• elasticsearch的搜索补全提示

    当用户在搜索框输入字符时，我们应该提示出与该字符有关的搜索项

    拼音分词器

    下载 

    要实现根据字母做补全，就必须对文档按照拼音分词，GitHub上有拼音分词插件

    GitHub - medcl/elasticsearch-analysis-pinyin: This Pinyin Analysis plugin is used to do conversion between Chinese characters and Pinyin.

    解压

    解压到一个文件夹中去

    上传 

    上传到服务器中，elasticsearch的plugin目录  

    重启 

    重启elasticsearch  

    docker restart es

     测试

    1. POST /_analyze
    2. {
    3.   "text": "如家酒店还不错",
    4.   "analyzer": "pinyin"
    5. }

    返回拼音 

    自定义分词器

    默认的拼音分词器会将每个汉字单独分为拼音，而我们希望的是每个词条形成一组拼音，需要对拼音分词器做个性化定制，形成自定义分词器。

    elasticsearch中分词器（analyzer）的组成包含三部分：

    • character filters：在tokenizer之前对文本进行处理。例如删除字符、替换字符

    • tokenizer：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

    • tokenizer 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

    自定义分词器 

    1. PUT /myanalyzer
    2. {
    3.   "settings": {
    4.     "analysis": {
    5.       "analyzer": { 
    6.       "my_analyzer": { 
    7.           "tokenizer": "ik_max_word",
    8.           "filter": "py"
    9.         }
    10.       },
    11.       "filter": { 
    12.         "py": { 
    13.         "type": "pinyin", 
    14. 		  "keep_full_pinyin": false,
    15.           "keep_joined_full_pinyin": true,
    16.           "keep_original": true,
    17.           "limit_first_letter_length": 16,
    18.           "remove_duplicated_term": true,
    19.           "none_chinese_pinyin_tokenize": false
    20.         }
    21.       }
    22.     }
    23.   },
    24.   "mappings": {
    25.       "properties": {
    26.       "name": {
    27.         "type": "text",
    28.         "analyzer": "my_analyzer",
    29.         "search_analyzer": "ik_smart"
    30.       }
    31.     }
    32.   }
    33. }
    • analyzer自定义分词器 
    • my_analyzer分词器名称
    • filter自定义tokenizer filter
    • py过滤器名称
    • filter.type过滤器类型，这里是pinyin
    • name分词的字段

     测试

    1. POST /myanalyzer/_analyze
    2. {
    3.   "text": ["华美达酒店还不错"],
    4.   "analyzer": "my_analyzer"
    5. }

    结果

    自动补全查询 

    创建索引库

    1. PUT /hotel
    2. {
    3.   "settings": {
    4.     "analysis": {
    5.       "analyzer": {
    6.         "text_anlyzer": {
    7.           "tokenizer": "ik_max_word",
    8.           "filter": "py"
    9.         },
    10.         "completion_analyzer": {
    11.           "tokenizer": "keyword",
    12.           "filter": "py"
    13.         }
    14.       },
    15.       "filter": {
    16.         "py": {
    17.           "type": "pinyin",
    18.           "keep_full_pinyin": false,
    19.           "keep_joined_full_pinyin": true,
    20.           "keep_original": true,
    21.           "limit_first_letter_length": 16,
    22.           "remove_duplicated_term": true,
    23.           "none_chinese_pinyin_tokenize": false
    24.         }
    25.       }
    26.     }
    27.   },
    28.   "mappings": {
    29.     "properties": {
    30.       "id":{
    31.         "type": "keyword"
    32.       },
    33.       "name":{
    34.         "type": "text",
    35.         "analyzer": "text_anlyzer",
    36.         "search_analyzer": "ik_smart",
    37.         "copy_to": "all"
    38.       },
    39.       "address":{
    40.         "type": "keyword",
    41.         "index": false
    42.       },
    43.       "price":{
    44.         "type": "integer"
    45.       },
    46.       "score":{
    47.         "type": "integer"
    48.       },
    49.       "brand":{
    50.         "type": "keyword",
    51.         "copy_to": "all"
    52.       },
    53.       "city":{
    54.         "type": "keyword"
    55.       },
    56.       "starName":{
    57.         "type": "keyword"
    58.       },
    59.       "business":{
    60.         "type": "keyword",
    61.         "copy_to": "all"
    62.       },
    63.       "location":{
    64.         "type": "geo_point"
    65.       },
    66.       "pic":{
    67.         "type": "keyword",
    68.         "index": false
    69.       },
    70.       "all":{
    71.         "type": "text",
    72.         "analyzer": "text_anlyzer",
    73.         "search_analyzer": "ik_smart"
    74.       },
    75.       "suggestion":{
    76.           "type": "completion",
    77.           "analyzer": "completion_analyzer"
    78.       }
    79.     }
    80.   }
    81. }

