整理一篇常用的CRUD查询语句,之前这篇文件是在17年左右发表的,从英文翻译过来,现在采用7.x 版本进行实验,弃用的功能或者参数,我这边会进行更新,一起来学习吧。

为了演示不同类型的 ElasticSearch 的查询,我们将使用书文档信息的集合(有以下字段:title(标题), authors(作者), summary(摘要), publish_date(发布日期)和 num_reviews(浏览数))。

在这之前,首先我们应该先创建一个新的索引(index),并批量导入一些文档:

创建索引:

PUT /bookdb_index
{ "settings": { "number_of_shards": 1 }}

批量上传文档:

注意:现在7.x 已经启用types 类型了,对应的操作语句也要修改下,POST /bookdb_index/book/_bulk换成POST /bookdb_index/_bulk ,然后进行操作。

POST /bookdb_index/_bulk
{ "index": { "_id": 1 }}
{ "title": "Elasticsearch: The Definitive Guide", "authors": ["clinton gormley", "zachary tong"], "summary" : "A distibuted real-time search and analytics engine", "publish_date" : "2015-02-07", "num_reviews": 20, "publisher": "oreilly" }
{ "index": { "_id": 2 }}
{ "title": "Taming Text: How to Find, Organize, and Manipulate It", "authors": ["grant ingersoll", "thomas morton", "drew farris"], "summary" : "organize text using approaches such as full-text search, proper name recognition, clustering, tagging, information extraction, and summarization", "publish_date" : "2013-01-24", "num_reviews": 12, "publisher": "manning" }
{ "index": { "_id": 3 }}
{ "title": "Elasticsearch in Action", "authors": ["radu gheorge", "matthew lee hinman", "roy russo"], "summary" : "build scalable search applications using Elasticsearch without having to do complex low-level programming or understand advanced data science algorithms", "publish_date" : "2015-12-03", "num_reviews": 18, "publisher": "manning" }
{ "index": { "_id": 4 }}
{ "title": "Solr in Action", "authors": ["trey grainger", "timothy potter"], "summary" : "Comprehensive guide to implementing a scalable search engine using Apache Solr", "publish_date" : "2014-04-05", "num_reviews": 23, "publisher": "manning" }

例子:

1. 基本的匹配(Query)查询

有两种方式来执行一个全文匹配查询:

  • 使用 Search Lite API,它从 url 中读取所有的查询参数
  • 使用完整 JSON 作为请求体,这样你可以使用完整的 Elasticsearch DSL

下面是一个基本的匹配查询,查询任一字段包含 Guide 的记录

GET /bookdb_index/_search?q=guide

[Results]
"hits": [
{
"_index": "bookdb_index",
"_type": "book",
"_id": "1",
"_score": 0.28168046,
"_source": {
"title": "Elasticsearch: The Definitive Guide",
"authors": ["clinton gormley", "zachary tong"],
"summary": "A distibuted real-time search and analytics engine",
"publish_date": "2015-02-07",
"num_reviews": 20,
"publisher": "manning"
}
},
{
"_index": "bookdb_index",
"_type": "book",
"_id": "4",
"_score": 0.24144039,
"_source": {
"title": "Solr in Action",
"authors": ["trey grainger", "timothy potter"],
"summary": "Comprehensive guide to implementing a scalable search engine using Apache Solr",
"publish_date": "2014-04-05",
"num_reviews": 23,
"publisher": "manning"
}
}
]

下面是完整 Search Profiler版本的查询,生成相同的内容:

{
"query": {
"multi_match" : {
"query" : "guide",
"fields" : [ "*" ]
}
}
}

multi_matchmatch 的作为在多个字段运行相同操作的一个速记法。fields 属性用来指定查询针对的字段,*代表所有字段,同时也可以使用单个字段进行查询,用逗号分隔开就可以。

在这个例子中,我们想要对文档的所有字段进行匹配。两个 API 都允许你指定要查询的字段。例如,查询 title 字段中包含 in Action 的书:

GET /bookdb_index/_search?q=title:in action

[Results]
"hits": [
{
"_index": "bookdb_index",
"_type": "book",
"_id": "4",
"_score": 0.6259885,
"_source": {
"title": "Solr in Action",
"authors": [
"trey grainger",
"timothy potter"
],
"summary": "Comprehensive guide to implementing a scalable search engine using Apache Solr",
"publish_date": "2014-04-05",
"num_reviews": 23,
"publisher": "manning"
}
},
{
"_index": "bookdb_index",
"_type": "book",
"_id": "3",
"_score": 0.5975345,
"_source": {
"title": "Elasticsearch in Action",
"authors": [
"radu gheorge",
"matthew lee hinman",
"roy russo"
],
"summary": "build scalable search applications using Elasticsearch without having to do complex low-level programming or understand advanced data science algorithms",
"publish_date": "2015-12-03",
"num_reviews": 18,
"publisher": "manning"
}
}
]

然而, 完整的 DSL 给予你灵活创建更复杂查询和指定返回结果的能力(后面,我们会一一阐述)。在下面例子中,我们指定 size 限定返回的结果条数,from 指定起始位子,_source 指定要返回的字段,以及语法高亮

POST /bookdb_index/_search
{
"query": {
"match" : {
"title" : "in action"
}
},
"size": 2,
"from": 0,
"_source": [ "title", "summary", "publish_date" ],
"highlight": {
"fields" : {
"title" : {}
}
}
} [Results]
"hits": {
"total": 2,
"max_score": 0.9105287,
"hits": [
{
"_index": "bookdb_index",
"_type": "book",
"_id": "3",
"_score": 0.9105287,
"_source": {
"summary": "build scalable search applications using Elasticsearch without having to do complex low-level programming or understand advanced data science algorithms",
"title": "Elasticsearch in Action",
"publish_date": "2015-12-03"
},
"highlight": {
"title": [
"Elasticsearch <em>in</em> <em>Action</em>"
]
}
},
{
"_index": "bookdb_index",
"_type": "book",
"_id": "4",
"_score": 0.9105287,
"_source": {
"summary": "Comprehensive guide to implementing a scalable search engine using Apache Solr",
"title": "Solr in Action",
"publish_date": "2014-04-05"
},
"highlight": {
"title": [
"Solr <em>in</em> <em>Action</em>"
]
}
}
]
}

注意:对于多个词查询,match 允许指定是否使用 and 操作符来取代默认的 or 操作符。你还可以指定 mininum_should_match 选项来调整返回结果的相关程度。具体看后面的例子。

2. 多字段(Multi-filed)查询

正如我们已经看到来的,为了根据多个字段检索(e.g. 在 titlesummary 字段都是相同的查询字符串的结果),你可以使用 multi_match 语句

POST /bookdb_index/_search
{
"query": {
"multi_match" : {
"query" : "elasticsearch guide",
"fields": ["title", "summary"]
}
}
} [Results]
"hits": {
"total": 3,
"max_score": 0.9448582,
"hits": [
{
"_index": "bookdb_index",
"_type": "book",
"_id": "1",
"_score": 0.9448582,
"_source": {
"title": "Elasticsearch: The Definitive Guide",
"authors": [
"clinton gormley",
"zachary tong"
],
"summary": "A distibuted real-time search and analytics engine",
"publish_date": "2015-02-07",
"num_reviews": 20,
"publisher": "manning"
}
},
{
"_index": "bookdb_index",
"_type": "book",
"_id": "3",
"_score": 0.17312013,
"_source": {
"title": "Elasticsearch in Action",
"authors": [
"radu gheorge",
"matthew lee hinman",
"roy russo"
],
"summary": "build scalable search applications using Elasticsearch without having to do complex low-level programming or understand advanced data science algorithms",
"publish_date": "2015-12-03",
"num_reviews": 18,
"publisher": "manning"
}
},
{
"_index": "bookdb_index",
"_type": "book",
"_id": "4",
"_score": 0.14965448,
"_source": {
"title": "Solr in Action",
"authors": [
"trey grainger",
"timothy potter"
],
"summary": "Comprehensive guide to implementing a scalable search engine using Apache Solr",
"publish_date": "2014-04-05",
"num_reviews": 23,
"publisher": "manning"
}
}
]
}

