官术网_书友最值得收藏!

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.

主站蜘蛛池模板: 德江县| 连江县| 迁安市| 曲水县| 富源县| 澄城县| 璧山县| 尤溪县| 宜良县| 新竹市| 丹寨县| 泰和县| 澎湖县| 张家口市| 颍上县| 建水县| 庆城县| 宁城县| 信宜市| 瓮安县| 囊谦县| 霍林郭勒市| 赫章县| 洛南县| 乌恰县| 虹口区| 兖州市| 绿春县| 浦北县| 石阡县| 广东省| 治县。| 丰城市| 台东县| 西昌市| 温州市| 临西县| 南木林县| 汉寿县| 合水县| 梁平县|