白话Elasticsearch11-深度探秘搜索技术之基于tie_breaker参数优化dis_max搜索效果

本文涉及的产品
Elasticsearch Serverless通用抵扣包,测试体验金 200元
简介: 白话Elasticsearch11-深度探秘搜索技术之基于tie_breaker参数优化dis_max搜索效果

20190806092132811.jpg


概述


继续跟中华石杉老师学习ES,第十一篇

课程地址: https://www.roncoo.com/view/55


官方文档


https://www.elastic.co/guide/en/elasticsearch/guide/current/_tuning_best_fields_queries.html


https://www.elastic.co/guide/en/elasticsearch/reference/7.2/query-dsl-dis-max-query.html

2019071300245974.png



例子


数据同 上篇博文 构造索引的DSL

这次我们使用dis_max查询 java beginner , DSL如下

GET /forum/article/_search
{
  "query": {
    "dis_max": {
      "queries": [
        {
          "match": {
            "title": "java beginner"
          }
        },
        {
          "match": {
            "content": "java beginner"
          }
        }
      ]
    }
  }
}


返回

{
  "took": 2,
  "timed_out": false,
  "_shards": {
    "total": 1,
    "successful": 1,
    "skipped": 0,
    "failed": 0
  },
  "hits": {
    "total": 5,
    "max_score": 1.0341108,
    "hits": [
      {
        "_index": "forum",
        "_type": "article",
        "_id": "3",
        "_score": 1.0341108,
        "_source": {
          "articleID": "JODL-X-1937-#pV7",
          "userID": 2,
          "hidden": false,
          "postDate": "2017-01-01",
          "tag": [
            "hadoop"
          ],
          "tag_cnt": 1,
          "view_cnt": 100,
          "title": "this is elasticsearch blog",
          "content": "i am only an elasticsearch beginner"
        }
      },
      {
        "_index": "forum",
        "_type": "article",
        "_id": "2",
        "_score": 0.93952733,
        "_source": {
          "articleID": "KDKE-B-9947-#kL5",
          "userID": 1,
          "hidden": false,
          "postDate": "2017-01-02",
          "tag": [
            "java"
          ],
          "tag_cnt": 1,
          "view_cnt": 50,
          "title": "this is java blog",
          "content": "i think java is the best programming language"
        }
      },
      {
        "_index": "forum",
        "_type": "article",
        "_id": "4",
        "_score": 0.79423964,
        "_source": {
          "articleID": "QQPX-R-3956-#aD8",
          "userID": 2,
          "hidden": true,
          "postDate": "2017-01-02",
          "tag": [
            "java",
            "elasticsearch"
          ],
          "tag_cnt": 2,
          "view_cnt": 80,
          "title": "this is java, elasticsearch, hadoop blog",
          "content": "elasticsearch and hadoop are all very good solution, i am a beginner"
        }
      },
      {
        "_index": "forum",
        "_type": "article",
        "_id": "5",
        "_score": 0.7116974,
        "_source": {
          "articleID": "DHJK-B-1395-#Ky5",
          "userID": 3,
          "hidden": false,
          "postDate": "2019-05-01",
          "tag": [
            "elasticsearch"
          ],
          "tag_cnt": 1,
          "view_cnt": 10,
          "title": "this is spark blog",
          "content": "spark is best big data solution based on scala ,an programming language similar to java"
        }
      },
      {
        "_index": "forum",
        "_type": "article",
        "_id": "1",
        "_score": 0.4889865,
        "_source": {
          "articleID": "XHDK-A-1293-#fJ3",
          "userID": 1,
          "hidden": false,
          "postDate": "2017-01-01",
          "tag": [
            "java",
            "hadoop"
          ],
          "tag_cnt": 2,
          "view_cnt": 30,
          "title": "this is java and elasticsearch blog",
          "content": "i like to write best elasticsearch article"
        }
      }
    ]
  }
}

