记一次springboot2.3.*项目整合elasticsearch7.6.2实现中文拼音分词搜索

一、elasticsearch官网下载：Elasticsearch 7.6.2 | Elastic

二、拼音、ik、繁简体转换插件安装

ik分词：GitHub - medcl/elasticsearch-analysis-ik: The IK Analysis plugin integrates Lucene IK analyzer into elasticsearch, support customized dictionary.

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

繁简体转换：GitHub - medcl/elasticsearch-analysis-stconvert: STConvert is analyzer that convert chinese characters between traditional and simplified.中文简繁體互相转换.

安装过程：从github上下载源码到本地，idea打开项目，修改对应项目中的pom.xml将

<elasticsearch.version>7.6.2</elasticsearch.version>修改为对应的elasticsearch版本

，alt+f12打开cmd命令界面，输入mvn install，项目编译成功后会在对应目录中生成对应zip包，效果如图：

将对应zip包解压到elasticsearch存放目录的plugins下：

然后启动elasticsearch.bat，

这样对应插件就算安装成功了

三、springboot项目集成elasticsearch，pom.xml修改如下

<properties><elasticsearch.version>7.6.2</elasticsearch.version><remote-passwd>123456</remote-passwd></properties> <dependencies><dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-data-elasticsearch</artifactId></dependency>
</dependencies>

spring-boot.yml新增elasticsearch配置：

spring:data:elasticsearch:cluster-name: elasticsearchcluster-nodes: 127.0.0.1:9300repositories:enabled: true

document查询对象：

 import lombok.*;
import org.springframework.data.annotation.Id;
import org.springframework.data.elasticsearch.annotations.*;import java.io.Serializable;@Data
@Builder
@Setting(settingPath = "/json/esTest_setting.json")
@Mapping(mappingPath = "/json/esTest_mapping.json")
@Document(indexName = "chin_new_index")public class EsTest implements Serializable {/***使用步骤：一、首先使用下面的命令在elasticsearch中创建对应的索引、setting、mapping1.创建索引并设置settingpostman put   http://localhost:9200/chin_new_index  json:xxxx_setting.json2.给索引设置mapping 7.x以后逇版本默认都是type为_doc 还需要加上 include_type_name=true ， 但是该属性会在8.x废弃  postman   put  http://localhost:9200/chin_test_index/_mapping/_doc?include_type_name=true   json： xxxx_mapping.json3.如何查看对象的分词情况：postman  post   http://localhost:9200/chin_new_index/_doc/{你想查询对象的id}/_termvectors?fields={你的字段名字}二、启动项目 初始化elsaticsearch 将数据库中的数据放入es中, 使用查询方法即可进行查询了**/@Idprivate String id ;private String title;private String content;public EsTest () {}public EsTest (String id, String title, String content) {this.id = id;this.title = title;this.content = content;}}

在src/main/sources目录下新建json文件夹存放setting、mapping

setting.json

{"settings": {"index": {"analysis": {"filter": {"edge_ngram_filter": {"type": "edge_ngram","min_gram": 1,"max_gram": 50},"pinyin_simple_filter": {"type": "pinyin","keep_separate_first_letter": true,"keep_full_pinyin": true,"keep_original": true,"limit_first_letter_length": 16,"lowercase": true,"remove_duplicated_term": true}},"char_filter": {"tsconvert": {"type": "stconvert","convert_type": "t2s"}},"analyzer": {" ikSearchAnalyzer": {"type": "custom","tokenizer": "ik_max_word","char_filter": ["tsconvert"]},"pinyinSimpleIndexAnalyzer": {"type": "custom","tokenizer": "ik_max_word","filter": ["pinyin_simple_filter","edge_ngram_filter","lowercase"]}}}}}
}

mapping.json

{"properties": {"id": {"type": "text"},"content": {"type": "text","analyzer": "ik_max_word","search_analyzer": "ik_max_word","fields": {"pinyin": {"type": "text","analyzer": "pinyinSimpleIndexAnalyzer","search_analyzer": "pinyinSimpleIndexAnalyzer"}}},"title": {"type": "text","analyzer": "ik_max_word","search_analyzer": "ik_max_word","fields": {"pinyin": {"type": "text","analyzer": "pinyinSimpleIndexAnalyzer","search_analyzer": "pinyinSimpleIndexAnalyzer"}}}}
}

curd接口

@Repository
public interface EsTestRepository extends ElasticsearchRepository<EsTest, String> {}

controller:


@RestController
@RequestMapping("testEs")
@Api(tags = "elasticsearch测试")
public class EsMaintenanceController {//这里用你自己的连接数据库的services用来取数据@Autowiredprivate YourServices yourService;@Autowiredprivate EsTestRepository searchService;@Autowiredprivate ElasticsearchRestTemplate searchTemp;/*** @return   */@GetMapping("initEs")@ApiOperation(value = "初始化es", notes = "")public void save() {searchService.deleteAll();searchTemp.putMapping(EsMaintenance.class);List<SqlEntity> dataList =  yourService.selectAll();;List<EsTest> esList = new ArrayList<>();dataList.forEach(item ->{esList.add(new EsMaintenance(item.getId() , item.getName(), item.getContent()));});searchService.saveAll(esList);}@GetMapping("searchByKey")@ApiOperation(value = "根据关键字搜索", notes = "")public R searchByKey(@RequestParam String key ){/*** 不指定具体字段，在所有field中进行查询*///QueryStringQueryBuilder query = QueryBuilders.queryStringQuery(key);/*** 这里使用了多字段匹配方法，multiMatchQuery （String key , String... fieldName）* withPageable 采用 分页查询，  elasticsearch分页是从第0页开始的*//* MultiMatchQueryBuilder queryBuilder2 = QueryBuilders.multiMatchQuery(key, "title", "content", "title.pinyin" , "content.pinyin");NativeSearchQuery query = new NativeSearchQueryBuilder().withQuery(    queryBuilder2   ).withPageable(PageRequest.of(0, 10)).build();*/DisMaxQueryBuilder disMaxQuery = QueryBuilders.disMaxQuery();MatchQueryBuilder title = QueryBuilders.matchQuery("title", key);MatchQueryBuilder content = QueryBuilders.matchQuery("content", key);MatchQueryBuilder pinyContent = QueryBuilders.matchQuery("content.pinyin", key);MatchQueryBuilder pinyTitle = QueryBuilders.matchQuery("title.pinyin", key);disMaxQuery.add(title);disMaxQuery.add(content);disMaxQuery.add(pinyContent);disMaxQuery.add(pinyTitle);NativeSearchQueryBuilder nativBuilder = new NativeSearchQueryBuilder().withQuery(disMaxQuery);NativeSearchQuery query = nativBuilder.build();//单个字段模糊匹配查询/*NativeSearchQuery query = new NativeSearchQueryBuilder().withQuery(QueryBuilders.matchQuery("title", key)).withQuery(QueryBuilders.matchQuery("content", key)).build();*/Iterable<EsMaintenance> search = searchService.search(query).getContent();JSON.toJSON(search));return R.ok().put("data", search);}@GetMapping("searchHighValue")@ApiOperation(value = "根据关键字搜索高亮显示", notes = "")public R searchHighValue(@RequestParam String key){//设置查询条件BoolQueryBuilder queryBuilder = QueryBuilders.boolQuery().should(QueryBuilders.matchQuery("title", key)).should(QueryBuilders.matchQuery("content", key)).should(QueryBuilders.matchQuery("title.pinyin", key)).should(QueryBuilders.matchQuery("content.pinyin", key));NativeSearchQuery query = new NativeSearchQueryBuilder().withQuery(queryBuilder)//设定高亮显示字段.withHighlightFields(new HighlightBuilder.Field("title"), new HighlightBuilder.Field("content"),new HighlightBuilder.Field("title.pinyin"), new HighlightBuilder.Field("content.pinyin")  )//设置高亮显示内容样式.withHighlightBuilder(new HighlightBuilder().preTags(" <p style='color:red'>").postTags("</p>")).build();SearchHits<EsMaintenance> search = searchTemp.search(query, EsMaintenance.class);List<SearchHit<EsMaintenance>> datas = search.getSearchHits();ArrayList<EsMaintenance> returnList = new ArrayList<>();//处理高亮显示数据for (SearchHit<EsMaintenance> item : datas) {Map<String, List<String>> fields = item.getHighlightFields();item.getContent().setTitle(fields.get("title") == null ? item.getContent().getTitle() : fields.get("title").get(0));item.getContent().setContent(fields.get("content") == null ? item.getContent().getContent() : fields.get("content").get(0));item.getContent().setTitle(fields.get("title.pinyin") == null ? item.getContent().getTitle() : fields.get("title.pinyin").get(0));item.getContent().setContent(fields.get("content.pinyin") == null ? item.getContent().getContent() : fields.get("content.pinyin").get(0));returnList.add(item.getContent());}return R.ok().put("data", returnList);}}

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