【SpringBoot整合ElasticSearch7.x及实战】

谁践踏了优雅 2023-09-24 17:46 44阅读 0赞

此笔记内容为狂神说SpringBoot整合ElasticSearch部分

**目录**

一、SpringBoot整合

1、创建工程

2、导入依赖

导入elasticsearch依赖

提前导入fastjson、lombok

3、创建并编写配置类

4、创建并编写实体类

5、测试

索引的操作

文档的操作

二、ElasticSearch实战

防京东商城搜索（高亮）

1、工程创建（springboot）

2、基本编码

①导入依赖

②导入前端素材

③编写 application.preperties配置文件

④测试controller和view

⑤编写Config

⑥编写service

⑦编写controller

⑧测试结果

3、爬虫（jsoup）

①搜索京东搜索页面，并分析页面

②爬取数据（获取请求返回的页面信息，筛选出可用的）

4、搜索高亮

①ContentService

②ContentController

③结果展示

5、前后端分离（简单使用Vue）

①下载并引入Vue.min.js和axios.js

②修改静态页面

使用term（精确查询）时遇到的问题

--------------------

# 一、SpringBoot整合 #

--------------------

## 1、创建工程 ##

创建一个springboot项目

**目录结构**

![2b36ae31ec684a2a835f4c8042a91079.png][]

## 2、导入依赖 ##

注意依赖版本和安装的版本一致

### 导入elasticsearch依赖 ###

<dependency>
        <groupId>org.springframework.boot</groupId>
        <artifactId>spring-boot-starter-data-elasticsearch</artifactId>
    </dependency>

### 提前导入fastjson、lombok ###

<dependency>
        <groupId>com.alibaba</groupId>
        <artifactId>fastjson</artifactId>
        <version>1.2.70</version>
    </dependency>
    
    <dependency>
        <groupId>org.projectlombok</groupId>
        <artifactId>lombok</artifactId>
        <optional>true</optional>
    </dependency>

## 3、创建并编写配置类 ##

@Configuration
    public class ElasticSearchConfig {
        // 注册 rest高级客户端 
        @Bean
        public RestHighLevelClient restHighLevelClient(){
            RestHighLevelClient client = new RestHighLevelClient(
                    RestClient.builder(
                            new HttpHost("127.0.0.1",9200,"http")
                    )
            );
            return client;
        }
    }

## 4、创建并编写实体类 ##

@Data
    @NoArgsConstructor
    @AllArgsConstructor
    public class User implements Serializable {
        private static final long serialVersionUID = -3843548915035470817L;
        private String name;
        private Integer age;
    }

## 5、测试 ##

所有测试均在 `SpringbootElasticsearchApplicationTests`中编写

**注入 `RestHighLevelClient`**

@Autowired
    public RestHighLevelClient restHighLevelClient;

### 索引的操作 ###

**1、索引的创建**

// 测试索引的创建， Request PUT liuyou_index
    @Test
    public void testCreateIndex() throws IOException {
        CreateIndexRequest request = new CreateIndexRequest("liuyou_index");
        CreateIndexResponse response = restHighLevelClient.indices().create(request, RequestOptions.DEFAULT);
        System.out.println(response.isAcknowledged());// 查看是否创建成功
        System.out.println(response);// 查看返回对象
        restHighLevelClient.close();
    }

**2、索引的获取，并判断其是否存在**

// 测试获取索引，并判断其是否存在
    @Test
    public void testIndexIsExists() throws IOException {
        GetIndexRequest request = new GetIndexRequest("index");
        boolean exists = restHighLevelClient.indices().exists(request, RequestOptions.DEFAULT);
        System.out.println(exists);// 索引是否存在
        restHighLevelClient.close();
    }

**3、索引的删除**

// 测试索引删除
    @Test
    public void testDeleteIndex() throws IOException {
        DeleteIndexRequest request = new DeleteIndexRequest("liuyou_index");
        AcknowledgedResponse response = restHighLevelClient.indices().delete(request, RequestOptions.DEFAULT);
        System.out.println(response.isAcknowledged());// 是否删除成功
        restHighLevelClient.close();
    }

