es(elasticsearch)整合SpringCloud（SpringBoot）搭建教程详解
作者：麦麦麦麦兜
这篇文章主要介绍了es(elasticsearch)整合SpringCloud（SpringBoot）搭建教程，本文通过实例图文相结合给大家介绍的非常详细，对大家的学习或工作具有一定的参考借鉴价值,需要的朋友可以参考下
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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