mysql用作持久化存储，ES用作检索
- index索引
类比mysql的数据库概念
- Type类型
类比mysql的表概念
- document文档
类比mysql的记录概念
index库>type表>document文档
- 为什么ES搜索快？倒排索引
检索： 1 红海特工行动？查出后计算相关性得分：3号记录命中了2次，且3号本身才有3个单词，2/3，所以3号最匹配 2 红海行动？ 关系型数据库中两个数据表示是独立的，即使他们里面有相同名称的列也不影响使用，但ES中不是这样的。 elasticsearch是基于Lucene开发的搜索引擎，而ES中不同type下名称相同的filed最终在Lucene中的处理方式是一样的。 • 两个不同type下的两个user_name，在ES同一个索引下其实被认为是同一个filed，你必须在两个不同的type中定义相同的filed映射。 否则，不同type中的相同字段名称就会在处理中出现冲突的情况，导致Lucene处理效率下降。去掉type就是为了提高ES处理数据的效率。 Elasticsearch 7.x URL中的type参数为可选。比如，索引一个文档不再要求提供文档类型。 Elasticsearch 8.x 不再支持URL中的type参数。 解决： 将索引从多类型迁移到单类型，每种类型文档一个独立索引
二、Docket安装ES 1、dokcer中安装elastic search
下载ealastic search（存储和检索）和kibana（可视化检索）
docker pull elasticsearch:7.4.2 docker pull kibana:7.4.2
注意版本要统一
2、配置
# 将docker里的目录挂载到linux的/usr/local/elasticsearch/data目录中，修改/mydata就可以改掉docker里的 mkdir -p /mydata/elasticsearch/config mkdir -p /mydata/elasticsearch/data # es可以被远程任何机器访问 echo "http.host: 0.0.0.0" >/mydata/elasticsearch/config/elasticsearch.yml # 递归更改权限，es需要访问 chmod -R 777 /mydata/elasticsearch/
3、启动Elastic search
# 9200是用户交互端口 9300是集群心跳端口 # -e指定是单阶段运行 # -e指定占用的内存大小，生产时可以设置32G sudo docker run --name elasticsearch -p 9200:9200 -p 9300:9300 -e "discovery.type=single-node" -e ES_JAVA_OPTS="-Xms64m -Xmx512m" -v /mydata/elasticsearch/config/elasticsearch.yml:/usr/share/elasticsearch/config/elasticsearch.yml -v /mydata/elasticsearch/data:/usr/share/elasticsearch/data -v /mydata/elasticsearch/plugins:/usr/share/elasticsearch/plugins -d elasticsearch:7.4.2
查看是否启动成功
docker ps
4、安装kibana
- 拉去kibana，注意版本对应
docker pull kibana:7.4.2
- 启动kibana
sudo docker run --name kibana -e ELASTICSEARCH_HOSTS=http://192.168.109.101:9200 -p 5601:5601 -d kibana:7.4.2
5、测试
- 查看elasticsearch版本信息：http://192.168.109.101:9200
- 显示elasticsearch节点信息：http://192.168.109.101:9200/_cat/nodes
127.0.0.1 14 92 29 0.48 0.96 0.60 dilm * 4fe4e202abf1 # 4fe4e202abf1代表上面的结点 *代表是主节点
- 访问Kibana：http://192.168.109.101:5601/app/kibana
6、初步检索
- _CAT
GET /_cat/nodes #查看所有节点 127.0.0.1 15 93 8 0.18 0.55 0.52 dilm * 4fe4e202abf1
GET /_cat/health #查看es健康状况 1633079094 09:04:54 elasticsearch green 1 1 3 3 0 0 0 0 - 100.0% # 注：green表示健康值正常
GET /_cat/master #查看主节点 Y9zawKrWSQWvFBx0wVi94g 127.0.0.1 127.0.0.1 4fe4e202abf1 # 主节点唯一编号 # 虚拟机地址
GET /_cat/indicies #查看所有索引,等价于mysql数据库的show databases green open .kibana_task_manager_1 DhtDmKrsRDOUHPJm1EFVqQ 1 0 2 3 40.8kb 40.8kb green open .apm-agent-configuration vxzRbo9sQ1SvMtGkx6aAHQ 1 0 0 0 230b 230b green open .kibana_1 rdJ5pejQSKWjKxRtx-EIkQ 1 0 5 1 18.2kb 18.2kb #这3个索引是kibana创建的
- PUT
必须携带id
#索引一个文档
#保存一个数据，保存在哪个索引的哪个类型下（哪张数据库哪张表下），保存时用唯一标识指定
put /achang/user/1 #这里的1是指定了id为1
{
"name":"achang",
"age":"18"
}
{
"_index" : "achang", #表明该数据在哪个数据库下
"_type" : "user", #表明该数据在哪个类型下
"_id" : "1", #表明被保存数据的id
"_version" : 1, #被保存数据的版本
