ElasticSearch利用IK实现全文搜索

要做到中文全文检索还需要按照中文分词库 ，这里就使用 IK来设置

安装中文分词库
相关命令：

whereis elasticsearch  找到目录
进入 到/usr/elasticsearch/bin
执行  ./elasticsearch-plugin插件命令 安装插件

./elasticsearch-plugin install https://github.com/medcl/elasticsearch-analysis-ik/releases/download/v6.6.1/elasticsearch-analysis-ik-6.6.1.zip

service elasticsearch restart 重启服务

安装好之后可以看到 plugin 下有 analysis-ik 

接下来按照官方的步骤往下面走

、创建一个索引

curl -XPUT http://localhost:9200/myfulltext

、创建

curl -XPOST http://localhost:9200/liyouming/liyoumingtext/_mapping -H 'Content-Type:application/json' -d'
{
        "properties": {
            "mytext": {
                "type": "text",
                "analyzer": "ik_max_word",
                "search_analyzer": "ik_max_word"
            }
        }

}'
这里要注意 content 不能冲突 ，分析器字段要定义
Mapper for [content] conflicts with existing mapping in other types:\n[mapper [content] has different [analyzer]]
Mapper for[content]与其他类型的现有映射冲突：[mapper[content]有不同的[分析器]

这里我们还是通过WebAPI来测试

首先创建我们的索引

OK后创建 全文检索相关设置 设置字段、分析器配置    ik_smart  、ik_max_word

分别添加如下数据

{
"url":"liyouming/liyoumingtext",
"param":{"mytext":"深夜还在写代码的人只有黎又铭"}
}
{
"url":"liyouming/liyoumingtext",
"param":{"mytext":"中午黎又铭在操场上打篮球"}
}
{
"url":"liyouming/liyoumingtext",
"param":{"mytext":"黎又铭早上吃了一碗面"}
}

查询下所有数据可以看到

{
  "took": ,
  "timed_out": false,
  "_shards": {
    "total": ,
    "successful": ,
    "skipped": ,
    "failed":
  },
  "hits": {
    "total": ,
    "max_score": 3.0561461,
    "hits": [
      {
        "_index": "liyouming",
        "_type": "liyoumingtext",
        "_id": "c7eQAWoB0Mh7sqcTGY-K",
        "_score": 3.0561461,
        "_source": {
          "mytext": "中午黎又铭在操场上打篮球"
        }
      },
      {
        "_index": "liyouming",
        "_type": "liyoumingtext",
        "_id": "dLeQAWoB0Mh7sqcTdo9b",
        "_score": 2.1251993,
        "_source": {
          "mytext": "深夜还在写代码的人只有黎又铭"
        }
      },
      {
        "_index": "liyouming",
        "_type": "liyoumingtext",
        "_id": "crePAWoB0Mh7sqcTzY-2",
        "_score": 0.8630463,
        "_source": {
          "mytext": "黎又铭早上吃了一碗面"
        }
      }
    ]
  }
}

检索下篮球并高亮文本内容可以看到下面的结果 <tag1>篮球</tag1> 已经被高亮标签处理

{
  "took": ,
  "timed_out": false,
  "_shards": {
    "total": ,
    "successful": ,
    "skipped": ,
    "failed":
  },
  "hits": {
    "total": ,
    "max_score": 1.0187154,
    "hits": [
      {
        "_index": "liyouming",
        "_type": "liyoumingtext",
        "_id": "c7eQAWoB0Mh7sqcTGY-K",
        "_score": 1.0187154,
        "_source": {
          "mytext": "中午黎又铭在操场上打篮球"
        },
        "highlight": {
          "mytext": [
            "中午黎又铭在操场上打<tag1>篮球</tag1>"
          ]
        }
      }
    ]
  }
}