5 根据文档ID删除职位
5.1 实现步骤
- 构建delete请求
- 使用RestHighLevelClient执行delete请求
参考代码：
@Override public void deleteById(long id) throws IOException { // 1. 构建delete请求 DeleteRequest deleteRequest = new DeleteRequest(JOB_IDX_NAME, id + ""); // 2. 使用client执行delete请求 restHighLevelClient.delete(deleteRequest, RequestOptions.DEFAULT); }
5.2 编写测试用例
- 在测试用例中执行根据ID删除文档操作
- 使用VSCode发送请求，查看指定ID的文档是否已经被删除
参考代码：
@Test public void deleteByIdTest() throws IOException { jobFullTextService.deleteById(1); }
6 根据关键字检索数据
6.1 实现步骤
- 构建SearchRequest检索请求
- 创建一个SearchSourceBuilder专门用于构建查询条件
- 使用QueryBuilders.multiMatchQuery构建一个查询条件（搜索title、jd），并配置到SearchSourceBuilder
- 调用SearchRequest.source将查询条件设置到检索请求
- 执行RestHighLevelClient.search发起请求
- 遍历结果
- 获取命中的结果
- 将JSON字符串转换为对象
- 使用SearchHit.getId设置文档ID
参考代码：
@Override public List<JobDetail> searchByKeywords(String keywords) throws IOException { // 1. 构建SearchRequest检索请求 SearchRequest searchRequest = new SearchRequest(JOB_IDX_NAME); // 2. 创建一个SearchSourceBuilder专门用于构建查询条件 SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); // 3. 使用QueryBuilders.multiMatchQuery构建一个查询条件，并配置到SearchSourceBuilder MultiMatchQueryBuilder queryBuilder = QueryBuilders.multiMatchQuery(keywords, "jd", "title"); searchSourceBuilder.query(queryBuilder); // 4. 调用SearchRequest.source将查询条件设置到检索请求 searchRequest.source(searchSourceBuilder); // 5. 执行RestHighLevelClient.search发起请求 SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT); // 6. 遍历结果 SearchHits hits = searchResponse.getHits(); List<JobDetail> jobDetailList = new ArrayList<>(); for (SearchHit hit : hits) { // 1) 获取命中的结果 String json = hit.getSourceAsString(); // 2) 将JSON字符串转换为对象 JobDetail jobDetail = JSON.parseObject(json, JobDetail.class); // 3) 使用SearchHit.getId设置文档ID jobDetail.setId(Long.parseLong(hit.getId())); jobDetailList.add(jobDetail); } return jobDetailList; }
6.2 编写测试用例
搜索标题、职位描述中包含销售的职位。
@Test public void searchByKeywordsTest() throws IOException { List<JobDetail> jobDetailList = jobFullTextService.searchByKeywords("销售"); for (JobDetail jobDetail : jobDetailList) { System.out.println(jobDetail); } }
7 分页检索
7.1 实现步骤
步骤和之前的关键字搜索类似，只不过构建查询条件的时候，需要加上分页的设置。
- 构建SearchRequest检索请求
- 创建一个SearchSourceBuilder专门用于构建查询条件
- 使用QueryBuilders.multiMatchQuery构建一个查询条件，并配置到SearchSourceBuilder
- 设置SearchSourceBuilder的from和size参数，构建分页
- 调用SearchRequest.source将查询条件设置到检索请求
- 执行RestHighLevelClient.search发起请求
- 遍历结果
- 获取命中的结果
- 将JSON字符串转换为对象
- 使用SearchHit.getId设置文档ID
- 将结果封装到Map结构中（带有分页信息）
a) total -> 使用SearchHits.getTotalHits().value获取到所有的记录数
b) content -> 当前分页中的数据
@Override public Map<String, Object> searchByPage(String keywords, int pageNum, int pageSize) throws IOException { // 1. 构建SearchRequest检索请求 SearchRequest searchRequest = new SearchRequest(JOB_IDX_NAME); // 2. 创建一个SearchSourceBuilder专门用于构建查询条件 SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); // 3. 使用QueryBuilders.multiMatchQuery构建一个查询条件，并配置到SearchSourceBuilder MultiMatchQueryBuilder queryBuilder = QueryBuilders.multiMatchQuery(keywords, "jd", "title"); searchSourceBuilder.query(queryBuilder); // 4. 设置SearchSourceBuilder的from和size参数，构建分页 searchSourceBuilder.from((pageNum – 1) * pageSize); searchSourceBuilder.size(pageSize); // 4. 调用SearchRequest.source将查询条件设置到检索请求 searchRequest.source(searchSourceBuilder); // 5. 执行RestHighLevelClient.search发起请求 SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT); // 6. 