Modern Big Data Processing with Hadoop
Expert techniques for architecting end-to-end big data solutions to get valuable insights
Price | $50.55 - $54.99
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Rating | |
Authors | Naresh Kumar, Prashant Shindgikar |
Publisher | Packt Publishing |
Published | 2018 |
Pages | 394 |
Language | English |
Format | Paper book / ebook (PDF) |
ISBN-10 | 178712276X |
ISBN-13 | 9781787122765 |
The complex structure of data these days requires sophisticated solutions for data transformation, to make the information more accessible to the users.This book empowers you to build such solutions with relative ease with the help of Apache Hadoop, along with a host of other Big Data tools.
This book will give you a complete understanding of the data lifecycle management with Hadoop, followed by modeling of structured and unstructured data in Hadoop. It will also show you how to design real-time streaming pipelines by leveraging tools such as Apache Spark, and build efficient enterprise search solutions using Elasticsearch. You will learn to build enterprise-grade analytics solutions on Hadoop, and how to visualize your data using tools such as Apache Superset. This book also covers techniques for deploying your Big Data solutions on the cloud Apache Ambari, as well as expert techniques for managing and administering your Hadoop cluster.
By the end of this book, you will have all the knowledge you need to build expert Big Data systems.
Build an efficient enterprise Big Data strategy centered around Apache Hadoop; Gain a thorough understanding of using Hadoop with various Big Data frameworks such as Apache Spark, Elasticsearch and more; Set up and deploy your Big Data environment on premises or on the cloud with Apache Ambari; Design effective streaming data pipelines and build your own enterprise search solutions; Utilize the historical data to build your analytics solutions and visualize them using popular tools such as Apache Superset; Plan, set up and administer your Hadoop cluster efficiently.
- Naresh Kumar
- Prashant Shindgikar
2 5 4
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