ElasticSearch是一个基于Lucene的搜索服务器,它是用Java开发的,并作为Apache许可条款下的开放源码发布,是当前流行的企业级搜索引擎。本文介绍了几种常用的Elasticsearch查询方式,并分别进行了举例,希望它们对你有帮助。(注:文章翻译自Tim Ojo的23 Useful Elasticsearch Example Queries。若有翻译不到位的地方,欢迎大家进行指正。喜欢的也不要忘了打赏、点赞、收藏哦:))
为了介绍Elasticsearch中的不同查询类型,我们将对带有下列字段的文档进行搜索:title(标题),authors(作者),summary(摘要),release date(发布时间)以及number of reviews(评论数量)。
首先,让我们创建一个新的索引,并通过bulk API查询文档:
PUT /bookdb_index { "settings": { "number_of_shards": 1 }}
POST /bookdb_index/book/_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" }
举例
基本匹配查询
有两种方式执行基本全文(匹配)查询:使用Search Lite API,它将搜索参数作为URL的一部分传递;使用完整的JSON请求消息体,它允许你使用完整的Elasticsearch DSL。
以下是基本的匹配查询,在所有字段中查询字符串“guide”:
GET /bookdb_index/book/_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" } } ]
这个查询的完整消息体如下,它产生的结果与上述查询相同:
{ "query": { "multi_match": { "query": "guide", "fields": [ "_all" ] } } }
作为对多个字段运行相同查询的简便方法,multi_match关键字可以用在match关键字的位置。fields属性指定要查询的字段,在这种情况下,我们要对文档中的所有字段进行查询。
两种API都允许你指定你想查询的字段。比如,指定搜索标题字段中含“in Action”的图书:
GET /bookdb_index/book/_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能提供更大的灵活性,让你可以创建更复杂的查询(我们在下文会提到)以及指定查询结果的返回方式。在下列示例中,我们指定了要返回的结果数量、偏移位置(对分页有用)、要返回的文档字段和高亮显示的项。
POST /bookdb_index/book/_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:对于多词(multi-word)查询,相应的匹配(match)查询允许你指定是否使用and运算符,而不是默认使用or运算符。你也可以指定minimum_should_match选项来调整返回结果的相关性。详细信息可以在Elasticsearch指南中找到。
多字段查询
为了在一次查询中查找多个字段(如,在title和summary中查找相同的字符串),你使用了multi_match查询:
POST /bookdb_index/book/_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" } } ] }
注:上面的查询匹配了3个结果,因为单词“guide”在summary(摘要)中有出现。
Boosting 算法
有时候,我们在多个字段中进行搜索,可能会希望提高某个字段中的权重。如,在下列设计示例中,我们将summary字段的权重提高三倍,以提高这个字段的重要性,从而增强文档 _id 4的相关性。
POST /bookdb_index/book/_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" } } ]
注:Boosting并不意味着计算的权重会被boost因子翻倍。实际的boost值会进行一些规范化和内部优化。想了解更多boost工作原理的信息,可参考Elasticsearch指南。
Bool 查询
为获得更具相关性和更具体的查询结果,AND / OR / NOT运算符可在我们的搜索查询进行微调。这在搜索API中作为bool查询实现。bool查询接受must参数(等效于AND),must_not参数(等效于NOT),should参数(等效于OR)。比如,我想查询标题中带有“Elasticsearch” 或(OR) “Solr”的书,并且(AND)是由“clinton gormley”创作,而不是(NOT) “radu gheorge”。
POST /bookdb_index/book/_search { "query": { "bool": { "must": { "bool": { "should": [ { "match": { "title": "Elasticsearch" } }, { "match": { "title": "Solr" } } ] } }, "must": { "match": { "authors": "clinton gormely" } }, "must_not": { "match": { "authors": "radu gheorge" } } } } } [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" } } ]
注:如你所见,bool查询囊括所有其他的搜索类型,包括其他类型的bool查询,以构建复杂和深层嵌套的查询体系。
模糊查询
模糊匹配可以在匹配和多重匹配查询上启用以捕获拼写错误。模糊程度由原始词之间的Levenshtein距离决定。
POST /bookdb_index/book/_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" } } ]
注: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%的人类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)章节。
通配符查询
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/book/_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" ] } } ]
正则查询
正则查询允许你指定比通配符查询更复杂的查询模式。
POST /bookdb_index/book/_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" ] } } ]
匹配短语查询
匹配短语查询要求查询字符串中的所有字词都在文档中存在,要遵循查询字符串的指定顺序还要彼此接近。默认情况下,术语要求彼此相同,但你可以指定slop值,进行文档匹配时,该值可以指定词的距离。
POST /bookdb_index/book/_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" } } ]
注:在上述例子中,对于非短语类型查询,文档_id 1通常会以较高的权重出现在文档_id 4之前,因为其字段长度更加短。然而,作为短语查询,术语的接近度也需要考虑在内,因此文档_id 4权重会更高。
匹配短语前缀查询
匹配短语前缀查询在查询时提供“自动搜索”功能(search-as-you-type)或者说词穷时的自动补充功能,你无需以任何方式准备数据。和match_phrase查询一样,它接受slop参数,使得字的顺序和相对位置的调整不那么死板。它还接受max_expansions参数,以限制匹配的术语数量,减少资源强度。
POST /bookdb_index/book/_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" } } ]
注:查询时(query-time)搜索类型具有性能成本。 所以你可以选择将索引时(index-time)搜索作为搜索类型。更多详情,请查看Completion Suggester API或使用Edge-Ngram filters获取。
查询字符串查询