:第三条被匹配,因为 guidesummary 字段中被找到。

3. Boosting

由于我们是多个字段查询,我们可能需要提高某一个字段的分值。在下面的例子中,我们把 summary 字段的分数提高三倍,为了提升 summary 字段的重要度;因此,我们把文档 4 的相关度提高了。

POST /bookdb_index/_search
{
"query": {
"multi_match" : {
"query" : "elasticsearch guide",
"fields": ["title", "summary^3"]
}
},
"_source": ["title", "summary", "publish_date"]
} [Results]
"hits": [
{
"_index": "bookdb_index",
"_type": "book",
"_id": "1",
"_score": 0.31495273,
"_source": {
"summary": "A distibuted real-time search and analytics engine",
"title": "Elasticsearch: The Definitive Guide",
"publish_date": "2015-02-07"
}
},
{
"_index": "bookdb_index",
"_type": "book",
"_id": "4",
"_score": 0.14965448,
"_source": {
"summary": "Comprehensive guide to implementing a scalable search engine using Apache Solr",
"title": "Solr in Action",
"publish_date": "2014-04-05"
}
},
{
"_index": "bookdb_index",
"_type": "book",
"_id": "3",
"_score": 0.13094766,
"_source": {
"summary": "build scalable search applications using Elasticsearch without having to do complex low-level programming or understand advanced data science algorithms",
"title": "Elasticsearch in Action",
"publish_date": "2015-12-03"
}
}
]

:提升不是简简单单通过提升因子把计算分数加成。实际的 boost 值通过归一化和一些内部优化给出的。相关信息请见 Elasticsearch guide

4. Bool 组合查询

为了提供更相关或者特定的结果,AND/OR/NOT 操作符可以用来调整我们的查询。它是以 布尔查询 的方式来实现的。布尔查询 接受如下参数:

  • must 等同于 AND
  • must_not 等同于 NOT
  • should 等同于 OR

上面的关键字中在一个query中只能出现一次

打比方,如果我想要查询这样类型的书:书名包含 ElasticSearch 或者(ORSolr,并且(AND)它的作者是 Clinton Gormley 不是(NOTRadu Gheorge

POST /bookdb_index/_search
{
"query": {
"bool": {
"must": { "match": { "authors": "clinton gormely" }},
"must_not": { "match": { "authors": "radu gheorge" }},
"should": [
{ "match": { "title": "Elasticsearch" }},
{ "match": { "title": "Solr" }}
]
}
}
} 格式化版本:
POST /bookdb_index/_search
{
"query": {
"bool": {
"must": {
"match": {
"authors": "clinton gormely"
}
},
"must_not": {
"match": {
"authors": "radu gheorge"
}
},
"should": [
{
"match": {
"title": "Elasticsearch"
}
},
{
"match": {
"title": "Solr"
}
}
]
}
}
} [Results]
"hits": [
{
"_index": "bookdb_index",
"_type": "book",
"_id": "1",
"_score": 0.3672021,
"_source": {
"title": "Elasticsearch: The Definitive Guide",
"authors": [
"clinton gormley",
"zachary tong"
],
"summary": "A distibuted real-time search and analytics engine",
"publish_date": "2015-02-07",
"num_reviews": 20,
"publisher": "oreilly"
}
}
]

:正如你所看到的,布尔查询 可以包装任何其他查询类型,包括其他布尔查询,以创建任意复杂或深度嵌套的查询。

5. 模糊(Fuzzy)查询

在进行匹配和多项匹配时,可以启用模糊匹配来捕捉拼写错误,模糊度是基于原始单词的编辑距离来指定的。

POST /bookdb_index/_search
{
"query": {
"multi_match" : {
"query" : "comprihensiv guide",
"fields": ["title", "summary"],
"fuzziness": "AUTO"
}
},
"_source": ["title", "summary", "publish_date"],
"size": 1
} [Results]
"hits": [
{
"_index": "bookdb_index",
"_type": "book",
"_id": "4",
"_score": 0.5961596,
"_source": {
"summary": "Comprehensive guide to implementing a scalable search engine using Apache Solr",
"title": "Solr in Action",
"publish_date": "2014-04-05"
}
}
]

