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社区首页 >专栏 >23个最有用的Elasticseaerch检索技巧(下)

23个最有用的Elasticseaerch检索技巧(下)

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小旋锋
发布2019-01-21 17:38:35
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发布2019-01-21 17:38:35
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前言

本文主要介绍 Elasticsearch 23种最有用的检索技巧,提供了详尽的源码举例,并配有相应的Java API实现,是不可多得的 Elasticsearch 学习&实战资料

注:由于公众号推送每篇文章最多 5w 字,所以原文分为两篇分别推送,本文为第二篇 测试使用的ES版本为6.3.2

12、Term/Terms检索(指定字段检索)

上面1-11小节的例子是全文搜索的例子。 有时我们对结构化搜索更感兴趣,我们希望在其中找到完全匹配并返回结果

在下面的例子中,我们搜索 Manning Publications 发布的索引中的所有图书(借助 term和terms查询 )

代码语言:javascript
复制
GET bookdb_index/book/_search
{
  "query": {
    "term": {
      "publisher": {
        "value": "manning"
      }
    }
  },
  "_source" : ["title","publish_date","publisher"]
}

[Results]
  "hits": {
    "total": 3,
    "max_score": 0.35667494,
    "hits": [
      {
        "_index": "bookdb_index",
        "_type": "book",
        "_id": "2",
        "_score": 0.35667494,
        "_source": {
          "publisher": "manning",
          "title": "Taming Text: How to Find, Organize, and Manipulate It",
          "publish_date": "2013-01-24"
        }
      },
      {
        "_index": "bookdb_index",
        "_type": "book",
        "_id": "3",
        "_score": 0.35667494,
        "_source": {
          "publisher": "manning",
          "title": "Elasticsearch in Action",
          "publish_date": "2015-12-03"
        }
      },
      {
        "_index": "bookdb_index",
        "_type": "book",
        "_id": "4",
        "_score": 0.35667494,
        "_source": {
          "publisher": "manning",
          "title": "Solr in Action",
          "publish_date": "2014-04-05"
        }
      }
    ]
  }

Multiple terms可指定多个关键词进行检索

代码语言:javascript
复制
GET bookdb_index/book/_search
{
  "query": {
    "terms": {
      "publisher": ["oreilly", "manning"]
    }
  }
}
13、Term排序检索-(Term Query - Sorted)

Term查询和其他查询一样,轻松的实现排序。多级排序也是允许的

代码语言:javascript
复制
GET bookdb_index/book/_search
{
  "query": {
    "term": {
      "publisher": {
        "value": "manning"
      }
    }
  },
  "_source" : ["title","publish_date","publisher"],
  "sort": [{"publisher.keyword": { "order": "desc"}},
    {"title.keyword": {"order": "asc"}}]
}

[Results]
  "hits": {
    "total": 3,
    "max_score": null,
    "hits": [
      {
        "_index": "bookdb_index",
        "_type": "book",
        "_id": "3",
        "_score": null,
        "_source": {
          "publisher": "manning",
          "title": "Elasticsearch in Action",
          "publish_date": "2015-12-03"
        },
        "sort": [
          "manning",
          "Elasticsearch in Action"
        ]
      },
      {
        "_index": "bookdb_index",
        "_type": "book",
        "_id": "4",
        "_score": null,
        "_source": {
          "publisher": "manning",
          "title": "Solr in Action",
          "publish_date": "2014-04-05"
        },
        "sort": [
          "manning",
          "Solr in Action"
        ]
      },
      {
        "_index": "bookdb_index",
        "_type": "book",
        "_id": "2",
        "_score": null,
        "_source": {
          "publisher": "manning",
          "title": "Taming Text: How to Find, Organize, and Manipulate It",
          "publish_date": "2013-01-24"
        },
        "sort": [
          "manning",
          "Taming Text: How to Find, Organize, and Manipulate It"
        ]
      }
    ]
  }

注意:Elasticsearch 6.x 全文搜索用text类型的字段,排序用 number, date 或 keyword 等类型的字段

14、范围检索(Range query)

