Elasticsearch文档操作

一、Elasticsearch的CURD

1、CURD之Create

PUT lqz/doc/1
{"name":"顾老二","age":30,"from": "gu","desc": "皮肤黑、武器长、性格直","tags": ["黑", "长", "直"]
}

他明处貌似还有俩老婆：

PUT lqz/doc/2
{"name":"大娘子","age":18,"from":"sheng","desc":"肤白貌美，娇憨可爱","tags":["白", "富","美"]
}PUT lqz/doc/3
{"name":"龙套偏房","age":22,"from":"gu","desc":"mmp，没怎么看，不知道怎么形容","tags":["造数据", "真","难"]
}

家里红旗不倒，家外彩旗飘摇：

PUT lqz/doc/4
{"name":"石头","age":29,"from":"gu","desc":"粗中有细，狐假虎威","tags":["粗", "大","猛"]
}PUT lqz/doc/5
{"name":"魏行首","age":25,"from":"广云台","desc":"仿佛兮若轻云之蔽月,飘飘兮若流风之回雪,mmp，最后竟然没有嫁给顾老二！","tags":["闭月","羞花"]
}

注意：当执行PUT命令时，如果数据不存在，则新增该条数据，如果数据存在则修改该条数据。

咱们通过GET命令查询一下：

GET lqz/doc/1

结果如下：

{"_index" : "lqz","_type" : "doc","_id" : "1","_version" : 1,"found" : true,"_source" : {"name" : "顾老二","age" : 30,"from" : "gu","desc" : "皮肤黑、武器长、性格直","tags" : ["黑","长","直"]}
}

查询也没啥问题，但是你可能说了，人家老二是黄种人，怎么是黑的呢？好吧咱改改desc和tags：

PUT lqz/doc/1
{"desc":"皮肤很黄，武器很长，性格很直","tags":["很黄","很长", "很直"]
}

上例，我们仅修改了desc和tags两处，而name、age和from三个属性没有变化，我们可以忽略不写吗？查查看：

GET lqz/doc/1

结果如下：

{"_index" : "lqz","_type" : "doc","_id" : "1","_version" : 3,"found" : true,"_source" : {"desc" : "皮肤很黄，武器很长，性格很直","tags" : ["很黄","很长","很直"]}
}

哎呀，出事故了！修改是修改了，但结果不太理想啊，因为name、age和from属性都没啦！
注意：**PUT命令，在做修改操作时，如果未指定其他的属性，则按照指定的属性进行修改操作。**也就是如上例所示的那样，我们修改时只修改了desc和tags两个属性，其他的属性并没有一起添加进去。

很明显，这是病！dai治！怎么治？上车，咱们继续往下走！

2、CURD之Update

让我们首先恢复一下事故现场：

PUT lqz/doc/1
{"name":"顾老二","age":30,"from": "gu","desc": "皮肤黑、武器长、性格直","tags": ["黑", "长", "直"]
}

我们要将黑修改成黄：

POST lqz/doc/1/_update
{"doc": {"desc": "皮肤很黄，武器很长，性格很直","tags": ["很黄","很长", "很直"]}
}

上例中，我们使用POST命令，在id后面跟_update，要修改的内容放到doc文档（属性）中即可。

我们再来查询一次：

GET lqz/doc/1

结果如下：

{"_index" : "lqz","_type" : "doc","_id" : "1","_version" : 5,"found" : true,"_source" : {"name" : "顾老二","age" : 30,"from" : "gu","desc" : "皮肤很黄，武器很长，性格很直","tags" : ["很黄","很长","很直"]}
}

结果如上例所示，现在其他的属性没有变化，只有desc和tags属性被修改。

注意：POST命令，这里可用来执行修改操作（还有其他的功能），POST命令配合_update完成修改操作，指定修改的内容放到doc中。

写了这么多，我也发现我上面有讲的不对的地方——石头不是跟顾老二不清不楚，石头是跟小桃不清不楚！好吧，刚才那个数据是一个错误示范！我们这就把它干掉！

3、CURD之Delete

DELETE lqz/doc/4

很简单，通过DELETE命令，就可以删除掉那个错误示范了！

删除效果如下：

{"_index" : "lqz","_type" : "doc","_id" : "4","_version" : 4,"result" : "deleted","_shards" : {"total" : 2,"successful" : 1,"failed" : 0},"_seq_no" : 4,"_primary_term" : 1
}

我们再来查询一遍：

GET lqz/doc/4

结果如下：

{"_index" : "lqz","_type" : "doc","_id" : "4","found" : false
}

上例中，found：false表示查询数据不存在。

4、CURD之Retrieve

我们上面已经不知不觉的使用熟悉这种简单查询方式，通过 GET命令查询指定文档：

GET lqz/doc/1

结果如下：

{"_index" : "lqz","_type" : "doc","_id" : "1","_version" : 5,"found" : true,"_source" : {"name" : "顾老二","age" : 30,"from" : "gu","desc" : "皮肤很黄，武器很长，性格很直","tags" : ["很黄","很长","很直"]}
}

二、Elasticsearch之查询的两种方式

1、前言

简单的没挑战，来点复杂的，elasticsearch提供两种查询方式：

• 查询字符串(query string)，简单查询，就像是像传递URL参数一样去传递查询语句，被称为简单搜索或查询字符串(query string)搜索。
• 另外一种是通过DSL语句来进行查询，被称为DSL查询(Query DSL),DSL是Elasticsearch提供的一种丰富且灵活的查询语言，该语言以json请求体的形式出现，通过restful请求与Elasticsearch进行交互。

