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Elasticsearch Essentials

Elasticsearch Essentials

By : Bharvi Dixit
4.3 (6)
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Elasticsearch Essentials

Elasticsearch Essentials

4.3 (6)
By: Bharvi Dixit

Overview of this book

With constantly evolving and growing datasets, organizations have the need to find actionable insights for their business. ElasticSearch, which is the world's most advanced search and analytics engine, brings the ability to make massive amounts of data usable in a matter of milliseconds. It not only gives you the power to build blazing fast search solutions over a massive amount of data, but can also serve as a NoSQL data store. This guide will take you on a tour to become a competent developer quickly with a solid knowledge level and understanding of the ElasticSearch core concepts. Starting from the beginning, this book will cover these core concepts, setting up ElasticSearch and various plugins, working with analyzers, and creating mappings. This book provides complete coverage of working with ElasticSearch using Python and performing CRUD operations and aggregation-based analytics, handling document relationships in the NoSQL world, working with geospatial data, and taking data backups. Finally, we’ll show you how to set up and scale ElasticSearch clusters in production environments as well as providing some best practices.
Table of Contents (12 chapters)
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11
Index

Relational data in the document-oriented NoSQL world


Relational databases have a lot of problems when it comes to dealing with a massive amount of data. Be it speed, efficient processing, effective parallelization, scalability, or costs, relational databases fail when the volume of data starts growing. The other challenge of relational databases is that relationships and schemas must be defined upfront. To overcome these problems, people started with normalizing data, dropping constraints, and relaxing transactional guarantees. Eventually, by compromising on these features, relational databases started resembling a NoSQL product. NoSQL is a combination of two terms, No and SQL. Some people say that it means no relational or no RDBMS, whereas other people say that it is "not only SQL". Whatever the meaning is, one thing is for sure, NoSQL is all about not following the rules of relational databases.

There is no doubt that document-oriented NoSQL databases have succeeded a lot in overcoming...

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