Elasticsearch查询的基本使用

#初始化准备（创建库和user）
#创建表
PUT /libzyh

{

“settings”:{

“number_of_shards” : 3,

“number_of_replicas” : 0

},

“mappings”:{

“user”:{

“properties”:{

“name”: {“type”:“text”},

“address”: {“type”:“text”},

“age”: {“type”:“integer”},

“interests”: {“type”:“text”},

“birthday”: {“type”:“date”}

}

}

}

}

#添加user
PUT /libzyh/user/1
{

“name”:“zhangsan”,

“address”:“bei jing chang ping qu sha yang lu”,

“age”:19,

“birthday”:“2000-10-12”,

“interests”:“xi huan hejiu,duanlian,lvyou”

}

PUT /libzyh/user/2
{

“name”:“lisi”,

“address”:“bei jing chang ping qu sha yang lu”,

“age”:18,

“birthday”:“2001-10-12”,

“interests”:“xi huan tingyinyue,changge,tiaowu”

}

PUT /libzyh/user/3
{

“name”:“wangwu”,

“address”:“bei jing chang ping qu sha yang lu”,

“age”:33,

“birthday”:“1986-10-12”,

“interests”:“xi huan meinv,meinv,meinv”

}

PUT /libzyh/user/4
{

“name”:“zhaoliu”,

“address”:“bei jing chang ping qu sha yang lu”,

“age”:31,

“birthday”:“1988-10-12”,

“interests”:“xi huan hejiu,wanyouxi,shuijiao”

}
PUT /libzyh/user/6
{

“name”:“lvyou”,

“address”:“bei jing chang ping qu sha yang lu,lvyou”,

“age”:32,

“birthday”:“1987-10-12”,

“interests”:“xi huan chifan,shuijiao,dadoudou,changge”

}

#查询所有
GET /libzyh/_search
#查询name为lisi的
GET /libzyh/_search?q=name:lisi
#查询年龄为18的
GET /libzyh/_search?q=age:18

#获取interests字段中有changge的
GET /libzyh/user/_search/
{

“query”: {

“term”: {“interests”: “changge”}

}

}

#from size 相当于sql语句中的limit
GET /libzyh/user/_search/
{
“from”: 0,
“size”: 1,
“query”: {

“term”: {“interests”: “changge”}

}

}

#显示数据的版本
GET /libzyh/user/_search/
{
“from”: 0,
“size”: 1,
“version”: true,
“query”: {

“term”: {“interests”: “changge”}

}

}

#匹配name为lisi的
GET /libzyh/user/_search/
{
“from”: 0,
“size”: 1,
“version”: true,
“query”: {
“match”: {
“name”: “lisi”
}
}

}

#查询user表中的所有
GET /libzyh/user/_search/
{
“version”: true,
“query”: {
“match_all”: {}
}
}

#多个匹配，query：匹配词语，field在哪个区域查询
GET /libzyh/user/_search
{
“query”:{
“multi_match”: {
“query”: “lvyou”,
“fields”: [“interests”,“name”]
}
}
}

#中的所有分词，并且保证各个分词的相对位置不变：，匹配interests字段中同时含有这两个词的user

GET libzyh/user/_search
{

“query”:{

“match_phrase”:{

“interests”: “duanlian，shuoxiangsheng”
}}}

#返回指定字段address，和name
GET /libzyh/user/_search
{

“_source”: [“address”,“name”],

“query”: {

“match”: {

“interests”: “changge”
}
}
}

#控制加载字段
GET /libzyh/user/_search
{

“query”: {

“match_all”: {}

},

“_source”: {

“includes”: [“name”,“address”],

“excludes”: [“age”,“birthday”]

}
}

#还可以使用通配符*
GET /libzyh/user/_search
{

“_source”: {

“includes”: “addr*”,

“excludes”: [“name”,“bir*”]

},

“query”: {

“match_all”: {}
}
}
DELETE lib3
#按照年龄的升序排序
GET /libzyh/user/_search
{

“query”: {

“match_all”: {}

},

“sort”: [

{

“age”: {

“order”:“asc”

}

}

]

}

#前缀查询，查询所有name以zhao开头
GET /libzyh/user/_search
{

“query”: {

“match_phrase_prefix”: {

“name”: {

“query”: “zhao”

}

}

}

}

#查询生日在这两个之间的
GET /libzyh/user/_search
{

“query”: {

  "range": {

    "birthday": {

        "from": "1990-10-10",

            "to": "2018-05-01"

}

}

}

}

#查询n年龄在20-25之间的user include_lower是否包含最小值，
#"include_upper"是否包含最大值
GET /libzyh/user/_search
{

“query”: {

“range”: {

“age”: {

“from”: 1,

“to”: 25,

“include_lower”: true,

“include_upper”: false

}

}

}

}

#wildcard通配查询，*代表多个字符，与sql查询中的%类似
#？代表单个字符，与sql查询中_相似只能匹配一个字符
GET /libzyh/user/_search
{

“query”: {

“wildcard”: {

“name”: “zhao*”

}

}

}

#查询name为lvyo？的user
GET /libzyh/user/_search
{

“query”: {

“wildcard”: {

“name”: “lvyo?”

}

}

}

#fuzzy实现模糊查询 就算有一点不一样也可以匹配的到
GET /libzyh/user/_search
{

“query”: {

“fuzzy”: {

“interests”: “chagge”

}

}

}

亮的区域, 般和查询的位置 致

GET /libzyh/user/_search
{

“query”:{

“match”:{

“interests”: “changge”

}

},

“highlight”: {

“fields”: {

“interests”: {}

}

}

}

#Filter查询
#filter是不计算相关性的，同时可以cache。因此，filter速度要快于query。测试，先创建一个表
DELETE /lib12
POST /lib12/items/_bulk
{“index”: {"_id": 1}}
{“price”: 40,“itemID”: “ID100123”}
{“index”: {"_id": 2}}
{“price”: 50,“itemID”: “ID100124”}
{“index”: {"_id": 3}}
{“price”: 25,“itemID”: “ID100124”}
{“index”: {"_id": 4}}
{“price”: 30,“itemID”: “ID100125”}
{“index”: {"_id": 5}}
{“price”: null,“itemID”: “ID100127”}

#过滤出价格为40的所有结果
GET /lib12/items/_search
{

“post_filter”: {

“term”: {

“price”: 40

}

}

}

#过滤出价格是25或40的所有结果
GET /lib12/items/_search
{

“post_filter”: {

“terms”: {

“price”: [25,40]

}

}

}

#因为itemid被分词索引了,如果使 term.需要加.keyword
GET /lib12/items/_search
{

“post_filter”: {

“term”: {

“itemID.keyword”: “ID100123”

}

}

}

#同上而match则不用
GET /lib12/items/_search
{

“post_filter”: {

“match”: {

“itemID”: “ID100123”

}

}

}

#查看分词索引
GET /lib12/_mapping