Elasticsearch --- 2. 常用操作
0.创建
PUT s1/doc/1 { "name":"张三", "age":"23", "sex":"男" } PUT s1/doc/2 { "name":"李四", "age":"30", "sex":"男" } PUT s1/doc/3 { "name":"小六", "age":"18", "sex":"女" }
GET s1/doc/_search #查询所有
GET s1/doc/1 #指定查询
1.两种条件查询方式
①字符串查询
GET s1/doc/_search?q=age:23
②结构化查询(DSL)
#1.match
GET s1/doc/_search
{
"query": {
"match": {
"age": "23"
}
}
}
#2.match_all
GET s18/doc/_search #查询所有
{
"query": {
"match_all": {}
}
}
#3.match_phrase (短语查询)
①
GET t1/doc/_search
{
"query": {
"match_phrase": {
"title": {
"query": "中国"
} } } }
②两个词组之间有了2个词的间隔
GET t1/doc/_search {
"query": {
"match_phrase": {
"title": {
"query": "中国世界",
"slop": 2
} } } }
#4.match_phrase_prefix（最左前缀查询）
GET t3/doc/_search {
"query": {
"match_phrase_prefix": {
"desc": "bea"
} } }
#5.multi_match(多字段查询)(与must效果一致)
GET t3/doc/_search {
"query": {
"multi_match": {
"query": "beautiful",
"fields": ["title", "desc"]
} } }
2.修改指定字段
#只修改文档1中的 "age" ,其他不变
POST s1/doc/1/_update { "doc":{ "age":25 } }
3.排序sort
#降序
GET s1/doc/_search { "query": { "match_all": {} }, "sort": [ { "age": { "order": "desc" } } ] }
#升序
GET s1/doc/_search { "query": { "match_all": {} }, "sort": [ { "age": { "order": "asc" } } ] }
4.分页
#按索引从1的位置开始查,查2个
GET s1/doc/_search { "query": { "match_all": {} }, "from": 1, "size": 2 }
5.布尔查询:
1.should(or),must(and),must_not(not)
#①查询姓名是"张三",或者年龄是"18"的
GET s1/doc/_search { "query": { "bool": { "should": [ { "match": { "name": "张三" } }, { "match": { "age": "18" } } ] } } }
#②查询出年龄是30的男性
GET s1/doc/_search { "query": { "bool": { "must": [ { "match": { "sex": "男" } }, { "match": { "age": "30" } } ] } } }
#③查询出既不是男性,又不是30岁的
GET s1/doc/_search { "query": { "bool": { "must_not": [ { "match": { "sex": "男" } }, { "match": { "age": "30" } } ] } } }
2.大于(gt),大于等于(gte),小于(lt),小于等于(lte)
#①大于(其他类似)
查询大于25岁的男性
GET s1/doc/_search { "query": { "bool": { "must": [ { "match": { "sex": "男" } } ], "filter": { "range": { "age": { "gt": 25 } } } } } }
#②查询小于25岁的非男性
GET s1/doc/_search { "query": { "bool": { "must_not": [ { "match": { "sex": "男" } } ], "filter": { "range": { "age": { "lt": 25 } } } } } }
6.高亮查询
PUT s2/doc/1 { "name":"wangdi", "desc": "骚的打漂" } GET s2/doc/_search { "query": { "match": { "desc": "打漂" } }, "highlight": { #高亮显示查询的结果 "pre_tags": "<b style='color:red;font-size:20px;' class='wangdi'>", "post_tags": "</b>", "fields": { "desc": {} } } }
7.结果过滤
#①只将结果的姓名显示
GET s1/doc/_search { "query": { "match": { "name": "张三" } }, "_source": "name" }
#②将结果的姓名和年龄显示
GET s1/doc/_search { "query": { "match": { "name": "张三" } }, "_source": ["name","age"] }
8.聚合查询(sum,max,min,avg)
求男性的年龄总和
GET s1/doc/_search { "query": { "match": { "sex": "男" } }, "aggs":{ "my_sum":{ "sum": { "field": "age" } } } }
