谷粒商城—分布式高级①.md

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 milliseconds
• timed_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 found
• hits.total.value - how many matching documents were found
• hits.sort - the document’s sort position (when not sorting by relevance score)
• hits._score - the document’s relevance score (not applicable when using match_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",