遍历结果 SearchHits hits = searchResponse.getHits(); List<JobDetail> jobDetailList = new ArrayList<>(); for (SearchHit hit : hits) { // 1) 获取命中的结果 String json = hit.getSourceAsString(); // 2) 将JSON字符串转换为对象 JobDetail jobDetail = JSON.parseObject(json, JobDetail.class); // 3) 使用SearchHit.getId设置文档ID jobDetail.setId(Long.parseLong(hit.getId())); jobDetailList.add(jobDetail); } // 8. 将结果封装到Map结构中（带有分页信息） // a) total -> 使用SearchHits.getTotalHits().value获取到所有的记录数 // b) content -> 当前分页中的数据 Map<String, Object> result = new HashMap<>(); result.put("total", hits.getTotalHits().value); result.put("content", jobDetailList); return result; }
6.7.2 编写测试用例
- 搜索关键字为“销售”，查询第0页，每页显示10条数据
- 打印搜索结果总记录数、对应分页的记录
参考代码：
@Test public void searchByPageTest() throws IOException { Map<String, Object> resultMap = jobFullTextService.searchByPage("销售", 0, 10); System.out.println("总共:" + resultMap.get("total")); List<JobDetail> jobDetailList = (List<JobDetail>)resultMap.get("content"); for (JobDetail jobDetail : jobDetailList) { System.out.println(jobDetail); } }
8 scroll分页检索
8.1 实现步骤
判断scrollId是否为空
a) 如果为空，那么首次查询要发起scroll查询，设置滚动快照的有效时间
b) 如果不为空，就表示之前应发起了scroll，直接执行scroll查询就可以
步骤和之前的关键字搜索类似，只不过构建查询条件的时候，需要加上分页的设置。
scrollId为空：
- 构建SearchRequest检索请求
- 创建一个SearchSourceBuilder专门用于构建查询条件
- 使用QueryBuilders.multiMatchQuery构建一个查询条件，并配置到SearchSourceBuilder
- 调用SearchRequest.source将查询条件设置到检索请求
- 设置每页多少条记录，调用SearchRequest.scroll设置滚动快照有效时间
- 执行RestHighLevelClient.search发起请求
- 遍历结果
- 获取命中的结果
8.将JSON字符串转换为对象
9.使用SearchHit.getId设置文档ID
8.将结果封装到Map结构中（带有分页信息）
a) scroll_id -> 从SearchResponse中调用getScrollId()方法获取scrollId
b) content -> 当前分页中的数据
scollId不为空：
9.用之前查询出来的scrollId，构建SearchScrollRequest请求
10.设置scroll查询结果的有效时间
11.使用RestHighLevelClient执行scroll请求
@Override public Map<String, Object> searchByScrollPage(String keywords, String scrollId, int pageSize) { Map<String, Object> result = new HashMap<>(); List<JobDetail> jobList = new ArrayList<>(); try { SearchResponse searchResponse = null; if(scrollId == null) { // 1. 创建搜索请求 SearchRequest searchRequest = new SearchRequest("job_idx"); // 2. 构建查询条件 SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); searchSourceBuilder.query(QueryBuilders.multiMatchQuery(keywords, "title", "jd")); // 3. 设置分页大小 searchSourceBuilder.size(pageSize); // 4. 设置查询条件、并设置滚动快照有效时间 searchRequest.source(searchSourceBuilder); searchRequest.scroll(TimeValue.timeValueMinutes(1)); // 5. 发起请求 searchResponse = client.search(searchRequest, RequestOptions.DEFAULT); } else { SearchScrollRequest searchScrollRequest = new SearchScrollRequest(scrollId); searchScrollRequest.scroll(TimeValue.timeValueMinutes(1)); searchResponse = client.scroll(searchScrollRequest, RequestOptions.DEFAULT); } // 6. 迭代响应结果 SearchHits hits = searchResponse.getHits(); for (SearchHit hit : hits) { JobDetail jobDetail = JSONObject.parseObject(hit.getSourceAsString(), JobDetail.class); jobDetail.setId(Long.parseLong(hit.getId())); jobList.add(jobDetail); } result.put("content", jobList); result.put("scroll_id", searchResponse.getScrollId()); } catch (IOException e) { e.printStackTrace(); } return result; }
8.2 编写测试用例
- 编写第一个测试用例，不带scrollId查询
- 编写第二个测试用例，使用scrollId查询