"result" : "created",#这里是创建了一条数据，如果重新put一条数据，则该状态会变为updated，并且版本号也会发生变化。
"_shards" : { #分片，集群的情况下
"total" : 2,
"successful" : 1,
"failed" : 0
},
"_seq_no" : 0, #并发控制字段，每次更新都会+1，用来做乐观锁
"_primary_term" : 1 #主分片重新分配，如重启，就会变化
}
- GET
get /achang/user/1
{
"_index" : "achang",
"_type" : "user",
"_id" : "1",
"_version" : 2,
"_seq_no" : 1,
"_primary_term" : 1,
"found" : true,
"_source" : { #真正的数据
"name" : "achang",
"age" : "20"
}
}
- 乐观锁
通过“if_seq_no=1&if_primary_term=1”，当序列号匹配的时候，才进行修改，否则不修改。
#如下两个请求并发发出
put /achang/user/1?if_seq_no=1&if_primary_term=1
{
"name" : "achang1"
}
put /achang/user/1?if_seq_no=1&if_primary_term=1
{
"name" : "achang2"
}
#再次查询，发现name被改成了achang1
get /achang/user/1
{
"_index" : "achang",
"_type" : "user",
"_id" : "1",
"_version" : 3,
"_seq_no" : 2,
"_primary_term" : 1,
"found" : true,
"_source" : {
"name" : "achang1"
}
}
- _update
POST customer/externel/1/_update
{
"doc":{
"name":"111"
}
}
#或者
POST customer/externel/1
{
"doc":{
"name":"222"
}
}
#或者
PUT customer/externel/1
{
"doc":{
"name":"222"
}
}
不同：
带有update情况下 POST操作会对比源文档数据，如果相同不会有什么操作，文档version不增加。
PUT操作总会重新保存并增加version版本
POST时带_update对比元数据如果一样就不进行任何操作。
看场景：
- 对于大并发更新，不带update
- 对于大并发查询偶尔更新，带update；对比更新，重新计算分配规则
- POST更新文档，带有_update
- 删除文档或索引
DELETE customer/external/1 DELETE customer #注：elasticsearch并没有提供删除类型的操作，只提供了删除索引和文档的操作。
#实例：删除整个costomer索引数据
#删除前，所有的索引
get /_cat/indices
green open .kibana_task_manager_1 DhtDmKrsRDOUHPJm1EFVqQ 1 0 2 0 31.3kb 31.3kb
green open .apm-agent-configuration vxzRbo9sQ1SvMtGkx6aAHQ 1 0 0 0 283b 283b
green open .kibana_1 rdJ5pejQSKWjKxRtx-EIkQ 1 0 8 3 28.8kb 28.8kb
yellow open customer mG9XiCQISPmfBAmL1BPqIw 1 1 9 1 8.6kb 8.6kb
#删除 “customer”索引
DELTE /customer
#响应
{
"acknowledged": true
}
#删除后，所有的索引/_cat/indices
green open .kibana_task_manager_1 DhtDmKrsRDOUHPJm1EFVqQ 1 0 2 0 31.3kb 31.3kb
green open .apm-agent-configuration vxzRbo9sQ1SvMtGkx6aAHQ 1 0 0 0 283b 283b
green open .kibana_1 rdJ5pejQSKWjKxRtx-EIkQ 1 0 8 3 28.8kb 28.8kb
- ES的批量操作——bulk
#匹配导入数据
post /customer/external/_bulk
{"index":{"_id":"1"}}#两行为一个整体
{"name":"a"}#真正的数据
{"index":{"_id":"2"}}#两行为一个整体
{"name":"b"}#真正的数据
#语法格式：
post /xxxxx/xxxxx/_bulk
{action:{metadata}}n
{request body }n
{action:{metadata}}n
{request body }n
这里的批量操作，当发生某一条执行发生失败时，其他的数据仍然能够接着执行，也就是说彼此之间是独立的。
bulk api以此按顺序执行所有的action（动作）。如果一个单个的动作因任何原因失败，它将继续处理它后面剩余的动作。当bulk api返回时，它将提供每个动作的状态（与发送的顺序相同），所以您可以检查是否一个指定的动作是否失败了。
#实例1: 执行多条数据
POST /customer/external/_bulk
{"index":{"_id":"1"}}
{"name":"John Doe"}
{"index":{"_id":"2"}}
{"name":"John Doe"}
#保存操作，指定了索引、id，真正的数据未name：xxx
#执行结果
{
"took" : 318, #花费了多少ms
"errors" : false, #没有发生任何错误
"items" : [ #每个数据的结果
{
"index" : { #保存
"_index" : "customer", #索引
"_type" : "external", #类型
"_id" : "1", #文档
"_version" : 1, #版本
"result" : "created", #创建
