java连接elasticsearch 进行聚合查询进行相应操作

一：对单个字段进行分组求和

1、表结构图片：

根据任务id分组，分别统计出每个任务id下有多少个文字标题

1.SQL：select id, count(*) as sum from task group by taskid;

java ES连接工具类

public classESClientConnectionUtil {public static TransportClient client=null;public final static String HOST = "192.168.200.211"; //服务器部署

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;

}

}

java ES语句(根据单列进行分组求和)

//根据 任务id分组进行求和

SearchRequestBuilder sbuilder = client.prepareSearch("hottopic").setTypes("hot");

//根据taskid进行分组统计，统计出的列别名叫sum

TermsAggregationBuilder termsBuilder= AggregationBuilders.terms("sum").field("taskid");

sbuilder.addAggregation(termsBuilder);

SearchResponse responses=sbuilder.execute().actionGet();//得到这个分组的数据集合

Terms terms = responses.getAggregations().get("sum");

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

System.out.println("=="+terms.getBuckets().get(i).getDocCount()+"------"+terms.getBuckets().get(i).getKey());

}

//分别打印出统计的数量和id值

根据多列进行分组求和

//根据 任务id分组进行求和

SearchRequestBuilder sbuilder = client.prepareSearch("hottopic").setTypes("hot");//根据taskid进行分组统计，统计出的列别名叫sum

TermsAggregationBuilder termsBuilder = AggregationBuilders.terms("sum").field("taskid");//根据第二个字段进行分组

TermsAggregationBuilder aAggregationBuilder2 = AggregationBuilders.terms("region_count").field("birthplace");

//如果存在第三个，以此类推；

sbuilder.addAggregation(termsBuilder.subAggregation(aAggregationBuilder2));

SearchResponse responses=sbuilder.execute().actionGet();//得到这个分组的数据集合

Terms terms = responses.getAggregations().get("sum");

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

System.out.println("=="+terms.getBuckets().get(i).getDocCount()+"------"+terms.getBuckets().get(i).getKey());

}//分别打印出统计的数量和id值

对多个field求max/min/sum/avg

SearchRequestBuilder requestBuilder =client.prepareSearch("hottopic").setTypes("hot");

//根据taskid进行分组统计，统计别名为sum

TermsAggregationBuilder aggregationBuilder1= AggregationBuilders.terms("sum").field("taskid")

//根据tasktatileid进行升序排列 .order(Order.aggregation("tasktatileid", true));

// 求tasktitleid 进行求平均数 别名为avg_title

AggregationBuilder aggregationBuilder2 = AggregationBuilders.avg("avg_title").field("tasktitleid");

//

AggregationBuilder aggregationBuilder3= AggregationBuilders.sum("sum_taskid").field("taskid");

requestBuilder.addAggregation(aggregationBuilder1.subAggregation(aggregationBuilder2).subAggregation(aggregationBuilder3));

SearchResponse response=requestBuilder.execute().actionGet();

Terms aggregation= response.getAggregations().get("sum");

Avg terms2= null;

Sum term3= null;for(Terms.Bucket bucket : aggregation.getBuckets()) {

terms2= bucket.getAggregations().get("avg_title"); //org.elasticsearch.search.aggregations.metrics.avg.InternalAvg

term3 = bucket.getAggregations().get("sum_taskid"); //org.elasticsearch.search.aggregations.metrics.sum.InternalSum

System.out.println("编号=" + bucket.getKey() + ";平均=" + terms2.getValue() + ";总=" +term3.getValue());

}

如上内容若有不恰当支持，请各位多多包涵并进行点评。技术在于沟通！