    HotelDoc实体

    1. import lombok.Data;
    2. import lombok.NoArgsConstructor;
    3.  
    4. import java.util.ArrayList;
    5. import java.util.Arrays;
    6. import java.util.Collections;
    7. import java.util.List;
    8.  
    9. @Data
    10. @NoArgsConstructor
    11. public class HotelDoc {
    12.     private Long id;
    13.     private String name;
    14.     private String address;
    15.     private Integer price;
    16.     private Integer score;
    17.     private String brand;
    18.     private String city;
    19.     private String starName;
    20.     private String business;
    21.     private String location;
    22.     private String pic;
    23.     private Object distance;
    24.     private Boolean isAD;
    25.     private List suggestion;
    26.  
    27.     public HotelDoc(Hotel hotel) {
    28.         this.id = hotel.getId();
    29.         this.name = hotel.getName();
    30.         this.address = hotel.getAddress();
    31.         this.price = hotel.getPrice();
    32.         this.score = hotel.getScore();
    33.         this.brand = hotel.getBrand();
    34.         this.city = hotel.getCity();
    35.         this.starName = hotel.getStarName();
    36.         this.business = hotel.getBusiness();
    37.         this.location = hotel.getLatitude() + ", " + hotel.getLongitude();
    38.         this.pic = hotel.getPic();
    39.         // 组装suggestion
    40.         if(this.business.contains("/")){
    41.             // business有多个值，需要切割
    42.             String[] arr = this.business.split("/");
    43.             // 添加元素
    44.             this.suggestion = new ArrayList<>();
    45.             this.suggestion.add(this.brand);
    46.             Collections.addAll(this.suggestion, arr);
    47.         }else {
    48.             this.suggestion = Arrays.asList(this.brand, this.business);
    49.         }
    50.     }
    51. }

    导入数据

    1.  @Test
    2.     void testBulkRequest() throws IOException {
    3.         // 批量查询酒店数据
    4.         List hotels = hotelService.list();
    5.  
    6.         // 1.创建Request
    7.         BulkRequest request = new BulkRequest();
    8.         // 2.准备参数，添加多个新增的Request
    9.         for (Hotel hotel : hotels) {
    10.             // 2.1.转换为文档类型HotelDoc
    11.             HotelDoc hotelDoc = new HotelDoc(hotel);
    12.             // 2.2.创建新增文档的Request对象
    13.             request.add(new IndexRequest("hotel")
    14.                     .id(hotelDoc.getId().toString())
    15.                     .source(JSON.toJSONString(hotelDoc), XContentType.JSON));
    16.         }
    17.         // 3.发送请求
    18.         client.bulk(request, RequestOptions.DEFAULT);
    19.     }

    controller类

    1.  
    2.  
    3. import cn.itcast.hotel.pojo.PageResult;
    4. import cn.itcast.hotel.pojo.RequestParams;
    5. import cn.itcast.hotel.service.IHotelService;
    6. import org.springframework.beans.factory.annotation.Autowired;
    7. import org.springframework.web.bind.annotation.*;
    8.  
    9. import java.util.List;
    10. import java.util.Map;
    11.  
    12. @RestController
    13. @RequestMapping("/hotel")
    14. public class HotelController {
    15.  
    16.     @Autowired
    17.     private IHotelService hotelService;
    18. 	// 搜索酒店数据
    19.  
    20.  
    21.     @GetMapping("suggestion")
    22.     public List getSuggestions(@RequestParam("key") String prefix) {
    23.         return hotelService.getSuggestions(prefix);
    24.     }
    25. }

