| 语法 | 范围 |
| /_search | 集群上所有的索引 |
| /index1/_search | index1 |
| /index1,index2/_search | index1,index2 |
| /index*/_search | 以index开头的索引 |
Term ：Beautiful Mind 等效于 Beautiful OR Mind。使用括号括起来：(Beautiful Mind)
Phrase："Beautiful Mind" 等效于 Beautiful AND Mind 。Phrase查询还要求前后顺序保持一致。使用引号
一、Url Search
在url中使用查询参数
//查询title字段包含2013的 GET movies/_search?q=2012&df=title { "profile": "true" } //查询title字段包含2013的 GET movies/_search?q=title:2012&sort=year:desc&from=0&size=10&timeout=1m { "profile": "true" } //查询所有字段包含2013的 GET movies/_search?q=2012 { "profile": "true" } //PhraseQuery GET movies/_search?q=title:"Beautiful Mind" { "profile": "true" } //TermQuery。两个Term在一起默认是 OR 的关系 GET movies/_search?q=title:(Beautiful Mind) { "profile": "true" } //title 必须包括Beautiful 和 Mind GET movies/_search?q=title:(Beautiful AND Mind) { "profile": "true" } //title 必须包括Beautiful 和 Mind GET movies/_search?q=title:(Beautiful %2BMind) { "profile": "true" } //title 必须包括Beautiful 不能包括Mind GET movies/_search?q=title:(Beautiful NOT Mind) { "profile": "true" } //查询1980以后的电影 GET movies/_search?q=year:>=1980 { "profile": "true" } //title包含b开头的 GET movies/_search?q=title:b* { "profile": "true" } //模糊匹配&近似匹配 GET movies/_search?q=title:beautifl~1 { "profile": "true" } GET movies/_search?q=title:"lord rings"~2 { "profile": "true" }
二、Request Body Search
使用elasticsearch提供的，基于json格式的更加完备的DSL
// 分页查询第一页，每页1条数据 GET kibana_sample_data_ecommerce/_search { "from": 0, "size": 1, "query": { "match_all": {} } } //根据order_date倒序 GET kibana_sample_data_ecommerce/_search { "sort":[{"order_date":"desc"}], "query": { "match_all": {} } } //只返回order_date字段 GET kibana_sample_data_ecommerce/_search { "_source": ["order_date"], "query": {"match_all": {}} } //脚本字段，新增一个new_field字段 GET kibana_sample_data_ecommerce/_search { "script_fields": { "new_field": { "script": { "lang": "painless", "source": "doc['order_date'].value+'_hello'" } } }, "query": {"match_all": {}} } //查询包含Last或者包含Christmas GET movies/_search { "query": { "match": { "title": "Last Christmas" } } , "profile": "true" } //查询即包含Last又包含Christmas GET movies/_search { "query": { "match": { "title": { "query": "Christmas Last", "operator": "and" } } } } //slop 指定中间忽略匹配的数量。搜索出的结果：One I Love, The GET movies/_search { "query": { "match_phrase": { "title":{ "query":"one love", "slop": 1 } } } }
1，Query String&Simple Query String
//title包含Homeward和Bound GET movies/_search { "query": { "query_string": { "default_field": "title", "query": "Homeward AND Bound" } } } //title包含Homeward和Bound 或者 包含Lost和in GET movies/_search { "query": { "query_string": { "default_field": "title", "query": "(Homeward AND Bound) or (Lost and in)" } } } //title包含Homeward和Bound GET movies/_search { "query": { "simple_query_string": { "query": "Homeward Bound", "fields": ["title"], "default_operator": "and" } } }
2，term查询
terms查询是用于结构化数据的查询。全文用match查询。而bool属于一种复合查询。可以结合terms查询和match查询
GET movies/_search { "query": { "term": { "title.keyword": { "value": "Homeward Bound: The Incredible Journey" } } } }
//跳过算分，提高性能 GET movies/_search { "query": { "constant_score": { "filter": { "term": { "title.keyword": { "value": "Homeward Bound: The Incredible Journey" } }} } } }
GET request_audit_logs/_search { "query": { "bool": { "filter": [ {"term": { "url": "http://localhost:18908/api/User/Login" }}, { "match":{ "request_content":"15607172222" } }, { "range": { "request_time": { "gte": "2020-01-01 00:00:00" } } } ] } } }
3，Query&Filtering与多字符多字段查询
gte：大等于
lte：小等于
gt：大于
lt：小于
| must | 必须匹配。贡献算分 |
| should | 选择性匹配。贡献算分 |
| must_not |
Filter Context 查询字句，必须不能匹配 |
| filter |
Filter Context 必须匹配，但不贡献算分 |
GET movies/_search { "query": { "bool": { "must": {"term": {"year":"1960"}}, "filter": {"term":{"title.keyword":"Pollyanna"}}, "must_not":{"range":{"year":{"lte":1961}}}, "should": [ {"term":{"genre.keyword": "Children"}}, {"term":{"genre.keyword": "Comedy"}} ] } } }
//title中包含The并且不包含Good GET movies/_search { "query": { "bool": { "must": [{"match": {"title": "The"}}], "must_not": [{"match": {"title": "Good"}}] } } }
//将title中包含The的语句排在靠前，包含Grifters排在靠后 GET movies/_search { "query": { "boosting": { "positive": {"match": { "title": "The" }}, "negative": {"match": { "title": "Grifters" }}, "negative_boost": 0.5 } } }
4，单字符串多字段查询：Dis Max Query
