ElasticSearch 7.X版本19个经常使用的查询语句
整理一篇经常使用的CRUD查询语句，以前这篇文件是在17年左右发表的，从英文翻译过来，如今采用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，一块儿来学习吧。html
为了演示不一样类型的 ElasticSearch 的查询，咱们将使用书文档信息的集合（有如下字段：title（标题）, authors（做者）, summary（摘要）, publish_date（发布日期）和 num_reviews（浏览数））。数组
在这以前，首先咱们应该先建立一个新的索引（index），并批量导入一些文档：缓存
建立索引：服务器
PUT /bookdb_index
{ "settings": { "number_of_shards": 1 }}
批量上传文档：app
注意：如今7.x 已经启用types 类型了，对应的操做语句也要修改下，
POST /bookdb_index/book/_bulk换成POST /bookdb_index/_bulk，而后进行操做。elasticsearch
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：ide
- 使用 Search Lite API，它从
url中读取全部的查询参数 - 使用完整 JSON 做为请求体，这样你可使用完整的 Elasticsearch DSL
下面是一个基本的匹配查询，查询任一字段包含 Guide 的记录函数
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：性能
{
"query": {
"multi_match" : {
"query" : "guide",
"fields" : [ "*" ]
}
}
}
multi_match 是 match 的做为在多个字段运行相同操做的一个速记法。fields 属性用来指定查询针对的字段，*表明全部字段，同时也可使用单个字段进行查询，用逗号分隔开就能够。学习
在这个例子中，咱们想要对文档的全部字段进行匹配。两个 API 都容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 给予你灵活建立更复杂查询和指定返回结果的能力（后面，咱们会一一阐述）。在下面例子中，咱们指定 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 容许指定是否使用 and 操做符来取代默认的 or 操做符。你还能够指定 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
正如咱们已经看到来的，为了根据多个字段检索（e.g. 在 title 和 summary 字段都是相同的查询字符串的结果），你可使用 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"
}
}
]
}
注：第三条被匹配，由于 guide 在 summary 字段中被找到。
3. Boosting
因为咱们是多个字段查询，咱们可能须要提升某一个字段的分值。在下面的例子中，咱们把 summary 字段的分数提升三倍，为了提高 summary 字段的重要度；所以，咱们把文档 4 的相关度提升了。
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"
}
}
]
注：提高不是简简单单经过提高因子把计算分数加成。实际的 boost 值经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 操做符能够用来调整咱们的查询。它是以 布尔查询 的方式来实现的。布尔查询 接受以下参数：
must等同于ANDmust_not等同于NOTshould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，若是我想要查询这样类型的书：书名包含 ElasticSearch 或者（OR） Solr，而且（AND）它的做者是 Clinton Gormley 不是（NOT）Radu 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"
}
}
]
注：正如你所看到的，布尔查询 能够包装任何其余查询类型，包括其余布尔查询，以建立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，能够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"
}
}
]
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”。可是，80％ 拼写错误的编辑距离为 1，因此，将模糊值设置为 1 可能会提升您的总体搜索性能。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 容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’开头的全部做者的记录：
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全部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。默认状况下，查询项之间必须紧密相连，但能够设置 slop 值来指定查询项之间能够分隔多远的距离，结果仍将被看成一次成功的匹配。
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"
}
}
]
注：在上述例子中，对于非整句类型的查询，_id 为 1 的文档通常会比 _id 为 4 的文档得分高，结果位置也更靠前，由于它的字段长度较短，可是对于 短语匹配类型 查询，因为查询项之间的接近程度是一个计算因素，所以 _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 可以进行 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 查询相似，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，下降对资源需求的强度）。
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"
}
}
]
注：采用 查询时即时搜索 具备较大的性能成本。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） 或 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 和范围查询。下面的例子中，咱们在那些做者是 “grant ingersoll” 或 “tom morton” 的某本书当中，使用查询项 “search algorithm” 进行一次模糊查询，搜索所有字段，但给 summary 的权重提高 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；由于它用 +/\|/- 分别替换了 AND/OR/NOT，而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。有时咱们对结构化查询更感兴趣，但愿获得更准确的匹配并返回结果，词条查询 和 多词条查询 可帮咱们实现。在下面的例子中，咱们要在索引中找到全部由 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"
}
}
]
可以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（和其余查询结果同样）能够被轻易排序，多级排序也被容许：
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
另外一个结构化查询的例子是 范围查询。在这个例子中，咱们要查找 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"
}
}
]
注：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
过滤查询容许你能够过滤查询结果。对于咱们的例子中，要在标题或摘要中检索一些书，查询项为 Elasticsearch，但咱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"
}
}
]
注：过滤查询 并不强制它做用于其上的查询必须存在。若是未指定查询，match_all 基本上会返回索引内的所有文档。实际上，过滤只在第一次运行，以减小所需的查询面积，而且，在第一次使用后过滤会被缓存，大大提升了性能。
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，咱们将会把它使用在 多重过滤 中。
16. 多重过滤（Multiple Filters）
多重过滤 能够结合 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. 做用分值: 域值（Field Value）因子
也许在某种状况下，你想把文档中的某个特定域做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升一个文档的相关性。在咱们的示例中，咱们想把最受欢迎的书（基于评论数判断）的权重进行提升，可以使用 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: 咱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，这让咱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高原始相关性分值效果的程度，好比 modifier, factor, boost_mode 等等，至于细节可在 Elasticsearch 指南中探索。
18. 做用分值: 衰变（Decay）函数
假设不想使用域值作递增提高，而你有一个理想目标值，并但愿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高。在以下的例子中，咱们查找在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
当内置的评分函数没法知足你的需求时，还能够用 Groovy 脚本。在咱们的例子中，想要指定一个脚本，能在决定把 num_reviews 的因子计算多少以前，先将 publish_date 考虑在内。由于很新的书也许不会有评论，分值不该该被惩罚。
评分脚本以下：
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
在 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。
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