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Modern Big Data Processing with Hadoop

You're reading from   Modern Big Data Processing with Hadoop Expert techniques for architecting end-to-end big data solutions to get valuable insights

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Product type Paperback
Published in Mar 2018
Publisher Packt
ISBN-13 9781787122765
Length 394 pages
Edition 1st Edition
Languages
Concepts
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Authors (3):
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Manoj R Patil Manoj R Patil
Author Profile Icon Manoj R Patil
Manoj R Patil
Prashant Shindgikar Prashant Shindgikar
Author Profile Icon Prashant Shindgikar
Prashant Shindgikar
V Naresh Kumar V Naresh Kumar
Author Profile Icon V Naresh Kumar
V Naresh Kumar
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Toc

Table of Contents (12) Chapters Close

Preface 1. Enterprise Data Architecture Principles FREE CHAPTER 2. Hadoop Life Cycle Management 3. Hadoop Design Consideration 4. Data Movement Techniques 5. Data Modeling in Hadoop 6. Designing Real-Time Streaming Data Pipelines 7. Large-Scale Data Processing Frameworks 8. Building Enterprise Search Platform 9. Designing Data Visualization Solutions 10. Developing Applications Using the Cloud 11. Production Hadoop Cluster Deployment

The need for an enterprise search engine

Just like we all need a tool to search our own things, every company also needs a search engine to build so that internal and external entities can find what they want.

For example, an employee has to search for his/her PTO balance, paystub of a particular month, and so on. The HR department may search for employees who are in finance group or so. In an e-commerce company, a product catalog is the most searchable object. It is a very sensitive object because it directly impacts the revenue of the company. If a customer wants to buy a pair of shoes, the first thing he/she can do is search the company product catalog. If the search time is more than a few seconds, the customer may lose interest in the product. It may also be possible that the same customer goes to another website to buy a pair of shoes, resulting in a loss of revenue.

It...

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