自动补全、

自动补全

需要安装拼音分词器

https://github.com/medcl/elasticsearch-analysis-pinyin

安装方式：

1.解压

2.上传到虚拟机中，elasticsearch的plugin目录

/var/lib/docker/volumes/es-plugins/_data

3.重启elserticsearch

 docker restart es

4.测试

POST /_analyze
{
  "text": ["如家酒店"]
  , "analyzer": "pinyin"
}

elasticsearch中分词器（analyzer）的组成包含三部分：

• lcharacter filters：在tokenizer之前对文本进行处理。例如删除字符、替换字符
• ltokenizer：将文本按照一定的规则切割成词条（term）。例如keyword，就是不分词；还有ik_smart
• ltokenizer filter：将tokenizer输出的词条做进一步处理。例如大小写转换、同义词处理、拼音处理等

我们在创建索引库时，通过setting来配置自定义的analyzer(分词器)

在创建索引时使用拼音分词器，但是在搜索时使用普通分词器

#自定义拼音分词器my_analyzer
PUT /test
{
  "settings": {
    "analysis": {
      "analyzer": { 
        "my_analyzer": { 
          "tokenizer": "ik_max_word",
          "filter": "py"
        }
      },
      "filter": {
        "py": { 
          "type": "pinyin",
          "keep_full_pinyin": false,
          "keep_joined_full_pinyin": true,
          "keep_original": true,
          "limit_first_letter_length": 16,
          "remove_duplicated_term": true,
          "none_chinese_pinyin_tokenize": false
        }
      }
    }
  }
}

completion suggester查询

参与补全查询的类型必须是completion类型

字段内容一般是用来补全多个词条形成的数组

示例：

#自定义拼音分词器my_analyzer
PUT /test23
{
  "settings": {
    "analysis": {
      "analyzer": { 
        "my_analyzer": { 
          "tokenizer": "ik_max_word",
          "filter": "py"
        }
      },
      "filter": {
        "py": { 
          "type": "pinyin",
          "keep_full_pinyin": false,
          "keep_joined_full_pinyin": true,
          "keep_original": true,
          "limit_first_letter_length": 16,
          "remove_duplicated_term": true,
          "none_chinese_pinyin_tokenize": false
        }
      }
    }
  },
  "mappings": {
    "properties": {
      "title":{
        "type": "completion"
      }
    }
  }
}

#自动补全的索引库
PUT test3
{
  
}
# 示例数据
POST /test23/_doc
{
  "title": ["Sony", "WH-1000XM3"]
}
POST tes23t/_doc
{
  "title": ["SK-II", "PITERA"]
}
POST test23/_doc
{
  "title": ["Nintendo", "switch"]
}



# 自动补全查询
POST /test23/_search
{
  "suggest": {
    "title_suggest": {
      "text": "s",  // 关键字
      "completion": {
        "field": "title", //补全字段
        "skip_duplicates": true,   //跳过重复的
        "size": 10   // 获取前10条结果
      }
    }
  }
}

RestAPI实现自动补全查询

案例：

实现hotel索引库的自动补全、拼音搜索功能

重新创建酒店的索引

// 酒店数据索引库
PUT /hotel
{
  "settings": {
    "analysis": {
      "analyzer": {
        "text_anlyzer": {
          "tokenizer": "ik_max_word",
          "filter": "py"
        },
        "completion_analyzer": {
          "tokenizer": "keyword",
          "filter": "py"
        }
      },
      "filter": {
        "py": {
          "type": "pinyin",
          "keep_full_pinyin": false,
          "keep_joined_full_pinyin": true,
          "keep_original": true,
          "limit_first_letter_length": 16,
          "remove_duplicated_term": true,
          "none_chinese_pinyin_tokenize": false
        }
      }
    }
  },
  "mappings": {
    "properties": {
      "id":{
        "type": "keyword"
      },
      "name":{
        "type": "text",
        "analyzer": "text_anlyzer",
        "search_analyzer": "ik_smart",
        "copy_to": "all"
      },
      "address":{
        "type": "keyword",
        "index": false
      },
      "price":{
        "type": "integer"
      },
      "score":{
        "type": "integer"
      },
      "brand":{
        "type": "keyword",
        "copy_to": "all"
      },
      "city":{
        "type": "keyword"
      },
      "starName":{
        "type": "keyword"
      },
      "business":{
        "type": "keyword",
        "copy_to": "all"
      },
      "location":{
        "type": "geo_point"
      },
      "pic":{
        "type": "keyword",
        "index": false
      },
      "all":{
        "type": "text",
        "analyzer": "text_anlyzer",
        "search_analyzer": "ik_smart"
      },
      "suggestion":{
          "type": "completion",
          "analyzer": "completion_analyzer"
      }
    }
  }
}

