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你还不会ES的CUD吗？
source link: http://www.cnblogs.com/liusy01/p/13721500.html
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近端时间在搬砖过程中对es进行了操作，但是对es查询文档不熟悉，所以这两周都在研究es，简略看了《Elasticsearch权威指南》，摸摸鱼又是一天。
es是一款基于Lucene的实时分布式搜索和分析引擎，今天咱不聊其应用场景，聊一下es索引增删改。
环境：Centos 7，Elasticsearch6.8.3，jdk8
（最新的es是7版本，7版本需要jdk11以上，所以装了es6.8.3版本。）
下面都将以student索引为例
一、创建索引
PUT http://192.168.197.100:9200/student
{
"mapping":{
"_doc":{ //“_doc”是类型type，es6中一个索引下只有一个type，不能有其它type
"properties":{
"id": {
"type": "keyword"
},
"name":{
"type":"text",
"index":"analyzed",
"analyzer":"standard"
},
"age":{
"type":"integer",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above":256
}
}
},
"birthday":{
"type":"date"
},
"gender":{
"type":"keyword"
},
"grade":{
"type":"text",
"fields":{
"keyword":{
"type":"keyword",
"ignore_above":256
}
}
},
"class":{
"type":"text",
"fields":{
"keyword":{
"type":"keyword",
"ignore_above":256
}
}
}
}
}
},
"settings":{
//主分片数量
"number_of_shards" : 1,
//分片副本数量
"number_of_replicas" : 1
}
}
type属性是text和keyword的区别：
（1）text在查询的时候会被分词，用于搜索
（2）keyword在查询的时候不会被分词，用于聚合
index属性是表示字符串以何种方式被索引，有三种值
（1）analyzed：字段可以被模糊匹配，类似于sql中的like
（2）not_analyzed：字段只能精确匹配，类似于sql中的“=”
（3）no：字段不提供搜索
analyzer属性是设置分词器，中文的话一般是ik分词器，也可以自定义分词器。
number_of_shards属性是主分片数量，默认是5，创建之后不能修改
number_of_replicas属性时分片副本数量，默认是1，可以修改
创建成功之后会返回如下json字符串
{ "acknowledged": true, "shards_acknowledged": true, "index": "student"}
创建之后如何查看索引的详细信息呢？
GET http://192.168.197.100:9200/student/_mapping
es6版本，索引之下只能有一个类型，例如上文中的“_doc”。
es跟关系型数据库比较：
二、修改索引
//修改分片副本数量为2
PUT http://192.168.197.100:9200/student/_settings
{
"number_of_replicas":2
}
三、删除索引
//删除单个索引 DELETE http://192.168.197.100:9200/student //删除所有索引 DELETE http://192.168.197.100:9200/_all
四、默认分词器standard和ik分词器比较
es默认的分词器是standard，它对英文的分词是以空格分割的，中文则是将一个词分成一个一个的文字，所以其不适合作为中文分词器。
例如：standard对英文的分词
//此api是查看文本分词情况的
POST http://192.168.197.100:9200/_analyze
{
"text":"the People's Republic of China",
"analyzer":"standard"
}
结果如下：
{
"tokens": [
{
"token": "the",
"start_offset": 0,
"end_offset": 3,
"type": "<ALPHANUM>",
"position": 0
},
{
"token": "people's",
"start_offset": 4,
"end_offset": 12,
"type": "<ALPHANUM>",
"position": 1
},
{
"token": "republic",
"start_offset": 13,
"end_offset": 21,
"type": "<ALPHANUM>",
"position": 2
},
{
"token": "of",
"start_offset": 22,
"end_offset": 24,
"type": "<ALPHANUM>",
"position": 3
},
{
"token": "china",
"start_offset": 25,
"end_offset": 30,
"type": "<ALPHANUM>",
"position": 4
}
]
}
对中文的分词：
POST http://192.168.197.100:9200/_analyze
{
"text":"中华人民共和国万岁",
"analyzer":"standard"
}
结果如下：
{
"tokens": [
{
"token": "中",
"start_offset": 0,
"end_offset": 1,
"type": "<IDEOGRAPHIC>",
"position": 0
},
{
"token": "华",
"start_offset": 1,
"end_offset": 2,
"type": "<IDEOGRAPHIC>",
"position": 1
},
{
"token": "人",
"start_offset": 2,
"end_offset": 3,
"type": "<IDEOGRAPHIC>",
"position": 2
},
{
"token": "民",
"start_offset": 3,
"end_offset": 4,
"type": "<IDEOGRAPHIC>",
"position": 3
},
{
"token": "共",
"start_offset": 4,
"end_offset": 5,