"_shards" : {
"total" : 2,
"successful" : 1,
"failed" : 0
},
"_seq_no" : 0,
"_primary_term" : 1,
"status" : 201 #新建完成
}
},
{
"index" : { #第二条记录
"_index" : "customer",
"_type" : "external",
"_id" : "2",
"_version" : 1,
"result" : "created",
"_shards" : {
"total" : 2,
"successful" : 1,
"failed" : 0
},
"_seq_no" : 1,
"_primary_term" : 1,
"status" : 201
}
}
]
}
#实例2：对于整个索引执行批量操作
POST /_bulk
{"delete":{"_index":"website","_type":"blog","_id":"123"}}#删除操作
{"create":{"_index":"website","_type":"blog","_id":"123"}}#保存操作，下面是数据
{"title":"my first blog post"}
{"index":{"_index":"website","_type":"blog"}}#保存操作，下面的是数据
{"title":"my second blog post"}
{"update":{"_index":"website","_type":"blog","_id":"123"}}#更新操作
{"doc":{"title":"my updated blog post"}}
#指定操作，索引，类型，id
#运行结果：
{
"took" : 414,
"errors" : false,
"items" : [
{
"delete" : {
"_index" : "website",
"_type" : "blog",
"_id" : "123",
"_version" : 1,
"result" : "not_found",
"_shards" : {
"total" : 2,
"successful" : 1,
"failed" : 0
},
"_seq_no" : 0,
"_primary_term" : 1,
"status" : 404
}
},
{
"create" : {
"_index" : "website",
"_type" : "blog",
"_id" : "123",
"_version" : 2,
"result" : "created",
"_shards" : {
"total" : 2,
"successful" : 1,
"failed" : 0
},
"_seq_no" : 1,
"_primary_term" : 1,
"status" : 201
}
},
{
"index" : {
"_index" : "website",
"_type" : "blog",
"_id" : "AOpgO3wB3UIR4wi8SrO8",
"_version" : 1,
"result" : "created",
"_shards" : {
"total" : 2,
"successful" : 1,
"failed" : 0
},
"_seq_no" : 2,
"_primary_term" : 1,
"status" : 201
}
},
{
"update" : {
"_index" : "website",
"_type" : "blog",
"_id" : "123",
"_version" : 3,
"result" : "updated",
"_shards" : {
"total" : 2,
"successful" : 1,
"failed" : 0
},
"_seq_no" : 3,
"_primary_term" : 1,
"status" : 200
}
}
]
}
- 样本测试数据
准备了一份顾客银行账户信息的虚构的JSON文档样本。每个文档都有下列的schema（模式）。
{
"account_number": 1,
"balance": 39225,
"firstname": "Amber",
"lastname": "Duke",
"age": 32,
"gender": "M",
"address": "880 Holmes Lane",
"employer": "Pyrami",
"email": "amberduke@pyrami.com",
"city": "Brogan",
"state": "IL"
}
https://gitee.com/xlh_blog/common_content/blob/master/es%E6%B5%8B%E8%AF%95%E6%95%B0%E6%8D%AE.json;导入测试数据
POST bank/account/_bulk #上面的数据
get /_cat/indices #刚导入了1000条
- 让Docker每次启动都自动启动ES
sudo docker update 【实例ID】 --restart=always
[root@s1 elasticsearch]# sudo docker ps -a ConTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES 5c43fff82773 kibana:7.4.2 "/usr/local/bin/dumb…" 2 hours ago Up 2 hours 0.0.0.0:5601->5601/tcp, :::5601->5601/tcp kibana 4fe4e202abf1 elasticsearch:7.4.2 "/usr/local/bin/dock…" 2 hours ago Up 2 hours 0.0.0.0:9200->9200/tcp, :::9200->9200/tcp, 0.0.0.0:9300->9300/tcp, :::9300->9300/tcp elasticsearch 879b641ebe6c redis "docker-entrypoint.s…" 11 days ago Up 2 hours 0.0.0.0:6379->6379/tcp, :::6379->6379/tcp redis b2b889f90cd9 mysql:5.7 "docker-entrypoint.s…" 11 days ago Up 2 hours 0.0.0.0:3306->3306/tcp, :::3306->3306/tcp, 33060/tcp mysql [root@s1 elasticsearch]# sudo docker update 5c4 --restart=always 5c4 [root@s1 elasticsearch]# sudo docker update 4fe --restart=always 4fe三、进阶检索