### 文档的操作 ###

**1、文档的添加**

// 测试添加文档(先创建一个User实体类，添加fastjson依赖)
    @Test
    public void testAddDocument() throws IOException {
        // 创建一个User对象
        User liuyou = new User("liuyou", 18);
        // 创建请求
        IndexRequest request = new IndexRequest("liuyou_index");
        // 制定规则 PUT /liuyou_index/_doc/1
        request.id("1");// 设置文档ID
        request.timeout(TimeValue.timeValueMillis(1000));// request.timeout("1s")
        // 将我们的数据放入请求中
        request.source(JSON.toJSONString(liuyou), XContentType.JSON);
        // 客户端发送请求，获取响应的结果
        IndexResponse response = restHighLevelClient.index(request, RequestOptions.DEFAULT);
        System.out.println(response.status());// 获取建立索引的状态信息 CREATED
        System.out.println(response);// 查看返回内容 IndexResponse[index=liuyou_index,type=_doc,id=1,version=1,result=created,seqNo=0,primaryTerm=1,shards={"total":2,"successful":1,"failed":0}]
    }

**2、文档信息的获取**

// 测试获得文档信息
    @Test
    public void testGetDocument() throws IOException {
        GetRequest request = new GetRequest("liuyou_index","1");
        GetResponse response = restHighLevelClient.get(request, RequestOptions.DEFAULT);
        System.out.println(response.getSourceAsString());// 打印文档内容
        System.out.println(request);// 返回的全部内容和命令是一样的
        restHighLevelClient.close();
    }

**3、文档的获取，并判断其是否存在**

// 获取文档，判断是否存在 get /liuyou_index/_doc/1
    @Test
    public void testDocumentIsExists() throws IOException {
        GetRequest request = new GetRequest("liuyou_index", "1");
        // 不获取返回的 _source的上下文了
        request.fetchSourceContext(new FetchSourceContext(false));
        request.storedFields("_none_");
        boolean exists = restHighLevelClient.exists(request, RequestOptions.DEFAULT);
        System.out.println(exists);
    }

**4、文档的更新**

// 测试更新文档内容
    @Test
    public void testUpdateDocument() throws IOException {
        UpdateRequest request = new UpdateRequest("liuyou_index", "1");
        User user = new User("lmk",11);
        request.doc(JSON.toJSONString(user),XContentType.JSON);
        UpdateResponse response = restHighLevelClient.update(request, RequestOptions.DEFAULT);
        System.out.println(response.status()); // OK
        restHighLevelClient.close();
    }

**5、文档的删除**

// 测试删除文档
    @Test
    public void testDeleteDocument() throws IOException {
        DeleteRequest request = new DeleteRequest("liuyou_index", "1");
        request.timeout("1s");
        DeleteResponse response = restHighLevelClient.delete(request, RequestOptions.DEFAULT);
        System.out.println(response.status());// OK
    }

**6、文档的查询**

// 查询
    // SearchRequest 搜索请求
    // SearchSourceBuilder 条件构造
    // HighlightBuilder 高亮
    // TermQueryBuilder 精确查询
    // MatchAllQueryBuilder
    // xxxQueryBuilder ...
    @Test
    public void testSearch() throws IOException {
        // 1.创建查询请求对象
        SearchRequest searchRequest = new SearchRequest();
        // 2.构建搜索条件
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        // (1)查询条件 使用QueryBuilders工具类创建
        // 精确查询
        TermQueryBuilder termQueryBuilder = QueryBuilders.termQuery("name", "liuyou");
        //        // 匹配查询
        //        MatchAllQueryBuilder matchAllQueryBuilder = QueryBuilders.matchAllQuery();
        // (2)其他<可有可无>：（可以参考 SearchSourceBuilder 的字段部分）
        // 设置高亮
        searchSourceBuilder.highlighter(new HighlightBuilder());
        //        // 分页
        //        searchSourceBuilder.from();
        //        searchSourceBuilder.size();
        searchSourceBuilder.timeout(new TimeValue(60, TimeUnit.SECONDS));
        // (3)条件投入
        searchSourceBuilder.query(termQueryBuilder);
        // 3.添加条件到请求
        searchRequest.source(searchSourceBuilder);
        // 4.客户端查询请求
        SearchResponse search = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
        // 5.查看返回结果
        SearchHits hits = search.getHits();
        System.out.println(JSON.toJSONString(hits));
        System.out.println("=======================");
        for (SearchHit documentFields : hits.getHits()) {
            System.out.println(documentFields.getSourceAsMap());
        }
    }

