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Elasticsearch Essentials

Elasticsearch Essentials

By : Bharvi Dixit
4.3 (6)
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Elasticsearch Essentials

Elasticsearch Essentials

4.3 (6)
By: Bharvi Dixit

Overview of this book

With constantly evolving and growing datasets, organizations have the need to find actionable insights for their business. ElasticSearch, which is the world's most advanced search and analytics engine, brings the ability to make massive amounts of data usable in a matter of milliseconds. It not only gives you the power to build blazing fast search solutions over a massive amount of data, but can also serve as a NoSQL data store. This guide will take you on a tour to become a competent developer quickly with a solid knowledge level and understanding of the ElasticSearch core concepts. Starting from the beginning, this book will cover these core concepts, setting up ElasticSearch and various plugins, working with analyzers, and creating mappings. This book provides complete coverage of working with ElasticSearch using Python and performing CRUD operations and aggregation-based analytics, handling document relationships in the NoSQL world, working with geospatial data, and taking data backups. Finally, we’ll show you how to set up and scale ElasticSearch clusters in production environments as well as providing some best practices.
Table of Contents (12 chapters)
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Preface
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Preface
What this book covers
What you need for this book
Who this book is for
Conventions
Reader feedback
Customer support
Free Chapter
1
1. Getting Started with Elasticsearch
1. Getting Started with Elasticsearch
Introducing Elasticsearch
Installing and configuring Elasticsearch
Basic operations with Elasticsearch
Summary
2
2. Understanding Document Analysis and Creating Mappings
2. Understanding Document Analysis and Creating Mappings
Text search
Document analysis
Elasticsearch mapping
Summary
3
3. Putting Elasticsearch into Action
3. Putting Elasticsearch into Action
CRUD operations using elasticsearch-py
CRUD operations using Java
Creating a search database
Elasticsearch Query-DSL
Understanding Query-DSL parameters
Search requests using Python
Search requests using Java
Sorting your data
Document routing
Summary
4
4. Aggregations for Analytics
4. Aggregations for Analytics
Introducing the aggregation framework
Metric aggregations
Bucket aggregations
Combining search, buckets, and metrics
Memory pressure and implications
Summary
5
5. Data Looks Better on Maps: Master Geo-Spatiality
5. Data Looks Better on Maps: Master Geo-Spatiality
Introducing geo-spatial data
Working with geo-point data
Geo-aggregations
Geo-shapes
Summary
6
6. Document Relationships in NoSQL World
6. Document Relationships in NoSQL World
Relational data in the document-oriented NoSQL world
Working with nested objects
Parent-child relationships
Considerations for using document relationships
Summary
7
7. Different Methods of Search and Bulk Operations
7. Different Methods of Search and Bulk Operations
Introducing search types in Elasticsearch
Cheaper bulk operations
Multi get and multi search APIs
Data pagination
Practical considerations for bulk processing
Summary
8
8. Controlling Relevancy
8. Controlling Relevancy
Introducing relevant searches
The Elasticsearch out-of-the-box tools
Controlling relevancy with custom scoring
Summary
9
9. Cluster Scaling in Production Deployments
9. Cluster Scaling in Production Deployments
Node types in Elasticsearch
Introducing Zen-Discovery
Node upgrades without downtime
Upgrading Elasticsearch version
Best Elasticsearch practices in production
Creating a cluster
Scaling your clusters
Summary
10
10. Backups and Security
10. Backups and Security
Introducing backup and restore mechanisms
Securing Elasticsearch
Summary
11
Index
Index

What this book covers

Chapter 1, Getting Started with Elasticsearch, provides an introduction to Elasticsearch and how it works. After going through the basic concepts and terminologies, you will learn how to install and configure Elasticsearch and perform basic operations with Elasticsearch.

Chapter 2, Understanding Document Analysis and Creating Mappings, covers the details of the built-in analyzers, tokenizers, and filters provided by Lucene. It also covers how to create custom analyzers and mapping with different data types.

Chapter 3, Putting Elasticsearch into Action, introduces Elasticsearch Query-DSL, various queries, and the data sorting techniques. You will also learn how to perform CRUD operations with Elasticsearch using Elasticsearch Python and Java clients.

Chapter 4, Aggregations for Analytics, is all about the Elasticsearch aggregation framework for building analytics on data. It provides many fundamental as well complex examples of data analytics that can be built using a combination of full-text search, term-based search, and multi level aggregations. The user will master the aggregation module of Elasticsearch by learning a complete set of practical code examples that are covered using Python and Java clients.

Chapter 5, Data Looks Better on Maps: Master Geo-Spatiality, discusses geo-data concepts and covers the rich geo-search functionalities offered by Elasticsearch including how to create mappings for geo-points and geo-shapes data, indexing documents, geo-aggregations, and sorting data based on geo-distance. It includes code examples for the most widely used geo-queries in both Python and Java.

Chapter 6, Document Relationships in NoSQL World, focuses on the techniques offered by Elasticsearch to handle relational data using nested and parent-child relationships and creating a schema for the same using real-world examples. The reader will also learn how to create mappings based on relational data and write code for indexing and querying data using Python and Java APIs.

Chapter 7, Different Methods of Search and Bulk Operations, covers the different types of search and bulk APIs that every programmer needs to know while developing applications and working with large data sets. You will learn examples of bulk processing, multi-searches, and faster data reindexing using both Python and Java, which will help you throughout your journey with Elasticsearch.

Chapter 8, Controlling Relevancy, discusses the most important aspect of search engines—relevancy. It covers the powerful scoring capabilities available in Elasticsearch and practical examples that show how you can control the scoring process according to your needs.

Chapter 9, Cluster Scaling in Production Deployments, shows how to create Elasticsearch clusters and configure different types of nodes with the right resource allocations. It also focuses on cluster scalability using the best practices in production environment.

Chapter 10, Backups and Security, focuses on the different mechanisms of creating data backups of an Elasticsearch cluster and restoring them back into the same or an other cluster. A step-by-step guide to setting up NFS (Network File System) is also provided. Finally, you will learn about setting up Nginx to secure Elasticsearch and load balance requests.

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