4

前言

最近在学习elasticsearch,想实现跟谷歌和百度类似的功能:下拉补全提示,如图所示:
image.png

准备

我使用的版本和依赖包,如下所示:

<properties>
    <java.version>17</java.version>
    <spring-boot.version>3.0.2</spring-boot.version>
    <spring-cloud.version>2022.0.0</spring-cloud.version>
    <spring-cloud-alibaba.version>2022.0.0.0-RC2</spring-cloud-alibaba.version>
</properties>

<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-data-elasticsearch</artifactId>
</dependency>
<dependency>
    <groupId>co.elastic.clients</groupId>
    <artifactId>elasticsearch-java</artifactId>
    <version>8.7.1</version>
</dependency>

devtools操作

首先,我们必须先创建index并设置成想要设置成下拉补全提示的字段为completion类型,如下所示:

PUT index_urls
{
  "mappings": {
    "properties": {
      "suggest": {
        "type": "completion",
        "analyzer": "ik_smart"
      }
    }
  }
}

这样我们创建了index_urls,并且设置好了suggest字段是completion类型。

接着,我们往里面加点数据,并且使用completion suggester进行查询,如下所示 :

// 自动补全查询
GET /index_urls/_search
{
  "suggest": {
    "title_suggest": {
      "text": "n", // 关键字
      "completion": {
        "field": "suggest", // 补全查询的字段
        "skip_duplicates": true, // 跳过重复的
        "size": 10 // 获取前10条结果
      }
    }
  }
} 

查询结果如下所示:

{
  "took": 1,
  "timed_out": false,
  "_shards": {
    "total": 1,
    "successful": 1,
    "skipped": 0,
    "failed": 0
  },
  "hits": {
    "total": {
      "value": 0,
      "relation": "eq"
    },
    "max_score": null,
    "hits": []
  },
  "suggest": {
    "title_suggest": [
      {
        "text": "n",
        "offset": 0,
        "length": 1,
        "options": [
          {
            "text": "npm、yarn的安装和设置淘宝镜像源_yarn设置淘宝镜像_cn_ljr的博客-CSDN博客",
            "_index": "index_urls",
            "_id": "64d0548bd8239d21cb9fe4e5",
            "_score": 1,
            "_source": {
              "_class": "com.seaurl.searchservice.document.UrlIndex",
              "id": "64d0548bd8239d21cb9fe4e5",
              "uid": "6461e6ac25d966329b7d7642",
              "categoryId": "64b89acfaf50e77e53ef89ef",
              "categoryName": "户外运动",
              "categoryParentId": "",
              "categoryParentName": "",
              "title": "npm、yarn的安装和设置淘宝镜像源_yarn设置淘宝镜像_cn_ljr的博客-CSDN博客",
              "suggest": {
                "input": [
                  "npm、yarn的安装和设置淘宝镜像源_yarn设置淘宝镜像_cn_ljr的博客-CSDN博客"
                ]
              },
              "url": "https://blog.csdn.net/cn_ljr/article/details/126319130",
              "domain": "blog.csdn.net",
              "description": "安装npm和yarn,配置npm和yarn的镜像源为淘宝镜像源_yarn设置淘宝镜像",
              "favicon": "https://cdn.seaurl.com/space/url/blog.csdn.net/favicon.ico",
              "env": "dev",
              "createdDt": 1691374731421,
              "updatedDt": 1691374731421
            }
          }
        ]
      }
    ]
  }
}

这样就完成了自动补全提示查询了,接下来我们使用java再实现一遍。

java操作

首先,我们创建实体类,并且定义completion类型的字段,如下所示:

@Data
public class UrlIndex {
    private String id;

    private String uid;

    // 分类id
    private String categoryId;

    private String categoryName;

    private String categoryParentId;

    private String categoryParentName;

    private String title;

    // 下拉提示建议使用的字段,注意:Completion类型字段,不能做筛选用
//    @CompletionField(analyzer="ik_smart",searchAnalyzer="ik_smart", maxInputLength = 100)
    private Completion suggest;

    private String url;

    private String domain;

    private String description;

