一、简单了解ik分词器(分词效果)
这个是底层自带的不属于ik分词，ik分词器属于第三方分词器
1.standard(单字分词器，es默认分词器)
POST _analyze
{
"analyzer":"standard",
"text":"我爱学搜索引擎"
}
效果（把每一个字都拆分，每个字都被分词了）
{
"tokens" : [
{
"token" : "我",
"start_offset" : 0,
"end_offset" : 1,
"type" : "<IDEOGRAPHIC>",
"position" : 0
},
{
"token" : "爱",
"start_offset" : 1,
"end_offset" : 2,
"type" : "<IDEOGRAPHIC>",
"position" : 1
},
{
"token" : "学",
"start_offset" : 2,
"end_offset" : 3,
"type" : "<IDEOGRAPHIC>",
"position" : 2
},
{
"token" : "搜",
"start_offset" : 3,
"end_offset" : 4,
"type" : "<IDEOGRAPHIC>",
"position" : 3
},
{
"token" : "索",
"start_offset" : 4,
"end_offset" : 5,
"type" : "<IDEOGRAPHIC>",
"position" : 4
},
{
"token" : "引",
"start_offset" : 5,
"end_offset" : 6,
"type" : "<IDEOGRAPHIC>",
"position" : 5
},
{
"token" : "擎",
"start_offset" : 6,
"end_offset" : 7,
"type" : "<IDEOGRAPHIC>",
"position" : 6
}
]
}
2.ik_smart分词(粗粒度的拆分)
和单字分词器的区别，就是按照比较粗的粒度去分词，把搜索引擎当成一个词来分词
POST _analyze
{
"analyzer":"ik_smart",
"text":"我爱学搜索引擎"
}
效果
{
"tokens" : [
{
"token" : "我",
"start_offset" : 0,
"end_offset" : 1,
"type" : "CN_CHAR",
"position" : 0
},
{
"token" : "爱",
"start_offset" : 1,
"end_offset" : 2,
"type" : "CN_CHAR",
"position" : 1
},
{
"token" : "学",
"start_offset" : 2,
"end_offset" : 3,
"type" : "CN_CHAR",
"position" : 2
},
{
"token" : "搜索引擎",
"start_offset" : 3,
"end_offset" : 7,
"type" : "CN_WORD",
"position" : 3
}
]
}
3.ik_max_word分词器（最细粒度拆分）
按照最细粒度进行分词，把认为能组成一个词的情况都拆分。
POST _analyze
{
"analyzer":"ik_max_word",
"text":"我爱学搜索引擎"
}
效果
{
"tokens" : [
{
"token" : "我",
"start_offset" : 0,
"end_offset" : 1,
"type" : "CN_CHAR",
"position" : 0
},
{
"token" : "爱",
"start_offset" : 1,
"end_offset" : 2,
"type" : "CN_CHAR",
"position" : 1
},
{
"token" : "学",
"start_offset" : 2,
"end_offset" : 3,
"type" : "CN_CHAR",
"position" : 2
},
{
"token" : "搜索引擎",
"start_offset" : 3,
"end_offset" : 7,
"type" : "CN_WORD",
"position" : 3
},
{
"token" : "搜索",
"start_offset" : 3,
"end_offset" : 5,
"type" : "CN_WORD",
"position" : 4
},
{
"token" : "索引",
"start_offset" : 4,
"end_offset" : 6,
"type" : "CN_WORD",
"position" : 5
},
{
"token" : "引擎",
"start_offset" : 5,
"end_offset" : 7,
"type" : "CN_WORD",
"position" : 6
}
]
}
二、指定默认分词器
1.为索引指定默认分词器
创建一个索引（mysql中对应database），名为test_index_database
指定默认分词器为：ik_max_word
PUT /test_index_database
{
"settings":{
"index":{
"analysis.analyzer.default.type":"ik_max_word"
}
}
}
三、ES操作数据
在7.x版本以后类型默认为_doc
1.概述
es是面向文档的，它可以储存整个对象或者文档，对该文档进行索引、搜索、排序、过滤。
使用json作为文档序列化格式
2.创建索引
PUT /test_index01
3.查询索引
GET /test_index01
查询信息如下
其中number_of_shards(分片数量)number_of_replicas(副本数量)
es7.6.1版本默认的分片和副本数量为1，这个默认数量和你es的版本有关系。可能其他版本默认不是1
{
"test_index01" : {
"aliases" : { },
"mappings" : { },
"settings" : {
"index" : {
"creation_date" : "1678969193239",
"number_of_shards" : "1",
"number_of_replicas" : "1",
"uuid" : "n6tD0dyxTB2aOQjqyDK0QQ",
"version" : {
