记一次springboot2.3.*项目整合elasticsearch7.6.2实现中文拼音分词搜索
作者：互联网
一、elasticsearch官网下载：Elasticsearch 7.6.2 | Elastic
二、拼音、ik、繁简体转换插件安装
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: elasticsearch
cluster-nodes: 127.0.0.1:9300
repositories:
enabled: truedocument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、mapping
1.创建索引并设置setting
postman put http://localhost:9200/chin_new_index json:xxxx_setting.json
2.给索引设置mapping 7.x以后逇版本默认都是type为_doc 还需要上 include_type_name=true ， 但是该属性会在8.x废弃 json： xxxx_mapping.json
postman put http://localhost:9200/chin_test_index/_mapping/_doc?include_type_name=true
3.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 , 使用查询方法即可进行查询了
*
*/
@Id
private 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
@Autowired
private YourServices yourService;
@Autowired
private EsTestRepository searchService;
@Autowired
private 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);
}
}
标签：title,elasticsearch7.6,pinyin,springboot2.3,content,item,elasticsearch,new,分词 来源： https://blog.csdn.net/limChin/article/details/120095701