springdata -----操作ES

一：配置springdata-Es

elasticseach-JPA.xml

<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
       xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
       xmlns:context="http://www.springframework.org/schema/context"
       xmlns:mvc="http://www.springframework.org/schema/mvc"
       xmlns:jpa="http://www.springframework.org/schema/data/jpa"
       xmlns:elasticsearch="http://www.springframework.org/schema/data/elasticsearch"
       xsi:schemaLocation="
         http://www.springframework.org/schema/beans
         http://www.springframework.org/schema/beans/spring-beans-4.3.xsd
         http://www.springframework.org/schema/context
         http://www.springframework.org/schema/context/spring-context-4.3.xsd
         http://www.springframework.org/schema/mvc
         http://www.springframework.org/schema/mvc/spring-mvc-4.3.xsd
         http://www.springframework.org/schema/data/jpa
         http://www.springframework.org/schema/data/jpa/spring-jpa-1.8.xsd
         http://www.springframework.org/schema/data/elasticsearch
         http://www.springframework.org/schema/data/elasticsearch/spring-elasticsearch-1.0.xsd
       ">
   <context:component-scan base-package="com.sf.heros.mq.consumer"/>   扫描包
    <elasticsearch:transport-client id="client" cluster-name="elasticsearch"
                                    cluster-nodes="127.0.0.1:9300" client-transport-sniff="false"/>  配置链接端口（默认的是9200，但是我们需要与之交互，要用到配置文件里所写那个端口，我的是9300）
    <elasticsearch:repositories base-package="com.sf.heros.mq.consumer.dao"  springdata操作ES的 接口类
                                elasticsearch-template-ref="elasticsearchTemplate"/>
    <bean name="elasticsearchTemplate"
          class="org.springframework.data.elasticsearch.core.ElasticsearchTemplate">
        <constructor-arg name="client" ref="client" />  ES操作类
    </bean>

</beans>

2：接口类

UserDao。java（增删改查方法 与其它springdata一致，findBy等等语法参考springdata）

public interface UserDao extends ElasticsearchRepository<User,Integer> {
    List<User> findByArticleInfId(Integer aid);
}

3：实体类

@Document(indexName = "article_inf_index", type = "articleInf")
@Setting(settingPath = "elasticsearch-analyser.json")
public class User implements Serializable {
    //elasticsearch
    @org.springframework.data.annotation.Id
    private Integer articleInfId;

    @Field(type = FieldType.String)//使用ngram进行单字分词
    private String articleTitle;

    @Field(type = FieldType.Date, store = true, format = DateFormat.custom, pattern ="yyyy-MM-dd HH:mm:ss")
    @JsonFormat(shape = JsonFormat.Shape.STRING, pattern ="yyyy-MM-dd HH:mm:ss")
    private Date releaseTime;

    public Integer getArticleInfId() {
        return articleInfId;
    }

    public void setArticleInfId(Integer articleInfId) {
        this.articleInfId = articleInfId;
    }

    public String getArticleTitle() {
        return articleTitle;
    }

    public void setArticleTitle(String articleTitle) {
        this.articleTitle = articleTitle;
    }

    public Date getReleaseTime() {
        return releaseTime;
    }

    public void setReleaseTime(Date releaseTime) {
        this.releaseTime = releaseTime;
    }

    @Override
    public String toString() {
        return "User{" +
                "articleInfId=" + articleInfId +
                ", articleTitle='" + articleTitle + '\'' +
                ", releaseTime=" + releaseTime +
                '}';
    }
}

4:serverce

@Service("testService")
public class ElasticsearchService {
    @Autowired
    private UserDao userDao;
    public void add(User user){
        userDao.save(user);
    }

    public List<User> search(Integer aid){
        Pageable pageable=new Pageable() {
            @Override
            public int getNumberOfPages() {
                return 0;
            }

            @Override
            public PageFormat getPageFormat(int pageIndex) throws IndexOutOfBoundsException {
                return null;
            }

            @Override
            public Printable getPrintable(int pageIndex) throws IndexOutOfBoundsException {
                return null;
            }
        };
        return this.userDao.findByArticleInfId(aid);
    }

public User searchByQuery(User user){
        BoolQueryBuilder qb= QueryBuilders. boolQuery();
        qb.must(QueryBuilders.matchQuery("articleInfId",12));
        Iterable<User> search = userDao.search(qb);
        return search.iterator().next();
    }
}

BoolQueryBuilder方法：

1.matchAllQuery() matchAllQuery()方法用来匹配全部文档
2.matchQuery("filedname","value")匹配单个字段，匹配字段名为filedname,值为value的文档
3.multiMatchQuery(Object text, String... fieldNames)多个字段匹配某一个值

QueryBuilder queryBuilder = QueryBuilders.multiMatchQuery("music",  "name", "interest");//搜索name中或interest中包含有music的文档（必须与music一致）

4.wildcardQuery()模糊查询   ?匹配单个字符，*匹配多个字符

5.使用BoolQueryBuilder进行复合查询

使用must：

1. //模糊查询
2. WildcardQueryBuilder queryBuilder1 = QueryBuilders.wildcardQuery(
3. "name", "*jack*");//搜索名字中含有jack的文档
4. WildcardQueryBuilder queryBuilder2 = QueryBuilders.wildcardQuery(
5. "interest", "*read*");//搜索interest中含有read的文档
6. BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
7. //name中必须含有jack,interest中必须含有read,相当于and
8. boolQueryBuilder.must(queryBuilder1);
9. boolQueryBuilder.must(queryBuilder2);

使用 should：

1. WildcardQueryBuilder queryBuilder1 = QueryBuilders.wildcardQuery(
2. "name", "*jack*");//搜索名字中含有jack的文档
3. WildcardQueryBuilder queryBuilder2 = QueryBuilders.wildcardQuery(
4. "interest", "*read*");//搜索interest中含有read的文档
5. BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
6. //name中含有jack或者interest含有read，相当于or
7. boolQueryBuilder.should(queryBuilder1);
8. boolQueryBuilder.should(queryBuilder2);