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 classESClientConnectionUtil {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 staticTransportClient 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(newInetSocketTransportAddress(InetAddress.getByName(HOST), PORT));

}catch(Exception ex) {

ex.printStackTrace();

System.out.println(ex.getMessage());

}

}

}returnclient;

}public staticTransportClient 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(newInetSocketTransportAddress(InetAddress.getByName(HOST), PORT));

}catch(Exception ex) {

ex.printStackTrace();

System.out.println(ex.getMessage());

}

}returnclient;

}//判断索引是否存在

public static booleanjudgeIndex(String index){

client=getESClientConnection();

IndicesAdminClient adminClient;//查询索引是否存在

adminClient=client.admin().indices();

IndicesExistsRequest request= newIndicesExistsRequest(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 classKnowledgeTopicListDTO {private Long totalCount;//总条数

private Integer page;//页数

private Integer limit;//每页查询条数

private List topicDTOList;//每页显示数据的对象集合

publicLong getTotalCount() {returntotalCount;

}public voidsetTotalCount(Long totalCount) {this.totalCount =totalCount;

}publicInteger getPage() {returnpage;

}public voidsetPage(Integer page) {this.page =page;

}publicInteger getLimit() {returnlimit;

}public voidsetLimit(Integer limit) {this.limit =limit;

}public ListgetTopicDTOList() {returntopicDTOList;

}public void setTopicDTOList(ListtopicDTOList) {this.topicDTOList =topicDTOList;

}

}

(二)页面显示数据对象实体

public classKnowledgeTopicDTO {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

privateString _id;privateString ids;publicString getIds() {returnids;

}public voidsetIds(String ids) {this.ids =ids;

}publicLong getId() {returnid;

}public voidsetId(Long id) {this.id =id;

}publicString getName() {returnname;

}public voidsetName(String name) {this.name =name;

}publicBoolean getActive() {returnactive;

}public voidsetActive(Boolean active) {this.active =active;

}publicString getActiveString() {returnactiveString;

}public voidsetActiveString(String activeString) {this.activeString =activeString;

}publicBoolean getNoSubscription() {returnnoSubscription;

}public voidsetNoSubscription(Boolean noSubscription) {this.noSubscription =noSubscription;

}publicString getNoSubscriptionString() {returnnoSubscriptionString;

}public voidsetNoSubscriptionString(String noSubscriptionString) {this.noSubscriptionString =noSubscriptionString;

}publicLong getQuantity() {returnquantity;

}public voidsetQuantity(Long quantity) {this.quantity =quantity;

}publicString get_id() {return_id;

}public voidset_id(String _id) {this._id =_id;

}

}

三、后台service层代码

publicKnowledgeTopicListDTO selectTopicByName(String name, Integer page, Integer limit) {

SearchResponse searchResponse=null;

Map 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 list = new ArrayList();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 = newKnowledgeTopicListDTO();

knowledgeTopicListDTO.setLimit(limit);

knowledgeTopicListDTO.setPage(page);

knowledgeTopicListDTO.setTopicDTOList(list);returnknowledgeTopicListDTO;

}

五、根据单个字段分组查询

public classESGroupByUtil {/***@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 staticTerms 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);returnterms;

}

}

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*/

public List groupList(Listlist,Terms terms){

List lists = new ArrayList<>();for(int i=0;i

String id =terms.getBuckets().get(i).getKey().toString();//id

Long sum =terms.getBuckets().get(i).getDocCount();//数量

BsKnowledgeInfoDTO bsKnowledgeInfoDTO1 = newBsKnowledgeInfoDTO();

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

list.get(j).setQuantity(lists.get(i).getSum());

}

}

}returnlist;

}

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。