java使用elasticsearch进行模糊查询之must使用-项目中实际使用

java使用elasticsearch进行多个条件模糊查询

文章说明：

1、本篇文章，本人会从java连接elasticsearch到查询结果生成并映射到具体实体类（涵盖分页功能）

2、代码背景：elasticsearch版本为：5.2.0;

3、本人以下代码是分别从两个索引中查询数据，再将两个数据进行整合，如果大家只需要分组查询，那么则选取文章中的分组查询部分代码

4、本人的实体类主要是按照layUI分页框架进行设计；实体大家可以根据自己的具体需求进行设计

一、java连接elasticsearch工具类

public class ESClientConnectionUtil {
    public static TransportClient client=null;
    public final static String HOST = "192.168.200.200"; //服务器部署ip 根据自己ip进行更改
    public final static Integer PORT = 9301; //端口

    public static TransportClient  getESClient(){
        System.setProperty("es.set.netty.runtime.available.processors", "false");
        if (client == null) {
            synchronized (ESClientConnectionUtil.class) {
                try {
                    //设置集群名称
                    Settings settings = Settings.builder().put("cluster.name", "es5").put("client.transport.sniff", true).build();
                    //创建client
                    client = new PreBuiltTransportClient(settings).addTransportAddress(new InetSocketTransportAddress(InetAddress.getByName(HOST), PORT));
                } catch (Exception ex) {
                    ex.printStackTrace();

                    System.out.println(ex.getMessage());
                }
            }
        }
        return client;
    }
    public static TransportClient  getESClientConnection(){
        if (client == null) {
            System.setProperty("es.set.netty.runtime.available.processors", "false");
                try {
                    //设置集群名称
                    Settings settings = Settings.builder().put("cluster.name", "es5").put("client.transport.sniff", true).build();
                    //创建client
                    client = new PreBuiltTransportClient(settings).addTransportAddress(new InetSocketTransportAddress(InetAddress.getByName(HOST), PORT));
                } catch (Exception ex) {
                    ex.printStackTrace();
                    System.out.println(ex.getMessage());
            }
        }
        return client;
    }
    //判断索引是否存在
    public static boolean judgeIndex(String index){
        client= getESClientConnection();
         IndicesAdminClient adminClient;
        //查询索引是否存在
        adminClient= client.admin().indices();
        IndicesExistsRequest request = new IndicesExistsRequest(index);
        IndicesExistsResponse responses = adminClient.exists(request).actionGet();

        if (responses.isExists()) {
            return true;
        }
        return false;
    }
}

二、实体类

（一）分页实体总类

public class KnowledgeTopicListDTO {
   private Long totalCount;//总条数
   private Integer page;//页数
   private Integer limit;//每页查询条数
   private List<KnowledgeTopicDTO> topicDTOList;//每页显示数据的对象集合

    public Long getTotalCount() {
        return totalCount;
    }

    public void setTotalCount(Long totalCount) {
        this.totalCount = totalCount;
    }

    public Integer getPage() {
        return page;
    }

    public void setPage(Integer page) {
        this.page = page;
    }

    public Integer getLimit() {
        return limit;
    }

    public void setLimit(Integer limit) {
        this.limit = limit;
    }

    public List<KnowledgeTopicDTO> getTopicDTOList() {
        return topicDTOList;
    }

    public void setTopicDTOList(List<KnowledgeTopicDTO> topicDTOList) {
        this.topicDTOList = topicDTOList;
    }
}

（二）页面显示数据对象实体

public class KnowledgeTopicDTO {
    private Long id;//知识主题id
    private String name;//知识主题名称
    private Boolean active;//有效无效 true，false
    private String activeString;//有效无效
    private Boolean noSubscription;//是否需要订阅 true，false
    private String noSubscriptionString;//是否需要订阅
    private Long quantity;//数据量
    private String _id;
    private String ids;

    public String getIds() {
        return ids;
    }

    public void setIds(String ids) {
        this.ids = ids;
    }

    public Long getId() {
        return id;
    }

    public void setId(Long id) {
        this.id = id;
    }

    public String getName() {
        return name;
    }

    public void setName(String name) {
        this.name = name;
    }

    public Boolean getActive() {
        return active;
    }

    public void setActive(Boolean active) {
        this.active = active;
    }

    public String getActiveString() {
        return activeString;
    }

    public void setActiveString(String activeString) {
        this.activeString = activeString;
    }

    public Boolean getNoSubscription() {
        return noSubscription;
    }

    public void setNoSubscription(Boolean noSubscription) {
        this.noSubscription = noSubscription;
    }

    public String getNoSubscriptionString() {
        return noSubscriptionString;
    }

    public void setNoSubscriptionString(String noSubscriptionString) {
        this.noSubscriptionString = noSubscriptionString;
    }