**前面的操作都无法批量添加数据**

// 上面的这些api无法批量增加数据（只会保留最后一个source）
    @Test
    public void test() throws IOException {
        IndexRequest request = new IndexRequest("bulk");// 没有id会自动生成一个随机ID
        request.source(JSON.toJSONString(new User("liu",1)),XContentType.JSON);
        request.source(JSON.toJSONString(new User("min",2)),XContentType.JSON);
        request.source(JSON.toJSONString(new User("kai",3)),XContentType.JSON);
        IndexResponse index = restHighLevelClient.index(request, RequestOptions.DEFAULT);
        System.out.println(index.status());// created
    }

**7、批量添加数据**

// 特殊的，真的项目一般会 批量插入数据
    @Test
    public void testBulk() throws IOException {
        BulkRequest bulkRequest = new BulkRequest();
        bulkRequest.timeout("10s");
        ArrayList<User> users = new ArrayList<>();
        users.add(new User("liuyou-1",1));
        users.add(new User("liuyou-2",2));
        users.add(new User("liuyou-3",3));
        users.add(new User("liuyou-4",4));
        users.add(new User("liuyou-5",5));
        users.add(new User("liuyou-6",6));
        // 批量请求处理
        for (int i = 0; i < users.size(); i++) {
            bulkRequest.add(
                    // 这里是数据信息
                    new IndexRequest("bulk")
                            .id(""+(i + 1)) // 没有设置id 会自定生成一个随机id
                            .source(JSON.toJSONString(users.get(i)),XContentType.JSON)
            );
        }
        BulkResponse bulk = restHighLevelClient.bulk(bulkRequest, RequestOptions.DEFAULT);
        System.out.println(bulk.status());// ok
    }

# 二、ElasticSearch实战 #

--------------------

## 防京东商城搜索（高亮） ##

## 1、工程创建（springboot） ##

创建一个springboot工程

![d094528c29f2422a915b8f98c3f7480d.png][]

## 2、基本编码 ##

### ①导入依赖 ###

<properties>
        <java.version>1.8</java.version>
        <elasticsearch.version>7.6.1</elasticsearch.version>
    </properties>
    <dependencies>
        
        
        <dependency>
            <groupId>org.jsoup</groupId>
            <artifactId>jsoup</artifactId>
            <version>1.10.2</version>
        </dependency>
        
        <dependency>
            <groupId>com.alibaba</groupId>
            <artifactId>fastjson</artifactId>
            <version>1.2.70</version>
        </dependency>
        
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-data-elasticsearch</artifactId>
        </dependency>
        
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-thymeleaf</artifactId>
        </dependency>
        
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-web</artifactId>
        </dependency>
        
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-devtools</artifactId>
            <scope>runtime</scope>
            <optional>true</optional>
        </dependency>
        
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-configuration-processor</artifactId>
            <optional>true</optional>
        </dependency>
        
        <dependency>
            <groupId>org.projectlombok</groupId>
            <artifactId>lombok</artifactId>
            <optional>true</optional>
        </dependency>
        
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-test</artifactId>
            <scope>test</scope>
        </dependency>
    </dependencies>

### ②导入前端素材 ###

导入statis和templates里的文件

链接：[百度网盘 请输入提取码][Link 1]  
提取码：qk8p

### ③编写 `application.preperties`配置文件 ###

# 更改端口，防止冲突
    server.port=9999
    # 关闭thymeleaf缓存
    spring.thymeleaf.cache=false

### ④测试controller和view ###

@Controller
    public class IndexController {
        @GetMapping({"/","index"})
        public String index(){
            return "index";
        }
    }

