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所在平台: Udemy |
课程主页: https://www.udemy.com/course/elasticsearch-as-you-have-never-known-it-before/
课程评论：没有评论
ElasticSearch 鲜为人知的一面：从入门到生产应用 本课程将带您深入探索ElasticSearch的强大功能，超越其作为全文本搜索引擎或ELK栈一部分的常见认知。您将学习如何利用ElasticSearch构建极其先进的搜索引擎和推荐模块，这些系统在效果上可能超越机器学习技术，同时又更为简洁。课程还会重点展示ElasticSearch在地理位置搜索过滤和聚合方面的强大能力。 本课程内容丰富，既适合初学者，也能帮助有经验的ElasticSearch使用者拓展实践知识，特别是对于计划近期构建推荐系统或高级搜索机制的人员。 课程分为五个模块： * **模块一：ElasticSearch基础（新手必看，有经验者可选跳过）** * 环境安装与配置（Docker） * 数据组织方式 * Mapping的重要性 * Tokenizer与Analyzer的解析 * **模块二：构建高级搜索系统** * 以简化版Booking.com为例，分步实践 * 深入讲解ElasticSearch的地理位置（Geo）能力 * **模块三：构建推荐模块** * 介绍当前推荐系统的主流方法及其优缺点 * 以虚拟房屋清洁市场为例，构建实际的推荐机制 * **模块四：语言库集成与微服务实践** * 演示PHP、Python、Java等语言库的集成 * 构建实际微服务，运用Builder模式、Filter模式等最佳编程实践和设计模式 * 探讨问题调试 * **模块五：ElasticSearch生产环境部署** * 高可用集群设置 * 分片（shard）大小与存储需求估算 * 高效索引海量文档 * 零停机再索引（reindexing）技巧
Everybody knows ElasticSearch as a popular full-text search engine or as part of ELK but I am going to show you ElasticSearch from the side you have never known before. I want to show you that with ElasticSearch you can build very advanced search engines or even recommendation modules that can be much more effective and together with that, much more simpler than similar systems built on top of machine learning technologies. I want to show the real geo power of ElasticSearch for building advanced search filters and aggregations. This course is built in such a way it would be useful both: for complete beginners and for people who are working with ElasticSearch but would like to extend their practice knowledge. It would be especially useful for those who are going to build some recommendation systems or advanced search mechanisms in the near future. The course consists of 5 modules. First module is aimed for beginners and can be skipped by people who are already working with ElasticSearch. Here I will tell you about basics: how to install and configure the environment using Docker, how data at ElasticSearch are organized, why mapping is so important and what all that mess around tokenizers and analyzers means. In the second section I will show how to build an advanced search system step by step on a real example of a simplified booking com version. We will touch the topics about ES geopower here. Next course section is devoted to the recommendation module. Here we will speak about recommendation systems in general - about pros and cons of today's methods. And again together we will build a real system using ElasticSearch. We will create a recommendation mechanism for virtual example of cleaning houses' marketplace. In the fourth section I will show real examples using php, python and Java libraries for integration with ElasticSearch. And again we will create real microservice applying best programming practices and interesting design patterns like builder pattern or filter pattern. I will touch here also the question of debugging the possible problems. The fifth and the last part is about using ElasticSearch for production. Here I will share with you my knowledge on how to set up a highly available cluster, how to calculate shard size and storage requirements, how to index millions of documents in the most efficient way and even how to preserve zero downtime at reindexing