查询字符串查询提供了以简明的速记语法执行multi_match查询,bool查询,boosting查询,模糊匹配查询,通配符查询,regexp和范围查询的方法。下面示例中,我对“search algorithm”执行了模糊查询,其中一本书的作者是“grant ingersoll” 或 “tom morton”,我对所有字段都进行查询,但在summary字段,boost值设为“2”。
POST /bookdb_index/book/_search { "query": { "query_string" : { "query": "(saerch~1 algorithm~1) AND (grant ingersoll) OR (tom morton)", "fields": ["_all", "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" ] } }
简单查询字符串查询
简单查询字符串(simple_query_string)查询是字符串(query_string)查询的一个版本,更适合用户在单个搜索框中使用。它分别用+ / | / - 替换AND / OR / NOT的使用,并且自动过滤掉查询的无效部分,而不是在用户犯错误时抛出异常。
POST /bookdb_index/book/_search { "query": { "simple_query_string" : { "query": "(saerch~1 algorithm~1) + (grant ingersoll) | (tom morton)", "fields": ["_all", "summary^2"] } }, "_source": [ "title", "summary", "authors" ], "highlight": { "fields" : { "summary" : {} } } }
术语查询
以上都是全文搜索的例子。但是有些盆友对结构化搜索更感兴趣,希望在其中找到完全匹配并返回结果。这时,术语查询便可以帮到我们。在下面例子中,我们将搜索Manning Publications出版的所有书籍。
POST /bookdb_index/book/_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" } } ]
可以使用术语关键字来指定多个术语,并传入搜索术语数组。
{ "query": { "terms" : { "publisher": ["oreilly", "packt"] } } }
术语查询——排序
术语查询结果(与所有其他查询结果一样)可以轻松排序, 也允许多级排序:
POST /bookdb_index/book/_search { "query": { "term" : { "publisher": "manning" } }, "_source" : ["title","publish_date","publisher"], "sort": [ { "publish_date": {"order":"desc"}}, { "title": { "order": "desc" }} ] } [Results]"hits": [ { "_index": "bookdb_index", "_type": "book", "_id": "3", "_score": null, "_source": { "publisher": "manning", "title": "Elasticsearch in Action", "publish_date": "2015-12-03" }, "sort": [ 1449100800000, "in" ] }, { "_index": "bookdb_index", "_type": "book", "_id": "4", "_score": null, "_source": { "publisher": "manning", "title": "Solr in Action", "publish_date": "2014-04-05" }, "sort": [ 1396656000000, "solr" ] }, { "_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": [ 1358985600000, "to" ] } ]
范围查询
另一个结构化查询示例是范围查询。 在此示例中,我们将搜索在2015年出版的图书:
POST /bookdb_index/book/_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" } } ]
注:范围查询适用于日期,数字和字符串类型字段。
过滤查询
过滤查询允许您过滤查询的结果。 例如,我们要查询标题或摘要中包含术语“Elasticsearch”的书籍,但要求结果过滤到包含20条以上评论的书。
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:过滤查询不要求过滤的查询的存在。如果没有指定查询,则运行match_all查询,它基本上能返回索引中的所有文档,然后对其进行过滤。 实际上,首先运行的是过滤器,这减少了需要查询的面积。 此外,过滤器在第一次使用后缓存,这能使它更高效。
POST /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"] }
这同样适用于下面示例中的过滤器。
多项过滤器
多项过滤器可以通过bool过滤器结合起来,在下一个示例中,过滤器指定返回的结果必须至少有20条评论,发布时间在2015年之后,并应由oreilly发布。
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" } } ]
函数权重:字段值要素
可能有这样的情况,您希望将文档中特定字段的值考虑到相关性权重的计算中。 这在脚本中很常见,基于其受欢迎程度,你会希望boost文档的相关性。 在我们的例子中,我们希望更受欢迎的书(根据评论的数量判断)得到boost。 这就可能使用到field_value_factor函数权重:
POST /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": 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:我们可以只运行一个常规的multi_match查询并按num_reviews字段排序,但是我们失去了获得相关性分值的好处。
注2:有许多额外的参数在原始相关性权重上增强boost的程度,比如“modifier”, “factor”,“boost_mode”等。这些在Elasticsearch指南中进行了详细探讨。
函数权重:关联功能递减函数
假设想要的不是让某个字段值按某种关联度递增,而是想让你关注的值按照同关联度递减。 这在基于lat / long,数字字段(如价格或日期)的boost中非常有用。 在下列示例中,我们要在“搜索引擎”上搜索于2014年6月发布的书籍。
POST /bookdb_index/book/_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" } } ]
函数权重: 脚本权重
在内置评分函数不能满足您的需要的情况下,可以选择指定一个Groovy脚本用于评分。在我们的示例中,我们想要指定一个考虑发布日期的脚本,然后再决定评论数,因为新出版的书可能没有足够的评论数。
权重脚本如下所示:
publish_date = doc['publish_date'].value num_reviews = doc['num_reviews'].valueif (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
要想动态使用权重脚本,我们需要使用脚本权重参数:
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:要使用动态脚本,必须在config / elasticsearch.yaml文件的Elasticsearch实例中激活。 当然,我们也可以使用存储在Elasticsearch服务器上的脚本。 更多相关信息,请参阅Elasticsearch参考文档。
注2:JSON不能包含嵌入的换行符,因此分号用来分隔语句。
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