    service类

    1.  
    2. import cn.itcast.hotel.mapper.HotelMapper;
    3. import cn.itcast.hotel.pojo.Hotel;
    4. import cn.itcast.hotel.pojo.HotelDoc;
    5. import cn.itcast.hotel.pojo.PageResult;
    6. import cn.itcast.hotel.pojo.RequestParams;
    7. import cn.itcast.hotel.service.IHotelService;
    8. import com.alibaba.fastjson.JSON;
    9. import com.baomidou.mybatisplus.extension.service.impl.ServiceImpl;
    10. import org.elasticsearch.action.search.SearchRequest;
    11. import org.elasticsearch.action.search.SearchResponse;
    12.  
    13. import org.elasticsearch.client.RequestOptions;
    14. import org.elasticsearch.client.RestHighLevelClient;
    15. import org.elasticsearch.common.geo.GeoPoint;
    16. import org.elasticsearch.common.unit.DistanceUnit;
    17. import org.elasticsearch.index.query.BoolQueryBuilder;
    18. import org.elasticsearch.index.query.QueryBuilders;
    19. import org.elasticsearch.index.query.functionscore.FunctionScoreQueryBuilder;
    20. import org.elasticsearch.index.query.functionscore.ScoreFunctionBuilders;
    21. import org.elasticsearch.search.SearchHit;
    22. import org.elasticsearch.search.SearchHits;
    23. import org.elasticsearch.search.aggregations.AggregationBuilders;
    24. import org.elasticsearch.search.aggregations.Aggregations;
    25. import org.elasticsearch.search.aggregations.bucket.terms.Terms;
    26. import org.elasticsearch.search.sort.SortBuilders;
    27. import org.elasticsearch.search.sort.SortOrder;
    28. import org.elasticsearch.search.suggest.Suggest;
    29. import org.elasticsearch.search.suggest.SuggestBuilder;
    30. import org.elasticsearch.search.suggest.SuggestBuilders;
    31. import org.elasticsearch.search.suggest.completion.CompletionSuggestion;
    32. import org.springframework.beans.factory.annotation.Autowired;
    33. import org.springframework.stereotype.Service;
    34.  
    35. import java.io.IOException;
    36. import java.util.ArrayList;
    37. import java.util.HashMap;
    38. import java.util.List;
    39. import java.util.Map;
    40.  
    41. @Service
    42. public class HotelService extends ServiceImpl implements IHotelService {
    43.  
    44.     @Autowired
    45.     private RestHighLevelClient client;
    46.  
    47.    
    48.  
    49.     @Override
    50.     public List getSuggestions(String prefix) {
    51.         try {
    52.             // 1.准备Request
    53.             SearchRequest request = new SearchRequest("hotel");
    54.             // 2.准备DSL
    55.             request.source().suggest(new SuggestBuilder().addSuggestion(
    56.                     "suggestions",
    57.                     SuggestBuilders.completionSuggestion("suggestion")
    58.                             .prefix(prefix)
    59.                             .skipDuplicates(true)
    60.                             .size(10)
    61.             ));
    62.             // 3.发起请求
    63.             SearchResponse response = client.search(request, RequestOptions.DEFAULT);
    64.             // 4.解析结果
    65.             Suggest suggest = response.getSuggest();
    66.             // 4.1.根据补全查询名称，获取补全结果
    67.             CompletionSuggestion suggestions = suggest.getSuggestion("suggestions");
    68.             // 4.2.获取options
    69.             List options = suggestions.getOptions();
    70.             // 4.3.遍历
    71.             List list = new ArrayList<>(options.size());
    72.             for (CompletionSuggestion.Entry.Option option : options) {
    73.                 String text = option.getText().toString();
    74.                 list.add(text);
    75.             }
    76.             return list;
    77.         } catch (IOException e) {
    78.             throw new RuntimeException(e);
    79.         }
    80.     }
    81.  
    82.   
    83.  
    84.    
    85.  
    86.   
    87. }

    测试 

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  • 原文地址：https://blog.csdn.net/qq_63431773/article/details/132688848