20190713003518308.png


不知道为啥id=3的相关度是最高的… 如果有知道的,烦请不吝赐教。



20190713003042109.png

dis_max只取某一个query最大的分数,完全不考虑其他query的分数


tie_breaker

使用tie_breaker将其他query的分数也考虑进去


tie_breaker参数的意义,在于说,将其他query的分数,乘以tie_breaker,然后综合与最高分数的那个query的分数,综合在一起进行计算,除了取最高分以外,还会考虑其他的query的分数。

tie_breaker的值,在0~1之间,是个小数。


GET /forum/article/_search
{
  "query": {
    "dis_max": {
      "queries": [
        {
          "match": {
            "title": "java beginner"
          }
        },
        {
          "match": {
            "content": "java beginner"
          }
        }
      ],
      "tie_breaker": 0.7
    }
  }
}

返回结果

{
  "took": 2,
  "timed_out": false,
  "_shards": {
    "total": 1,
    "successful": 1,
    "skipped": 0,
    "failed": 0
  },
  "hits": {
    "total": 5,
    "max_score": 1.344432,
    "hits": [
      {
        "_index": "forum",
        "_type": "article",
        "_id": "2",
        "_score": 1.344432,
        "_source": {
          "articleID": "KDKE-B-9947-#kL5",
          "userID": 1,
          "hidden": false,
          "postDate": "2017-01-02",
          "tag": [
            "java"
          ],
          "tag_cnt": 1,
          "view_cnt": 50,
          "title": "this is java blog",
          "content": "i think java is the best programming language"
        }
      },
      {
        "_index": "forum",
        "_type": "article",
        "_id": "4",
        "_score": 1.1365302,
        "_source": {
          "articleID": "QQPX-R-3956-#aD8",
          "userID": 2,
          "hidden": true,
          "postDate": "2017-01-02",
          "tag": [
            "java",
            "elasticsearch"
          ],
          "tag_cnt": 2,
          "view_cnt": 80,
          "title": "this is java, elasticsearch, hadoop blog",
          "content": "elasticsearch and hadoop are all very good solution, i am a beginner"
        }
      },
      {
        "_index": "forum",
        "_type": "article",
        "_id": "3",
        "_score": 1.0341108,
        "_source": {
          "articleID": "JODL-X-1937-#pV7",
          "userID": 2,
          "hidden": false,
          "postDate": "2017-01-01",
          "tag": [
            "hadoop"
          ],
          "tag_cnt": 1,
          "view_cnt": 100,
          "title": "this is elasticsearch blog",
          "content": "i am only an elasticsearch beginner"
        }
      },
      {
        "_index": "forum",
        "_type": "article",
        "_id": "5",
        "_score": 0.7116974,
        "_source": {
          "articleID": "DHJK-B-1395-#Ky5",
          "userID": 3,
          "hidden": false,
          "postDate": "2019-05-01",
          "tag": [
            "elasticsearch"
          ],
          "tag_cnt": 1,
          "view_cnt": 10,
          "title": "this is spark blog",
          "content": "spark is best big data solution based on scala ,an programming language similar to java"
        }
      },
      {
        "_index": "forum",
        "_type": "article",
        "_id": "1",
        "_score": 0.4889865,
        "_source": {
          "articleID": "XHDK-A-1293-#fJ3",
          "userID": 1,
          "hidden": false,
          "postDate": "2017-01-01",
          "tag": [
            "java",
            "hadoop"
          ],
          "tag_cnt": 2,
          "view_cnt": 30,
          "title": "this is java and elasticsearch blog",
          "content": "i like to write best elasticsearch article"
        }
      }
    ]
  }
}

