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Scaling Big Data with Hadoop and Solr, Second Edition

You're reading from Scaling Big Data with Hadoop and Solr, Second Edition

Product type Book

Published in Apr 2015

Publisher

ISBN-13 9781783553396

Pages 166 pages

Edition 1st Edition

Languages

Concepts

Author (1):

Hrishikesh Vijay Karambelkar

Table of Contents (13) Chapters

Scaling Big Data with Hadoop and Solr Second Edition

Credits

About the Author

About the Reviewers

www.PacktPub.com

Preface

1. Processing Big Data Using Hadoop and MapReduce

2. Understanding Apache Solr

3. Enabling Distributed Search using Apache Solr

4. Big Data Search Using Hadoop and Its Ecosystem

5. Scaling Search Performance

Use Cases for Big Data Search

Index

Understanding NoSQL

Traditional relational databases allow users to define a strict data structure, and use an SQL-based querying mechanism. NoSQL databases, rather than confining users to define the data structures, allow an open database with which they can store any kind of data and retrieve it by running queries that are not SQL based. In an enterprise, data is generated from all the software used in day-to-day operations. This data has different formats, and bringing in this data for big-data processing requires for a storage system that is flexible enough, to accommodate data with varying data models. The NoSQL database, by design is best suited for such storage.

Note

The CAP theorem or Brewer's theorem talks about distributed consistency. It states that it is impossible to achieve all of the following in a distributed system:

Consistency: Every client sees the most recently updated data state.
Availability: The distributed system functions as expected, even if there are node failures...

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Authors (1)

Hrishikesh Vijay Karambelkar

Hrishikesh Vijay Karambelkar is an innovator and an enterprise architect with 16 years of software design and development experience, specifically in the areas of big data, enterprise search, data analytics, text mining, and databases. He is passionate about architecting new software implementations for the next generation of software solutions for various industries, including oil and gas, chemicals, manufacturing, utilities, healthcare, and government infrastructure. In the past, he has authored three books for Packt Publishing: two editions of Scaling Big Data with Hadoop and Solr and one of Scaling Apache Solr. He has also worked with graph databases, and some of his work has been published at international conferences such as VLDB and ICDE.

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