访问 localhost:9999

![ad65f85136a2482f8535150d58527fd0.png][]

到这里可以先去编写爬虫，编写之后，回到这里

### ⑤编写Config ###

@Configuration
    public class ElasticSearchConfig {
        @Bean
        public RestHighLevelClient restHighLevelClient(){
            RestHighLevelClient client = new RestHighLevelClient(
                    RestClient.builder(
                            new HttpHost("127.0.0.1",9200,"http")
                    )
            );
            return client;
        }
    }

### ⑥编写service ###

因为是爬取的数据，那么就不走Dao，以下编写都不会编写接口，开发中必须严格要求编写

**ContentService**

@Service
    public class ContentService {
        @Autowired
        private RestHighLevelClient restHighLevelClient;
        // 1、解析数据放入 es 索引中
        public Boolean parseContent(String keyword) throws IOException {
            // 获取内容
            List<Content> contents = HtmlParseUtil.parseJD(keyword);
            // 内容放入 es 中
            BulkRequest bulkRequest = new BulkRequest();
            bulkRequest.timeout("2m"); // 可更具实际业务是指
            for (int i = 0; i < contents.size(); i++) {
                bulkRequest.add(
                        new IndexRequest("jd_goods")
                                .id(""+(i+1))
                                .source(JSON.toJSONString(contents.get(i)), XContentType.JSON)
                );
            }
            BulkResponse bulk = restHighLevelClient.bulk(bulkRequest, RequestOptions.DEFAULT);
            restHighLevelClient.close();
            return !bulk.hasFailures();
        }
            // 2、根据keyword分页查询结果
        public List<Map<String, Object>> search(String keyword, Integer pageIndex, Integer pageSize) throws IOException {
            if (pageIndex < 0){
                pageIndex = 0;
            }
            SearchRequest jd_goods = new SearchRequest("jd_goods");
            // 创建搜索源建造者对象
            SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
            // 条件采用：精确查询 通过keyword查字段name
            TermQueryBuilder termQueryBuilder = QueryBuilders.termQuery("name", keyword);
            searchSourceBuilder.query(termQueryBuilder);
            searchSourceBuilder.timeout(new TimeValue(60, TimeUnit.SECONDS));// 60s
            // 分页
            searchSourceBuilder.from(pageIndex);
            searchSourceBuilder.size(pageSize);
            // 高亮
            // ....
            // 搜索源放入搜索请求中
            jd_goods.source(searchSourceBuilder);
            // 执行查询，返回结果
            SearchResponse searchResponse = restHighLevelClient.search(jd_goods, RequestOptions.DEFAULT);
            restHighLevelClient.close();
            // 解析结果
            SearchHits hits = searchResponse.getHits();
            List<Map<String,Object>> results = new ArrayList<>();
            for (SearchHit documentFields : hits.getHits()) {
                Map<String, Object> sourceAsMap = documentFields.getSourceAsMap();
                results.add(sourceAsMap);
            }
            // 返回查询的结果
            return results;
        }
    }

### ⑦编写controller ###

@Controller
    public class ContentController {
        @Autowired
        private ContentService contentService;
        @ResponseBody
        @GetMapping("/parse/{keyword}")
        public Boolean parse(@PathVariable("keyword") String keyword) throws IOException {
            return contentService.parseContent(keyword);
        }
        @ResponseBody
        @GetMapping("/search/{keyword}/{pageIndex}/{pageSize}")
        public List<Map<String, Object>> parse(@PathVariable("keyword") String keyword,
                                               @PathVariable("pageIndex") Integer pageIndex,
                                               @PathVariable("pageSize") Integer pageSize) throws IOException {
            return contentService.search(keyword,pageIndex,pageSize);
        }
    }

### ⑧测试结果 ###

**1、解析数据放入 es 索引中**

![c32b1da360994bf7adfbc91d2b59c5ee.png][]

![812c0cc8f37448088e63f986f9ae6227.png][]

**根据keyword分页查询结果**

## 3、爬虫（jsoup） ##

数据获取：数据库、消息队列、爬虫、…

### ①搜索京东搜索页面，并分析页面 ###

> [java - 商品搜索 - 京东][java - _ -]

