es安装分词器

es安装分词器

一.安装es

1.解压

tar  xvf  elasticsearch-8.12.2-linux-aarch64.tar.gz  -C /usr/local/

2.创建一个用户并授权

groupadd esgroup
useradd esuser -p 123456
chown -R esuser:esgroup /usr/local/elasticsearch-8.12.2

3.修改配置

#修改sysctl.conf
vim /etc/sysctl.conf
#在文件的最后一行添加
vm.max_map_count=262144

调整 elasticsearch.yml

#进入config文件夹
cd /usr/local/elasticsearch-8.12.2/config
#修改elasticsearch.yml 配置信息
vim elasticsearch.yml

在文件夹的最后一行添加：
ingest.geoip.downloader.enabled: false
http.cors.enabled: true 
http.cors.allow-origin: "*"

4.切换用户再次启动

su esuser
#进入elasticsearch  bin目录下面
cd /usr/local/elasticsearch-8.12.2/bin
#启动
./elasticsearch

5.访问

访问之后如果拒绝

分析应该是：elasticsearch开启了认证和http加密

继续操作elasticsearch 系统会关闭服务

为了测试，先关闭一下认证，继续修改elasticsearch.yml

#切换到root用户
su root
#进入config文件夹
cd /usr/local/elasticsearch-8.12.2/config
#修改elasticsearch.yml 配置信息
vim elasticsearch.yml

关闭xpack认证 
xpack.security.enabled: true 改成 false
与客户端http链接是否加密，先选择不加密
xpack.security.http.ssl: true 改成 false

6.却换用户，再次启动

#却换用户
su esuser
#进入elasticsearch  bin目录下面
cd /usr/local/elasticsearch-8.12.2/bin
#启动
./elasticsearch

二.安装分词器

下载成功后解压放到es的plugins目录下，并改名字为ik

unzip elasticsearch-analysis-ik-8.12.2.zip -d /usr/local/elasticsearch-8.12.2/plugins/ik
chmod -R 777 /usr/local/elasticsearch-8.12.2/plugins/ik

启动es,看到ik分词器已经加载进来

三.安装kibana并测试

1解压

tar xvf kibana-8.12.2-linux-aarch64.tar.gz  -C /usr/local/

2.启动

cd /usr/local/kibana-8.12.2/config/
vim  kibana.yml
server.port: 5601         #kibana端口
server.host: "0.0.0.0"   #所有主机都能访问，或者也可以指定一个ip
server.publicBaseUrl: "http://192.168.199.233:5601"
elasticsearch.hosts: ["http://192.168.199.233:9200"]    #配置es的访问地址 高版本是.hosts 低版本的是url   
i18n.locale: "zh-CN"

cd /usr/local/kibana-8.12.2/bin
./kibana --allow-root

四.测试

#测试分词
POST /_analyze
{
  "text":"合理小姐是凑巧先生独一无二的女主角",
  "analyzer": "ik_max_word"
}

五.es8是否支持向量查询

在es8中是支持向量查询的

PUT image-index
{
  "mappings": {
    "properties": {
	  "image-vector": {
	    "type": "dense_vector",
		"dims": 3
	},
	"title":{
	  "type": "text"
	},
	"file-type": {
	  "type": "keyword"
	},
	"my_label": {
	  "type" : "text"
	}
   }
  }
}

POST image-index/_bulk
{ "index": {} }
{ "image-vector": [-5, 9, -12], "title": "Image A", "file-type": "jpeg", "my_label": "red" }
{ "index": {} }
{ "image-vector": [10, -2, 3], "title": "Image B", "file-type": "png", "my_label": "blue" }
{ "index": {} }
{ "image-vector": [4, 0, -1], "title": "Image C", "file-type": "gif", "my_label": "red" }
   
   
   
   
POST image-index/_search
{
  "knn": {
    "field": "image-vector",
	"query_vector": [-5, 10, -12], 
	"k": 10,
	"num_candidates": 100
  },
  "fields": [ "title", "file-type" ]
}

查询的结果

{
  "took": 1,
  "timed_out": false,
  "_shards": {
    "total": 1,
    "successful": 1,
    "skipped": 0,
    "failed": 0
  },
  "hits": {
    "total": {
      "value": 6,
      "relation": "eq"
    },
    "max_score": 0.99937135,
    "hits": [
      {
        "_index": "image-index",
        "_id": "WahncJMBn1Jiu5-p-dJ2",
        "_score": 0.99937135,
        "_source": {
          "image-vector": [
            -5,
            9,
            -12
          ],
          "title": "Image A",
          "file-type": "jpeg",
          "my_label": "red"
        },
        "fields": {
          "file-type": [
            "jpeg"
          ],
          "title": [
            "Image A"
          ]
        }
      },
      {
        "_index": "image-index",
        "_id": "XKhtcJMBn1Jiu5-ptNI9",
        "_score": 0.99937135,
        "_source": {
          "image-vector": [
            -5,
            9,
            -12
          ],
          "title": "Image A",
          "file-type": "jpeg",
          "my_label": "red"
        },
        "fields": {
          "file-type": [
            "jpeg"
          ],
          "title": [
            "Image A"
          ]
        }
      },
      {
        "_index": "image-index",
        "_id": "W6hncJMBn1Jiu5-p-dJ2",
        "_score": 0.44084936,
        "_source": {
          "image-vector": [
            4,
            0,
            -1
          ],
          "title": "Image C",
          "file-type": "gif",
          "my_label": "red"
        },
        "fields": {
          "file-type": [
            "gif"
          ],
          "title": [
            "Image C"
          ]
        }
      },
      {
        "_index": "image-index",
        "_id": "XqhtcJMBn1Jiu5-ptNI9",
        "_score": 0.44084936,
        "_source": {
          "image-vector": [
            4,
            0,
            -1
          ],
          "title": "Image C",
          "file-type": "gif",
          "my_label": "red"
        },
        "fields": {
          "file-type": [
            "gif"
          ],
          "title": [
            "Image C"
          ]
        }
      },
      {
        "_index": "image-index",
        "_id": "WqhncJMBn1Jiu5-p-dJ2",
        "_score": 0.19600916,
        "_source": {
          "image-vector": [
            10,
            -2,
            3
          ],
          "title": "Image B",
          "file-type": "png",
          "my_label": "blue"
        },
        "fields": {
          "file-type": [
            "png"
          ],
          "title": [
            "Image B"
          ]
        }
      },
      {
        "_index": "image-index",
        "_id": "XahtcJMBn1Jiu5-ptNI9",
        "_score": 0.19600916,
        "_source": {
          "image-vector": [
            10,
            -2,
            3
          ],
          "title": "Image B",
          "file-type": "png",
          "my_label": "blue"
        },
        "fields": {
          "file-type": [
            "png"
          ],
          "title": [
            "Image B"
          ]
        }
      }
    ]
  }
}