Book Image

Learning Elasticsearch

By : Abhishek Andhavarapu
Book Image

Learning Elasticsearch

By: Abhishek Andhavarapu

Overview of this book

Elasticsearch is a modern, fast, distributed, scalable, fault tolerant, and open source search and analytics engine. You can use Elasticsearch for small or large applications with billions of documents. It is built to scale horizontally and can handle both structured and unstructured data. Packed with easy-to- follow examples, this book will ensure you will have a firm understanding of the basics of Elasticsearch and know how to utilize its capabilities efficiently. You will install and set up Elasticsearch and Kibana, and handle documents using the Distributed Document Store. You will see how to query, search, and index your data, and perform aggregation-based analytics with ease. You will see how to use Kibana to explore and visualize your data. Further on, you will learn to handle document relationships, work with geospatial data, and much more, with this easy-to-follow guide. Finally, you will see how you can set up and scale your Elasticsearch clusters in production environments.
Table of Contents (11 chapters)
10
Exploring Elastic Stack (Elastic Cloud, Security, Graph, and Alerting)

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.