页面如下

![29fdf3c8287a4b679b58a9f70d1f6f5d.png][]

审查页面元素

**页面列表id：J\_goodsList**

![8593e7d53e1a40abad0650b3780e8a9a.png][]

**目标元素：img、price、name**

![b21843654e86471ba26c4b50dccb0282.png][]

### ②爬取数据（获取请求返回的页面信息，筛选出可用的） ###

创建HtmlParseUtil，并简单编写

public class HtmlParseUtil {
        public static void main(String[] args) throws IOException {
            /// 使用前需要联网
            // 请求url
            String url = "http://search.jd.com/search?keyword=java";
            // 1.解析网页(jsoup 解析返回的对象是浏览器Document对象)
            Document document = Jsoup.parse(new URL(url), 30000);
            // 使用document可以使用在js对document的所有操作
            // 2.获取元素（通过id）
            Element j_goodsList = document.getElementById("J_goodsList");
            // 3.获取J_goodsList ul 每一个 li
            Elements lis = j_goodsList.getElementsByTag("li");
            // 4.获取li下的 img、price、name
            for (Element li : lis) {
                String img = li.getElementsByTag("img").eq(0).attr("src");// 获取li下 第一张图片
                String name = li.getElementsByClass("p-name").eq(0).text();
                String price = li.getElementsByClass("p-price").eq(0).text();
                System.out.println("=======================");
                System.out.println("img : " + img);
                System.out.println("name : " + name);
                System.out.println("price : " + price);
            }
        }
    }

**运行结果**

![ef2b2ba3595e490f85f9b674db6efa53.png][]

> 一般图片特别多的网站，所有的图片都是通过延迟加载的

// 打印标签内容
    Elements lis = j_goodsList.getElementsByTag("li");
    System.out.println(lis);

打印所有li标签，发现img标签中并没有属性src的设置，只是data-lazy-ing设置图片加载的地址

![e85b43ee5c8c4b5092a8d3393e59251b.png][]

**创建HtmlParseUtil、改写**

*  更改图片获取属性为 `data-lazy-img`
 *  与实体类结合，实体类如下

@Data
    @AllArgsConstructor
    @NoArgsConstructor
    public class Content implements Serializable {
        private static final long serialVersionUID = -8049497962627482693L;
        private String name;
        private String img;
        private String price;
    }

*  封装为方法

public class HtmlParseUtil {
        public static void main(String[] args) throws IOException {
            System.out.println(parseJD("java"));
        }
        public static List<Content> parseJD(String keyword) throws IOException {
            /// 使用前需要联网
            // 请求url
            String url = "http://search.jd.com/search?keyword=" + keyword;
            // 1.解析网页(jsoup 解析返回的对象是浏览器Document对象)
            Document document = Jsoup.parse(new URL(url), 30000);
            // 使用document可以使用在js对document的所有操作
            // 2.获取元素（通过id）
            Element j_goodsList = document.getElementById("J_goodsList");
            // 3.获取J_goodsList ul 每一个 li
            Elements lis = j_goodsList.getElementsByTag("li");
    //        System.out.println(lis);
            // 4.获取li下的 img、price、name
            // list存储所有li下的内容
            List<Content> contents = new ArrayList<Content>();
            for (Element li : lis) {
                // 由于网站图片使用懒加载，将src属性替换为data-lazy-img
                String img = li.getElementsByTag("img").eq(0).attr("data-lazy-img");// 获取li下 第一张图片
                String name = li.getElementsByClass("p-name").eq(0).text();
                String price = li.getElementsByClass("p-price").eq(0).text();
                // 封装为对象
                Content content = new Content(name,img,price);
                // 添加到list中
                contents.add(content);
            }
    //        System.out.println(contents);
            // 5.返回 list
            return contents;
        }
    }

**结果展示**

![351d520cc73149cf9bcce0f253ecb04d.png][]