    //如果没获取前端显示domain首字母
    private String favicon;

    private Date createdDt;//创建时间

    private Date updatedDt;//更新时间
}

接着,我们往es中添加数据,并且把查询转化成java代码,如下所示:

private SearchResponse getEsSuggestionData(String filedName, String fieldValue) {
        try {
            String index = getEsIndexByEnv();
            Suggester suggester = Suggester.of(s -> s
                    .suggesters("title-suggest", FieldSuggester.of(fs -> fs
                            .completion(cs -> cs.skipDuplicates(true)
                                    .size(10)
                                    .field(filedName)
                            )
                    ))
                    .text(fieldValue)
            );

            return elasticsearchClient.search(s ->
                            s.index(index)
                                    // 使用source可以返回固定字段
//                                    .source()
                                    .suggest(suggester)
                    , Map.class);
        } catch (Exception ex) {
            log.info("getEsSuggestionData error={}", ex.getMessage());
            return null;
        }
    }

这样就完成了查询的功能,接下来,我们要把返回的数据拿出来,并转换之后返回给前端显示,如下所示:

@Override
    public List<UrlIndexDto> searchSuggestionDataBy(String fieldName, String fieldValue) {
        SearchResponse response = getEsSuggestionData(fieldName, fieldValue);
        if (response != null) {
            Map suggestMap = response.suggest();
            if (suggestMap != null) {
                List<?> titleSuggestionList = (List<?>) suggestMap.get("title-suggest");
                if (titleSuggestionList != null) {
                    for (Object titleSuggestion : titleSuggestionList) {
                        if (titleSuggestion instanceof Suggestion) {
                            Suggestion suggestion = (Suggestion) titleSuggestion;

                            if (suggestion.isCompletion()) {
                                CompletionSuggest completionSuggest = suggestion.completion();
                                List<co.elastic.clients.elasticsearch.core.search.CompletionSuggestOption> options = completionSuggest.options();
                                List<UrlIndexDto> urlIndexDtos = new ArrayList<>();
                                for (co.elastic.clients.elasticsearch.core.search.CompletionSuggestOption option : options) {
                                    Object obj = option.source();
                                    ObjectMapper objectMapper = new ObjectMapper();
                                    UrlIndexDto urlIndexDto = objectMapper.convertValue(obj, UrlIndexDto.class);
                                    urlIndexDtos.add(urlIndexDto);
                                }
                                return urlIndexDtos;
                            }
                        }
                    }

                }
            }
        }
        return null;
    }

这样就完成了查询并返回的操作,下面我们讲解下前端如何实现。

前端操作

我们使用react和antd来实现,先定义组件和相关方法,如下所示:

<AutoComplete allowClear className={styles.input} options={options} onSelect={onSelect} value={input} onChange={async (e) => {
              setInput(e)
              debouncedOnChange(e);
            }}>
    <Input placeholder={'请输入搜索内容'} prefix={<SearchOutlined/>} size={'large'}
           onPressEnter={onSearch} />
</AutoComplete>

相关方法:

 const [input, setInput] = useState('')
const [options, setOptions] = useState([])

// 在组件外部定义防抖函数
const debouncedOnChange = _.debounce(async (e) => {
    // 调用自动补全接口
    const res = await dispatch(webSearchSuggestion({
        q: e
    }))
    const resData = res.payload.data
    if (resData && resData.length>0){
        let list = []
        resData.forEach(item =>{
            console.log('item resData=', item)
            list.push({
                label: item.title,
                value: item.title,
                url: item.url
            })
        })
        // 将数据设置到options中 
        setOptions(list)
    }else{
        setOptions([])
    }
}, 500);

// 搜索框回车事件,调用查询接口(非自动补全接口)
async function onSelect(value, option){
    dispatch(webSearch({
        q: option.value,
        pageNum: 1,
        pageSize: 20
    }))
}

我们使用了ladash的防抖函数来实现搜索。

完成了准备工作,我们来看看实现效果,如下所示:
image.png

注意

1、不是你在实体类中定义了Completion类型的字段就ok了,要提前声明Completion才管用,亲自踩过的坑!!!

总结

1、完成这些代码其实花费了一点时间的,主要是不知道如何把devtools的查询转换成java代码,并且我的版本是最新的,用的依赖包是上面提到的,所以写法上市面上没有找到过,完全靠自己搜索和chatgpt给的提示完成的。

引用

Completion Suggester — Java API Client
十.全文检索ElasticSearch经典入门-自动补全功能


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