优化Traffic和IP top10趋势图统计功能
This commit is contained in:
zhangdongxu
@@ -11,6 +11,7 @@ import com.zdjizhi.utils.StringUtil;
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import org.springframework.beans.factory.annotation.Autowired;
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import org.springframework.stereotype.Service;
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import java.text.ParseException;
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import java.text.SimpleDateFormat;
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import java.util.*;
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import java.util.Map.Entry;
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@@ -435,56 +436,78 @@ public class DashboardService extends BaseService {
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/**
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* 获取活跃IPtop10 的趋势图
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*/
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public List<HashMap> ipActiveFiveMinute(Date beginDate, Date endDate) {
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ArrayList<HashMap> listMap = new ArrayList<HashMap>();
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ArrayList<LinkedHashMap> ipListTop10 = trafficIpActiveStatisticDao.ipActiveChart(beginDate, endDate);
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public List<Map> ipActiveFiveMinute(Date beginDate, Date endDate) {
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List<Map> listMap = new ArrayList<Map>();
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List<LinkedHashMap> ipListTop10 = trafficIpActiveStatisticDao.ipActiveChart(beginDate, endDate);
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if (ipListTop10 != null && ipListTop10.size() > 0) {
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StringBuilder ipStr = new StringBuilder();
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for (LinkedHashMap map : ipListTop10) {
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HashMap m1 = new HashMap();
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String ipAddr = (String) map.get("ipAddr");
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m1.put("ipAddr", ipAddr);
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ArrayList<TrafficIpActiveStatistic> ipList = trafficIpActiveStatisticDao.ipActiveFiveMinute(ipAddr,
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beginDate, endDate);
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List timeList = new ArrayList();
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List sumList1 = new ArrayList();
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Map<String, Comparable> m = new HashMap<String, Comparable>();
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int inter = 1000 * 60 * 5;// 间隔时间为五分钟
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// 开始时间，结束时间 时间戳
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Long b = dateToStamp(DateUtils.formatDateTime(beginDate));
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Long e = dateToStamp(DateUtils.formatDateTime(endDate));
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int num = 0;
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Long pointTime = b;
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while (pointTime < e) {
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Map rm = new HashMap();
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Long sum1 = 0l;
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if (pointTime >= e) {
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break; // 停止
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}
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for (TrafficIpActiveStatistic e1 : ipList) {
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// 实际时间
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String time = e1.getTime();
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Long t = dateToStamp(time);
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if (t >= pointTime && t < pointTime + inter) {
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// 范围之内分到此pointTime组
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sum1 = sum1 + e1.getCount();
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ipStr.append("'"+(String) map.get("ipAddr")+"',");
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}
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if (!StringUtil.isEmpty(ipStr)&&ipStr.indexOf(",")>0) {
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ipStr.deleteCharAt(ipStr.lastIndexOf(","));
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}
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//如果所有IP在最后一个时间点的count都为0，则移除最后一个点
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//开始划分时间段,间隔5分钟
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List<Date> dateRangeList = new ArrayList<Date>();
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List<String> strDateRangeList = new ArrayList<String>();
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Calendar calendar = Calendar.getInstance();
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calendar.setTime(beginDate);
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SimpleDateFormat sdf = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
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while (calendar.getTime().compareTo(endDate)<=0) {
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dateRangeList.add(calendar.getTime());
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strDateRangeList.add(sdf.format(calendar.getTime()));
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calendar.add(Calendar.MINUTE, 5);
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}
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ArrayList<TrafficIpActiveStatistic> ipInfoList = trafficIpActiveStatisticDao.ipActiveFiveMinute(ipStr.toString(),
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beginDate, endDate);
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//存放每个IP，每个时间点的总数
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Map<String,List<Long>> ipCountListMap = new HashMap<String, List<Long>>();
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int index=0;
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for (int i = 0; i < dateRangeList.size(); i++) {
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//存放一个时间点中每个IP的总数
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Map<String, Long> ipCountMap = new HashMap<String, Long>();
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Date date = dateRangeList.get(i);
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for (int j = index; j < ipInfoList.size(); j++) {
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TrafficIpActiveStatistic ipInfo = ipInfoList.get(j);
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if (ipInfo.getStatTime()!=null){
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if(ipInfo.getStatTime().compareTo(date)>=0&&(i+1<dateRangeList.size()&&ipInfo.getStatTime().compareTo(dateRangeList.get(i+1))<0)) {
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Long num = ipInfo.getCount();
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if (ipCountMap.containsKey(ipInfo.getIpAddr())) {
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num=num+ipCountMap.get(ipInfo.getIpAddr());
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}
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ipCountMap.put(ipInfo.getIpAddr(), num);
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}else{
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index = j;
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break;
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}
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}
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// 在结束时间只有当值大于0时才记录数据，防止折线降为0引起误会
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if (pointTime >= e - inter && sum1 > 0) {
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sumList1.add(sum1);
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timeList.add(stampToDate(pointTime));
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}
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if (pointTime < e - inter) {
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sumList1.add(sum1);
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timeList.add(stampToDate(pointTime));
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}
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num = num + 1;
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pointTime = b + inter * num;
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}
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m1.put("linkNum", sumList1);
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m1.put("statTime", timeList);
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listMap.add(m1);
