ES常见查询示例

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demo

Demo1

{"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。

Published by

风君子

独自遨游何稽首 揭天掀地慰生平

发表回复

您的电子邮箱地址不会被公开。 必填项已用 * 标注