发布于 2016-11-17 13:44:04 | 579 次阅读 | 评论: 0 | 来源: PHPERZ
这里有新鲜出炉的ElasticSearch权威指南，程序狗速度看过来！
ElasticSearch 基于Lucene的搜索引擎
ElasticSearch是一个基于Lucene构建的开源，分布式，RESTful搜索引擎。设计用于云计算中，能够达到实时搜索，稳定，可靠，快速，安装使用方便。支持通过HTTP使用JSON进行数据索引。
我们建立一个网站或应用程序，并要添加搜索功能，令我们受打击的是：搜索工作是很难的。我们希望我们的搜索解决方案要快，我们希望有一个零配置和一个完全免费的搜索模式，我们希望能够简单地使用JSON通过HTTP的索引数据，我们希望我们的搜索服务器始终可用，我们希望能够一台开始并扩展到数百，我们要实时搜索，我们要简单的多租户，我们希望建立一个云的解决方案。Elasticsearch旨在解决所有这些问题和更多的。
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" }
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。
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。
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。
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（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" : {}
}
}
}
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"
]
}
]
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"
}
}
]
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。
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"
}
}
]
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'].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