官方API：
https://www.elastic.co/guide/en/elasticsearch/reference/7.x/search-your-data.html
1、search Api
- 通过REST request uri 发送搜索参数 （uri +检索参数）；
- 通过REST request body 来发送它们（uri+请求体）；
- 请求参数方式检索
检索bank索引中查询全部，并按account_number升序排序;
检索了1000条数据，但是根据相关性算法，只返回10条
GET bank/_search?q=*&sort=account_number:asc # q=* 查询所有 # sort 排序字段 # asc升序
检索bank下所有信息，包括type和docs
GET bank/_search
返回格式
took – 花费多少ms搜索 timed_out – 是否超时 _shards – 多少分片被搜索了，以及多少成功/失败的搜索分片 max_score –文档相关性最高得分 hits.total.value - 多少匹配文档被找到 hits.sort - 结果的排序key，没有的话按照score排序 hits._score - 相关得分 (not applicable when using match_all)
- uri+请求体进行检索
GET /bank/_search
{
"query": { "match_all": {} },
"sort": [
{ "account_number": "asc" },
{"balance":"desc"}
]
}
2、Query DSL
什么get的请求体叫query DSL
-
基本语法格式
Elasticsearch提供了一个可以执行查询的Json风格的DSL(domain-specific language领域特定语言)。这个被称为Query DSL，该查询语言非常全面。
- 典型结构
QUERY_NAME:{ ARGUMENT:VALUE, ARGUMENT:VALUE, ... }如果针对于某个字段，那么它的结构如下：
{ QUERY_NAME:{ FIELD_NAME:{ ARGUMENT:VALUE, ARGUMENT:VALUE,... } } }- 示例
GET bank/_search { "query": { #查询形式 "match_all": {} #查询所有 }, "from": 0, #开始位置 "size": 5, #显示数 "_source":["balance"],#返回部分字段 "sort": [ #排序 { "account_number": { "order": "desc" } } ] } # _source为要返回的字段
-
基本类型（非字符串），精确控制
GET bank/_search { "query": { "match": { "account_number": "999" } } }
查询结果
{
"took" : 8,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 1,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "bank",
"_type" : "account",
"_id" : "999",
"_score" : 1.0,
"_source" : {
"account_number" : 999,
"balance" : 6087,
"firstname" : "Dorothy",
"lastname" : "Barron",
"age" : 22,
"gender" : "F",
"address" : "499 Laurel Avenue",
"employer" : "Xurban",
"email" : "dorothybarron@xurban.com",
"city" : "Belvoir",
"state" : "CA"
}
}
]
}
}
- 字符串，全文检索
GET bank/_search
{
"query": {
"match": {
"address": "kings" #字符串
}
}
}
全文检索，最终会按照评分进行排序，会对检索条件进行分词匹配。
{
"took" : 9,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 2,
"relation" : "eq"
},
"max_score" : 5.9908285,
"hits" : [
{
"_index" : "bank",
"_type" : "account",
"_id" : "20",
"_score" : 5.9908285,
"_source" : {
"account_number" : 20,
"balance" : 16418,
"firstname" : "Elinor",
"lastname" : "Ratliff",
"age" : 36,
"gender" : "M",
"address" : "282 Kings Place", #分词匹配
"employer" : "Scentric",
"email" : "elinorratliff@scentric.com",
"city" : "Ribera",
"state" : "WA"
}
},
{
"_index" : "bank",
"_type" : "account",
"_id" : "722",
"_score" : 5.9908285,
"_source" : {
"account_number" : 722,
"balance" : 27256,
"firstname" : "Roberts",
"lastname" : "Beasley",
