DockerFile构建ElasticSearch镜像安装IK中文分词器插件
为什么要安装IK中文分词器?
ES提供的分词是英文分词,对中文做分词时会拆成单字而不是词语,非常不友好,因此索引信息含中文时需要使用中文分词器插件。
一、环境及文件准备
环境准备
- VMWare版本:15.5.5
- 操作系统:CentOS7
- Docker版本:19.03.12
文件准备:
- 拉取ElasticSearch镜像,版本:7.8.0
docker pull elasticsearch:7.8.0
- 下载中文分词器插件,版本:7.8.0
# 在Linux根目录创建docker文件夹并进入文件夹
mkdir /docker
cd /docker
# 下载IK插件文件(如果提示没有wget命令则先执行:`yum install -y wget`,再执行下载命令)
wget https://github.com/medcl/elasticsearch-analysis-ik/releases/download/v7.8.0/elasticsearch-analysis-ik-7.8.0.zip
# 可选项:wget下载过慢可先用浏览器将文件下载到本地再上传到Linux(如果提示没有rz命令则先执行:`yum install -y lrzsz`,再执行上传命令,选择elasticsearch-analysis-ik-7.8.0.zip文件)
rz
# 解压(如果提示没有unzip命令则先执行:`yum install -y unzip`,再执行下载命令)
unzip elasticsearch-analysis-ik-7.8.0.zip -d elasticsearch-analysis-ik
注意:ElasticSearch镜像版本要与IK分词器一致(我使用elasticsearch:7.8.1镜像与elasticsearch-analysis-ik-7.8.0插件,构建镜像后无法使用)
二、构建镜像并启动:
1. 创建DockerFile:进入docker文件夹执行vi DockerFile
FROM elasticsearch:7.8.0
ADD elasticsearch-analysis-ik /usr/share/elasticsearch/plugins/elasticsearch-analysis-ik
2. 创建镜像:在docker文件夹路径下执行docker build -f DockerFile -t elasticsearch-ik:7.8.0 .
镜像构建成功:
[root@localhost elasticsearch-ik]# docker build -f DockerFile -t elasticsearch-ik:7.8.0 .
Sending build context to Docker daemon 14.39MB
Step 1/2 : FROM elasticsearch:7.8.0
---> 121454ddad72
Step 2/2 : ADD elasticsearch-analysis-ik /usr/share/elasticsearch/plugins/elasticsearch-analysis-ik
---> Using cache
---> 2af03d5426d3
Successfully built 2af03d5426d3
Successfully tagged elasticsearch-ik:7.8.0
3. 创建并启动容器
docker run -d -p 9200:9200 -p 9300:9300 -e "discovery.type=single-node" --name elasticsearch_test elasticsearch-ik:7.8.0
4. 验证ElasticSearch启动成功:curl localhost:9200
显示如下即启动成功:
[root@localhost docker]# curl localhost:9200
{
"name" : "9f832bbeb44a",
"cluster_name" : "docker-cluster",
"cluster_uuid" : "8GAjHyQEToO6PMl8dDoemQ",
"version" : {
"number" : "7.8.0",
"build_flavor" : "default",
"build_type" : "docker",
"build_hash" : "757314695644ea9a1dc2fecd26d1a43856725e65",
"build_date" : "2020-06-14T19:35:50.234439Z",
"build_snapshot" : false,
"lucene_version" : "8.5.1",
"minimum_wire_compatibility_version" : "6.8.0",
"minimum_index_compatibility_version" : "6.0.0-beta1"
},
"tagline" : "You Know, for Search"
}
三、测试分词器:
这里使用的是postman
请求url:http://192.168.0.199:9200/_analyze
请求方式:post
在请求体body中请求入参格式:
{
"analyzer": "chinese",
"text": "今天是个好日子"
}
参数说明:
analyzer:可填项有:chinese|ik_max_word|ik_smart,其中chinese是ES的默认分词器选项,ik_max_word(最细粒度划分)和ik_smart(最少划分)是ik中文分词器选项
text:要进行分词操作的内容
1. 测试使用默认分词器
{
"analyzer": "chinese",
"text": "今天是个好日子"
}
结果:
{
"tokens": [
{
"token": "今",
"start_offset": 0,
"end_offset": 1,
"type": "<IDEOGRAPHIC>",
"position": 0
},
{
"token": "天",
"start_offset": 1,
"end_offset": 2,
"type": "<IDEOGRAPHIC>",
"position": 1
},
{
"token": "是",
"start_offset": 2,
"end_offset": 3,
"type": "<IDEOGRAPHIC>",
"position": 2
},
{
"token": "个",
"start_offset": 3,
"end_offset": 4,
"type": "<IDEOGRAPHIC>",
"position": 3
},
{
"token": "好",
"start_offset": 4,
"end_offset": 5,
"type": "<IDEOGRAPHIC>",
"position": 4
},
{
"token": "日",
"start_offset": 5,
"end_offset": 6,
"type": "<IDEOGRAPHIC>",
"position": 5
},
{
"token": "子",
"start_offset": 6,
"end_offset": 7,
"type": "<IDEOGRAPHIC>",
"position": 6
}
]
}
2. 测试使用ik分词器ik_smart
{
"analyzer": "ik_smart",
"text": "今天是个好日子"
}
结果:
{
"tokens": [
{
"token": "今天是",
"start_offset": 0,
"end_offset": 3,
"type": "CN_WORD",
"position": 0
},
{
"token": "个",
"start_offset": 3,
"end_offset": 4,
"type": "CN_CHAR",
"position": 1
},
{
"token": "好日子",
"start_offset": 4,
"end_offset": 7,
"type": "CN_WORD",
"position": 2
}
]
}
3. 测试使用ik分词器ik_max_word
{
"analyzer": "ik_max_word",
"text": "今天是个好日子"
}
结果:
{
"tokens": [
{
"token": "今天是",
"start_offset": 0,
"end_offset": 3,
"type": "CN_WORD",
"position": 0
},
{
"token": "今天",
"start_offset": 0,
"end_offset": 2,
"type": "CN_WORD",
"position": 1
},
{
"token": "是",
"start_offset": 2,
"end_offset": 3,
"type": "CN_CHAR",
"position": 2
},
{
"token": "个",
"start_offset": 3,
"end_offset": 4,
"type": "CN_CHAR",
"position": 3
},
{
"token": "好日子",
"start_offset": 4,
"end_offset": 7,
"type": "CN_WORD",
"position": 4
},
{
"token": "日子",
"start_offset": 5,
"end_offset": 7,
"type": "CN_WORD",
"position": 5
}
]
}