ElasticSearch查询模板
需要的jar包，我这里使用maven的pom.xml导入，可以自己下载jar包并导入到项目中
org.elasticsearch.client
transport
5.4.2
org.elasticsearch
elasticsearch
5.4.2
连接集群ClientConnect.java
import java.net.InetSocketAddress;
import org.elasticsearch.client.transport.TransportClient;
import org.elasticsearch.common.settings.Settings;
import org.elasticsearch.common.transport.InetSocketTransportAddress;
import org.elasticsearch.transport.client.PreBuiltTransportClient;
/**
*
* @createDate 2018年3月8日
* @class_name ClientConnect 连接ES集群
* @description : 建立es的client，通过getClient()调用，只能连接es5.4.2
*/
public class ClientConnect {
private TransportClient client;
public TransportClient getClient() {
return client;
}
/**
*
* @param clusterName 集群名称
* @param clusterAddress 集群ip地址
* @param port 端口号
*/
@SuppressWarnings({ "unchecked", "resource" })
public ClientConnect(String clusterName, String clusterAddress, int port) {
Settings settings = Settings.builder().put("cluster.name", clusterName)
.build();
client = new PreBuiltTransportClient(settings)
.addTransportAddress(new InetSocketTransportAddress(
new InetSocketAddress(clusterAddress, port)));
System.out.println("success connect");
}
}查询模板BaseSearch.java
package util;
import java.util.Arrays;
import java.util.Iterator;
import org.apache.lucene.search.Sort;
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.action.search.SearchType;
import org.elasticsearch.action.search.SearchRequestBuilder;
import org.elasticsearch.client.transport.TransportClient;
import org.elasticsearch.common.lucene.search.function.CombineFunction;
import org.elasticsearch.common.lucene.search.function.FieldValueFactorFunction.Modifier;
import org.elasticsearch.index.query.MultiMatchQueryBuilder.Type;
import org.elasticsearch.index.query.QueryBuilder;
import org.elasticsearch.index.query.QueryBuilders;
import org.elasticsearch.index.query.functionscore.FunctionScoreQueryBuilder.FilterFunctionBuilder;
import org.elasticsearch.index.query.functionscore.ScoreFunctionBuilders;
import org.elasticsearch.search.SearchHit;
import org.elasticsearch.search.SearchHits;
import org.elasticsearch.search.fetch.subphase.highlight.HighlightBuilder;
import org.elasticsearch.search.sort.SortOrder;
import org.junit.Test;
/**
* @date 2018年3月8日
* @class_name baseSearch
* @description : 查询模板
*/
public class BaseSearch {
private TransportClient client;
private SearchResponse response;
private SearchRequestBuilder searchRequestBuilder;
/**
* @description : 构造一个搜索实例
* @param client es服务器的ip地址
*/
public BaseSearch(TransportClient client){
this.client=client;
}
/**
* @description : 使用前必须先自定义搜索语句
*/
private QueryBuilder setQuery(){
/*
* must 查询子句must出现在文档中，并且会影响文档得分score
* filter 查询子句must出现在文档中，但是不会影响文档得分，并且会缓存
* should 查询子句should出现在文档中，即并列的should子句必须有一个或者多个出现在文档中，可以通过设置参数 minimum_should_match来指定最少匹配的查询子句
* must_not 查询子句一定不能出现在文档中，处于filter上下文，不影响文档得分，会被缓存
*
* 1. 加权查询,数据在"title","summary","author","content"四个字段中包含搜索关键词"国经理",并将该次查询分数变成1.0倍。
* 2. 整句查询,数据在"title","summary"字段中包含搜索关键短语"事件反腐风暴",事件反腐风暴不分词，事件反腐风暴中间可间隔2位
* 3. 模糊查询,数据在"title","summary"字段中包含搜索关键词"国经理",并将该次查询设置为模糊查询,模糊程度"AUTO"
* 4. 数据在"title"字段中包含搜索符合关键词"反腐","国家","公司"中任意一个条件，并并将该次查询分数变成-0.9倍
* 5. 数据不在"title","summary","author","content"任意一个字段内含有关键词"交易"
* 6. 通配符查询,数据在"author"字段中含有通配符表达式"*w*"，支持？ 匹配任何字符，*匹配零个或多个字符
* 7. 正则查询,数据在"author"字段中含有正则表达式"[a-z]k[a-z]"
* 8. 前缀短语查询,数据在"summary"字段中以"据"开头的数据
* 9-11。数据在3个should中满足至少一个查询子句
* 12. 设置至少要符合多少个条件,参数为百分比，或者整型
* 13. 数据在"publish_time"字段里的数据在from("2018-01-13 14:21:09")和to("2018-01-17 14:21:09")之间
* 14. 数据存在"title"字段
* 15. 衰减函数DecayFunction(field, origin, scale, offset, decay),有linear,gauss,exponential三种,数据离origin越近得分越高
* 16. 域值因子fieldValueFactorFunction(field).通过字段field里的值提高数据的得分
