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

Introduction to segment merging


In the Full text searching section of Chapter 1, Getting Started with Elasticsearch Cluster, we mentioned segments and their immutability. We wrote that the Lucene library, and thus Elasticsearch, writes data to certain structures that are written once and never change. This allows for some simplification, but also introduces the need for additional work. One such example is deletion. Because segment, cannot be altered, information about deletions must be stored alongside and dynamically applied during search. This is done by filtering deleted documents from the returned result set. The other example is the inability to modify the documents (however, some modifications are possible, such as modifying numeric doc values). Of course, one can say that Elasticsearch supports document updates (refer to the Manipulating data with the REST API section of Chapter 1, Getting Started with Elasticsearch Cluster). However, under the hood, the old document is marked as...