## 4、搜索高亮 ##

在3、的基础上添加内容

### ①ContentService ###

// 3、 在2的基础上进行高亮查询
    public List<Map<String, Object>> highlightSearch(String keyword, Integer pageIndex, Integer pageSize) throws IOException {
        SearchRequest searchRequest = new SearchRequest("jd_goods");
        SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
        // 精确查询，添加查询条件
        TermQueryBuilder termQueryBuilder = QueryBuilders.termQuery("name", keyword);
        searchSourceBuilder.timeout(new TimeValue(60, TimeUnit.SECONDS));
        searchSourceBuilder.query(termQueryBuilder);
        // 分页
        searchSourceBuilder.from(pageIndex);
        searchSourceBuilder.size(pageSize);
        // 高亮 =========
        HighlightBuilder highlightBuilder = new HighlightBuilder();
        highlightBuilder.field("name");
        highlightBuilder.preTags("<span style='color:red'>");
        highlightBuilder.postTags("</span>");
        searchSourceBuilder.highlighter(highlightBuilder);
        // 执行查询
        searchRequest.source(searchSourceBuilder);
        SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
        // 解析结果 ==========
        SearchHits hits = searchResponse.getHits();
        List<Map<String, Object>> results = new ArrayList<>();
        for (SearchHit documentFields : hits.getHits()) {
            // 使用新的字段值（高亮），覆盖旧的字段值
            Map<String, Object> sourceAsMap = documentFields.getSourceAsMap();
            // 高亮字段
            Map<String, HighlightField> highlightFields = documentFields.getHighlightFields();
            HighlightField name = highlightFields.get("name");
            // 替换
            if (name != null){
                Text[] fragments = name.fragments();
                StringBuilder new_name = new StringBuilder();
                for (Text text : fragments) {
                    new_name.append(text);
                }
                sourceAsMap.put("name",new_name.toString());
            }
            results.add(sourceAsMap);
        }
        return results;
    }

### ②ContentController ###

@ResponseBody
    @GetMapping("/h_search/{keyword}/{pageIndex}/{pageSize}")
    public List<Map<String, Object>> highlightParse(@PathVariable("keyword") String keyword,
                                           @PathVariable("pageIndex") Integer pageIndex,
                                           @PathVariable("pageSize") Integer pageSize) throws IOException {
        return contentService.highlightSearch(keyword,pageIndex,pageSize);
    }

### ③结果展示 ###

![0a4cb56873874fa2a4df2a5b9eb2484f.png][]

## 5、前后端分离（简单使用Vue） ##

> 删除Controller 方法上的 [@ResponseBody][ResponseBody]注解

![4d6212a850a2484da6d873c92f1eb5f3.png][]

### ①下载并引入Vue.min.js和axios.js ###

如果安装了nodejs，可以按如下步骤，没有的素材里有

打开电脑cmd命令窗口，执行以下命令

> npm init
> 
> npm install vue  
> npm install axios

![7b9a9a2d9419419a9277440f6dcc21fc.png][]

没有axios和vue文件的网上下载一个就行，然后复制到项目里

![e4f8c030a97b48dc89b4f67cf8885275.png][]

### ②修改静态页面 ###

**引入js**

**修改后的index.html**

<!DOCTYPE html>
    <html xmlns:th="http://www.thymeleaf.org">
    <head>
        <meta charset="utf-8"/>
        <title>狂神说Java-ES仿京东实战</title>
        <link rel="stylesheet" th:href="@{/css/style.css}"/>
        <script th:src="@{/js/jquery.min.js}"></script>
    </head>
    <body class="pg">
    <div class="page">
        <div id="app" class=" mallist tmall- page-not-market ">
            
            <div id="header" class=" header-list-app">
                <div class="headerLayout">
                    <div class="headerCon ">
                        
                        <h1 id="mallLogo">
                            <img th:src="@{/images/jdlogo.png}" alt="">
                        </h1>
                        <div class="header-extra">
                            