"age" : 34,
"gender" : "F",
"address" : "305 Kings Hwy",#分词匹配
"employer" : "Quintity",
"email" : "robertsbeasley@quintity.com",
"city" : "Hayden",
"state" : "PA"
}
}
]
}
}
4、match_phrase 【短句匹配】
- match_phrase
将需要匹配的值当成一整个单词（不分词）进行检索
前面的是包含mill或road就查出来，我们现在要都包含才查出
GET bank/_search
{
"query": {
"match_phrase": {
"address": "mill road"
}
}
}
查处address中包含mill road的所有记录，并给出相关性得分
{
"took" : 50,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 1,
"relation" : "eq"
},
"max_score" : 8.926605,
"hits" : [
{
"_index" : "bank",
"_type" : "account",
"_id" : "970",
"_score" : 8.926605,
"_source" : {
"account_number" : 970,
"balance" : 19648,
"firstname" : "Forbes",
"lastname" : "Wallace",
"age" : 28,
"gender" : "M",
"address" : "990 Mill Road",
"employer" : "Pheast",
"email" : "forbeswallace@pheast.com",
"city" : "Lopezo",
"state" : "AK"
}
}
]
}
}
- match_phrase和match的区别，观察如下实例
GET bank/_search
{
"query": {
"match_phrase": {
"address": "990 Mill"
}
}
}
结果
{
"took" : 1,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 1,
"relation" : "eq"
},
"max_score" : 10.806405,
"hits" : [
{
"_index" : "bank",
"_type" : "account",
"_id" : "970",
"_score" : 10.806405,
"_source" : {
"account_number" : 970,
"balance" : 19648,
"firstname" : "Forbes",
"lastname" : "Wallace",
"age" : 28,
"gender" : "M",
"address" : "990 Mill Road", #
"employer" : "Pheast",
"email" : "forbeswallace@pheast.com",
"city" : "Lopezo",
"state" : "AK"
}
}
]
}
}
使用match的keyword
GET bank/_search
{
"query": {
"match": {
"address.keyword": "990 Mill"
}
}
}
查询结果，一条也未匹配到
{
"took" : 0,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 0,
"relation" : "eq"
},
"max_score" : null,
"hits" : [ ] #
}
}
修改匹配条件为“990 Mill Road”
GET bank/_search
{
"query": {
"match": {
"address.keyword": "990 Mill Road"
}
}
}
修改匹配条件为“990 Mill Road”
{
"took" : 0,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 1,
"relation" : "eq"
},
"max_score" : 6.5032897,
"hits" : [
{
"_index" : "bank",
"_type" : "account",
"_id" : "970",
"_score" : 6.5032897,
"_source" : {
"account_number" : 970,
"balance" : 19648,
"firstname" : "Forbes",
"lastname" : "Wallace",
"age" : 28,
"gender" : "M",
"address" : "990 Mill Road", #
"employer" : "Pheast",
"email" : "forbeswallace@pheast.com",
"city" : "Lopezo",
"state" : "AK"
}
}
]
}
}
查询出一条数据
{
"took" : 0,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 1,
"relation" : "eq"
},
"max_score" : 6.5032897,
"hits" : [
{
"_index" : "bank",
"_type" : "account",
"_id" : "970",
"_score" : 6.5032897,
"_source" : {
"account_number" : 970,
"balance" : 19648,
"firstname" : "Forbes",
"lastname" : "Wallace",
"age" : 28,
"gender" : "M",
"address" : "990 Mill Road",
"employer" : "Pheast",
"email" : "forbeswallace@pheast.com",
"city" : "Lopezo",
"state" : "AK"
}
}
]
}
}