"created" : "7060199"
},
"provided_name" : "test_index01"
}
}
}
}
4.删除索引
DELETE /test_index01
5.添加文档
格式: PUT /索引名称/类型/id
PUT /test_index01/_doc/1
{
"name": "张三",
"sex": 1,
"age": 25,
"address": "北京",
"remark": "java"
}
执行结果_index:索引名称_type：类型_id：id_version：版本（因为这条数据可能会被修改，所以版本可能不是1）result:结果(操作结果，创建，更新等)
{
"_index" : "test_index01",
"_type" : "_doc",
"_id" : "1",
"_version" : 1,
"result" : "created",
"_shards" : {
"total" : 2,
"successful" : 1,
"failed" : 0
},
"_seq_no" : 0,
"_primary_term" : 1
}
6.查询索引库
查询格式：GET /索引名称/类型/id
GET /test_index01/_doc/1
查询结果
{
"_index" : "test_index01",
"_type" : "_doc",
"_id" : "1",
"_version" : 1,
"_seq_no" : 0,
"_primary_term" : 1,
"found" : true,
"_source" : {
"name" : "张三",
"sex" : 1,
"age" : 25,
"address" : "北京",
"remark" : "java"
}
}
6.1查询索引库中所有内容
格式: GET /索引名称/类型/_search
GET /test_index01/_doc/_search
相当于mysql中的 select *
结果（我这里只有一条数据）
#! Deprecation: [types removal] Specifying types in search requests is deprecated.
{
"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" : "test_index01",
"_type" : "_doc",
"_id" : "1",
"_score" : 1.0,
"_source" : {
"name" : "秀儿",
"sex" : 1,
"age" : 25,
"address" : "上海",
"remark" : "java"
}
}
]
}
}
6.2简单等值查询
格式: GET /索引名称/类型/_search?q=:**
GET /test_index01/_doc/_search?q=age:25
6.3简单范围查询
格式: GET /索引名称/类型/_search?q=***[left TO tight]
GET /test_index01/_doc/_search?q=age[25 TO 26]
6.4 通过id进行in查询
格式: GET /索引名称/类型/_mget
GET /test_index01/_doc/_mget
{
"ids":["1","2"]
}
6.5分页查询
GET /索引名称/类型/_search?from=0&size=1
GET /索引名称/类型/_search?q=条件&from=0&size=1
GET /test_index01/_doc/_search?from=0&size=1
GET /test_index01/_doc/_search?q=age[25 TO 26]&from=0&size=1
6.6对查询结果只显示指定字段
GET /索引名称/类型/_search?_source=字段,字段
GET /test_index01/_doc/_search?_source=name,age
6.7排序查询
GET /索引名称/类型/_search?sort=字段 desc
GET /test_index01/_doc/_search?sort=age:desc
GET /test_index01/_doc/_search?sort=age:asc
7.修改索引内容
格式：PUT /索引名称/类型/id
PUT /test_index01/_doc/1
{
"name": "秀儿",
"sex": 1,
"age": 25,
"address": "上海",
"remark": "java"
}
结果
{
"_index" : "test_index01",
"_type" : "_doc",
"_id" : "1",
"_version" : 2,
"result" : "updated",
"_shards" : {
"total" : 2,
"successful" : 1,
"failed" : 0
},
"_seq_no" : 1,
"_primary_term" : 1
}
8.删除索引内容
格式: DELETE /索引名称/类型/id
DELETE /test_index01/_doc/1
结果文章来源：https://www.toymoban.com/news/detail-405513.html
{
"_index" : "test_index01",
"_type" : "_doc",
"_id" : "1",
"_version" : 3,
"result" : "deleted",
"_shards" : {
"total" : 2,
"successful" : 1,
"failed" : 0
},
"_seq_no" : 2,
"_primary_term" : 1
}
9.PUT和POST区别
post和put都能实现创建和更新操作
①PUT:
(1)需要对一个具体的资源进行操作，所以必须要有id才能更新和创建操作。没有就会执行失败
(2)只会将json数据全都进行替换
(3)与delete都是幂等操作，无论操作多少次结果都一样
②POST:
(1)针对整个资源集合进行操作，如果不写id就会由es生成一个唯一的id进行创建文档，如果指定id则会对应创建或者更新文档。
(2)只会更新相同字段的值文章来源地址https://www.toymoban.com/news/detail-405513.html
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