Book Image

Elasticsearch Server - Third Edition

By : Rafal Kuc
Book Image

Elasticsearch Server - Third Edition

By: Rafal Kuc

Overview of this book

ElasticSearch is a very fast and scalable open source search engine, designed with distribution and cloud in mind, complete with all the goodies that Apache Lucene has to offer. ElasticSearch’s schema-free architecture allows developers to index and search unstructured content, making it perfectly suited for both small projects and large big data warehouses, even those with petabytes of unstructured data. This book will guide you through the world of the most commonly used ElasticSearch server functionalities. You’ll start off by getting an understanding of the basics of ElasticSearch and its data indexing functionality. Next, you will see the querying capabilities of ElasticSearch, followed by a through explanation of scoring and search relevance. After this, you will explore the aggregation and data analysis capabilities of ElasticSearch and will learn how cluster administration and scaling can be used to boost your application performance. You’ll find out how to use the friendly REST APIs and how to tune ElasticSearch to make the most of it. By the end of this book, you will have be able to create amazing search solutions as per your project’s specifications.
Table of Contents (18 chapters)
Elasticsearch Server Third Edition
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Preface
Index

Understanding the explain information


Compared to databases, using systems capable of performing full-text search can often be anything other than obvious. We can search in many fields simultaneously and the data in the index can vary from the ones provided as the values of the document fields (because of the analysis process, synonyms, abbreviations, and others). It's even worse! By default, search engines sort data by relevance, which means that each document is given a number indicating how similar the document is to the query. The key point here is understanding the how similar phrase. As we discussed in the beginning of the chapter, scoring takes many factors into account – how many searched words were found in the document, how frequent the word is, how many terms are in the field, and so on. This seems complicated and finding out why a document was found and why another document is better is not easy. Fortunately, Elasticsearch provides us with tools that can answer these questions...