: Mastering Hadoop 3: Big data processing at scale to unlock unique business insights

Synopsis

A comprehensive guide to mastering the most advanced Hadoop 3 concepts


Key Features:

  • Get to grips with the newly introduced features and capabilities of Hadoop 3
  • Crunch and process data using MapReduce, YARN, and a host of tools within the Hadoop ecosystem
  • Sharpen your Hadoop skills with real-world case studies and code


Book Description:

Apache Hadoop is one of the most popular big data solutions for distributed storage and for processing large chunks of data. With Hadoop 3, Apache promises to provide a high-performance, more fault-tolerant, and highly efficient big data processing platform, with a focus on improved scalability and increased efficiency.


With this guide, you'll understand advanced concepts of the Hadoop ecosystem tool. You'll learn how Hadoop works internally, study advanced concepts of different ecosystem tools, discover solutions to real-world use cases, and understand how to secure your cluster. It will then walk you through HDFS, YARN, MapReduce, and Hadoop 3 concepts. You'll be able to address common challenges like using Kafka efficiently, designing low latency, reliable message delivery Kafka systems, and handling high data volumes. As you advance, you'll discover how to address major challenges when building an enterprise-grade messaging system, and how to use different stream processing systems along with Kafka to fulfil your enterprise goals.


By the end of this book, you'll have a complete understanding of how components in the Hadoop ecosystem are effectively integrated to implement a fast and reliable data pipeline, and you'll be equipped to tackle a range of real-world problems in data pipelines.


What You Will Learn:

  • Gain an in-depth understanding of distributed computing using Hadoop 3
  • Develop enterprise-grade applications using Apache Spark, Flink, and more
  • Build scalable and high-performance Hadoop data pipelines with security, monitoring, and data governance
  • Explore batch data processing patterns and how to model data in Hadoop
  • Master best practices for enterprises using, or planning to use, Hadoop 3 as a data platform
  • Understand security aspects of Hadoop, including authorization and authentication


Who this book is for:

If you want to become a big data professional by mastering the advanced concepts of Hadoop, this book is for you. You'll also find this book useful if you're a Hadoop professional looking to strengthen your knowledge of the Hadoop ecosystem. Fundamental knowledge of the Java programming language and basics of Hadoop is necessary to get started with this book.

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About the Authors

Chanchal Singh has over half decades experience in Product Development and Architect Design. He has been working very closely with leadership team of various companies including directors ,CTO's and Founding members to define technical road-map for company.He is the Founder and Speaker at meetup group Big Data and AI Pune MeetupExperience Speaks. He is Co-Author of Book Building Data Streaming Application with Apache Kafka. He has a Bachelor's degree in Information Technology from the University of Mumbai and a Master's degree in Computer Application from Amity University. He was also part of the Entrepreneur Cell in IIT Mumbai. His Linkedin Profile can be found at with the username Chanchal Singh.

Manish Kumar is a technical architect at DataMetica Solution Pvt. Ltd. He has approximately 11 years' experience in data management, working as a data architect and product architect. He has extensive experience of building effective ETL pipelines, implementing security over Hadoop, and providing the best possible solutions to data science problems. Before joining the world of big data, he worked as a tech lead for Sears Holding, India. Manish has a bachelor's degree in information technology, and he is a coauthor of Building Data Streaming Applications with Apache Kafka.

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