1. ELASTICSEARCH
1、安装elastic search
dokcer中安装elastic search
(1)下载ealastic search和kibana
docker pull elasticsearch:7.6.2
docker pull kibana:7.6.2
(2)配置
mkdir -p /mydata/elasticsearch/config
mkdir -p /mydata/elasticsearch/data
echo "http.host: 0.0.0.0" >/mydata/elasticsearch/config/elasticsearch.yml
chmod -R 777 /mydata/elasticsearch/
(3)启动Elastic search
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:7.6.2
设置开机启动elasticsearch
docker update elasticsearch --restart=always
(4)启动kibana:
docker run --name kibana -e ELASTICSEARCH_HOSTS=http://172.17.0.3:9200 -p 5601:5601 -d kibana:7.6.2
设置开机启动kibana
docker update kibana --restart=always
(5)测试
查看elasticsearch版本信息: http://#:9200/
{
"name": "0adeb7852e00",
"cluster_name": "elasticsearch",
"cluster_uuid": "9gglpP0HTfyOTRAaSe2rIg",
"version": {
"number": "7.6.2",
"build_flavor": "default",
"build_type": "docker",
"build_hash": "ef48eb35cf30adf4db14086e8aabd07ef6fb113f",
"build_date": "2020-03-26T06:34:37.794943Z",
"build_snapshot": false,
"lucene_version": "8.4.0",
"minimum_wire_compatibility_version": "6.8.0",
"minimum_index_compatibility_version": "6.0.0-beta1"
},
"tagline": "You Know, for Search"
}
显示elasticsearch 节点信息http://#:9200/_cat/nodes ,
127.0.0.1 76 95 1 0.26 1.40 1.22 dilm * 0adeb7852e00
访问Kibana: http://#:5601/app/kibana
2、初步检索
1)_CAT
(1)GET/cat/nodes:查看所有节点
如:http://#:9200/_cat/nodes :
127.0.0.1 61 91 11 0.08 0.49 0.87 dilm * 0adeb7852e00
注:*表示集群中的主节点
(2)GET/cat/health:查看es健康状况
如: http://#:9200/_cat/health
1588332616 11:30:16 elasticsearch green 1 1 3 3 0 0 0 0 - 100.0%
注:green表示健康值正常
(3)GET/cat/master:查看主节点
如: http://#:9200/_cat/master
vfpgxbusTC6-W3C2Np31EQ 127.0.0.1 127.0.0.1 0adeb7852e00
(4)GET/_cat/indicies:查看所有索引 ,等价于mysql数据库的show databases;
如: http://#:9200/_cat/indices
green open .kibana_task_manager_1 KWLtjcKRRuaV9so_v15WYg 1 0 2 0 39.8kb 39.8kb
green open .apm-agent-configuration cuwCpJ5ER0OYsSgAJ7bVYA 1 0 0 0 283b 283b
green open .kibana_1 PqK_LdUYRpWMy4fK0tMSPw 1 0 7 0 31.2kb 31.2kb
2)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,指定用那个唯一标识
PUT customer/external/1;在customer索引下的external类型下保存1号数据为
PUT customer/external/1
{
"name":"John Doe"
}
PUT和POST都可以
POST新增。如果不指定id,会自动生成id。指定id就会修改这个数据,并新增版本号;
PUT可以新增也可以修改。PUT必须指定id;由于PUT需要指定id,我们一般用来做修改操作,不指定id会报错。
下面是在postman中的测试数据:
创建数据成功后,显示201 created表示插入记录成功。
{
"_index": "customer",
"_type": "external",
"_id": "1",
"_version": 1,
"result": "created",
"_shards": {
"total": 2,
"successful": 1,
"failed": 0
},
"_seq_no": 0,
"_primary_term": 1
}
这些返回的JSON串的含义;这些带有下划线开头的,称为元数据,反映了当前的基本信息。
“_index”: “customer” 表明该数据在哪个数据库下;
“_type”: “external” 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。
下面选用POST方式:
添加数据的时候,不指定ID,会自动的生成id,并且类型是新增:
再次使用POST插入数据,仍然是新增的:
添加数据的时候,指定ID,会使用该id,并且类型是新增:
再次使用POST插入数据,类型为updated
3)查看文档
GET /customer/external/1
http://#:9200/customer/external/1
{
"_index": "customer",//在哪个索引
"_type": "external",//在哪个类型
"_id": "1",//记录id
"_version": 3,//版本号
"_seq_no": 6,//并发控制字段,每次更新都会+1,用来做乐观锁
"_primary_term": 1,//同上,主分片重新分配,如重启,就会变化
"found": true,
"_source": {
"name": "John Doe"
}
}
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。
实例:将id=1的数据更新为name=1,然后再次更新为name=2,起始_seq_no=6,_primary_term=1
(1)将name更新为1
http://#:9200/customer/external/1?if_seq_no=6&if_primary_term=1
(2)将name更新为2,更新过程中使用seq_no=6
http://#:9200/customer/external/1?if_seq_no=6&if_primary_term=1
出现更新错误。
(3)查询新的数据
http://#:9200/customer/external/1
能够看到_seq_no变为7。
(4)再次更新,更新成功
