去重算法

				logger.info("fetchData end, eids.length={}, eids={}", eids.length, eids);
				//复杂的去重处理,先把相同的数据统一起来,最后在取相同数据中最大的EID数据
				long [] a = new long[eids.length];
				List<HashMap<String,Object>> list = new ArrayList<HashMap<String,Object>>();
				List<String> companyCodeList = new ArrayList<String>();
				//添加COMPANYCODE
				for (long eid : eids) {
					DataRow zbyzInfo = dao.queryZBYZInfo(eid); 
					if(zbyzInfo!=null && zbyzInfo.size()>0) {
						Date noticeDate = (Date) zbyzInfo.get("NOTICEDATE");//公告日期
						String COMPANYCODE= zbyzInfo.getString("COMPANYCODE");//公司代码
						String DESCRIPTION = zbyzInfo.getString("DESCRIPTION").toString();//内容
						//先保存所有的数据
						HashMap<String,Object> map = new HashMap<String,Object>();
						map.put("eid", eid);
						map.put("noticeDate", noticeDate);
						map.put("COMPANYCODE", COMPANYCODE);
						map.put("DESCRIPTION", DESCRIPTION);
						companyCodeList.add(COMPANYCODE);
						list.add(map);
					}
				}
				if(companyCodeList.size() > 0 && list.size() > 0){
					Map<String,ArrayList<HashMap<String, Object>>> map2 = new HashMap<String,ArrayList<HashMap<String,Object>>>();
					for (String companyCode : companyCodeList) {
						ArrayList<HashMap<String, Object>> list2 = new ArrayList<HashMap<String,Object>>();
						//根据公司代码遍历所有的数据来分类
						for (HashMap<String, Object> map : list) {
							if(map.containsKey(companyCode)){
								//存在
								list2.add(map);
							}
						}
						map2.put(companyCode, list2);
					}
					
					//处理同一公司code的数据  最复杂的地方
					//1.遍历map
					Iterator<Entry<String, ArrayList<HashMap<String, Object>>>> iterator = map2.entrySet().iterator(); 
					while(iterator.hasNext()){
						Entry<String, ArrayList<HashMap<String, Object>>> entry = iterator.next();
						ArrayList<HashMap<String,Object>> value = entry.getValue();
						for (HashMap<String, Object> hashMap : value) {
							//同一公司  日期相同的筛选
							
						}
					}
				}
				
				//return Arrays.asList(ArrayUtils.toObject(eids));