20190713003409329.png


相关实践学习
以电商场景为例搭建AI语义搜索应用
本实验旨在通过阿里云Elasticsearch结合阿里云搜索开发工作台AI模型服务,构建一个高效、精准的语义搜索系统,模拟电商场景,深入理解AI搜索技术原理并掌握其实现过程。
ElasticSearch 最新快速入门教程
本课程由千锋教育提供。全文搜索的需求非常大。而开源的解决办法Elasricsearch(Elastic)就是一个非常好的工具。目前是全文搜索引擎的首选。本系列教程由浅入深讲解了在CentOS7系统下如何搭建ElasticSearch,如何使用Kibana实现各种方式的搜索并详细分析了搜索的原理,最后讲解了在Java应用中如何集成ElasticSearch并实现搜索。  
相关文章
|
1月前
|
缓存 监控 前端开发
顺企网 API 开发实战:搜索 / 详情接口从 0 到 1 落地(附 Elasticsearch 优化 + 错误速查)
企业API开发常陷参数、缓存、错误处理三大坑?本指南拆解顺企网双接口全流程,涵盖搜索优化、签名验证、限流应对,附可复用代码与错误速查表,助你2小时高效搞定开发,提升响应速度与稳定性。
|
1月前
|
存储 Linux iOS开发
Elasticsearch Enterprise 9.1.5 发布 - 分布式搜索和分析引擎
Elasticsearch Enterprise 9.1.5 (macOS, Linux, Windows) - 分布式搜索和分析引擎
235 0
|
2月前
|
JSON 监控 Java
Elasticsearch 分布式搜索与分析引擎技术详解与实践指南
本文档全面介绍 Elasticsearch 分布式搜索与分析引擎的核心概念、架构设计和实践应用。作为基于 Lucene 的分布式搜索引擎,Elasticsearch 提供了近实时的搜索能力、强大的数据分析功能和可扩展的分布式架构。本文将深入探讨其索引机制、查询 DSL、集群管理、性能优化以及与各种应用场景的集成,帮助开发者构建高性能的搜索和分析系统。
246 0
|
6月前
|
存储 安全 Linux
Elasticsearch Enterprise 9.0 发布 - 分布式搜索和分析引擎
Elasticsearch Enterprise 9.0 (macOS, Linux, Windows) - 分布式搜索和分析引擎
296 0
|
6月前
|
JSON 安全 数据可视化
Elasticsearch(es)在Windows系统上的安装与部署(含Kibana)
Kibana 是 Elastic Stack(原 ELK Stack)中的核心数据可视化工具,主要与 Elasticsearch 配合使用,提供强大的数据探索、分析和展示功能。elasticsearch安装在windows上一般是zip文件,解压到对应目录。文件,elasticsearch8.x以上版本是自动开启安全认证的。kibana安装在windows上一般是zip文件,解压到对应目录。elasticsearch的默认端口是9200,访问。默认用户是elastic,密码需要重置。
3106 0
|
7月前
|
安全 Java Linux
Linux安装Elasticsearch详细教程
Linux安装Elasticsearch详细教程
1197 1
|
存储 安全 数据管理
如何在 Rocky Linux 8 上安装和配置 Elasticsearch
本文详细介绍了在 Rocky Linux 8 上安装和配置 Elasticsearch 的步骤,包括添加仓库、安装 Elasticsearch、配置文件修改、设置内存和文件描述符、启动和验证 Elasticsearch,以及常见问题的解决方法。通过这些步骤,你可以快速搭建起这个强大的分布式搜索和分析引擎。
453 5
|
NoSQL 关系型数据库 Redis
mall在linux环境下的部署(基于Docker容器),Docker安装mysql、redis、nginx、rabbitmq、elasticsearch、logstash、kibana、mongo
mall在linux环境下的部署(基于Docker容器),docker安装mysql、redis、nginx、rabbitmq、elasticsearch、logstash、kibana、mongodb、minio详细教程,拉取镜像、运行容器
mall在linux环境下的部署(基于Docker容器),Docker安装mysql、redis、nginx、rabbitmq、elasticsearch、logstash、kibana、mongo
|
存储 JSON Java
elasticsearch学习一:了解 ES,版本之间的对应。安装elasticsearch,kibana,head插件、elasticsearch-ik分词器。
这篇文章是关于Elasticsearch的学习指南,包括了解Elasticsearch、版本对应、安装运行Elasticsearch和Kibana、安装head插件和elasticsearch-ik分词器的步骤。
1199 0
elasticsearch学习一:了解 ES,版本之间的对应。安装elasticsearch,kibana,head插件、elasticsearch-ik分词器。
|
数据可视化 Docker 容器
一文教会你如何通过Docker安装elasticsearch和kibana 【详细过程+图解】
这篇文章提供了通过Docker安装Elasticsearch和Kibana的详细过程和图解,包括下载镜像、创建和启动容器、处理可能遇到的启动失败情况(如权限不足和配置文件错误)、测试Elasticsearch和Kibana的连接,以及解决空间不足的问题。文章还特别指出了配置文件中空格的重要性以及环境变量中字母大小写的问题。
一文教会你如何通过Docker安装elasticsearch和kibana 【详细过程+图解】

热门文章

最新文章