Preface

Welcome to Learning Elasticsearch. We will start by describing the basic concepts of Elasticsearch. You will see how to install Elasticsearch and Kibana and learn how to index and update your data. We will use an e-commerce site as an example to explain how a search engine works and how to query your data. The real power of Elasticsearch is aggregations. You will see how to perform aggregation-based analytics with ease. You will also see how to use Kibana to explore and visualize your data. Finally, we will discuss how to use Graph to discover relations in your data and use alerting to set up alerts and notification on different trends in your data.

To better explain various concepts, lots of examples have been used throughout the book. Detailed instructions to install Elasticsearch, Kibana and how to execute the examples is included in Chapter 2, Setting Up Elasticsearch and Kibana.

What this book covers

Chapter 1, Introduction to Elasticsearch, describes the building blocks of Elasticsearch and what makes Elasticsearch scalable and distributed. In this chapter, we also discuss the strengths and limitations of Elasticsearch.

Chapter 2, Setting Up Elasticsearch and Kibana, covers the installation of Elasticsearch and Kibana.

Chapter 3,Modeling Your Data and Document Relations, focuses on modeling your data. To support text search, Elasticsearch preprocess the data before indexing. This chapter describes why preprocessing is necessary and various analyzers Elasticsearch supports. In addition to that, we discuss how to handle relationships between different document types.

Chapter 4, Indexing and Updating Your Data, covers how to index and update your data and what happens internally when you index and update. The data indexed in Elasticsearch is only available after a small delay, we discuss the reason for the delay and how to control the delay.

Chapter 5, Organizing Your Data and Bulk Data Ingestion, describes how to organize and manage indices in Elasticsearch using aliases and templates and more. This chapter also covers various Bulk API's Elasticsearch supports and how to rebuild your existing indices using Reindex and Shrink API.

Chapter 6, All About Search, covers how to search, sort and paginate on your data. The concept of relevance is introduced and we discuss how to tune the relevance score to get the most relevant search results at the top.

Chapter 7,More Than a Search Engine (Geofilters, Autocomplete and More), covers how to filter based on geolocation, using Elasticsearch suggesters for autocomplete, correcting user typo's and lot more.

Chapter 8, How to Slice and Dice Your Data Using Aggregations, covers different kinds of aggregations Elasticsearch supports and how to visualize the data using Kibana.

Chapter 9, Production and Beyond, covers important settings to configure and monitor in production.

Chapter 10, Exploring Elastic Stack (Elastic Cloud, Security, Graph, and Alerting), covers Elastic Cloud, which is managed cloud hosting and other products that are part of X-Pack.

What you need for this book

The book was written using Elasticsearch 5.1.2, and all the examples used in the book should work with it. The request format used in this book is based on the Kibana Console and you'll need Kibana Console or Sense Chrome plugin to execute the examples used in this book. Please refer to Query format used in this book section of Chapter 2, Setting up Elasticsearch and Kibana for more details. If using Kibana or Sense is not option, you can use other HTTP clients such as cURL or Postman. The request format is slightly different and is explained in the Using cURL or Postman section of Chapter 2, Setting Up Elasticsearch and Kibana.

Who this book is for

This book is for software developers who are planning to build a search and analytics engine or are trying to learn Elasticsearch.

Some familiarity with web technologies (JavaScript, REST, JSON) would be helpful.

Conventions

In this book, you will find a number of text styles that distinguish between different kinds of information. Here are some examples of these styles and an explanation of their meaning.

Code words in text, database table names, folder names, filenames, file extensions, path names, dummy URLs, user input, and Twitter handles are shown as follows: "We can include other contexts through the use of the include directive."

A block of code is set as follows:

{
    "articleid": 1,
    "name": "Introduction to Elasticsearch"
}

When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:

{
    "articleid": 1,
"name": "Introduction to Elasticsearch" 
}

New terms and important words are shown in bold. Words that you see on the screen, for example, in menus or dialog boxes, appear in the text like this: "Clicking the Next button moves you to the next screen."

Note

Warnings or important notes appear in a box like this.

Note

Tips and tricks appear like this.

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