                            <div id="mallSearch" class="mall-search">
                                <form name="searchTop" class="mallSearch-form clearfix">
                                    <fieldset>
                                        <legend>天猫搜索</legend>
                                        <div class="mallSearch-input clearfix">
                                            <div class="s-combobox" id="s-combobox-685">
                                                <div class="s-combobox-input-wrap">
                                                    <input v-model="keyword"  type="text" autocomplete="off" id="mq"
                                                           class="s-combobox-input"  aria-haspopup="true">
                                                </div>
                                            </div>
                                            <button type="submit" @click.prevent="searchKey" id="searchbtn">搜索</button>
                                        </div>
                                    </fieldset>
                                </form>
                                <ul class="relKeyTop">
                                    <li><a>狂神说Java</a></li>
                                    <li><a>狂神说前端</a></li>
                                    <li><a>狂神说Linux</a></li>
                                    <li><a>狂神说大数据</a></li>
                                    <li><a>狂神聊理财</a></li>
                                </ul>
                            </div>
                        </div>
                    </div>
                </div>
            </div>
            
            <div id="content">
                <div class="main">
                    
                    <form class="navAttrsForm">
                        <div class="attrs j_NavAttrs" style="display:block">
                            <div class="brandAttr j_nav_brand">
                                <div class="j_Brand attr">
                                    <div class="attrKey">
                                        品牌
                                    </div>
                                    <div class="attrValues">
                                        <ul class="av-collapse row-2">
                                            <li><a href="#"> 狂神说 </a></li>
                                            <li><a href="#"> Java </a></li>
                                        </ul>
                                    </div>
                                </div>
                            </div>
                        </div>
                    </form>
                    
                    <div class="filter clearfix">
                        <a class="fSort fSort-cur">综合<i class="f-ico-arrow-d"></i></a>
                        <a class="fSort">人气<i class="f-ico-arrow-d"></i></a>
                        <a class="fSort">新品<i class="f-ico-arrow-d"></i></a>
                        <a class="fSort">销量<i class="f-ico-arrow-d"></i></a>
                        <a class="fSort">价格<i class="f-ico-triangle-mt"></i><i class="f-ico-triangle-mb"></i></a>
                    </div>
                    
                    <div class="view grid-nosku" >
                        <div class="product" v-for="result in results">
                            <div class="product-iWrap">
                                
                                <div class="productImg-wrap">
                                    <a class="productImg">
                                        <img :src="result.img">
                                    </a>
                                </div>
                                
                                <p class="productPrice">
                                    <em v-text="result.price"></em>
                                </p>
                                
                                <p class="productTitle">
                                    <a v-html="result.name"></a>
                                </p>
                                
                                <div class="productShop">
                                    <span>店铺： 狂神说Java </span>
                                </div>
                                
                                <p class="productStatus">
                                    <span>月成交<em>999笔</em></span>
                                    <span>评价 <a>3</a></span>
                                </p>
                            </div>
                        </div>
                    </div>
                </div>
            </div>
        </div>
    </div>
    <script th:src="@{/js/vue.min.js}"></script>
    <script th:src="@{/js/axios.min.js}"></script>
    <script>
        new Vue({
            el:"#app",
            data:{
                "keyword": '', // 搜索的关键字
                "results":[] // 后端返回的结果
            },
            methods:{
                searchKey(){
                    var keyword = this.keyword;
                    console.log(keyword);
                    axios.get('h_search/'+keyword+'/0/20').then(response=>{
                        console.log(response.data);
                        this.results=response.data;
                    })
                }
            }
        });
    </script>
    </body>
    </html>

**测试**

![55b6d74c50a94fb09825fd6b302822bf.png][]

## 使用term（精确查询）时遇到的问题 ##

> 字段值必须是一个词（索引中存在的词），才能匹配
> 
>  *  问题：中文字符串，term查询时无法查询到数据（比如，“编程”两字在文档中存在，但是搜索不到）
>  *  原因：索引为配置中文分词器（默认使用standard，即所有中文字符串都会被切分为单个中文汉字作为单词），所以没有超过1个汉字的词，也就无法匹配，进而查不到数据
>  *  解决：创建索引时配置中文分词器，如
> 
>     PUT example
>     {
>       "mappings": {
>         "properties": {
>           "name":{
>             "type": "text",
>             "analyzer": "ik_max_word"  // ik分词器
>           }
>         }
>       }
>     }
> 
>  *  查询的英文字符只能是小写，大写都无效
>  *  查询时英文单词必须是完整的