"type": "<IDEOGRAPHIC>",
"position": 4
},
{
"token": "和",
"start_offset": 5,
"end_offset": 6,
"type": "<IDEOGRAPHIC>",
"position": 5
},
{
"token": "国",
"start_offset": 6,
"end_offset": 7,
"type": "<IDEOGRAPHIC>",
"position": 6
},
{
"token": "万",
"start_offset": 7,
"end_offset": 8,
"type": "<IDEOGRAPHIC>",
"position": 7
},
{
"token": "岁",
"start_offset": 8,
"end_offset": 9,
"type": "<IDEOGRAPHIC>",
"position": 8
}
]
}
ik分词器是支持对中文进行词语分割的，其有两个分词器，分别是ik_smart和ik_max_word。
（1）ik_smart：对中文进行最大粒度的划分，简略划分
例如：
POST http://192.168.197.100:9200/_analyze
{
"text":"中华人民共和国万岁",
"analyzer":"ik_smart"
}
结果如下：
{
"tokens": [
{
"token": "中华人民共和国",
"start_offset": 0,
"end_offset": 7,
"type": "CN_WORD",
"position": 0
},
{
"token": "万岁",
"start_offset": 7,
"end_offset": 9,
"type": "CN_WORD",
"position": 1
}
]
}
（2）ik_max_word：对中文进行最小粒度的划分，将文本划分尽量多的词语
例如：
POST http://192.168.197.100:9200/_analyze
{
"text":"中华人民共和国万岁",
"analyzer":"ik_max_word"
}
结果如下：
{
"tokens": [
{
"token": "中华人民共和国",
"start_offset": 0,
"end_offset": 7,
"type": "CN_WORD",
"position": 0
},
{
"token": "中华人民",
"start_offset": 0,
"end_offset": 4,
"type": "CN_WORD",
"position": 1
},
{
"token": "中华",
"start_offset": 0,
"end_offset": 2,
"type": "CN_WORD",
"position": 2
},
{
"token": "华人",
"start_offset": 1,
"end_offset": 3,
"type": "CN_WORD",
"position": 3
},
{
"token": "人民共和国",
"start_offset": 2,
"end_offset": 7,
"type": "CN_WORD",
"position": 4
},
{
"token": "人民",
"start_offset": 2,
"end_offset": 4,
"type": "CN_WORD",
"position": 5
},
{
"token": "共和国",
"start_offset": 4,
"end_offset": 7,
"type": "CN_WORD",
"position": 6
},
{
"token": "共和",
"start_offset": 4,
"end_offset": 6,
"type": "CN_WORD",
"position": 7
},
{
"token": "国",
"start_offset": 6,
"end_offset": 7,
"type": "CN_CHAR",
"position": 8
},
{
"token": "万岁",
"start_offset": 7,
"end_offset": 9,
"type": "CN_WORD",
"position": 9
},
{
"token": "万",
"start_offset": 7,
"end_offset": 8,
"type": "TYPE_CNUM",
"position": 10
},
{
"token": "岁",
"start_offset": 8,
"end_offset": 9,
"type": "COUNT",
"position": 11
}
]
}
ik分词器对英文的分词：
POST http://192.168.197.100:9200/_analyze
{
"text":"the People's Republic of China",
"analyzer":"ik_smart"
}
结果如下：会将不重要的词去掉，但standard分词器会保留（英语水平已经退化到a an the都不知道是属于什么类型的词了，身为中国人，这个不能骄傲）
{
"tokens": [
{
"token": "people",
"start_offset": 4,
"end_offset": 10,
"type": "ENGLISH",
"position": 0
},
{
"token": "s",
"start_offset": 11,
"end_offset": 12,
"type": "ENGLISH",
"position": 1
},
{
"token": "republic",
"start_offset": 13,
"end_offset": 21,
"type": "ENGLISH",
"position": 2
},
{
"token": "china",
"start_offset": 25,
"end_offset": 30,
"type": "ENGLISH",
"position": 3
}
]
}
五、添加文档
可以任意添加字段
//1是“_id”的值，唯一的，也可以随机生成
POST http://192.168.197.100:9200/student/_doc/1
{
"id":1,
"name":"tom",
"age":20,
"gender":"male",
"grade":"7",
"class":"1"
}
六、更新文档
POST http://192.168.197.100:9200/student/_doc/1/_update
{
"doc":{
"name":"jack"
}
}
七、删除文档
//1是“_id”的值 DELETE http://192.168.197.100:9200/student/_doc/1
上述就是简略的对es进行索引创建，修改，删除，文档添加，删除，修改等操作，为避免篇幅太长，文档查询操作将在下篇进行更新。
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