http://#:9200/customer/external/1?if_seq_no=7&if_primary_term=1
4)更新文档
(1)POST更新文档,带有_update
http://#:9200/customer/external/1/_update
如果再次执行更新,则不执行任何操作,序列号也不发生变化
POST更新方式,会对比原来的数据,和原来的相同,则不执行任何操作(version和_seq_no)都不变。
(2)POST更新文档,不带_update
在更新过程中,重复执行更新操作,数据也能够更新成功,不会和原来的数据进行对比。
5)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id=1的数据,删除后继续查询
实例:删除整个costomer索引数据
删除前,所有的索引
green open .kibana_task_manager_1 KWLtjcKRRuaV9so_v15WYg 1 0 2 0 39.8kb 39.8kb
green open .apm-agent-configuration cuwCpJ5ER0OYsSgAJ7bVYA 1 0 0 0 283b 283b
green open .kibana_1 PqK_LdUYRpWMy4fK0tMSPw 1 0 7 0 31.2kb 31.2kb
yellow open customer nzDYCdnvQjSsapJrAIT8Zw 1 1 4 0 4.4kb 4.4kb
删除“ customer ”索引
删除后,所有的索引
green open .kibana_task_manager_1 KWLtjcKRRuaV9so_v15WYg 1 0 2 0 39.8kb 39.8kb
green open .apm-agent-configuration cuwCpJ5ER0OYsSgAJ7bVYA 1 0 0 0 283b 283b
green open .kibana_1 PqK_LdUYRpWMy4fK0tMSPw 1 0 7 0 31.2kb 31.2kb
6)eleasticsearch的批量操作——bulk
语法格式:
{
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"}
执行结果
#! Deprecation: [types removal] Specifying types in bulk requests is deprecated.
{
"took" : 491,
"errors" : false,
"items" : [
{
"index" : {
"_index" : "customer",
"_type" : "external",
"_id" : "1",
"_version" : 1,
"result" : "created",
"_shards" : {
"total" : 2,
"successful" : 1,
"failed" : 0
},
"_seq_no" : 0,
"_primary_term" : 1,
"status" : 201
}
},
{
"index" : {
"_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"}}
{
"create":{
"_index":"website","_type":"blog","_id":"123"}}
{
"title":"my first blog post"}
{
"index":{
"_index":"website","_type":"blog"}}
{
"title":"my second blog post"}
{
"update":{
"_index":"website","_type":"blog","_id":"123"}}
{
"doc":{
"title":"my updated blog post"}}
运行结果:
#! Deprecation: [types removal] Specifying types in bulk requests is deprecated.
{
"took" : 608,
"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" : "MCOs0HEBHYK_MJXUyYIz",
"_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
}
}
]
}
7)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://github.com/elastic/elasticsearch/blob/master/docs/src/test/resources/accounts.json ,导入测试数据,
POST bank/account/_bulk
3、检索
1)search Api
ES支持两种基本方式检索;
- 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);
信息检索
uri+请求体进行检索
GET /bank/_search
{
"query": {
"match_all": {
} },
"sort": [
{
"account_number": "asc" },
{
"balance":"desc"}
]
}
HTTP客户端工具(),get请求不能够携带请求体,
GET bank/_search?q=*&sort=account_number:asc
返回结果:
{
"took" : 235,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 1000,
"relation" : "eq"
},
"max_score" : null,
"hits" : [
{
"_index" : "bank",
"_type" : "account",
"_id" : "0",
"_score" : null,
"_source" : {
"account_number" : 0,
"balance" : 16623,
"firstname" : "Bradshaw",
"lastname" : "Mckenzie",
"age" : 29,
"gender" : "F",
"address" : "244 Columbus Place",
"employer" : "Euron",
"email" : "bradshawmckenzie@euron.com",
"city" : "Hobucken",
"state" : "CO"
},
"sort" : [
0
]
},
{
"_index" : "bank",
"_type" : "account",
"_id" : "1",
"_score" : null,
"_source" : {
"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"
},
"sort" : [
1
]
},
{
"_index" : "bank",
"_type" : "account",
"_id" : "2",
"_score" : null,
"_source" : {
"account_number" : 2,
"balance" : 28838,
"firstname" : "Roberta",
"lastname" : "Bender",
"age" : 22,
"gender" : "F",
"address" : "560 Kingsway Place",
"employer" : "Chillium",
"email" : "robertabender@chillium.com",
"city" : "Bennett",
"state" : "LA"
},
"sort" : [
2
]
},
{
"_index" : "bank",
"_type" : "account",
