java使用elasticsearch分组进行聚合查询（group by）-项目中实际应用

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 class ESClientConnectionUtil {
    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 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;
    }
}

 

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<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
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<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
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！