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Elasticsearch Server - Third Edition

You're reading from   Elasticsearch Server - Third Edition Leverage Elasticsearch to create a robust, fast, and flexible search solution with ease

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Product type Paperback
Published in Feb 2016
Publisher
ISBN-13 9781785888816
Length 556 pages
Edition 3rd Edition
Languages
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Authors (2):
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Rafal Kuc Rafal Kuc
Author Profile Icon Rafal Kuc
Rafal Kuc
Marek Rogozinski Marek Rogozinski
Author Profile Icon Marek Rogozinski
Marek Rogozinski
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Table of Contents (13) Chapters Close

Preface 1. Getting Started with Elasticsearch Cluster 2. Indexing Your Data FREE CHAPTER 3. Searching Your Data 4. Extending Your Querying Knowledge 5. Extending Your Index Structure 6. Make Your Search Better 7. Aggregations for Data Analysis 8. Beyond Full-text Searching 9. Elasticsearch Cluster in Detail 10. Administrating Your Cluster 11. Scaling by Example Index

Elasticsearch spatial capabilities


The search servers such as Elasticsearch are usually looked at from the perspective of full-text searching. Elasticsearch, because of its marketing as being part of ELK (Elasticsearch, Logstash, and Kibana), is also highly known for being able to handle large amount of time series data. However, this is only a part of the whole view. Sometimes both of the mentioned use cases are not enough. Imagine searching for local services. For the end user, the most important thing is the accuracy of the results. By accuracy, we not only mean the proper results of the full-text search, but also the results being as near as they can in terms of location. In several cases, this is the same as a text search on geographical names such as cities or streets, but in other cases we can find it very useful to be able to search on the basis of the geographical coordinates of our indexed documents. And this is also a functionality that Elasticsearch is capable of handling.

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