"_id" : "3",
"_score" : null,
"_source" : {
"account_number" : 3,
"balance" : 44947,
"firstname" : "Levine",
"lastname" : "Burks",
"age" : 26,
"gender" : "F",
"address" : "328 Wilson Avenue",
"employer" : "Amtap",
"email" : "levineburks@amtap.com",
"city" : "Cochranville",
"state" : "HI"
},
"sort" : [
3
]
},
{
"_index" : "bank",
"_type" : "account",
"_id" : "4",
"_score" : null,
"_source" : {
"account_number" : 4,
"balance" : 27658,
"firstname" : "Rodriquez",
"lastname" : "Flores",
"age" : 31,
"gender" : "F",
"address" : "986 Wyckoff Avenue",
"employer" : "Tourmania",
"email" : "rodriquezflores@tourmania.com",
"city" : "Eastvale",
"state" : "HI"
},
"sort" : [
4
]
},
{
"_index" : "bank",
"_type" : "account",
"_id" : "5",
"_score" : null,
"_source" : {
"account_number" : 5,
"balance" : 29342,
"firstname" : "Leola",
"lastname" : "Stewart",
"age" : 30,
"gender" : "F",
"address" : "311 Elm Place",
"employer" : "Diginetic",
"email" : "leolastewart@diginetic.com",
"city" : "Fairview",
"state" : "NJ"
},
"sort" : [
5
]
},
{
"_index" : "bank",
"_type" : "account",
"_id" : "6",
"_score" : null,
"_source" : {
"account_number" : 6,
"balance" : 5686,
"firstname" : "Hattie",
"lastname" : "Bond",
"age" : 36,
"gender" : "M",
"address" : "671 Bristol Street",
"employer" : "Netagy",
"email" : "hattiebond@netagy.com",
"city" : "Dante",
"state" : "TN"
},
"sort" : [
6
]
},
{
"_index" : "bank",
"_type" : "account",
"_id" : "7",
"_score" : null,
"_source" : {
"account_number" : 7,
"balance" : 39121,
"firstname" : "Levy",
"lastname" : "Richard",
"age" : 22,
"gender" : "M",
"address" : "820 Logan Street",
"employer" : "Teraprene",
"email" : "levyrichard@teraprene.com",
"city" : "Shrewsbury",
"state" : "MO"
},
"sort" : [
7
]
},
{
"_index" : "bank",
"_type" : "account",
"_id" : "8",
"_score" : null,
"_source" : {
"account_number" : 8,
"balance" : 48868,
"firstname" : "Jan",
"lastname" : "Burns",
"age" : 35,
"gender" : "M",
"address" : "699 Visitation Place",
"employer" : "Glasstep",
"email" : "janburns@glasstep.com",
"city" : "Wakulla",
"state" : "AZ"
},
"sort" : [
8
]
},
{
"_index" : "bank",
"_type" : "account",
"_id" : "9",
"_score" : null,
"_source" : {
"account_number" : 9,
"balance" : 24776,
"firstname" : "Opal",
"lastname" : "Meadows",
"age" : 39,
"gender" : "M",
"address" : "963 Neptune Avenue",
"employer" : "Cedward",
"email" : "opalmeadows@cedward.com",
"city" : "Olney",
"state" : "OH"
},
"sort" : [
9
]
}
]
}
}
(1)只有6条数据,这是因为存在分页查询;
使用from
和size
可以指定查询
GET /bank/_search
{
"query": { "match_all": {} },
"sort": [
{ "account_number": "asc" },
{"balance":"desc"}
],
"from": 20,
"size": 10
}
(2)详细的字段信息,参照: https://www.elastic.co/guide/en/elasticsearch/reference/current/getting-started-search.html
The response also provides the following information about the search request:
took
– how long it took Elasticsearch to run the query, in millisecondstimed_out
– whether or not the search request timed out_shards
– how many shards were searched and a breakdown of how many shards succeeded, failed, or were skipped.max_score
– the score of the most relevant document foundhits.total.value
- how many matching documents were foundhits.sort
- the document’s sort position (when not sorting by relevance score)hits._score
- the document’s relevance score (not applicable when usingmatch_all
)
2)Query DSL
(1)基本语法格式
Elasticsearch提供了一个可以执行查询的Json风格的DSL。这个被称为Query DSL,该查询语言非常全面。
一个查询语句的典型结构
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,...