文本字段的匹配，使用keyword，匹配的条件就是要显示字段的全部值，要进行精确匹配的。
match_phrase是做短语匹配，只要文本中包含匹配条件，就能匹配到。
5、multi_math【多字段匹配】
字段中或关系，state或者address中包含mill，并且在查询过程中，会对于查询条件进行分词。
GET bank/_search
{
"query": {
"multi_match": {
"query": "mill",
"fields": [
"state",
"address"
]
}
}
}
查询结果：
{
"took" : 28,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 4,
"relation" : "eq"
},
"max_score" : 5.4032025,
"hits" : [
{
"_index" : "bank",
"_type" : "account",
"_id" : "970",
"_score" : 5.4032025,
"_source" : {
"account_number" : 970,
"balance" : 19648,
"firstname" : "Forbes",
"lastname" : "Wallace",
"age" : 28,
"gender" : "M",
"address" : "990 Mill Road",
"employer" : "Pheast",
"email" : "forbeswallace@pheast.com",
"city" : "Lopezo",
"state" : "AK"
}
},
{
"_index" : "bank",
"_type" : "account",
"_id" : "136",
"_score" : 5.4032025,
"_source" : {
"account_number" : 136,
"balance" : 45801,
"firstname" : "Winnie",
"lastname" : "Holland",
"age" : 38,
"gender" : "M",
"address" : "198 Mill Lane",
"employer" : "Neteria",
"email" : "winnieholland@neteria.com",
"city" : "Urie",
"state" : "IL"
}
},
{
"_index" : "bank",
"_type" : "account",
"_id" : "345",
"_score" : 5.4032025,
"_source" : {
"account_number" : 345,
"balance" : 9812,
"firstname" : "Parker",
"lastname" : "Hines",
"age" : 38,
"gender" : "M",
"address" : "715 Mill Avenue",
"employer" : "Baluba",
"email" : "parkerhines@baluba.com",
"city" : "Blackgum",
"state" : "KY"
}
},
{
"_index" : "bank",
"_type" : "account",
"_id" : "472",
"_score" : 5.4032025,
"_source" : {
"account_number" : 472,
"balance" : 25571,
"firstname" : "Lee",
"lastname" : "Long",
"age" : 32,
"gender" : "F",
"address" : "288 Mill Street",
"employer" : "Comverges",
"email" : "leelong@comverges.com",
"city" : "Movico",
"state" : "MT"
}
}
]
}
}
6、bool用来做复合查询
复合语句可以合并，任何其他查询语句，包括符合语句。
这也就意味着，复合语句之间可以互相嵌套，可以表达非常复杂的逻辑。
- must：
- 必须达到must所列举的所有条件
- must_not：
- 必须不匹配must_not所列举的所有条件。
- should：
- 应该满足should所列举的条件。满足条件最好，不满足也可以，满足得分更高
- must 必须是指定的情况
实例：查询gender=m，并且address=mill的数据
GET bank/_search
{
"query":{
"bool":{
"must":[
{"match":{"address":"mill"}},
{"match":{"gender":"M"}}
]
}
}
}
结果
{
"took" : 83,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 3,
"relation" : "eq"
},
"max_score" : 6.0824604,
"hits" : [
{
"_index" : "bank",
"_type" : "account",
"_id" : "970",
"_score" : 6.0824604,
"_source" : {
"account_number" : 970,
"balance" : 19648,
"firstname" : "Forbes",
"lastname" : "Wallace",
"age" : 28,
"gender" : "M",
"address" : "990 Mill Road",
"employer" : "Pheast",
"email" : "forbeswallace@pheast.com",
"city" : "Lopezo",
"state" : "AK"
}
},
{
"_index" : "bank",
"_type" : "account",
"_id" : "136",
"_score" : 6.0824604,
"_source" : {
"account_number" : 136,
"balance" : 45801,
"firstname" : "Winnie",
"lastname" : "Holland",
"age" : 38,