:当术语长度大于 5 个字符时,AUTO 的模糊值等同于指定值 “2”。但是,80% 拼写错误的编辑距离为 1,所以,将模糊值设置为 1 可能会提高您的整体搜索性能。更多详细信息,请参阅Elasticsearch指南中的“排版和拼写错误”(Typos and Misspellings)

6. 通配符(Wildcard)查询

通配符查询 允许你指定匹配的模式,而不是整个术语。

  • 匹配任何字符
  • * 匹配零个或多个字符。

例如,要查找名称以字母’t’开头的所有作者的记录:

POST /bookdb_index/_search
{
"query": {
"wildcard" : {
"authors" : "t*"
}
},
"_source": ["title", "authors"],
"highlight": {
"fields" : {
"authors" : {}
}
}
} [Results]
"hits": [
{
"_index": "bookdb_index",
"_type": "book",
"_id": "1",
"_score": 1,
"_source": {
"title": "Elasticsearch: The Definitive Guide",
"authors": [
"clinton gormley",
"zachary tong"
]
},
"highlight": {
"authors": [
"zachary <em>tong</em>"
]
}
},
{
"_index": "bookdb_index",
"_type": "book",
"_id": "2",
"_score": 1,
"_source": {
"title": "Taming Text: How to Find, Organize, and Manipulate It",
"authors": [
"grant ingersoll",
"thomas morton",
"drew farris"
]
},
"highlight": {
"authors": [
"<em>thomas</em> morton"
]
}
},
{
"_index": "bookdb_index",
"_type": "book",
"_id": "4",
"_score": 1,
"_source": {
"title": "Solr in Action",
"authors": [
"trey grainger",
"timothy potter"
]
},
"highlight": {
"authors": [
"<em>trey</em> grainger",
"<em>timothy</em> potter"
]
}
}
]

7. 正则(Regexp)查询

正则查询 让你可以使用比 通配符查询 更复杂的模式进行查询:

POST /bookdb_index/_search
{
"query": {
"regexp" : {
"authors" : "t[a-z]*y"
}
},
"_source": ["title", "authors"],
"highlight": {
"fields" : {
"authors" : {}
}
}
} [Results]
"hits": [
{
"_index": "bookdb_index",
"_type": "book",
"_id": "4",
"_score": 1,
"_source": {
"title": "Solr in Action",
"authors": [
"trey grainger",
"timothy potter"
]
},
"highlight": {
"authors": [
"<em>trey</em> grainger",
"<em>timothy</em> potter"
]
}
}
]

8. 短语匹配(Match Phrase)查询

短语匹配查询 要求在请求字符串中的所有查询项必须都在文档中存在,文中顺序也得和请求字符串一致,且彼此相连。默认情况下,查询项之间必须紧密相连,但可以设置 slop 值来指定查询项之间可以分隔多远的距离,结果仍将被当作一次成功的匹配。

POST /bookdb_index/_search
{
"query": {
"multi_match" : {
"query": "search engine",
"fields": ["title", "summary"],
"type": "phrase",
"slop": 3
}
},
"_source": [ "title", "summary", "publish_date" ]
} [Results]
"hits": [
{
"_index": "bookdb_index",
"_type": "book",
"_id": "4",
"_score": 0.22327082,
"_source": {
"summary": "Comprehensive guide to implementing a scalable search engine using Apache Solr",
"title": "Solr in Action",
"publish_date": "2014-04-05"
}
},
{
"_index": "bookdb_index",
"_type": "book",
"_id": "1",
"_score": 0.16113183,
"_source": {
"summary": "A distibuted real-time search and analytics engine",
"title": "Elasticsearch: The Definitive Guide",
"publish_date": "2015-02-07"
}
}
]

:在上述例子中,对于非整句类型的查询,_id 为 1 的文档一般会比 _id 为 4 的文档得分高,结果位置也更靠前,因为它的字段长度较短,但是对于 短语匹配类型 查询,由于查询项之间的接近程度是一个计算因素,因此 _id 为 4 的文档得分更高。