//1,获取最佳匹配语句的评分_score //2,将其他匹配语句的评分与tie_breaker相乘 //3,对以上评分求和并规范 //tie_breaker是一个介于0-1之间的浮点数。0代表使用最佳匹配；1代表所有语句同等重要 POST blogs/_search { "query": { "dis_max": { "queries": [ { "match": { "title": "Quick pets" }}, { "match": { "body": "Quick pets" }} ], "tie_breaker": 0 } } }
5，单字符串多字段查询：Mult Match
最佳字段（Best Fields）：当字段之间相互竞争，有相互关联。例如title和body这样的字段。评分来自最匹配字段
多数字段（Most Fields）：处理英文内容时：一种常见的手段是，在主字段（English Analyzer），抽取词干，加入同义词，以匹配更多的文档。相同的文本，加入子字段（Standard Analyzer），以提供更加精确的匹配。其他字段作为匹配文档提高相关度的信号。匹配字段越多则越好
混合字段（Corss Fields）：对于某些实体，例如人名、地址、图书信息。需要在多字字段中确定信息，单个字段只能作为整理的一部分。希望在任何这些列出的字段中找到尽可能多的词
POST blogs/_search { "query": { "multi_match": { "type": "best_fields", "query": "Quick pets", "fields": ["title","body"], "tie_breaker": 0.2, "minimum_should_match": "20%" } } }
//英文分词器可以提高算分值，标准分词器可以提高精度 POST titles/_bulk { "index": { "_id": 1 }} { "title": "My dog barks" } { "index": { "_id": 2 }} { "title": "I see a lot of barking dogs on the road " } PUT /titles { "mappings": { "properties": { "title": { "type": "text", "analyzer": "english", "fields": {"std": {"type": "text","analyzer": "standard"}} } } } } GET /titles/_search { "query": { "multi_match": { "query": "barking dogs", "type": "most_fields", "fields": [ "title", "title.std" ] } } }
GET /titles/_search { "query": { "multi_match": { "query": "barking dogs", "type": "cross_fields", "operator": "and", "fields": [ "title", "title.std" ] } } }
6，Search Template与 Index Alias
//删除搜索模版 DELETE _scripts/tmdb //设置搜索模版 POST _scripts/tmdb { "script":{ "lang": "mustache", "source": { "_source":["title"], "size":20, "query":{ "bool": { "must": [ {"term": { "title.keyword":"{{q}}" }} ] } } } } } //使用搜索模版 POST movies/_search/template { "id":"tmdb", "params": { "q":"Lamerica" } } //删除别名 POST _aliases { "actions": [ { "remove": { "index": "movies", "alias": "movies2" } } ] } //设置别名 POST _aliases { "actions": [ { "add": { "index": "movies", "alias": "movies2" } } ] } //使用别名查询 GET movies2/_search
7，Function Score Query优化算分
//fields算分度 * votes POST /blogs/_search { "query": { "function_score": { "query": { "multi_match": { "query": "popularity", "fields": [ "title", "content" ] } }, "field_value_factor": { "field": "votes" } } } } //log（fields算分度 * votes） POST /blogs/_search { "query": { "function_score": { "query": { "multi_match": { "query": "popularity", "fields": [ "title", "content" ] } }, "field_value_factor": { "field": "votes", "modifier": "log1p" } } } }
8，Term Suggester与Phrese Suggester
missing 如索引中已经存在，就不建议提供
popular 推荐出现频率更加高的词
always 无论是否存在，都提供建议
POST /articles/_search { "size": 1, "query": { "match": { "body": "lucen rock" } }, "suggest": { "term": { "text": "lucen rock", "term": { "suggest_mode": "missing", "field": "body" } } } }
phrase多增加了几个参数
max_errors 最多可以拼错的terms数
confidence 限制返回的结果数
POST /articles/_search { "suggest": { "my-suggestion": { "text": "lucne and elasticsear rock hello world ", "phrase": { "field": "body", "max_errors":2, "confidence":0, "direct_generator":[{ "field":"body", "suggest_mode":"always" }], "highlight": { "pre_tag": "<em>", "post_tag": "</em>" } } } } }
9，自动补全与基于上下文的提示
DELETE articles //设置mapper PUT articles { "mappings": { "properties": { "title_completion":{ "type": "completion" } } } } POST articles/_bulk { "index" : { } } { "title_completion": "lucene is very cool"} { "index" : { } } { "title_completion": "Elasticsearch builds on top of lucene"} { "index" : { } } { "title_completion": "Elasticsearch rocks"} { "index" : { } } { "title_completion": "elastic is the company behind ELK stack"} { "index" : { } } { "title_completion": "Elk stack rocks"} { "index" : {} } POST articles/_search?pretty { "size": 0, "suggest": { "article-suggester": { "prefix": "elk", "completion": { "field": "title_completion" } } } } GET comments/_search DELETE comments PUT comments //设置mapper，多了contexts PUT comments/_mapping { "properties": { "comment_autocomplete":{ "type": "completion", "contexts":[{ "type":"category", "name":"comment_category" }] } } } POST comments/_doc { "comment":"I love the star war movies", "comment_autocomplete":{ "input":["star wars"], "contexts":{ "comment_category":"movies" } } } POST comments/_doc { "comment":"Where can I find a Starbucks", "comment_autocomplete":{ "input":["starbucks"], "contexts":{ "comment_category":"coffee" } } } POST comments/_search { "suggest": { "MY_SUGGESTION": { "prefix": "sta", "completion":{ "field":"comment_autocomplete", "contexts":{ "comment_category":"coffee" } } } } }