另一个结构化检索的例子是范围检索。下面的举例中,我们检索了2015年发布的书籍。

代码语言:javascript
复制
GET bookdb_index/book/_search
{
  "query": {
    "range": {
      "publish_date": {
        "gte": "2015-01-01",
        "lte": "2015-12-31"
      }
    }
  },
  "_source" : ["title","publish_date","publisher"]
}

[Results]
  "hits": {
    "total": 2,
    "max_score": 1,
    "hits": [
      {
        "_index": "bookdb_index",
        "_type": "book",
        "_id": "1",
        "_score": 1,
        "_source": {
          "publisher": "oreilly",
          "title": "Elasticsearch: The Definitive Guide",
          "publish_date": "2015-02-07"
        }
      },
      {
        "_index": "bookdb_index",
        "_type": "book",
        "_id": "3",
        "_score": 1,
        "_source": {
          "publisher": "manning",
          "title": "Elasticsearch in Action",
          "publish_date": "2015-12-03"
        }
      }
    ]
  }

注意:范围查询适用于日期,数字和字符串类型字段

15、过滤检索(Filtered query)

(5.0版本起已不再存在,不必关注)

过滤的查询允许您过滤查询的结果。 如下的例子,我们在标题或摘要中查询名为“Elasticsearch”的图书,但是我们希望将结果过滤到只有20个或更多评论的结果。

代码语言:javascript
复制
POST /bookdb_index/book/_search
{
    "query": {
        "filtered": {
            "query" : {
                "multi_match": {
                    "query": "elasticsearch",
                    "fields": ["title","summary"]
                }
            },
            "filter": {
                "range" : {
                    "num_reviews": {
                        "gte": 20
                    }
                }
            }
        }
    },
    "_source" : ["title","summary","publisher", "num_reviews"]
}


[Results]
"hits": [
      {
        "_index": "bookdb_index",
        "_type": "book",
        "_id": "1",
        "_score": 0.5955761,
        "_source": {
          "summary": "A distibuted real-time search and analytics engine",
          "publisher": "oreilly",
          "num_reviews": 20,
          "title": "Elasticsearch: The Definitive Guide"
        }
      }
    ]

注意:已过滤的查询不要求存在要过滤的查询。 如果没有指定查询,则运行 match_all 查询,基本上返回索引中的所有文档,然后对其进行过滤。 实际上,首先运行过滤器,减少需要查询的表面积。 此外,过滤器在第一次使用后被缓存,这使得它非常有效

更新: 已筛选的查询已推出的Elasticsearch 5.X版本中移除,有利于布尔查询。 这是与上面重写的使用bool查询相同的示例。 返回的结果是完全一样的。

代码语言:javascript
复制
GET bookdb_index/book/_search
{
  "query": {
    "bool": {
      "must": [
        {
          "multi_match": {
            "query": "elasticsearch",
            "fields": ["title","summary"]
          }
        }
      ],
      "filter": {
        "range": {
          "num_reviews": {
            "gte": 20
          }
        }
      }
    }
  },
  "_source" : ["title","summary","publisher", "num_reviews"]
}
16、多个过滤器检索(Multiple Filters)

(5.x不再支持,无需关注) 多个过滤器可以通过使用布尔过滤器进行组合。

在下一个示例中,过滤器确定返回的结果必须至少包含20个评论,不得在2015年之前发布,并且应该由oreilly发布

代码语言:javascript
复制
POST /bookdb_index/book/_search
{
    "query": {
        "filtered": {
            "query" : {
                "multi_match": {
                    "query": "elasticsearch",
                    "fields": ["title","summary"]
                }
            },
            "filter": {
                "bool": {
                    "must": {
                        "range" : { "num_reviews": { "gte": 20 } }
                    },
                    "must_not": {
                        "range" : { "publish_date": { "lte": "2014-12-31" } }
                    },
                    "should": {
                        "term": { "publisher": "oreilly" }
                    }
                }
            }
        }
    },
    "_source" : ["title","summary","publisher", "num_reviews", "publish_date"]
}


[Results]
"hits": [
      {
        "_index": "bookdb_index",
        "_type": "book",
        "_id": "1",
        "_score": 0.5955761,
        "_source": {
          "summary": "A distibuted real-time search and analytics engine",
          "publisher": "oreilly",
          "num_reviews": 20,
          "title": "Elasticsearch: The Definitive Guide",
          "publish_date": "2015-02-07"
        }
      }
    ]
17、 Function 得分:Field值因子( Function Score: Field Value Factor)