2、准备数据

PUT lqz/doc/1
{"name":"顾老二","age":30,"from": "gu","desc": "皮肤黑、武器长、性格直","tags": ["黑", "长", "直"]
}PUT lqz/doc/2
{"name":"大娘子","age":18,"from":"sheng","desc":"肤白貌美，娇憨可爱","tags":["白", "富","美"]
}PUT lqz/doc/3
{"name":"龙套偏房","age":22,"from":"gu","desc":"mmp，没怎么看，不知道怎么形容","tags":["造数据", "真","难"]
}PUT lqz/doc/4
{"name":"石头","age":29,"from":"gu","desc":"粗中有细，狐假虎威","tags":["粗", "大","猛"]
}PUT lqz/doc/5
{"name":"魏行首","age":25,"from":"广云台","desc":"仿佛兮若轻云之蔽月,飘飘兮若流风之回雪,mmp，最后竟然没有嫁给顾老二！","tags":["闭月","羞花"]
}

3、查询字符串

GET lqz/doc/_search?q=from:gu

还是使用GET命令，通过_serarch查询，查询条件是什么呢？条件是from属性是gu家的人都有哪些。最后，别忘了_search和from属性中间的英文分隔符?

结果如下：

{"took" : 1,"timed_out" : false,"_shards" : {"total" : 5,"successful" : 5,"skipped" : 0,"failed" : 0},"hits" : {"total" : 3,"max_score" : 0.6931472,"hits" : [{"_index" : "lqz","_type" : "doc","_id" : "4","_score" : 0.6931472,"_source" : {"name" : "石头","age" : 29,"from" : "gu","desc" : "粗中有细，狐假虎威","tags" : ["粗","大","猛"]}},{"_index" : "lqz","_type" : "doc","_id" : "1","_score" : 0.2876821,"_source" : {"name" : "顾老二","age" : 30,"from" : "gu","desc" : "皮肤黑、武器长、性格直","tags" : ["黑","长","直"]}},{"_index" : "lqz","_type" : "doc","_id" : "3","_score" : 0.2876821,"_source" : {"name" : "龙套偏房","age" : 22,"from" : "gu","desc" : "mmp，没怎么看，不知道怎么形容","tags" : ["造数据","真","难"]}}]}
}

我们来重点说下hits，hits是返回的结果集——所有from属性为gu的结果集。重点中的重点是_score得分，得分是什么呢？根据算法算出跟查询条件的匹配度，匹配度高得分就高。后面再说这个算法是怎么回事。

4、结构化查询

我们现在使用DSL方式，来完成刚才的查询，查看来自顾家的都有哪些人。

GET lqz/doc/_search
{"query": {"match": {"from": "gu"}}
}

上例，查询条件是一步步构建出来的，将查询条件添加到match中即可，而match则是查询所有from字段的值中含有gu的结果就会返回。
当然结果没啥变化：

{"took" : 0,"timed_out" : false,"_shards" : {"total" : 5,"successful" : 5,"skipped" : 0,"failed" : 0},"hits" : {"total" : 3,"max_score" : 0.6931472,"hits" : [{"_index" : "lqz","_type" : "doc","_id" : "4","_score" : 0.6931472,"_source" : {"name" : "石头","age" : 29,"from" : "gu","desc" : "粗中有细，狐假虎威","tags" : ["粗","大","猛"]}},{"_index" : "lqz","_type" : "doc","_id" : "1","_score" : 0.2876821,"_source" : {"name" : "顾老二","age" : 30,"from" : "gu","desc" : "皮肤黑、武器长、性格直","tags" : ["黑","长","直"]}},{"_index" : "lqz","_type" : "doc","_id" : "3","_score" : 0.2876821,"_source" : {"name" : "龙套偏房","age" : 22,"from" : "gu","desc" : "mmp，没怎么看，不知道怎么形容","tags" : ["造数据","真","难"]}}]}
}

三、term与match查询

1、match查询

1.1 准备数据

PUT lqz/doc/1
{"name":"顾老二","age":30,"from": "gu","desc": "皮肤黑、武器长、性格直","tags": ["黑", "长", "直"]
}PUT lqz/doc/2
{"name":"大娘子","age":18,"from":"sheng","desc":"肤白貌美，娇憨可爱","tags":["白", "富","美"]
}PUT lqz/doc/3
{"name":"龙套偏房","age":22,"from":"gu","desc":"mmp，没怎么看，不知道怎么形容","tags":["造数据", "真","难"]
}PUT lqz/doc/4
{"name":"石头","age":29,"from":"gu","desc":"粗中有细，狐假虎威","tags":["粗", "大","猛"]
}PUT lqz/doc/5
{"name":"魏行首","age":25,"from":"广云台","desc":"仿佛兮若轻云之蔽月,飘飘兮若流风之回雪,mmp，最后竟然没有嫁给顾老二！","tags":["闭月","羞花"]
}

1.2 match系列之match（按条件查询）

我们查看来自顾家的都有哪些人。

GET lqz/doc/_search
{"query": {"match": {"from": "gu"}}
}

上例，查询条件是一步步构建出来的，将查询条件添加到match中即可，而match则是查询所有from字段的值中含有gu的结果就会返回。
结果如下：

{"took" : 0,"timed_out" : false,"_shards" : {"total" : 5,"successful" : 5,"skipped" : 0,"failed" : 0},"hits" : {"total" : 3,"max_score" : 0.6931472,"hits" : [{"_index" : "lqz","_type" : "doc","_id" : "4","_score" : 0.6931472,"_source" : {"name" : "石头","age" : 29,"from" : "gu","desc" : "粗中有细，狐假虎