注意:适用于springboot或者springcloud框架 1.首先下载相关文件 2.然后需要去启动相关的启动文件 3、导入相关jar包(如果有相关的依赖包不需要导入)以及配置配置文件,并且写一个dao接
注意:适用于springboot或者springcloud框架
1.首先下载相关文件
2.然后需要去启动相关的启动文件
3、导入相关jar包(如果有相关的依赖包不需要导入)以及配置配置文件,并且写一个dao接口继承一个类,在启动类上标注地址
<dependency> <groupId>org.projectlombok</groupId> <artifactId>lombok</artifactId> </dependency> <dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-web</artifactId> </dependency> <dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-data-elasticsearch</artifactId> </dependency>
## ElasticSearch - start #开启 Elasticsearch 仓库(默认值:true) spring.data.elasticsearch.repositories.enabled=true spring.data.elasticsearch.cluster-nodes=localhost:9300 spring.data.elasticsearch.cluster-name=myes
Shop:是下面创建的实体类名称(不能写错),String(传参时的类型,我这里id也给的String,因为integer报错)
import com.jk.user.model.Shop; import org.springframework.data.elasticsearch.repository.ElasticsearchRepository; public interface EsDao extends ElasticsearchRepository<Shop,String> { }
启动类上加上注解,后面跟的是dao的包名
@EnableElasticsearchRepositories(basePackages = "com.jk.web.dao")
4.实体类
indexName相当于数据库名, type 相当于表名 ,必须加上id,type 类型,analyzer 分词器名称(ik分词)
@Document(indexName = "zth",type = "t_shangpin") public class Shop implements Serializable { private static final long serialVersionUID = 2006762641515872124L; private String id; @Field(type = FieldType.Text, analyzer = "ik_max_word") //商品名称 private String shopname; //优惠价格 private Long reducedprice; }
5.然后写controller层(这里直接注入dao接口),这里新增我选的是对象循环赋值,其实可以直接赋集合(参考)
//elasticsearch 生成表 // @RequestMapping("el") // @ResponseBody // public void el(){ // List<ElasticsearchBean> list=shoppService.queryelasticsearch(); // for (ElasticsearchBean ss: list) { // ss.setScrenicName(ss.getScrenicName()+""+ss.getHotelName()); // } // elasticsearch.saveAll(list); // }
@Autowired private EsDao esDao; // 查询时需要 @Autowired private ElasticsearchTemplate elasticsearchTemplate ; //更新es服务器数据 @RequestMapping("addEs") public boolean addShopEs() { List<TShangpin> list = webUserService.queryShouye();//先去后台查出数据在赋值 Shop shop = new Shop(); try { for (int i = 0; i < list.size(); i++) { shop.setId(list.get(i).getShopid().toString()); shop.setShopname(list.get(i).getShopname()); esDao.save(shop); } return true; } catch (Exception e) { e.printStackTrace(); return false; } } //es搜索商品 @RequestMapping("queryShop") public List ellist(String name, HttpSession session, Integer page, Integer rows){ if (name==null||"".equals(name)){ name = session.getAttribute("name").toString(); } page=1; rows=3; HashMap<String, Object> resultMap = new HashMap<>(); //创建一个要搜索的索引库 SearchRequestBuilder searchRequestBuilder = elasticsearchTemplate.getClient().prepareSearch("zth").setTypes("t_shangpin"); //创建组合查询 BoolQueryBuilder boolQueryBuilder = new BoolQueryBuilder(); if (name!=null && !"".equals(name)){ boolQueryBuilder.should(QueryBuilders.matchQuery("shopname",name)); } //设置查询的类型 searchRequestBuilder.setSearchType(SearchType.DFS_QUERY_THEN_FETCH); searchRequestBuilder.setQuery(boolQueryBuilder); //分页 searchRequestBuilder.setFrom((page-1)*rows); searchRequestBuilder.setSize(rows); //设置高亮字段 HighlightBuilder highlightBuilder = new HighlightBuilder(); highlightBuilder.field("shopname") .preTags("<font color='red'>") .postTags("</font>"); searchRequestBuilder.highlighter(highlightBuilder); //直接搜索返回响应数据 (json) SearchResponse searchResponse = searchRequestBuilder.get(); SearchHits hits = searchResponse.getHits(); //获取总条数 long totalHits = hits.getTotalHits(); resultMap.put("total",totalHits); ArrayList<Map<String,Object>> list = new ArrayList<>(); //获取Hits中json对象数据 SearchHit[] hits1 = hits.getHits(); for (int i=0;i<hits1.length;i++){ //获取Map对象 Map<String, Object> sourceAsMap = hits1[i].getSourceAsMap(); //获取高亮字段 Map<String, HighlightField> highlightFields = hits1[i].getHighlightFields(); //!!如果有高亮字段就取出赋给上面sourceAsMap中原有的名字给他替换掉!! if (name!=null && !"".equals(name)){ sourceAsMap.put("shopname",highlightFields.get("shopname").getFragments()[0].toString()); } list.add(sourceAsMap); } return list; }
6.最后 如果无法搜索,可能是需要加一个ik的json文件,因为在实体类中规定了是ik分词器,如果不规定当它存进去后其实是还没有分词。
film-mapping.json
{ "film": { "_all": { "enabled": true }, "properties": { "id": { "type": "integer" },"name": { "type": "text", "analyzer": "ikSearchAnalyzer", "search_analyzer": "ikSearchAnalyzer", "fields": { "pinyin": { "type": "text", "analyzer": "pinyinSimpleIndexAnalyzer", "search_analyzer": "pinyinSimpleIndexAnalyzer" } } }, "nameOri": { "type": "text" },"publishDate": { "type": "text" },"type": { "type": "text" },"language": { "type": "text" },"fileDuration": { "type": "text" },"director": { "type": "text", "index": "true", "analyzer": "ikSearchAnalyzer" },"created": { "type": "date", "format": "yyyy-MM-dd HH:mm:ss||yyyy-MM-dd||epoch_millis" } } } }
film-setting.json
{ "index": { "analysis": { "filter": { "edge_ngram_filter": { "type": "edge_ngram", "min_gram": 1, "max_gram": 50 },"pinyin_simple_filter": { "type": "pinyin", "first_letter": "prefix", "padding_char": " ", "limit_first_letter_length": 50, "lowercase": true } },"char_filter": { "tsconvert": { "type": "stconvert", "convert_type": "t2s" } },"analyzer": { "ikSearchAnalyzer": { "type": "custom", "tokenizer": "ik_max_word", "char_filter": [ "tsconvert" ] },"pinyinSimpleIndexAnalyzer": { "tokenizer": "keyword", "filter": [ "pinyin_simple_filter", "edge_ngram_filter", "lowercase" ] } } } } }
总结
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