2、新增属性suggestion

@Data
@NoArgsConstructor
public class HotelDoc {
    private Long id;
    private String name;
    private String address;
    private Integer price;
    private Integer score;
    private String brand;
    private String city;
    private String starName;
    private String business;
    private String location;
    private String pic;

    private Object distance;

    private Boolean isAD;

    private List<String> suggestion;

    public HotelDoc(Hotel hotel) {
        this.id = hotel.getId();
        this.name = hotel.getName();
        this.address = hotel.getAddress();
        this.price = hotel.getPrice();
        this.score = hotel.getScore();
        this.brand = hotel.getBrand();
        this.city = hotel.getCity();
        this.starName = hotel.getStarName();
        this.business = hotel.getBusiness();
        this.location = hotel.getLatitude() + ", " + hotel.getLongitude();
        this.pic = hotel.getPic();


        if (this.business.contains("、")){
            //需要切割
            String[] arr = this.business.split("、");

            this.suggestion=new ArrayList<>();
            this.suggestion.add(this.brand);

            Collections.addAll(this.suggestion,arr);
        }
        else {
            this.suggestion = Arrays.asList(this.brand, this.business);
        }
    }
}

重新批量查询酒店数据

3、测试自动补全功能

sh

# 自动补全查询
POST /hotel/_search
{
  "suggest": {
    "title_suggest": {
      "text": "sh", 
      "completion": {
        "field": "suggestion", 
        "skip_duplicates": true, 
        "size": 10 
      }
    }
  }
}

RestAPI实现自动补全

@Test
    void testSuggest() throws IOException {
        //准备search
        SearchRequest request=new SearchRequest("hotel");
        //准备dsl
        request.source().suggest(new SuggestBuilder().addSuggestion("suggestion" , SuggestBuilders.completionSuggestion("suggestion").prefix("h").skipDuplicates(true).size(10)));

        //发起请求
        SearchResponse search = client.search(request, RequestOptions.DEFAULT);
       //结果解析
        Suggest suggest = search.getSuggest();
      CompletionSuggestion suggestion = suggest.getSuggestion("suggestion");
        List<CompletionSuggestion.Entry.Option> options = suggestion.getOptions();
        for (CompletionSuggestion.Entry.Option option : options) {
            String s = option.getText().toString();
            System.out.println(s);
        }
    }

实现前端

在Controller中

@GetMapping("suggestion")
public List<String> getSuggestion(@RequestParam("key") String prefix){
    return hotelService.getSuggestions(prefix);
}

创建getSuggestions方法，将搜索框内的值传入进去

//自动补全
@Override
public List<String> getSuggestions(String prefix) {
    try {


        //准备search
        SearchRequest request = new SearchRequest("hotel");
        //准备dsl
        request.source().suggest(new SuggestBuilder().addSuggestion
                ("suggestion", SuggestBuilders.completionSuggestion("suggestion")
                        .prefix(prefix)
                        .skipDuplicates(true)
                        .size(10)));

        //发起请求
        SearchResponse search = client.search(request, RequestOptions.DEFAULT);
        //结果解析
        List<String> list=new ArrayList<>();
        Suggest suggest = search.getSuggest();
        // CompletionSuggestion
        CompletionSuggestion suggestion = suggest.getSuggestion("suggestion");
        List<CompletionSuggestion.Entry.Option> options = suggestion.getOptions();
        for (CompletionSuggestion.Entry.Option option : options) {
            String s = option.getText().toString();
            list.add(s);
        }

        return list;
    }catch (Exception e){
        throw new RuntimeException(e);
    }
}