@Test public void searchByScrollPageTest1() throws IOException { Map<String, Object> result = jobFullTextService.searchByScrollPage("销售", null, 10); System.out.println("scrollId: " + result.get("scrollId")); List<JobDetail> content = (List<JobDetail>)result.get("content"); for (JobDetail jobDetail : content) { System.out.println(jobDetail); } } @Test public void searchByScrollPageTest2() throws IOException { Map<String, Object> result = jobFullTextService.searchByScrollPage("销售", "DXF1ZXJ5QW5kRmV0Y2gBAAAAAAAAAA0WRG4zZFVwODJSU2Uxd1BOWkQ4cFdCQQ==", 10); System.out.println("scrollId: " + result.get("scrollId")); List<JobDetail> content = (List<JobDetail>)result.get("content"); for (JobDetail jobDetail : content) { System.out.println(jobDetail); } }
9 高亮查询
9.1 高亮查询简介
在进行关键字搜索时，搜索出的内容中的关键字会显示不同的颜色，称之为高亮。百度搜索关键字"csdn"
京东商城搜索"笔记本"
9.2 高亮显示的html分析
通过开发者工具查看高亮数据的html代码实现：
ElasticSearch可以对查询出的内容中关键字部分进行标签和样式的设置，但是你需要告诉ElasticSearch使用什么标签对高亮关键字进行包裹
9.3 实现高亮查询
1.在我们构建查询请求时，我们需要构建一个HighLightBuilder，专门来配置高亮查询。
a) 构建一个HighlightBuilder
b) 设置高亮字段（title、jd）
c) 设置高亮前缀（）
d) 设置高亮后缀（）
e) 将高亮添加到SearchSourceBuilder
代码如下：
// 设置高亮 HighlightBuilder highlightBuilder = new HighlightBuilder(); highlightBuilder.field("title"); highlightBuilder.field("jd"); highlightBuilder.preTags("<font color='red'>"); highlightBuilder.postTags("</font>"); searchSourceBuilder.highlighter(highlightBuilder);
2.我们将高亮的查询结果取出，并替换掉原先没有高亮的结果
a) 获取高亮字段
i. 获取title高亮字段
ii. 获取jd高亮字段
b) 将高亮字段进行替换普通字段
i. 处理title高亮，判断高亮是否为空，不为空则将高亮碎片拼接在一起
ii. 替换原有普通字段
参考代码：
// 1. 获取高亮字段 Map<String, HighlightField> highlightFieldMap = hit.getHighlightFields(); // 1.1 获取title高亮字段 HighlightField titleHl = highlightFieldMap.get("title"); // 1.2 获取jd高亮字段 HighlightField jdHl = highlightFieldMap.get("jd"); // 2. 将高亮字段进行替换普通字段 // 2.1 处理title高亮，判断高亮是否为空，不为空则将高亮Fragment（碎片）拼接在一起，替换原有普通字段 if(titleHl != null) { Text[] fragments = titleHl.getFragments(); StringBuilder stringBuilder = new StringBuilder(); for (Text fragment : fragments) { stringBuilder.append(fragment.string()); } jobDetail.setTitle(stringBuilder.toString()); } // 2.2 处理jd高亮 if(jdHl != null) { Text[] fragments = jdHl.getFragments(); StringBuilder stringBuilder = new StringBuilder(); for (Text fragment : fragments) { stringBuilder.append(fragment.string()); } jobDetail.setJd(stringBuilder.toString()); }
我们再查询，发现查询的结果中就都包含了高亮。
10 完整参考代码
public class JobFullTextServiceImpl implements JobFullTextService { private RestHighLevelClient restHighLevelClient; private static final String JOB_IDX_NAME = "job_idx"; public JobFullTextServiceImpl() { restHighLevelClient = new RestHighLevelClient(RestClient.builder( new HttpHost("node1.itcast.cn", 9200, "http") , new HttpHost("node2.itcast.cn", 9200, "http") , new HttpHost("node3.itcast.cn", 9200, "http") )); } @Override public void add(JobDetail jobDetail) { // 1. 构建IndexRequest对象，用来描述ES发起请求的数据。 IndexRequest indexRequest = new IndexRequest(JOB_IDX_NAME); // 2. 设置文档ID。 indexRequest.id(jobDetail.getId() + ""); // 3. 构建一个实体类对象，并使用FastJSON将实体类对象转换为JSON。 String json = JSON.toJSONString(jobDetail); // 4. 使用IndexRequest.source方法设置请求数据。 indexRequest.source(json, XContentType.JSON); try { // 5. 使用ES High level client调用index方法发起请求 restHighLevelClient.index(indexRequest, RequestOptions.DEFAULT); } catch (IOException e) { e.printStackTrace(); } System.out.println("索引创建成功!"); } @Override public void update(JobDetail jobDetail) throws IOException { // 1. 判断对应ID的文档是否存在 // a) 构建GetRequest GetRequest getRequest = new GetRequest(JOB_IDX_NAME, jobDetail.getId() + ""); // b) 执行client的exists方法，发起请求，判断是否存在 boolean exists = restHighLevelClient.exists(getRequest, RequestOptions.DEFAULT); if(!exists) return; // 2. 