可能有一种情况,您想要将文档中特定字段的值纳入相关性分数的计算。 这在您希望基于其受欢迎程度提升文档的相关性的情况下是有代表性的场景

在我们的例子中,我们希望增加更受欢迎的书籍(按评论数量判断)。 这可以使用field_value_factor函数得分

代码语言:javascript
复制
GET bookdb_index/book/_search
{
  "query": {
    "function_score": {
      "query": {
        "multi_match": {
          "query": "search engine",
          "fields": ["title","summary"]
        }
      },
      "field_value_factor": {
        "field": "num_reviews",
        "modifier": "log1p",
        "factor": 2
      }
    }
  },
  "_source": ["title", "summary", "publish_date", "num_reviews"]
}

[Results]
    "hits": [
      {
        "_index": "bookdb_index",
        "_type": "book",
        "_id": "1",
        "_score": 1.5694137,
        "_source": {
          "summary": "A distibuted real-time search and analytics engine",
          "num_reviews": 20,
          "title": "Elasticsearch: The Definitive Guide",
          "publish_date": "2015-02-07"
        }
      },
      {
        "_index": "bookdb_index",
        "_type": "book",
        "_id": "4",
        "_score": 1.4725765,
        "_source": {
          "summary": "Comprehensive guide to implementing a scalable search engine using Apache Solr",
          "num_reviews": 23,
          "title": "Solr in Action",
          "publish_date": "2014-04-05"
        }
      },
      {
        "_index": "bookdb_index",
        "_type": "book",
        "_id": "3",
        "_score": 0.14181662,
        "_source": {
          "summary": "build scalable search applications using Elasticsearch without having to do complex low-level programming or understand advanced data science algorithms",
          "num_reviews": 18,
          "title": "Elasticsearch in Action",
          "publish_date": "2015-12-03"
        }
      },
      {
        "_index": "bookdb_index",
        "_type": "book",
        "_id": "2",
        "_score": 0.13297246,
        "_source": {
          "summary": "organize text using approaches such as full-text search, proper name recognition, clustering, tagging, information extraction, and summarization",
          "num_reviews": 12,
          "title": "Taming Text: How to Find, Organize, and Manipulate It",
          "publish_date": "2013-01-24"
        }
      }
    ]
  }

注1:我们可以运行一个常规的multi_match查询,并按num_reviews字段排序,但是我们失去了相关性得分的好处。 注2:有许多附加参数可以调整对原始相关性分数 (如“ modifier ”,“ factor ”,“boost_mode”等)的增强效果的程度。 详见 Elasticsearch guide.

18、 Function 得分:衰减函数( Function Score: Decay Functions )

假设,我们不是想通过一个字段的值逐渐增加得分,以获取理想的结果。 举例:价格范围、数字字段范围、日期范围。 在我们的例子中,我们正在搜索2014年6月左右出版的“ search engines ”的书籍。

代码语言:javascript
复制
GET bookdb_index/book/_search
{
  "query": {
    "function_score": {
      "query": {
        "multi_match": {
          "query": "search engine",
          "fields": ["title", "summary"]
        }
      },
      "functions": [
        {
          "exp": {
            "publish_date": {
              "origin": "2014-06-15",
              "scale": "30d",
              "offset": "7d"
            }
          }
        }
      ],
      "boost_mode": "replace"
    }
  },
  "_source": ["title", "summary", "publish_date", "num_reviews"]
}