求男性的最大值
GET s1/doc/_search { "query": { "match": { "sex": "男" } }, "aggs":{ "my_max":{ "max": { "field": "age" } } } }
# 求所有人的平均值 avg GET s1/doc/_search { "aggs": { "my_avg": { "avg": { "field": "age" } } } }
9.分组
#根据年龄，10-20，,20-30， 30-50 进行分组
GET s1/doc/_search { "aggs": { "my_group":{ "range": { "field": "age", "ranges": [ { "from": 10, "to": 20 }, { "from": 20, "to": 30 }, { "from": 30, "to": 50 } ] } } } }
对分组结果进行求和
GET s1/doc/_search { "aggs": { "my_group":{ "range": { "field": "age", "ranges": [ { "from": 10, "to": 20 }, { "from": 20, "to": 30 }, { "from": 30, "to": 50 } ] }, "aggs":{ "my_sum":{ "sum":{ "field":"age" } } } } } }
10.映射(mappings)
自定义表结构
简单类型，如文本（text）、关键字（keyword）、日期（data）、整形（long）、
双精度（double）、布尔（boolean）或ip。
可以是支持JSON的层次结构性质的类型，如对象或嵌套。
或者一种特殊类型，如geo_point、geo_shape或completion。
①基本的映射(可添加新字段,es自动生成)
PUT s3 { "mappings": { "doc":{ "properties":{ "name":{ "type":"text" }, "age":{ "type":"long" }, "desc":{ "type":"text" } } } } } GET s3/_mapping
GET s3
②dynamic的三种状态
#① true 状态(默认状态,可以添加新字段,可建立新映射关系,)
PUT s4 { "mappings": { "doc":{ "dynamic": true, "properties":{ "name":{ "type":"text" } } } } }
② false 状态(可建立新字段,不能建立新的映射关系,不能做查询的条件,伴随主查询条件出现)
PUT s5 { "mappings": { "doc":{ "dynamic": false, "properties":{ "name":{ "type":"text" } } } } }
③ strict 状态(严格类型,不可添加新字段)
PUT s6 { "mappings": { "doc":{ "dynamic":"strict", "properties":{ "name":{ "type":"text" } } } } }
③ ignore_above(限制字节数)
超过时不能进行搜索(索引),但会插入数据
PUT s7 { "mappings": { "doc":{ "properties":{ "title":{ "type":"keyword", "ignore_above": 10 } } } } }
④ index()
# true:可以对该字段(作为主查询)进行搜索 (默认)
# false: 不能对该字段作为搜索条件 进行搜索
PUT s8 { "mappings": { "doc":{ "properties":{ "t1":{ "type":"text", "index": true }, "t2":{ "type":"text", "index": false } } } } }
⑤copy_to 复制属性
该属性允许我们将多个字段的值复制到组字段中，然后将组字段作为单个字段进行查询
建立映射
PUT s9 { "mappings": { "doc":{ "properties":{ "t1":{ "type":"text", "copy_to":"full_name" }, "t2":{ "type":"text", "copy_to":"full_name" }, "full_name":{ "type":"text" } } } } }
插入数据
PUT s9/doc/1 { "t1":"xxx", "t2":"ooo" }
进行查询两种方式
GET s9/doc/_search { "query": { "match": { "t1": "xxx" } } } GET s9/doc/_search { "query": { "match": { "full_name": "xxx" } } }
⑥多层嵌套(内套在加peoperties)
PUT w1 { "mappings": { "doc":{ "properties":{ "name":{ "type":"text" }, "age":{ "type":"long" }, "info":{ "properties":{ "addr":{ "type":"text" }, "tel":{ "type":"long" } } } } } } }
插入数据
PUT w1/doc/2 { "name":"tom", "age":"18", "info":{ "addr":"北京", "tel":"10010" } }
查询嵌套的条件
GET w1/doc/_search { "query": { "match": { "info.tel": "10010" } } }
⑦settings(设置主,副分片)
PUT w2 { "mappings": { "doc":{ "properties":{ "title":{ "type":"text" } } } }, "settings": { "number_of_shards": 3, #主 "number_of_replicas": 3 #副 } }
