19 个很有用的 ElasticSearch 查询语句 · N3xtChen 的博客

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：

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" }
#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/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"
下面是完整 Body 版本的查询，生成相同的内容：
{
    "query": {
        "multi_match" : {
            "query" : "guide",
            "fields" : ["_all"]
multi_match 是 match 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，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/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 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/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 title 和 summary 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/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：第三条被匹配，因为 guide 在 summary 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/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：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 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
打比方，如果我想要查询这样类型的书：书名包含 ElasticSearch 或者（OR） Solr，并且（AND）它的作者是 Clinton Gormley 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：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/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％ 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/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"
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/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"
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/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/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：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） 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，我们在那些作者是 “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，搜索全部字段，但给 summary 的权重提升 2 倍。
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"
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/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" : {}
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 和 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/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/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,
        "_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,
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/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 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。
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 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/book/_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/book/_search
    "query": {
        "filtered": {
            "query" : {
                "multi_match": {
                    "query": "elasticsearch",
                    "fields": ["title","summary"]
            "filter": {
                "bool": {
                    "must": {
                        "range" : { "num_reviews": { "gte": 20 } }
                    "must_not": {
                        "range" : { "publish_date": { "lte": "2014-12-31" } }
                    "should": {
                        "term": { "publisher": "oreilly" }
    "_source" : ["title","summary","publisher", "num_reviews", "publish_date"]
[Results]
"hits": [
        "_index": "bookdb_index",
        "_type": "book",
        "_id": "1",
        "_score": 0.5955761,
        "_source": {
          "summary": "A distibuted real-time search and analytics engine",
          "publisher": "oreilly",
          "num_reviews": 20,
          "title": "Elasticsearch: The Definitive Guide",
          "publish_date": "2015-02-07"
17. 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/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/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"
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
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

1. 基本的匹配（Query）查询 #

2. 多字段（Multi-filed）查询 #

3. Boosting #

4. Bool 查询 #

5. 模糊（Fuzzy）查询 #

6. 通配符（Wildcard）查询 #

7. 正则（Regexp）查询 #

8. 短语匹配(Match Phrase)查询 #

9. 短语前缀（Match Phrase Prefix）查询 #

10. 查询字符串（Query String） #

11. 简单查询字符串（Simple Query String） #

12. 词条（Term）/多词条（Terms）查询 #

13. 词条（Term）查询 - 排序（Sorted） #

14. 范围查询 #

15. 过滤(Filtered)查询 #

16. 多重过滤（Multiple Filters） #

17. 作用分值: 域值（Field Value）因子 #

18. 作用分值: 衰变（Decay）函数 #

19. 函数分值: 脚本评分 #