针对不同的地图级别对大数据量的点进行聚合

package com.sb.service.impl;

import java.text.SimpleDateFormat;
import java.util.ArrayList;
import java.util.Date;
import java.util.List;

import com.sb.entity.SG_GROUPINDEX;
import com.sb.entity.SG_PIPEPOINT;


//聚合类 不同的地图级别聚合的距离不一样，每一个地图级别都对应一个聚合结果
public class MarkerClusterer {
    public MarkerClusterer() {
         
    }
    protected int total;
   //创建聚合
    //points 点集
    //dis 聚合距离
    //return clusters 聚合点集合
   public List<SG_GROUPINDEX> createClusterer(List<SG_PIPEPOINT> points,double dis,int zoom,String thisDay) {
       //List<SG_PIPEPOINT> points,double dis,int zoom,String thisDay
        List<SG_GROUPINDEX> clusters= new ArrayList<SG_GROUPINDEX>();
        for(int i=0;i<points.size();i++) {
             boolean incluster=false;
               SG_PIPEPOINT tmpPT=points.get(i);
               
             for(int j=0;j<clusters.size();j++){
                //在指定的聚合距离(dis)之内
               if(this.getDistance(clusters.get(j).getCenterx(),clusters.get(j).getCentery(),tmpPT)<dis){
                  if(clusters.get(j).getMinX()>tmpPT.getJd()) clusters.get(j).setMinX(tmpPT.getJd());
                  if(clusters.get(j).getMaxX()<tmpPT.getJd()) clusters.get(j).setMaxX(tmpPT.getJd());
                  if(clusters.get(j).getMinY()>tmpPT.getWd()) clusters.get(j).setMinY(tmpPT.getWd());
                  if(clusters.get(j).getMaxY()<tmpPT.getWd()) clusters.get(j).setMaxY(tmpPT.getWd());
                  clusters.get(j).addNum();
                  incluster=true;
                  break;
               }
            }
            if(!incluster) //否则就单独创建一个聚合点
            {
                clusters.add(this.createCluster(tmpPT,dis,zoom,thisDay));
            }
        }
        return clusters;
   }
   //创建一个聚合
   private SG_GROUPINDEX createCluster(SG_PIPEPOINT p,double dis,int zoom,String thisDay)
   {
       SG_GROUPINDEX cluster=new SG_GROUPINDEX();
       cluster.setNum(1);
       cluster.setCenterx(p.getJd());
       cluster.setCentery(p.getWd());
       cluster.setMinX(p.getJd());
       cluster.setMinY(p.getJd());
       cluster.setMaxX(p.getWd());
       cluster.setMaxY(p.getWd());
       cluster.setDis(dis);
       cluster.setZoom(zoom);
       cluster.setCreatetime(thisDay);
       return cluster;
       
   }
   //计算两点之间的距离
   private double getDistance(double x,double y,SG_PIPEPOINT point2){
    double pk = 180 / 3.14169  ;
    double a1 = y / pk  ;
    double a2 = x / pk  ;
    double b1 = point2.getWd() / pk  ;
    double b2 = point2.getJd() / pk  ;
    double t1 =Math.cos(a1) * Math.cos(a2) * Math.cos(b1) * Math.cos(b2)  ;
    double t2 = Math.cos(a1) * Math.sin(a2) * Math.cos(b1) * Math.sin(b2)  ;
    double t3 = Math.sin(a1) * Math.sin(b1);
    double tt = Math.acos(t1 + t2 + t3);
    return 6366000 * tt;
   }

}


 

标签：聚合,java,int,List,对大,数据量,clusters,import
来源： https://www.cnblogs.com/GIScore/p/13608997.html