构建UpdateRequest请求 UpdateRequest updateRequest = new UpdateRequest(JOB_IDX_NAME, jobDetail.getId() + ""); // 3. 设置UpdateRequest的文档，并配置为JSON格式 updateRequest.doc(JSON.toJSONString(jobDetail), XContentType.JSON); // 4. 执行client发起update请求 restHighLevelClient.update(updateRequest, RequestOptions.DEFAULT); } @Override public JobDetail findById(long id) throws IOException { // 1. 构建GetRequest请求。 GetRequest getRequest = new GetRequest(JOB_IDX_NAME, id + ""); // 2. 使用RestHighLevelClient.get发送GetRequest请求，并获取到ES服务器的响应。 GetResponse response = restHighLevelClient.get(getRequest, RequestOptions.DEFAULT); // 3. 将ES响应的数据转换为JSON字符串 String json = response.getSourceAsString(); // 4. 并使用FastJSON将JSON字符串转换为JobDetail类对象 JobDetail jobDetail = JSONObject.parseObject(json, JobDetail.class); // 5. 设置ID字段 jobDetail.setId(id); return jobDetail; } @Override public void deleteById(long id) throws IOException { // 1. 构建delete请求 DeleteRequest deleteRequest = new DeleteRequest(JOB_IDX_NAME, id + ""); // 2. 使用client执行delete请求 restHighLevelClient.delete(deleteRequest, RequestOptions.DEFAULT); } @Override public List<JobDetail> searchByKeywords(String keywords) throws IOException { // 1. 构建SearchRequest检索请求 SearchRequest searchRequest = new SearchRequest(JOB_IDX_NAME); // 2. 创建一个SearchSourceBuilder专门用于构建查询条件 SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); // 3. 使用QueryBuilders.multiMatchQuery构建一个查询条件，并配置到SearchSourceBuilder MultiMatchQueryBuilder queryBuilder = QueryBuilders.multiMatchQuery(keywords, "jd", "title"); searchSourceBuilder.query(queryBuilder); // 4. 调用SearchRequest.source将查询条件设置到检索请求 searchRequest.source(searchSourceBuilder); // 5. 执行RestHighLevelClient.search发起请求 SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT); // 6. 遍历结果 SearchHits hits = searchResponse.getHits(); List<JobDetail> jobDetailList = new ArrayList<>(); for (SearchHit hit : hits) { // 1) 获取命中的结果 String json = hit.getSourceAsString(); // 2) 将JSON字符串转换为对象 JobDetail jobDetail = JSON.parseObject(json, JobDetail.class); // 3) 使用SearchHit.getId设置文档ID jobDetail.setId(Long.parseLong(hit.getId())); jobDetailList.add(jobDetail); } return jobDetailList; } @Override public Map<String, Object> searchByPage(String keywords, int pageNum, int pageSize) throws IOException { // 1. 构建SearchRequest检索请求 SearchRequest searchRequest = new SearchRequest(JOB_IDX_NAME); // 2. 创建一个SearchSourceBuilder专门用于构建查询条件 SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); // 3. 使用QueryBuilders.multiMatchQuery构建一个查询条件，并配置到SearchSourceBuilder MultiMatchQueryBuilder queryBuilder = QueryBuilders.multiMatchQuery(keywords, "jd", "title"); searchSourceBuilder.query(queryBuilder); // 4. 设置SearchSourceBuilder的from和size参数，构建分页 searchSourceBuilder.from(pageNum); searchSourceBuilder.size(pageSize); // 4. 调用SearchRequest.source将查询条件设置到检索请求 searchRequest.source(searchSourceBuilder); // 5. 执行RestHighLevelClient.search发起请求 SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT); // 6. 遍历结果 SearchHits hits = searchResponse.getHits(); List<JobDetail> jobDetailList = new ArrayList<>(); for (SearchHit hit : hits) { // 1) 获取命中的结果 String json = hit.getSourceAsString(); // 2) 将JSON字符串转换为对象 JobDetail jobDetail = JSON.parseObject(json, JobDetail.class); // 3) 使用SearchHit.getId设置文档ID jobDetail.setId(Long.parseLong(hit.getId())); jobDetailList.add(jobDetail); } // 8. 