Mastering Hadoop 3
- Paperback: 544 pages
- Publisher: WOW! eBook (February 28, 2019)
- Language: English
- ISBN-10: 1788620445
- ISBN-13: 978-1788620444
Mastering Hadoop 3: A comprehensive guide to mastering the most advanced Hadoop 3 concepts
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.
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
By the end of this Mastering Hadoop 3 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.