Elasticsearch全方位指南:入门与核心概念

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"《Packt Elasticsearch A Complete Guide B01MTFBKWY.pdf》是一部全面介绍Elasticsearch的指南,涵盖了从基础到高级的各种主题,旨在帮助读者理解并掌握Elasticsearch的核心概念和技术。" 在本书中,作者首先介绍了Elasticsearch的基本概念,包括其主要特性。Elasticsearch是一款开源的全文搜索引擎,它基于分布式、RESTful风格的搜索和分析引擎,设计用于实时的全文检索,同时具备高可扩展性和高可用性。 关于REST(Representational State Transfer)和JSON(JavaScript Object Notation),书中阐述了它们在Elasticsearch中的作用。REST是一种软件架构风格,常用于构建Web服务,而JSON则是一种轻量级的数据交换格式,易于人阅读和编写,同时也易于机器解析和生成,是Elasticsearch中数据交互的主要方式。 接着,书中详细讲解了Elasticsearch与传统关系型数据库的结构差异,帮助读者理解Elasticsearch的分布式文档存储模型。此外,还提供了在Ubuntu和CentOS上安装Elasticsearch的步骤,以及安装后的目录布局和基本参数配置。 扩展集群是Elasticsearch的一个重要特性,书中提到了如何添加新节点到现有的Elasticsearch集群中。同时,还介绍了安装和管理Elasticsearch插件的方法,如检查已安装的插件,以及安装用于可视化和交互的Head插件和Sense工具。 在实际操作部分,读者将学习如何在Elasticsearch中创建索引、索引文档,了解基本的CRUD(Create、Read、Update、Delete)操作,这些都是进行数据管理和搜索的基础。 这本书提供了一个全面的学习路径,无论你是初学者还是希望深入理解Elasticsearch的开发者,都能从中获益。通过这本书,你可以了解到Elasticsearch的全貌,从安装配置到实际应用,提升你在搜索和数据分析领域的技能。
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End-to-end Search and Analytics About This Book Solve your data analytics problems with the Elastic Stack Improve your user search experience with Elasticsearch and develop your own Elasticsearch plugins Design your index, configure it, and distribute it — you'll also learn how it works Who This Book Is For This course is for anyone who wants to build efficient search and analytics applications. Some development experience is expected. What You Will Learn Install and configure Elasticsearch, Logstash, and Kibana Write CRUDE operations and other search functionalities using the Elasticsearch Python and Java Clients Build analytics using aggregations Set up and scale Elasticsearch clusters using best practices Master document relationships and geospatial data Build your own data pipeline using Elastic Stack Choose the appropriate amount of shards and replicas for your deployment Become familiar with the Elasticsearch APIs In Detail Elasticsearch is a modern, fast, distributed, scalable, fault tolerant, open source search and analytics engine. It provides a new level of control over how you can index and search even huge sets of data. This course will take you from the basics of Elasticsearch to using Elasticsearch in the Elastic Stack and in production. You'll start with the very basics: Elasticsearch terminology, installation, and configuring Elasticsearch. After this, you'll take a look at analytics and indexing, search, and querying. You'll learn how to create maps and visualizations. You'll also be briefed on cluster scaling, search and bulk operations, backups, and security. Then you'll be ready to get into Elasticsearch's internal functionalities including caches, Apache Lucene library, and its monitoring capabilities. You'll learn about the practical usage of Elasticsearch configuration parameters and how to use the monitoring API. You'll discover how to improve the user search experience, index distribution, segment statistics, merging, and more. Once you have mastered this, you'll dive into end-to-end visualize-analyze-log techniques with Elastic Stack (also known as the ELK stack). You'll explore Elasticsearch, Logstash, and Kibana and see how to make them work together to build fresh insights and business metrics out of data. You'll be able to use Elasticsearch with other de facto components in order to get the most out of Elasticsearch. By the end of this course, you'll have developed a full-fledged data pipeline. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: Elasticsearch Essentials Mastering Elasticsearch, Second Edition Learning ELK Stack Style and approach This course aims to create a smooth learning path that will teach you how to effectively use Elasticsearch with other de facto components and get the most out of Elasticsearch. Through this comprehensive course, you'll learn the basics of Elasticsearch and progress to using Elasticsearch in the Elastic stack and in production. Table of Contents Chapter 1. Module 1 Chapter 2. Understanding Document Analysis and Creating Mappings Chapter 3. Putting Elasticsearch into Action Chapter 4. Aggregations for Analytics Chapter 5. Data Looks Better on Maps: Master Geo-Spatiality Chapter 6. Document Relationships in NoSQL World Chapter 7. Different Methods of Search and Bulk Operations Chapter 8. Controlling Relevancy Chapter 9. Cluster Scaling in Production Deployments Chapter 10. Backups and Security