9. 短语前缀(Match Phrase Prefix)查询

短语前缀式查询 能够进行 即时搜索(search-as-you-type) 类型的匹配,或者说提供一个查询时的初级自动补全功能,无需以任何方式准备你的数据。和 match_phrase 查询类似,它接收slop 参数(用来调整单词顺序和不太严格的相对位置)和 max_expansions 参数(用来限制查询项的数量,降低对资源需求的强度)。

POST /bookdb_index/_search
{
"query": {
"match_phrase_prefix" : {
"summary": {
"query": "search en",
"slop": 3,
"max_expansions": 10
}
}
},
"_source": [ "title", "summary", "publish_date" ]
} [Results]
"hits": [
{
"_index": "bookdb_index",
"_type": "book",
"_id": "4",
"_score": 0.5161346,
"_source": {
"summary": "Comprehensive guide to implementing a scalable search engine using Apache Solr",
"title": "Solr in Action",
"publish_date": "2014-04-05"
}
},
{
"_index": "bookdb_index",
"_type": "book",
"_id": "1",
"_score": 0.37248808,
"_source": {
"summary": "A distibuted real-time search and analytics engine",
"title": "Elasticsearch: The Definitive Guide",
"publish_date": "2015-02-07"
}
}
]

:采用 查询时即时搜索 具有较大的性能成本。更好的解决方案是采用 索引时即时搜索。更多信息,请查看 自动补齐接口(Completion Suggester API)边缘分词器(Edge-Ngram filters)的用法

10. 查询字符串(Query String)

查询字符串 类型(query_string)的查询提供了一个方法,用简洁的简写语法来执行 多匹配查询布尔查询提权查询模糊查询通配符查询正则查询范围查询。下面的例子中,我们在那些作者是 “grant ingersoll”“tom morton” 的某本书当中,使用查询项 “search algorithm” 进行一次模糊查询,搜索全部字段,但给 summary 的权重提升 2 倍。

POST /bookdb_index/_search
{
"query": {
"query_string": {
"query": "(saerch~1 algorithm~1) AND (grant ingersoll) OR (tom morton)",
"fields": [
"*",
"summary^2"
]
}
},
"_source": [
"title",
"summary",
"authors"
],
"highlight": {
"fields": {
"summary": {}
}
}
} [Results]
"hits": [
{
"_index": "bookdb_index",
"_type": "book",
"_id": "2",
"_score": 0.14558059,
"_source": {
"summary": "organize text using approaches such as full-text search, proper name recognition, clustering, tagging, information extraction, and summarization",
"title": "Taming Text: How to Find, Organize, and Manipulate It",
"authors": [
"grant ingersoll",
"thomas morton",
"drew farris"
]
},
"highlight": {
"summary": [
"organize text using approaches such as full-text <em>search</em>, proper name recognition, clustering, tagging, information extraction, and summarization"
]
}
}
]

11. 简单查询字符串(Simple Query String)

简单请求字符串 类型(simple_query_string)的查询是请求字符串类型query_string)查询的一个版本,它更适合那种仅暴露给用户一个简单搜索框的场景;因为它用 +/\|/- 分别替换了 AND/OR/NOT,并且自动丢弃了请求中无效的部分,不会在用户出错时,抛出异常。

POST /bookdb_index/_search
{
"query": {
"simple_query_string" : {
"query": "(saerch~1 algorithm~1) + (grant ingersoll) | (tom morton)",
"fields": ["*", "summary^2"]
}
},
"_source": [ "title", "summary", "authors" ],
"highlight": {
"fields" : {
"summary" : {}
}
}
} [Results]
"hits" : {
"total" : {
"value" : 1,
"relation" : "eq"
},
"max_score" : 3.5710216,
"hits" : [
{
"_index" : "bookdb_index",
"_type" : "book",
"_id" : "2",
"_score" : 3.5710216,
"_source" : {
"summary" : "organize text using approaches such as full-text search, proper name recognition, clustering, tagging, information extraction, and summarization",
"title" : "Taming Text: How to Find, Organize, and Manipulate It",
"authors" : [
"grant ingersoll",
"thomas morton",
"drew farris"
]
},
"highlight" : {
"summary" : [
"organize text using approaches such as full-text <em>search</em>, proper name recognition, clustering, tagging"
]
}
}
]
}

