ES常见查询示例
ES常见查询示例
guaotianxia
已于2022-04-18 16:32:42修改
17661
收藏
44
文章标签：
elasticsearch
经验分享
于2022-04-18 15:29:33首次发布
环境：es(7.14.0)+kibana(7.14.2)
一、ES查询示例 1、查看es信息GET /
2、创建索引PUT demo_person
3、删除索引DELETE demo_person
说明：
DELETE /index_one,index_two --删除两个索引
DELETE /index_* --删除index_k开头的索引
DELETE /_all --删除全部索引
DELETE /* --删除全部索引
4、创建索引包含setting和mapping PUT demo_person { "settings": { "number_of_shards": 5, "number_of_replicas": 1 }, "mappings": { "properties": { "about": { "type": "text", "fields": { "keyword": { "type": "keyword", "ignore_above": 256 } } }, "age": { "type": "long" }, "first_name": { "type": "text", "fields": { "keyword": { "type": "keyword", "ignore_above": 256 } } }, "interests": { "type": "text", "fields": { "keyword": { "type": "keyword", "ignore_above": 256 } }, "fielddata": true }, "last_name": { "type": "keyword" } } } } 5、修改setting PUT demo_person/_settings { "number_of_replicas" : 2 }只能修改副本分片，主分片在创建索引时确定，后续不可以再次修改
6、修改mapping PUT demo_person/_mapping/_doc?include_type_name=true { "properties":{ "interests":{ "type":"text", "fielddata":true } } } 7、查询总数 GET demo_person/_count { "query": { "match_all": {} } } 8、添加/修改数据 PUT /demo_person/_doc/1 { "first_name" : "John", "last_name" : "Smith", "age" : 25, "about" : "I love to go rock climbing", "interests": [ "sports", "music" ] } 9、批量插入数据 POST demo_person/_bulk {"index":{}} {"first_name":"zhang","last_name":"san","age" :44,"about":"I like to collect hehe albums","interests":["music"]} {"index":{}} {"first_name":"li","last_name":"si","age":12,"about":"I like to drink","interests":["drink"]} 10、查询所有数据 GET demo_person/_search { "query": { "match_all": {} } } 11、查询指定条数 GET demo_person/_search { "size": 20, "query": { "match_all": {} } } 12、根据ID查询GET /demo_person/_doc/1?pretty
13、一个查询字符串搜索GET /demo_person/_search?q=last_name:Smith
14、match搜索 GET /demo_person/_search { "query" : { "match" : { "last_name" : "Smith" } } } 15、term搜索 GET /demo_person/_search { "query": { "term": { "last_name": { "value": "Smith" } } } }基于词项的查询
如 term 或 fuzzy 这样的底层查询不需要分析阶段，它们对单个词项进行操作。用 term 查询词项 Foo 只要在倒排索引中查找 准确词项 ，并且用 TF/IDF 算法为每个包含该词项的文档计算相关度评分 _score 。
记住 term 查询只对倒排索引的词项精确匹配，这点很重要，它不会对词的多样性进行处理（如， foo 或 FOO ）。这里，无须考虑词项是如何存入索引的。如果是将 ["Foo","Bar"] 索引存入一个不分析的（ not_analyzed ）包含精确值的字段，或者将 Foo Bar 索引到一个带有 whitespace 空格分析器的字段，两者的结果都会是在倒排索引中有 Foo 和 Bar 这两个词。
基于全文的查询
像 match 或 query_string 这样的查询是高层查询，它们了解字段映射的信息：
如果查询 日期（date） 或 整数（integer） 字段，它们会将查询字符串分别作为日期或整数对待。
如果查询一个（ not_analyzed ）未分析的精确值字符串字段，它们会将整个查询字符串作为单个词项对待。
但如果要查询一个（ analyzed ）已分析的全文字段，它们会先将查询字符串传递到一个合适的分析器，然后生成一个供查询的词项列表。
16、bool搜索 GET /demo_person/_search { "query": { "bool": { "must": [ {"match": { "last_name": "Smith" }} ], "filter": [ {"range": { "age": { "gte": 30 } }} ] } } }说明：
must: 完全匹配条件 相当于sql中的and
should： 至少满足一个条件 相当于sql中的 or
must_not: 文档必须不匹配条件 相当于sql中的!=
17、must多条件匹配查询 GET /demo_person/_search { "query": { "bool": { "must": [ { "match": { "last_name": "Smith" } }, { "match": { "age": 32 } } ] } } } 18、Should满足一个条件查询 GET /demo_person/_search { "query": { "bool": { "should": [ { "match": { "last_name": "Fir" } }, { "match": { "age": 32 } } ] } } } 19、must_not必须不匹配查询 GET /demo_person/_search { "query": { "bool": { "must_not": [ { "match": { "last_name": "Fir" } }, { "match": { "age": 32 } } ] } } } 20、多个字段查询内容 GET /demo_person/_search { "query": { "multi_match": { "query": "collect rock", "fields": ["last_name","about"] } } } 21、一个字段查询多个内容 GET /demo_person/_search { "query": { "terms": { "about": [ "rock", "hehe" ] } } } 22、通配符和正则匹配 GET /demo_person/_search { "query": { "bool": { "filter": [ { "wildcard":{ "last_name":"*mi*" } }] } } } 23、前缀查询 GET /demo_person/_search { "query": { "prefix": { "last_name": { "value": "Smi" } } } } 24、短语匹配 GET /demo_person/_search { "query" : { "match_phrase" : { "about" : "rock climbing" } } } 25、输入即搜索 GET /demo_person/_search { "query": { "match_phrase_prefix": { "about": "I like to collect" } } } 26、高亮搜索 GET /demo_person/_search { "query" : { "match_phrase" : { "about" : "rock climbing" } }, "highlight": { "fields" : { "about" : {} } } } 27、统计 GET /demo_person/_search { "aggs": { "all_result": { "terms": { "field": "interests" } } } } 28、根据条件统计 GET /demo_person/_search { "query": { "match": { "last_name": "smith" } }, "aggs": { "all_interests": { "terms": { "field": "interests" } } } } 29、获取平均数 GET /demo_person/_search { "aggs" : { "all_interests" : { "terms" : { "field" : "interests" }, "aggs" : { "avg_age" : { "avg" : { "field" : "age" } } } } } } 30、多个字段匹配查询 GET /demo_person/_search { "query": { "multi_match": { "query": "Smith", "fields": ["last_name","about"] } } } 31、范围查询 GET demo_person/_search { "query": { "range": { "age": { "gte": 30, "lt": 35 } } } } 32、排序 GET /demo_person/_search { "query": { "bool": { "must": [ {"term": { "last_name.keyword": { "value": "Smith" } }}, { "term": { "about": { "value": "climbing" } } } ] } }, "sort": [ { "last_name": { "order": "desc" } } ] } 33、删除一条数据DELETE /demo_person/_doc/TC4cJ4ABPbcGgBnacj_w
34、批量删除 POST /_bulk {"delete":{"_index":"demo_person","_id":"1"}} {"delete":{"_index":"demo_person","_id":"12"}} 35、分页查询 GET /demo_person/_search?from=1&size=10 或者 GET /demo_person/_search { "from": 1, "size": 10 }Size：显示应该返回的结果数量，默认是 10
From：显示应该跳过的初始结果数量，默认是 0
36、游标查询 GET /demo_person/_search?scroll=5m { "query": { "match_all": {} }, "sort": [ { "_doc": { "order": "desc" } } ], "size": 1 }然后获取scroll_id继续查询，如下
GET _search/scroll { "scroll":"5m", "scroll_id":"FGluY2x1ZGVfY29udGV4dF91dWlkDnF1ZXJ5VGhlbkZldGNoBRZybzdMSjJ2NVNiV0poWVhwbFEtYmdnAAAAAAEj8FgWV0QzQ0pVQm9URnVBVFpmOGpDSC05QRZybzdMSjJ2NVNiV0poWVhwbFEtYmdnAAAAAAEj8FkWV0QzQ0pVQm9URnVBVFpmOGpDSC05QRZybzdMSjJ2NVNiV0poWVhwbFEtYmdnAAAAAAEj8FoWV0QzQ0pVQm9URnVBVFpmOGpDSC05QRZybzdMSjJ2NVNiV0poWVhwbFEtYmdnAAAAAAEj8FsWV0QzQ0pVQm9URnVBVFpmOGpDSC05QRZybzdMSjJ2NVNiV0poWVhwbFEtYmdnAAAAAAEj8FwWV0QzQ0pVQm9URnVBVFpmOGpDSC05QQ==" } 37、字段存在查询 GET /demo_person/_search { "query": { "exists": {"field": "aa"} } } 38、复杂查询demoDemo1
{ "bool": { "must": { "match": { "tweet": "elasticsearch" }}, "must_not": { "match": { "name": "mary" }}, "should": { "match": { "tweet": "full text" }}, "filter": { "range": { "age" : { "gt" : 30 }} } } }demo2
{ "bool": { "must": { "match": { "email": "business opportunity" }}, "should": [ { "match": { "starred": true }}, { "bool": { "must": { "match": { "folder": "inbox" }}, "must_not": { "match": { "spam": true }} }} ], "minimum_should_match": 1 } }
Demo3
GET /my_store/products/_search { "query" : { "filtered" : { "filter" : { "bool" : { "should" : [ { "term" : {"productID" : "KDKE-B-9947-#kL5"}}, { "bool" : { "must" : [ { "term" : {"productID" : "JODL-X-1937-#pV7"}}, { "term" : {"price" : 30}} ] }} ] } } } } } 39、拷贝索引 POST _reindex { "source": { "index": "twitter" }, "dest": { "index": "new_twitter" } } 40、索引别名PUT /my_index_v1 –创建索引
PUT /my_index_v1/_alias/my_index --创建my_index_v1别名为my_index
GET /*/_alias/my_index –-查看别名指向哪个索引
GET /my_index_v1/_alias/* --查看哪些别名指向此索引
41、查询集群健康GET /_cluster/health
status 字段指示着当前集群在总体上是否工作正常。它的三种颜色含义如下：
green：所有的主分片和副本分片都正常运行。
Yellow：所有的主分片都正常运行，但不是所有的副本分片都正常运行。
Red:有主分片没能正常运行。