最后附上我自己用的依赖

<dependencies>
    <dependency>
    <groupId>org.elasticsearch</groupId>
    <artifactId>elasticsearch</artifactId>
    <version>7.8.0</version>
    </dependency>
    
    <dependency>
    <groupId>org.elasticsearch.client</groupId>
    <artifactId>elasticsearch-rest-high-level-client</artifactId>
    <version>7.8.0</version>
    </dependency>
    
    <dependency>
    <groupId>org.apache.logging.log4j</groupId>
    <artifactId>log4j-api</artifactId>
    <version>2.8.2</version>
    </dependency>
    <dependency>
    <groupId>org.apache.logging.log4j</groupId>
    <artifactId>log4j-core</artifactId>
    <version>2.8.2</version>
    </dependency>
    <dependency>
    <groupId>com.fasterxml.jackson.core</groupId>
    <artifactId>jackson-databind</artifactId>
    <version>2.9.9</version>
    </dependency>
    
    <dependency>
    <groupId>junit</groupId>
    <artifactId>junit</artifactId>
    <version>4.12</version>
    </dependency>
    </dependencies>

结束！

[2b36ae31ec684a2a835f4c8042a91079.png]: https://img-blog.csdnimg.cn/2b36ae31ec684a2a835f4c8042a91079.png
[d094528c29f2422a915b8f98c3f7480d.png]: https://img-blog.csdnimg.cn/d094528c29f2422a915b8f98c3f7480d.png
[Link 1]: https://pan.baidu.com/s/1M5uWdYsCZyzIAOcgcRkA_A
[ad65f85136a2482f8535150d58527fd0.png]: https://img-blog.csdnimg.cn/ad65f85136a2482f8535150d58527fd0.png
[c32b1da360994bf7adfbc91d2b59c5ee.png]: https://img-blog.csdnimg.cn/c32b1da360994bf7adfbc91d2b59c5ee.png
[812c0cc8f37448088e63f986f9ae6227.png]: https://img-blog.csdnimg.cn/812c0cc8f37448088e63f986f9ae6227.png
[java - _ -]: http://search.jd.com/search?keyword=java
[29fdf3c8287a4b679b58a9f70d1f6f5d.png]: https://img-blog.csdnimg.cn/29fdf3c8287a4b679b58a9f70d1f6f5d.png
[8593e7d53e1a40abad0650b3780e8a9a.png]: https://img-blog.csdnimg.cn/8593e7d53e1a40abad0650b3780e8a9a.png
[b21843654e86471ba26c4b50dccb0282.png]: https://img-blog.csdnimg.cn/b21843654e86471ba26c4b50dccb0282.png
[ef2b2ba3595e490f85f9b674db6efa53.png]: https://img-blog.csdnimg.cn/ef2b2ba3595e490f85f9b674db6efa53.png
[e85b43ee5c8c4b5092a8d3393e59251b.png]: https://img-blog.csdnimg.cn/e85b43ee5c8c4b5092a8d3393e59251b.png
[351d520cc73149cf9bcce0f253ecb04d.png]: https://img-blog.csdnimg.cn/351d520cc73149cf9bcce0f253ecb04d.png
[0a4cb56873874fa2a4df2a5b9eb2484f.png]: https://img-blog.csdnimg.cn/0a4cb56873874fa2a4df2a5b9eb2484f.png
[ResponseBody]: https://github.com/ResponseBody
[4d6212a850a2484da6d873c92f1eb5f3.png]: https://img-blog.csdnimg.cn/4d6212a850a2484da6d873c92f1eb5f3.png
[7b9a9a2d9419419a9277440f6dcc21fc.png]: https://img-blog.csdnimg.cn/7b9a9a2d9419419a9277440f6dcc21fc.png
[e4f8c030a97b48dc89b4f67cf8885275.png]: https://img-blog.csdnimg.cn/e4f8c030a97b48dc89b4f67cf8885275.png
[55b6d74c50a94fb09825fd6b302822bf.png]: https://img-blog.csdnimg.cn/55b6d74c50a94fb09825fd6b302822bf.png