"gender" : "M",#
"address" : "198 Mill Lane",#
"employer" : "Neteria",
"email" : "winnieholland@neteria.com",
"city" : "Urie",
"state" : "IL"
}
},
{
"_index" : "bank",
"_type" : "account",
"_id" : "345",
"_score" : 6.0824604,
"_source" : {
"account_number" : 345,
"balance" : 9812,
"firstname" : "Parker",
"lastname" : "Hines",
"age" : 38,
"gender" : "M",#
"address" : "715 Mill Avenue",#
"employer" : "Baluba",
"email" : "parkerhines@baluba.com",
"city" : "Blackgum",
"state" : "KY"
}
}
]
}
}
- must_not 必须不是指定的情况
实例：查询gender=m，并且address=mill的数据，但是age不等于38的
GET bank/_search
{
"query": {
"bool": {
"must": [
{ "match": { "gender": "M" }},
{ "match": {"address": "mill"}}
],
"must_not": [
{ "match": { "age": "38" }}
]
}
}
}
结果
{
"took" : 8,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 1,
"relation" : "eq"
},
"max_score" : 6.0824604,
"hits" : [
{
"_index" : "bank",
"_type" : "account",
"_id" : "970",
"_score" : 6.0824604,
"_source" : {
"account_number" : 970,
"balance" : 19648,
"firstname" : "Forbes",
"lastname" : "Wallace",
"age" : 28,#
"gender" : "M", #
"address" : "990 Mill Road", #
"employer" : "Pheast",
"email" : "forbeswallace@pheast.com",
"city" : "Lopezo",
"state" : "AK"
}
}
]
}
}
- should
应该达到should列举的条件，如果到达会增加相关文档的评分，并不会改变查询的结果。
如果query中只有should且只有一种匹配规则，那么should的条件就会被作为默认匹配条件二区改变查询结果。
实例：匹配lastName应该等于Wallace的数据
GET bank/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"gender": "M"
}
},
{
"match": {
"address": "mill"
}
}
],
"must_not": [
{
"match": {
"age": "18"
}
}
],
"should": [
{
"match": {
"lastname": "Wallace"
}
}
]
}
}
}
查询结果：能够看到相关度越高，得分也越高。
{
"took" : 7,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 3,
"relation" : "eq"
},
"max_score" : 12.585751,
"hits" : [
{
"_index" : "bank",
"_type" : "account",
"_id" : "970",
"_score" : 12.585751,
"_source" : {
"account_number" : 970,
"balance" : 19648,
"firstname" : "Forbes",
"lastname" : "Wallace",#
"age" : 28,#
"gender" : "M",#
"address" : "990 Mill Road",#
"employer" : "Pheast",
"email" : "forbeswallace@pheast.com",
"city" : "Lopezo",
"state" : "AK"
}
},
{
"_index" : "bank",
"_type" : "account",
"_id" : "136",
"_score" : 6.0824604,
"_source" : {
"account_number" : 136,
"balance" : 45801,
"firstname" : "Winnie",
"lastname" : "Holland",#
"age" : 38,#
"gender" : "M",#
"address" : "198 Mill Lane",#
"employer" : "Neteria",
"email" : "winnieholland@neteria.com",
"city" : "Urie",
"state" : "IL"
}
},
{
"_index" : "bank",
"_type" : "account",
"_id" : "345",
"_score" : 6.0824604,
"_source" : {
"account_number" : 345,
"balance" : 9812,
"firstname" : "Parker",
"lastname" : "Hines",#
"age" : 38,#
"gender" : "M",#
"address" : "715 Mill Avenue",#
"employer" : "Baluba",
"email" : "parkerhines@baluba.com",
"city" : "Blackgum",
"state" : "KY"
}
}
]
}
}
7、Filter【结果过滤】
明天继续！！！