*/
return QueryBuilders
.boolQuery()
/*1*/ // .must(QueryBuilders.multiMatchQuery("国经理", "title","summary","author","content").boost(1.0f))
/*2*/ // .must(QueryBuilders.multiMatchQuery("事件反腐风暴", "title","summary").type(Type.PHRASE).slop(2))
/*3*/ // .must(QueryBuilders.multiMatchQuery("报道", "title","summary").fuzziness("AUTO"))
/*4*/ // .must(QueryBuilders.termsQuery("title", "反腐","国家","公司").boost(-0.9f))
/*5*/ // .mustNot(QueryBuilders.multiMatchQuery("交易", "title","summary","author","content"))
/*6*/ // .must(QueryBuilders.wildcardQuery("author", "*w*"))
/*7*/ // .must(QueryBuilders.regexpQuery("author", "[a-z]k[a-z]"))
/*8*/ // .must(QueryBuilders.matchPhrasePrefixQuery("summary","据"))
/*9*/ // .should(QueryBuilders.multiMatchQuery("亿元","title","summary","author","content"))
/*10*/ // .should(QueryBuilders.multiMatchQuery("严格","title","summary","author","content"))
/*11*/ // .should(QueryBuilders.multiMatchQuery("发表","title","summary","author","content"))
/*12*/ // .minimumShouldMatch("55%")
/*13*/ // .must(QueryBuilders.rangeQuery("publish_time").from("2018-01-13 14:21:09").to("2018-01-17 14:21:09"))//50.45 59.12 1741 1749.66
/*14*/ // .must(QueryBuilders.existsQuery("title"))
/*15*/ // .must(QueryBuilders.functionScoreQuery(ScoreFunctionBuilders.linearDecayFunction("price",67,20,5,0.5)))
/*16*/ // .must(QueryBuilders.functionScoreQuery(ScoreFunctionBuilders.fieldValueFactorFunction("comment").modifier(Modifier.LN1P).factor(0.1f)).boostMode(CombineFunction.SUM))
;
}
/**
* @description : 使用前必须先自定义过滤语句,过滤不影响得分,
*/
private QueryBuilder setFilter(){
/*
* must 查询子句must出现在文档中，并且会影响文档得分score
* filter 查询子句must出现在文档中，但是不会影响文档得分，并且会缓存
* should 查询子句should出现在文档中，即并列的should子句必须有一个或者多个出现在文档中，可以通过设置参数 minimum_should_match来指定最少匹配的查询子句
* must_not 查询子句一定不能出现在文档中，处于filter上下文，不影响文档得分，会被缓存
*
* 1. 加权查询,数据在"title","summary","author","content"四个字段中包含搜索关键词"国经理",并将该次查询分数变成1.5倍。
* 2. 整句查询,数据在"title","summary"字段中包含搜索关键短语"事件反腐风暴",事件反腐风暴不分词，事件反腐风暴中间可间隔2位
* 3. 模糊查询,数据在"title","summary"字段中包含搜索关键词"国经理",并将该次查询设置为模糊查询,模糊程度"AUTO"
* 4. 数据在"title"字段中包含搜索符合关键词"反腐","国家","公司"中任意一个条件，并并将该次查询分数变成-0.9倍
* 5. 数据不在"title","summary","author","content"任意一个字段内含有关键词"交易"
* 6. 通配符查询,数据在"author"字段中含有通配符表达式"*w*"，支持？ 匹配任何字符，*匹配零个或多个字符
* 7. 正则查询,数据在"author"字段中含有正则表达式"[a-z]k[a-z]"
* 8. 前缀短语查询,数据在"summary"字段中以"据"开头的数据
* 9-11。 数据在3个should中满足至少一个查询子句
* 12. 设置至少要符合多少个条件,参数为百分比，或者整型
* 13. 数据在"publish_time"字段里的数据在from("2018-01-13 14:21:09")和to("2018-01-17 14:21:09")之间
*/
return QueryBuilders
.boolQuery()
/*1*/ // .must(QueryBuilders.multiMatchQuery("国经理", "title","summary","author","content").boost(1.5f))
/*2*/ // .must(QueryBuilders.multiMatchQuery("事件反腐风暴", "title","summary").type(Type.PHRASE).slop(2))
/*3*/ // .must(QueryBuilders.multiMatchQuery("报道", "title","summary").fuzziness("AUTO"))
/*4*/ // .must(QueryBuilders.termsQuery("title", "反腐","国家","公司").boost(-0.9f))
/*5*/ // .mustNot(QueryBuilders.multiMatchQuery("交易", "title","summary","author","content"))
/*6*/ // .must(QueryBuilders.wildcardQuery("author", "*w*"))
/*7*/ // .must(QueryBuilders.regexpQuery("author", "[a-z]k[a-z]"))
/*8*/ // .must(QueryBuilders.matchPhrasePrefixQuery("summary","据"))
/*9*/ // .should(QueryBuilders.multiMatchQuery("亿元","title","summary","author","content"))
/*10*/ // .should(QueryBuilders.multiMatchQuery("严格","title","summary","author","content"))
/*11*/ // .should(QueryBuilders.multiMatchQuery("发表","title","summary","author","content"))
/*12*/ // .minimumShouldMatch("55%")
/*13*/ // .must(QueryBuilders.rangeQuery("publish_time").from("2018-01-13 14:21:09").to("2018-01-17 14:21:09"))
;
}
/**
* @description : 使用前必须先自定义高亮设置语句
*/
private HighlightBuilder setHighlight(){