[Results]
  "hits": {
    "total": 4,
    "max_score": 0.22793062,
    "hits": [
      {
        "_index": "bookdb_index",
        "_type": "book",
        "_id": "4",
        "_score": 0.22793062,
        "_source": {
          "summary": "Comprehensive guide to implementing a scalable search engine using Apache Solr",
          "num_reviews": 23,
          "title": "Solr in Action",
          "publish_date": "2014-04-05"
        }
      },
      {
        "_index": "bookdb_index",
        "_type": "book",
        "_id": "1",
        "_score": 0.0049215667,
        "_source": {
          "summary": "A distibuted real-time search and analytics engine",
          "num_reviews": 20,
          "title": "Elasticsearch: The Definitive Guide",
          "publish_date": "2015-02-07"
        }
      },
      {
        "_index": "bookdb_index",
        "_type": "book",
        "_id": "2",
        "_score": 0.000009612435,
        "_source": {
          "summary": "organize text using approaches such as full-text search, proper name recognition, clustering, tagging, information extraction, and summarization",
          "num_reviews": 12,
          "title": "Taming Text: How to Find, Organize, and Manipulate It",
          "publish_date": "2013-01-24"
        }
      },
      {
        "_index": "bookdb_index",
        "_type": "book",
        "_id": "3",
        "_score": 0.0000049185574,
        "_source": {
          "summary": "build scalable search applications using Elasticsearch without having to do complex low-level programming or understand advanced data science algorithms",
          "num_reviews": 18,
          "title": "Elasticsearch in Action",
          "publish_date": "2015-12-03"
        }
      }
    ]
  }
19、Function得分:脚本得分( Function Score: Script Scoring )

在内置计分功能不符合您需求的情况下,可以选择指定用于评分的Groovy脚本

在我们的示例中,我们要指定一个考虑到publish_date的脚本,然后再决定考虑多少评论。 较新的书籍可能没有这么多的评论,所以他们不应该为此付出“代价”

得分脚本如下所示:

代码语言:javascript
复制
publish_date = doc['publish_date'].value
num_reviews = doc['num_reviews'].value

if (publish_date > Date.parse('yyyy-MM-dd', threshold).getTime()) {
  my_score = Math.log(2.5 + num_reviews)
} else {
  my_score = Math.log(1 + num_reviews)
}
return my_score

要动态使用评分脚本,我们使用script_score参数

代码语言:javascript
复制
GET /bookdb_index/book/_search
{
  "query": {
    "function_score": {
      "query": {
        "multi_match": {
          "query": "search engine",
          "fields": ["title","summary"]
        }
      },
      "functions": [
        {
          "script_score": {
            "script": {
              "params": {
                "threshold": "2015-07-30"
              },  
              "lang": "groovy", 
              "source": "publish_date = doc['publish_date'].value; num_reviews = doc['num_reviews'].value; if (publish_date > Date.parse('yyyy-MM-dd', threshold).getTime()) { return log(2.5 + num_reviews) }; return log(1 + num_reviews);"
            }
          }
        }
      ]
    }
  },
  "_source": ["title","summary","publish_date", "num_reviews"]
}

注1:要使用动态脚本,必须为config / elasticsearch.yml文件中的Elasticsearch实例启用它。 也可以使用已经存储在Elasticsearch服务器上的脚本。 查看 Elasticsearch reference docs 以获取更多信息。 注2: JSON不能包含嵌入的换行符,因此分号用于分隔语句。 原文作者: by Tim Ojo Aug. 05, 16 · Big Data Zone 原文地址:https://dzone.com/articles/23-useful-elasticsearch-example-queries 注意:ES6.3 怎样启用 groovy 脚本?配置未成功 script.allowed_types: inline & script.allowed_contexts: search, update

Java API 实现

Java API 实现上面的查询,代码见 https://github.com/whirlys/elastic-example/tree/master/UsefullESSearchSkill

注:Java API 实现仍在测试中,尽快上传


更多内容请访问我的个人博客:http://laijianfeng.org 参考文章: 铭毅天下:[译]你必须知道的23个最有用的Elasticseaerch检索技巧 英文原文:23 Useful Elasticsearch Example Queries

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目录
  • 前言
    • 12、Term/Terms检索(指定字段检索)
      • 13、Term排序检索-(Term Query - Sorted)
        • 14、范围检索(Range query)
          • 15、过滤检索(Filtered query)
            • 16、多个过滤器检索(Multiple Filters)
              • 17、 Function 得分:Field值因子( Function Score: Field Value Factor)
                • 18、 Function 得分:衰减函数( Function Score: Decay Functions )
                  • 19、Function得分:脚本得分( Function Score: Script Scoring )
                  • Java API 实现
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