java使用elasticsearch分組進行聚合查詢過程解析
這篇文章主要介紹了java使用elasticsearch分組進行聚合查詢過程解析,文中通過示例代碼介紹的非常詳細,對大家的學習或者工作具有一定的參考學習價值,需要的朋友可以參考下
java連接elasticsearch 進行聚合查詢進行相應操作
一:對單個字段進行分組求和
1、表結構圖片:

根據(jù)任務id分組,分別統(tǒng)計出每個任務id下有多少個文字標題
1.SQL:select id, count(*) as sum from task group by taskid;
java ES連接工具類
public class ESClientConnectionUtil {
public static TransportClient client=null;
public final static String HOST = "192.168.200.211"; //服務器部署
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 {
//設置集群名稱
Settings settings = Settings.builder().put("cluster.name", "es5").put("client.transport.sniff", true).build();
//創(chuàng)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 {
//設置集群名稱
Settings settings = Settings.builder().put("cluster.name", "es5").put("client.transport.sniff", true).build();
//創(chuàng)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;
}
//判斷索引是否存在
public static boolean judgeIndex(String index){
client= getESClientConnection();
IndicesAdminClient adminClient;
//查詢索引是否存在
adminClient= client.admin().indices();
IndicesExistsRequest request = new IndicesExistsRequest(index);
IndicesExistsResponse responses = adminClient.exists(request).actionGet();
if (responses.isExists()) {
return true;
}
return false;
}
}
java ES語句(根據(jù)單列進行分組求和)
//根據(jù) 任務id分組進行求和
SearchRequestBuilder sbuilder = client.prepareSearch("hottopic").setTypes("hot");
//根據(jù)taskid進行分組統(tǒng)計,統(tǒng)計出的列別名叫sum
TermsAggregationBuilder termsBuilder = AggregationBuilders.terms("sum").field("taskid");
sbuilder.addAggregation(termsBuilder);
SearchResponse responses= sbuilder.execute().actionGet();
//得到這個分組的數(shù)據(jù)集合
Terms terms = responses.getAggregations().get("sum");
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();//數(shù)量
System.out.println("=="+terms.getBuckets().get(i).getDocCount()+"------"+terms.getBuckets().get(i).getKey());
}
//分別打印出統(tǒng)計的數(shù)量和id值
根據(jù)多列進行分組求和
//根據(jù) 任務id分組進行求和
SearchRequestBuilder sbuilder = client.prepareSearch("hottopic").setTypes("hot");
//根據(jù)taskid進行分組統(tǒng)計,統(tǒng)計出的列別名叫sum
TermsAggregationBuilder termsBuilder = AggregationBuilders.terms("sum").field("taskid");
//根據(jù)第二個字段進行分組
TermsAggregationBuilder aAggregationBuilder2 = AggregationBuilders.terms("region_count").field("birthplace");
//如果存在第三個,以此類推;
sbuilder.addAggregation(termsBuilder.subAggregation(aAggregationBuilder2));
SearchResponse responses= sbuilder.execute().actionGet();
//得到這個分組的數(shù)據(jù)集合
Terms terms = responses.getAggregations().get("sum");
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();//數(shù)量
System.out.println("=="+terms.getBuckets().get(i).getDocCount()+"------"+terms.getBuckets().get(i).getKey());
}
//分別打印出統(tǒng)計的數(shù)量和id值
對多個field求max/min/sum/avg
SearchRequestBuilder requestBuilder = client.prepareSearch("hottopic").setTypes("hot");
//根據(jù)taskid進行分組統(tǒng)計,統(tǒng)計別名為sum
TermsAggregationBuilder aggregationBuilder1 = AggregationBuilders.terms("sum").field("taskid")
//根據(jù)tasktatileid進行升序排列
.order(Order.aggregation("tasktatileid", true));
// 求tasktitleid 進行求平均數(shù) 別名為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("編號=" + bucket.getKey() + ";平均=" + terms2.getValue() + ";總=" + term3.getValue());
}
以上就是本文的全部內容,希望對大家的學習有所幫助,也希望大家多多支持腳本之家。
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