HighlightBuilder highlightBuild = new HighlightBuilder()
// 设置被高亮的字段
.field("summary").field("title")
// 设置高亮的标签
.preTags("").postTags("");
return highlightBuild;
}
/**
* @param response
* @description : 打印搜索结果
*/
public void printResponse(){
response=this.getResponse();
// timed_out
boolean isTimedOut = response.isTimedOut();
System.out.println("查询成功，timed_out:"+isTimedOut);
// _shards，查询总分片数,查询成功片数,查询失败片数
int totalShards = response.getTotalShards();
int successfulShards = response.getSuccessfulShards();
int failedShards = response.getFailedShards();
System.out.println("查询分片数:{ total="+totalShards+" successful="+successfulShards+" failed="+failedShards+"},查询到"+response.getHits().totalHits+"条记录");
// 文档在hit数组中，更多方法使用请看API中SearchHits
SearchHits searchHits = response.getHits();
Iterator iterator = searchHits.iterator();
while(iterator.hasNext()) {
SearchHit hit = iterator.next();
String hitIndex = hit.getIndex();
String hitType = hit.getType();
String id = hit.getId();
float score = hit.getScore();
System.out.println("index="+hitIndex+" type="+hitType+" id="+id+" score="+score+" source-->"+hit.getSourceAsString());
System.out.println(hit.getHighlightFields());
}
System.out.println("查询结束...");
}
/**
* @description 获取搜索结果,需先修改BasaSearch里的方法setQuery(),setFilter(),setHighlight()
* @param indexs 索引名称
* @param types 类型名称
*/
public void getSearchByIndexAndType(String[] indexs,String[] types) {
System.out.print("集群中查询索引为"+Arrays.deepToString(indexs)
+"和类型为"+Arrays.deepToString(types)
+"的所有数据");
//查询
QueryBuilder queryBulid=this.setQuery();
QueryBuilder filterBulid=this.setFilter();
HighlightBuilder highlightBuild1=this.setHighlight();
searchRequestBuilder =
//设置查询的index，例{"twitter","indexName"}
client.prepareSearch(indexs)
//设置查询的type，例{"tweet","typeName"}
.setTypes(types)
/* 设置查询类型
* 1.SearchType.DFS_QUERY_THEN_FETCH = 最精确
* 2.SearchType.QUERY_THEN_FETCH = 比较快
*/
.setSearchType(SearchType.DFS_QUERY_THEN_FETCH)
//设置查询
.setQuery(queryBulid)
//设置过滤器
.setPostFilter(filterBulid)
//设置获取查询数据的位置
.setFrom(0)
//设置获取查询数据的数量
.setSize(50)
//设置是否按查询匹配度排序,很耗资源,只能用作调试工具,千万不要用于生产环境
// .setExplain(true)
//设置显示高亮，
.highlighter(highlightBuild1)
//设置根据"publish_time"排序
// .addSort("publish_time", SortOrder.DESC)
;
System.out.println("开始查询...");
//建立查询，并返回结果
SearchResponse response = searchRequestBuilder.get();
this.setResponse(response);
}
/**
* @description : 获取发送给服务器的请求的JSON格式
* @return String
*/
public String getRequestJSON(){
return searchRequestBuilder.toString();
}
public TransportClient getClient() {
return client;
}
public void setClient(TransportClient client) {
this.client = client;
}
public SearchRequestBuilder getSearchRequestBuilder() {
return searchRequestBuilder;
}
public void setSearchRequestBuilder(SearchRequestBuilder searchRequestBuilder) {
this.searchRequestBuilder = searchRequestBuilder;
}
public SearchResponse getResponse() {
return response;
}
public void setResponse(SearchResponse response) {
this.response = response;
}
} 测试实例SearchTest.java
package instancetest;
import org.elasticsearch.client.transport.TransportClient;
import util.BaseSearch;
import util.ClientConnect;
public class SearchTest {
public static void main(String[] args) {
// TODO Auto-generated method stub
TransportClient client = new ClientConnect("elasticsearch", "192.168.203.201", 9320).getClient();
BaseSearch bs = new BaseSearch(client);
String[] index = {};
String[] type = {};
// 从index和type中搜索，为空则为全部搜索
bs.getSearchByIndexAndType(index, type);
// 打印服务器的回复
bs.printResponse();
// 打印发送的请求
System.out.println(bs.getRequestJSON());
}
}
根据需求修改查询模板BaseSearch.java来获取想要的检索结果。
通过进行各种尝试来掌握ElasticSearch的查询功能。
注意：使用的ElasticSearch的jar包要和集群使用的版本一样，不然可能出现连接不上集群的错误。