将结果封装到Map结构中（带有分页信息） // a) total -> 使用SearchHits.getTotalHits().value获取到所有的记录数 // b) content -> 当前分页中的数据 Map<String, Object> result = new HashMap<>(); result.put("total", hits.getTotalHits().value); result.put("content", jobDetailList); return result; } @Override public Map<String, Object> searchByScrollPage(String keywords, String scrollId, int pageSize) throws IOException { SearchResponse searchResponse = null; if(scrollId == null) { // 1. 构建SearchRequest检索请求 SearchRequest searchRequest = new SearchRequest(JOB_IDX_NAME); // 2. 创建一个SearchSourceBuilder专门用于构建查询条件 SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); // 3. 使用QueryBuilders.multiMatchQuery构建一个查询条件，并配置到SearchSourceBuilder MultiMatchQueryBuilder queryBuilder = QueryBuilders.multiMatchQuery(keywords, "jd", "title"); searchSourceBuilder.query(queryBuilder); searchSourceBuilder.size(pageSize); // 设置高亮查询 HighlightBuilder highlightBuilder = new HighlightBuilder(); highlightBuilder.preTags("<font color='red'>"); highlightBuilder.postTags("</font>"); highlightBuilder.field("title"); highlightBuilder.field("jd"); searchSourceBuilder.highlighter(highlightBuilder); // 4. 调用searchRequest.scroll设置滚动快照有效时间 searchRequest.scroll(TimeValue.timeValueMinutes(10)); // 5. 调用SearchRequest.source将查询条件设置到检索请求 searchRequest.source(searchSourceBuilder); // 6. 执行RestHighLevelClient.search发起请求 searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT); } else { SearchScrollRequest searchScrollRequest = new SearchScrollRequest(scrollId); searchScrollRequest.scroll(TimeValue.timeValueMinutes(10)); searchResponse = restHighLevelClient.scroll(searchScrollRequest, RequestOptions.DEFAULT); } if(searchResponse != null) { // 7. 遍历结果 SearchHits hits = searchResponse.getHits(); List<JobDetail> jobDetailList = new ArrayList<>(); for (SearchHit hit : hits) { // 1) 获取命中的结果 String json = hit.getSourceAsString(); // 2) 将JSON字符串转换为对象 JobDetail jobDetail = JSON.parseObject(json, JobDetail.class); // 3) 使用SearchHit.getId设置文档ID jobDetail.setId(Long.parseLong(hit.getId())); // 1. 获取高亮字段 Map<String, HighlightField> highlightFieldMap = hit.getHighlightFields(); // 1.1 获取title高亮字段 HighlightField titleHl = highlightFieldMap.get("title"); // 1.2 获取jd高亮字段 HighlightField jdHl = highlightFieldMap.get("jd"); // 2. 将高亮字段进行替换普通字段 // 2.1 处理title高亮，判断高亮是否为空，不为空则将高亮Fragment（碎片）拼接在一起，替换原有普通字段 if(titleHl != null) { Text[] fragments = titleHl.getFragments(); StringBuilder stringBuilder = new StringBuilder(); for (Text fragment : fragments) { stringBuilder.append(fragment.string()); } jobDetail.setTitle(stringBuilder.toString()); } // 2.2 处理jd高亮 if(jdHl != null) { Text[] fragments = jdHl.getFragments(); StringBuilder stringBuilder = new StringBuilder(); for (Text fragment : fragments) { stringBuilder.append(fragment.string()); } jobDetail.setJd(stringBuilder.toString()); } jobDetailList.add(jobDetail); } // 8. 将结果封装到Map结构中（带有分页信息） // a) total -> 使用SearchHits.getTotalHits().value获取到所有的记录数 // b) content -> 当前分页中的数据 Map<String, Object> result = new HashMap<>(); result.put("scrollId", searchResponse.getScrollId()); result.put("content", jobDetailList); return result; } return null; } @Override public void close() { try { restHighLevelClient.close(); } catch (IOException e) { e.printStackTrace(); } } }
