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Elasticsearch Server - Third Edition

Elasticsearch Server - Third Edition

By : Marek Rogozinski, Rafal Kuc
5 (1)
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Elasticsearch Server - Third Edition

Elasticsearch Server - Third Edition

5 (1)
By: Marek Rogozinski, 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 (13 chapters)
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12
Index

What this book covers

Chapter 1, Getting Started with Elasticsearch Cluster, covers what full-text searching is, what Apache Lucene is, what text analysis is, how to run and configure Elasticsearch, and finally, how to index and search your data in the most basic way.

Chapter 2, Indexing Your Data, shows how indexing works, how to prepare index structure, what data types we are allowed to use, how to speed up indexing, what segments are, how merging works, and what routing is.

Chapter 3, Searching Your Data, introduces the full-text search capabilities of Elasticsearch by discussing how to query it, how the querying process works, and what types of basic and compound queries are available. In addition to this, we will show how to use position-aware queries in Elasticsearch.

Chapter 4, Extending Your Query Knowledge, shows how to efficiently narrow down your search results by using filters, how highlighting works, how to sort your results, and how query rewrite works.

Chapter 5, Extending Your Index Structure, shows how to index more complex data structures. We learn how to index tree-like data types, how to index data with relationships between documents, and how to modify index structure.

Chapter 6, Make Your Search Better, covers Apache Lucene scoring and how to influence it in Elasticsearch, the scripting capabilities of Elasticsearch, and its language analysis capabilities.

Chapter 7, Aggregations for Data Analysis, introduces you to the great world of data analysis by showing you how to use the Elasticsearch aggregation framework. We will discuss all types of aggregations—metrics, buckets, and the new pipeline aggregations that have been introduced in Elasticsearch.

Chapter 8, Beyond Full-text Searching, discusses non full-text search-related functionalities such as percolator—reversed search, and the geo-spatial capabilities of Elasticsearch. This chapter also discusses suggesters, which allow us to build a spellchecking functionality and an efficient autocomplete mechanism, and we will show how to handle deep-paging efficiently.

Chapter 9, Elasticsearch Cluster in Detail, discusses nodes discovery mechanism, recovery and gateway Elasticsearch modules, templates, caches, and settings update API.

Chapter 10, Administrating Your Cluster, covers the Elasticsearch backup functionality, rebalancing, and shards moving. In addition to this, you will learn how to use the warm up functionality, use the Cat API, and work with aliases.

Chapter 11, Scaling by Example, is dedicated to scaling and tuning. We will start with hardware preparations and considerations and a single Elasticsearch node-related tuning. We will go through cluster setup and vertical scaling, ending the chapter with high querying and indexing use cases and cluster monitoring.

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