}
}
}
GET bank/_search
{
"query": {
"match_all": {
}
},
"from": 0,
"size": 5,
"sort": [
{
"account_number": {
"order": "desc"
}
}
]
}
query定义如何查询;
- match_all查询类型【代表查询所有的所有】,es中可以在query中组合非常多的查询类型完成复杂查询;
- 除了query参数之外,我们可也传递其他的参数以改变查询结果,如sort,size;
- from+size限定,完成分页功能;
- sort排序,多字段排序,会在前序字段相等时后续字段内部排序,否则以前序为准;
(2)返回部分字段
GET bank/_search
{
"query": {
"match_all": {
}
},
"from": 0,
"size": 5,
"sort": [
{
"account_number": {
"order": "desc"
}
}
],
"_source": ["balance","firstname"]
}
查询结果:
{
"took" : 18,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 1000,
"relation" : "eq"
},
"max_score" : null,
"hits" : [
{
"_index" : "bank",
"_type" : "account",
"_id" : "999",
"_score" : null,
"_source" : {
"firstname" : "Dorothy",
"balance" : 6087
},
"sort" : [
999
]
},
{
"_index" : "bank",
"_type" : "account",
"_id" : "998",
"_score" : null,
"_source" : {
"firstname" : "Letha",
"balance" : 16869
},
"sort" : [
998
]
},
{
"_index" : "bank",
"_type" : "account",
"_id" : "997",
"_score" : null,
"_source" : {
"firstname" : "Combs",
"balance" : 25311
},
"sort" : [
997
]
},
{
"_index" : "bank",
"_type" : "account",
"_id" : "996",
"_score" : null,
"_source" : {
"firstname" : "Andrews",
"balance" : 17541
},
"sort" : [
996
]
},
{
"_index" : "bank",
"_type" : "account",
"_id" : "995",
"_score" : null,
"_source" : {
"firstname" : "Phelps",
"balance" : 21153
},
"sort" : [
995
]
}
]
}
}
(3)match匹配查询
- 基本类型(非字符串),精确控制
GET bank/_search
{
"query": {
"match": {
"account_number": "20"
}
}
}
match返回account_number=20的数据。
查询结果:
{
"took" : 1,
"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" : "20",
"_score" : 1.0,
"_source" : {
"account_number" : 20,
"balance" : 16418,
"firstname" : "Elinor",
"lastname" : "Ratliff",
"age" : 36,
"gender" : "M",
"address" : "282 Kings Place",
"employer" : "Scentric",
"email" : "elinorratliff@scentric.com",
"city" : "Ribera",
"state" : "WA"
}
}
]
}
}
- 字符串,全文检索
GET bank/_search
{
"query": {
"match": {
"address": "kings"
}
}
}
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。
查询结果:
{
"took" : 30,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 2,
"relation" : "eq"
},
"max_score" : 5.990829,
"hits" : [
{
"_index" : "bank",
"_type" : "account",
"_id" : "20",
"_score" : 5.990829,
"_source" : {
"account_number" : 20,
"balance" : 16418,
"firstname" : "Elinor",
"lastname" : "Ratliff",
"age" : 36,
"gender" : "M",
"address" : "282 Kings Place",
"employer" : "Scentric",
"email" : "elinorratliff@scentric.com",
"city" : "Ribera",
"state" : "WA"
}
},
{
"_index" : "bank",
"_type" : "account",
"_id" : "722",
"_score" : 5.990829,
"_source" : {
"account_number" : 722,
"balance" : 27256,
"firstname" : "Roberts",
"lastname" : "Beasley",
"age" : 34,
"gender" : "F",
"address" : "305 Kings Hwy",
"employer" : "Quintity",
"email" : "robertsbeasley@quintity.com",
"city" : "Hayden",
"state" : "PA"
}
}
]
}
}
(4) match_phrase [短句匹配]
将需要匹配的值当成一整个单词(不分词)进行检索
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
查看结果:
{
"took" : 32,
"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"
}
}
}
查询结果:
{
"took" : 0,
"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"
}
}
}
查询出一条数据
{
"took" : 1,
"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】
GET bank/_search
{
"query": {
"multi_match": {
"query": "mill",
"fields": [
"state",
"address"
]
}
}
}
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。
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
GET bank/_search
{
"query":{
"bool":{
"must":[
{
"match":{
"address":"mill"}},
{
"match":{
"gender":"M"}}
]
}
}
}
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。
实例:查询gender=m,并且address=mill的数据
GET bank/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"gender": "M"
}
},
{
"match": {
"address": "mill"
}
}
]
}
}
}
查询结果:
{
"took" : 1,
"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"
}
}
]
}
}
查询结果:
{
"took" : 4,
"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",