12. 词条(Term)/多词条(Terms)查询

以上例子均为 full-text(全文检索) 的示例。有时我们对结构化查询更感兴趣,希望得到更准确的匹配并返回结果,词条查询多词条查询 可帮我们实现。在下面的例子中,我们要在索引中找到所有由 Manning 出版的图书。

POST /bookdb_index/_search
{
"query": {
"term" : {
"publisher": "manning"
}
},
"_source" : ["title","publish_date","publisher"]
} [Results]
"hits": [
{
"_index": "bookdb_index",
"_type": "book",
"_id": "2",
"_score": 1.2231436,
"_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": 1.2231436,
"_source": {
"publisher": "manning",
"title": "Elasticsearch in Action",
"publish_date": "2015-12-03"
}
},
{
"_index": "bookdb_index",
"_type": "book",
"_id": "4",
"_score": 1.2231436,
"_source": {
"publisher": "manning",
"title": "Solr in Action",
"publish_date": "2014-04-05"
}
}
]

可使用词条关键字来指定多个词条,将搜索项用数组传入。

{
"query": {
"terms" : {
"publisher": ["oreilly", "packt"]
}
}
}

13. 词条(Term)查询 - 排序(Sorted)

词条查询 的结果(和其他查询结果一样)可以被轻易排序,多级排序也被允许:

POST /bookdb_index/_search
{
"query": {
"term": {
"publisher": "manning"
}
},
"_source": [
"publish_date",
"publisher"
],
"sort": [
{
"publish_date": {
"order": "desc"
}
}
]
} [Results]
"hits" : {
"total" : {
"value" : 3,
"relation" : "eq"
},
"max_score" : null,
"hits" : [
{
"_index" : "bookdb_index",
"_type" : "book",
"_id" : "3",
"_score" : null,
"_source" : {
"publisher" : "manning",
"publish_date" : "2015-12-03"
},
"sort" : [
1449100800000
]
},
{
"_index" : "bookdb_index",
"_type" : "book",
"_id" : "4",
"_score" : null,
"_source" : {
"publisher" : "manning",
"publish_date" : "2014-04-05"
},
"sort" : [
1396656000000
]
},
{
"_index" : "bookdb_index",
"_type" : "book",
"_id" : "2",
"_score" : null,
"_source" : {
"publisher" : "manning",
"publish_date" : "2013-01-24"
},
"sort" : [
1358985600000
]
}
]
}

14. 范围查询

另一个结构化查询的例子是 范围查询。在这个例子中,我们要查找 2015 年出版的书。

POST /bookdb_index/_search
{
"query": {
"range": {
"publish_date": {
"gte": "2015-01-01",
"lte": "2015-12-31"
}
}
},
"_source": [
"title",
"publish_date",
"publisher"
]
} [Results]
"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"
}
}
]

范围查询 用于日期、数字和字符串类型的字段。

15. 过滤(Filtered)查询

过滤查询允许你可以过滤查询结果。对于我们的例子中,要在标题或摘要中检索一些书,查询项为 Elasticsearch,但我们又想筛出那些仅有 20 个以上评论的。

新版本不支持filtered 查询,已经弃用这个关键字

POST /bookdb_index/_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"
}
}
]

过滤查询 并不强制它作用于其上的查询必须存在。如果未指定查询,match_all 基本上会返回索引内的全部文档。实际上,过滤只在第一次运行,以减少所需的查询面积,并且,在第一次使用后过滤会被缓存,大大提高了性能。

更新过滤查询 将在 ElasticSearch 5 中移除,使用 布尔查询 替代。 下面有个例子使用 布尔查询 重写上面的例子:

POST /bookdb_index/_search
{
"query": {
"bool": {
"must" : {
"multi_match": {
"query": "elasticsearch",
"fields": ["title","summary"]
}
},
"filter": {
"range" : {
"num_reviews": {
"gte": 20
}
}
}
}
},
"_source" : ["title","summary","publisher", "num_reviews"]
}

在后续的例子中,我们将会把它使用在 多重过滤 中。

16. 多重过滤(Multiple Filters)

多重过滤 可以结合 布尔查询 使用,下一个例子中,过滤查询决定只返回那些包含至少20条评论,且必须在 2015 年前出版,且由 O’Reilly 出版的结果。

POST /bookdb_index/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"title": "Elasticsearch"
}
}
],
"filter": [
{
"term": {
"publisher": "oreilly"
}
},
{
"range": {
"publish_date": {
"gte": "2014-12-31"
}
}
}
]
}
},
"_source": [
"title",
"publisher",
"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. 作用分值: 域值(Field Value)因子

也许在某种情况下,你想把文档中的某个特定域作为计算相关性分值的一个因素,比较典型的场景是你想根据普及程度来提高一个文档的相关性。在我们的示例中,我们想把最受欢迎的书(基于评论数判断)的权重进行提高,可使用 field_value_factor 用以影响分值。

POST /bookdb_index/_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": 0.44831306,
"_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": 0.3718407,
"_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": 0.046479136,
"_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": 0.041432835,
"_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: 我们可能刚运行了一个常规的 multi_match (多匹配)查询,并对 num_reviews 域进行了排序,这让我们失去了评估相关性分值的好处。

注2: 有大量的附加参数可用来调整提升原始相关性分值效果的程度,比如 modifier, factor, boost_mode 等等,至于细节可在 Elasticsearch 指南中探索。

18. 作用分值: 衰变(Decay)函数

假设不想使用域值做递增提升,而你有一个理想目标值,并希望用这个加权因子来对这个离你较远的目标值进行衰减。有个典型的用途是基于经纬度、价格或日期等数值域的提升。在如下的例子中,我们查找在2014年6月左右出版的,查询项是 search engines 的书。

POST /bookdb_index/_search
{
"query": {
"function_score": {
"query": {
"multi_match" : {
"query" : "search engine",
"fields": ["title", "summary"]
}
},
"functions": [
{
"exp": {
"publish_date" : {
"origin": "2014-06-15",
"offset": "7d",
"scale" : "30d"
}
}
}
],
"boost_mode" : "replace"
}
},
"_source": ["title", "summary", "publish_date", "num_reviews"]
} [Results]
"hits": [
{
"_index": "bookdb_index",
"_type": "book",
"_id": "4",
"_score": 0.27420625,
"_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": 0.005920768,
"_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": 0.000011564,
"_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": 0.0000059171475,
"_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. 函数分值: 脚本评分

当内置的评分函数无法满足你的需求时,还可以用 Groovy 脚本。在我们的例子中,想要指定一个脚本,能在决定把 num_reviews 的因子计算多少之前,先将 publish_date 考虑在内。因为很新的书也许不会有评论,分值不应该被惩罚。

评分脚本如下:

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

script_score 参数内动态调用评分脚本:

POST /bookdb_index/book/_search
{
"query": {
"function_score": {
"query": {
"multi_match" : {
"query" : "search engine",
"fields": ["title", "summary"]
}
},
"functions": [
{
"script_score": {
"params" : {
"threshold": "2015-07-30"
},
"script": "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"]
} [Results]
"hits": {
"total": 4,
"max_score": 0.8463001,
"hits": [
{
"_index": "bookdb_index",
"_type": "book",
"_id": "1",
"_score": 0.8463001,
"_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": 0.7067348,
"_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": 0.08952084,
"_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": 0.07602123,
"_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: 要在 Elasticsearch 实例中使用动态脚本,必须在 config/elasticsearch.yaml 文件中启用它;也可以使用存储在 Elasticsearch 服务器上的脚本。建议看看 Elasticsearch 指南文档获取更多信息。

注2: 因 JSON 不能包含嵌入式换行符,请使用分号来分割语句。

引用自:23 USEFUL ELASTICSEARCH EXAMPLE QUERIES

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