    public Long getQuantity() {
        return quantity;
    }

    public void setQuantity(Long quantity) {
        this.quantity = quantity;
    }

    public String get_id() {
        return _id;
    }

    public void set_id(String _id) {
        this._id = _id;
    }
}

三、后台service层代码

 public KnowledgeTopicListDTO selectTopicByName(String name, Integer page, Integer limit) {
        SearchResponse searchResponse=null;
        Map<String,Object> map = new HashMap<>();
        TransportClient transportClient =  ESClientConnectionUtil.getESClientConnection();
            SearchRequestBuilder requestBuilder = client.prepareSearch("knowledge").setTypes("knowledge_theme");
            // 声明where条件
            BoolQueryBuilder qbs = QueryBuilders.boolQuery();
            /**此处使用模糊匹配查询 类比数据库中 like*/
            QueryBuilder qb1 = QueryBuilders.matchPhraseQuery("name", name);
            BoolQueryBuilder bqb1 = QueryBuilders.boolQuery().must(qb1);
            qbs.must(bqb1);
            requestBuilder.setQuery(qbs);
            int num=limit*(page-1);
            SearchResponse response = requestBuilder.setFrom(0).setSize(10).execute().actionGet();
            //获取总条数
//        long totalCount = searchResponse.getHits().getTotalHits();
            List<KnowledgeTopicDTO> list = new ArrayList<KnowledgeTopicDTO>();
            for (SearchHit hit : response.getHits().getHits()) {
                //获取到当前页的数据
                JSONObject obj = new JSONObject().fromObject(hit.getSourceAsString());//将json字符串转换为json对象
                KnowledgeTopicDTO topic = (KnowledgeTopicDTO) JSONObject.toBean(obj, KnowledgeTopicDTO.class);//将建json对象转换为Person对象
                list.add(topic);
            }
            //查询主题总数
        Terms terms= ESGroupByUtil.GroupByOne(client,"hottopic","hot","sum","tasktitleid");
        list= groupList(list,terms);//调用组合主题总数方法
        KnowledgeTopicListDTO knowledgeTopicListDTO = new KnowledgeTopicListDTO();
        knowledgeTopicListDTO.setLimit(limit);
        knowledgeTopicListDTO.setPage(page);
        knowledgeTopicListDTO.setTopicDTOList(list);
        return knowledgeTopicListDTO;
    }

五、根据单个字段分组查询

public class ESGroupByUtil {

    /**
     *@description: 根据单个字段分组求和
     *@author:cyb
     *@date: 2018-11-16 17:31
    *@param: client ES连接
    *@param: indices 索引
    *@param: types 类型
    *@param: alias 分组求和别名
    *@param: DomName 分组目标字段名
     *@return: org.elasticsearch.search.aggregations.bucket.terms.Terms
     */
    public static Terms GroupByOne(TransportClient client,String indices,String types,String alias,String DomName){
        SearchRequestBuilder sbuilder = client.prepareSearch(indices).setTypes(types);
        TermsAggregationBuilder termsBuilder = AggregationBuilders.terms(alias).field(DomName);
        sbuilder.addAggregation(termsBuilder);
        SearchResponse responses= sbuilder.execute().actionGet();
        Terms terms = responses.getAggregations().get(alias);
        return terms;
    }

}

六 、将分组查询的数据进行整合到已查询到的集合中

 /**
     *@description:将查询的总数合并到list中
     *@author:cyb
     *@date: 2018-11-16 17:51
    *@param: list
    *@param: terms
     *@return: java.util.List<com.yjlc.platform.bsKnowledge.KnowledgeTopicDTO>
     */
      public List<KnowledgeTopicDTO> groupList(List<KnowledgeTopicDTO> list,Terms terms){
        List<BsKnowledgeInfoDTO> lists = new ArrayList<>();
        for(int i=0;i<terms.getBuckets().size();i++){
            //statistics
            String id =terms.getBuckets().get(i).getKey().toString();//id
            Long sum =terms.getBuckets().get(i).getDocCount();//数量
            BsKnowledgeInfoDTO bsKnowledgeInfoDTO1 = new BsKnowledgeInfoDTO();
            bsKnowledgeInfoDTO1.setId(id);
            bsKnowledgeInfoDTO1.setSum(sum);
            lists.add(bsKnowledgeInfoDTO1);
            System.out.println("=="+ terms.getBuckets().get(i).getDocCount()+"------"+terms.getBuckets().get(i).getKey());
        }
        for(int i=0;i<lists.size();i++){
            for(int j=0;j<list.size();j++){
                if(lists.get(i).getId().equals(list.get(j).getId())){
                    list.get(j).setQuantity(lists.get(i).getSum());
                }
            }
        }

        return list;
    }

总结：以上代码是本人的亲自测试通过的，分页后期建议大家不用使用from，size格式，当数据量超过1w的时候，速度会越来越慢，并可能造成宕机。

精准条件查询

MatchPhraseQueryBuilder mpq1 = QueryBuilders
                    .matchPhraseQuery("id",knowledgeId);
            qbs.must(mpq1);//主题id

模糊条件查询

 QueryBuilder qb1 = QueryBuilders.matchPhraseQuery("title", keyword);
qbs.must(qb1);
 requestBuilder.setQuery(qbs);