安装启动elasticsearch
mac
curl -L -O https://artifacts.elastic.co/downloads/elasticsearch/elasticsearch-7.6.1-darwin-x86_64.tar.gz
tar -xzvf elasticsearch-7.6.1-darwin-x86_64.tar.gz
cd elasticsearch-7.6.1
./bin/elasticsearch
验证elasticsearch是否运行成功
发送如下请求验证：
curl http://127.0.0.1:9200
如下结果，即表示运行成功：
{
"name" : "xxx",
"cluster_name" : "elasticsearch",
"cluster_uuid" : "rEAVwisyREqY5TYkmUhpgA",
"version" : {
"number" : "7.6.1",
"build_flavor" : "default",
"build_type" : "tar",
"build_hash" : "aa751e09be0a5072e8570670309b1f12348f023b",
"build_date" : "2020-02-29T00:15:25.529771Z",
"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"
}
安装中文分词插件
2020年3月10日
在elasticsearch的教程可以看到官方推荐使用SmartCN中文分词插件，不过也可以尝试使用ik分词插件，这里使用SmartCN插件。
安装SmartCN
sudo bin/elasticsearch-plugin install analysis-smartcn
安装完成后，需要重启当前节点。
测试SmartCN分词效果
curl --location --request POST 'http://127.0.0.1:9200/_analyze/ ' \
--header 'Content-Type: application/json' \
--data-raw '{"analyzer":"smartcn","text":"你好,我是SmartCN"} '
效果:
{
"tokens": [
{
"token": "你好",
"start_offset": 0,
"end_offset": 2,
"type": "word",
"position": 0
},
{
"token": "我",
"start_offset": 3,
"end_offset": 4,
"type": "word",
"position": 2
},
{
"token": "是",
"start_offset": 4,
"end_offset": 5,
"type": "word",
"position": 3
},
{
"token": "smartcn",
"start_offset": 5,
"end_offset": 12,
"type": "word",
"position": 4
}
]
}
分词效果还可以。
Index
查询所有索引：
curl -X GET 'http://localhost:9200/_cat/indices?v'
新建索引：
curl -X PUT 'localhost:9200/weather'
返回结果：
{
"acknowledged":true,
"shards_acknowledged":true
}
acknowledged为true表示新建索引成功。
删除索引：
curl -X DELETE 'localhost:9200/weather'
查询所有索引的映射：
curl 'localhost:9200/_mapping?pretty=true'
新建索引
curl --location --request PUT 'localhost:9200/accounts' \
--header 'Content-Type: application/json' \
--data-raw '{
"mappings": {
"properties": {
"user": {
"type": "text",
"analyzer": "smartcn",
"search_analyzer": "smartcn"
},
"title": {
"type": "text",
"analyzer": "smartcn",
"search_analyzer": "smartcn"
},
"desc": {
"type": "text",
"analyzer": "smartcn",
"search_analyzer": "smartcn"
}
}
}
}'
这里新建索引的过程中，顺便定义了这个索引的映射属性，已经这些属性的数据类型和分词插件。
插入json文档记录
curl --location --request POST 'localhost:9200/accounts/_doc/' \
--header 'Content-Type: application/json' \
--data-raw '{
"user": "李四",
"title": "工程师",
"desc": "系统管理"
}'
结果：
{
"_index": "accounts",
"_type": "_doc",
"_id": "ZW86w3AB8yT7_DRZEOIa",
"_version": 1,
"result": "created",
"_shards": {
"total": 2,
"successful": 1,
"failed": 0
},
"_seq_no": 3,
"_primary_term": 1
}
更新json文档
curl --location --request PUT 'localhost:9200/accounts/_doc/1' \
--header 'Content-Type: application/json' \
--data-raw '{
"user": "张三",
"title": "工程师",
"desc": "数据库管理"
}'
即把插入json文档请求改成put方式即可。
查询所有json文档记录
curl --location --request GET 'localhost:9200/accounts/_doc/_search?pretty=true'
结果：
{
"took": 59,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 2,
"relation": "eq"
},
"max_score": 1.0,
"hits": [
{
"_index": "accounts",
"_type": "_doc",
"_id": "1",
"_score": 1.0,
"_source": {
"user": "张三",
"title": "工程师",
"desc": "数据库管理"
}
},
{
"_index": "accounts",
"_type": "_doc",
"_id": "ZW86w3AB8yT7_DRZEOIa",
"_score": 1.0,
"_source": {
"user": "李四",
"title": "工程师",
"desc": "系统管理"
}
}
]
}
}
根据id查询json文档
curl --location --request GET 'localhost:9200/accounts/_doc/1'
将插入json文档请求，改成GET方式请求即可。
根据id删除json文档
curl --location --request DELETE 'localhost:9200/accounts/_doc/1'
在插入json文档请求的基础，改成DELETE方式请求即可。
全文搜索
重点来了，elasticsearch的全文搜索在Query DSL定义了很多方式来进行查询。
curl --location --request GET 'localhost:9200/accounts/_search?pretty=true' \
--header 'Content-Type: application/json' \
--data-raw '{
"query" : {
"match" : { "desc" : "数据库" }
}
}'
这里是对其中一个字段进行全文搜索，结果如下：
{
"took": 4,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 1,
"relation": "eq"
},
"max_score": 0.6931471,
"hits": [
{
"_index": "accounts",
"_type": "_doc",
"_id": "1",
"_score": 0.6931471,
"_source": {
"user": "张三",
"title": "工程师",
"desc": "数据库管理"
}
}
]
}
}
and or查询
只需要调整请求Body如下：
or方式
{
"query": {
"bool": {
"should": [
{
"match": {
"desc": "管理"
}
},
{
"match": {
"desc": "数据库"
}
}
]
}
}
}
and方式
{
"query": {
"bool": {
"must": [
{
"match": {
"desc": "管理"
}
},
{
"match": {
"desc": "数据库"
}
}
]
}
}
}
这里主要使用elasticsearch的布尔查询语法，其中must表示为and操作，should表示为or操作。
总结
elasticsearch文档很详细，只要理解了倒排索引原理，熟悉elasticsearch中的Index，Document，分词插件，搜索API，查询语法和其他查询方式，应该是能够轻松运用的。
参考
来源：CSDN
作者：亚林瓜子
链接：https://blog.csdn.net/fxtxz2/article/details/104770751