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for (LinkedHashMap map : ipListTop10) {
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String ip = (String) map.get("ipAddr");
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Long sum = 0l;
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if (ipCountMap.containsKey(ip)) {
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sum=ipCountMap.get(ip);
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}
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if (ipCountListMap.containsKey(ip)) {
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ipCountListMap.get(ip).add(sum);
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}else{
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List<Long> list = new ArrayList<Long>();
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list.add(sum);
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ipCountListMap.put(ip, list);
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}
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}
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}
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//整合IP count time
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Iterator iterator = ipCountListMap.keySet().iterator();
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while (iterator.hasNext()) {
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String ip = iterator.next()+"";
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Map ipTrafficMap = new HashMap();
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ipTrafficMap.put("ipAddr", ip);
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ipTrafficMap.put("linkNum", ipCountListMap.get(ip));
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ipTrafficMap.put("statTime", strDateRangeList);
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listMap.add(ipTrafficMap);
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}
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}
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return listMap;
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@@ -1127,109 +1150,112 @@ public class DashboardService extends BaseService {
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return fieldType == null ? null : fieldType.split(",");
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}
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public Map<String, List<HashMap>> getBandwidthTransEntrance(String beginDate, String endDate) {
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long start = System.currentTimeMillis();
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Map<String, List<TrafficTransStatistic>> listMap = new HashMap<String, List<TrafficTransStatistic>>();
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List<TrafficTransStatistic> bandwidthList = new ArrayList<TrafficTransStatistic>();
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bandwidthList = ntcTotalReportDao.getBandwidthTrans2(beginDate, endDate);
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String[] addrTypes = getFiledTypeByName("addr_type");
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String[] transTypes = getFiledTypeByName("trans_type");
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String[] entranceIds = getFiledTypeByName("entrance_id");
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for (String entranceId : entranceIds) {
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for (String addrType : addrTypes) {
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listMap.put("ipv" + addrType + "Type" + entranceId, new ArrayList<TrafficTransStatistic>());
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public Map<String, Map> getBandwidthTransEntrance(String beginDate, String endDate) throws ParseException {
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Map<String, Map> resultMap = new HashMap<String, Map>();
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Map<String, ArrayList<TrafficTransStatistic>> listMap = new HashMap<String, ArrayList<TrafficTransStatistic>>();
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List<TrafficTransStatistic> bandwidthListIPvx = new ArrayList<TrafficTransStatistic>();
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List<TrafficTransStatistic> bandwidthListProtocol = new ArrayList<TrafficTransStatistic>();
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bandwidthListIPvx = ntcTotalReportDao.getBandwidthTransIPVx(beginDate, endDate);
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bandwidthListProtocol = ntcTotalReportDao.getBandwidthTransProtocol(beginDate, endDate);
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Map<String, Map> trafficMap = new HashMap<String, Map>();
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if((!StringUtil.isEmpty(bandwidthListIPvx)&&bandwidthListIPvx.size()>0)||(!StringUtil.isEmpty(bandwidthListProtocol)&&bandwidthListProtocol.size()>0)){
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//划分时间段
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SimpleDateFormat sdf = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
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Date startTime = sdf.parse(beginDate);
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Date endTime = sdf.parse(endDate);
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List<Date> dateRangeList = new ArrayList<Date>();
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List<String> strDateRangeList = new ArrayList<String>();
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Calendar calendar = Calendar.getInstance();
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calendar.setTime(startTime);
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while (calendar.getTime().compareTo(endTime)<=0) {
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dateRangeList.add(calendar.getTime());
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strDateRangeList.add(sdf.format(calendar.getTime()));
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calendar.add(Calendar.MINUTE, 5);
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}
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}
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for (String entranceId : entranceIds) {
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for (String transType : transTypes) {
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listMap.put("trans" + transType + "Type" + entranceId, new ArrayList<TrafficTransStatistic>());
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}
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}
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for (TrafficTransStatistic tts : bandwidthList) {
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String addrType = tts.getAddrType();
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Integer entranceId = tts.getEntranceId();
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Integer transType = tts.getTransType();
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String key1 = "ipv" + addrType + "Type" + entranceId;
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String key2 = "trans" + transType + "Type" + entranceId;
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listMap.get(key1).add(tts);
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listMap.get(key2).add(tts);
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}
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Map<String, List<HashMap>> resultMap = new HashMap<String, List<HashMap>>();
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Set<Entry<String, List<TrafficTransStatistic>>> entrySet = listMap.entrySet();
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for (Entry<String, List<TrafficTransStatistic>> entry : entrySet) {
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String key = entry.getKey();
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String entranceId = key.substring(key.length() - 1);
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List<TrafficTransStatistic> value = entry.getValue();
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HashMap newData = getNewData(beginDate, endDate, value);
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newData.put("entranceId", entranceId);
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ArrayList<HashMap> resultList = new ArrayList<HashMap>();
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resultList.add(newData);
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resultMap.put(key, resultList);
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}
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return resultMap;
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}
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private HashMap getNewData(String beginDate, String endDate, List<TrafficTransStatistic> bandwidthList) {
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HashMap resulMap = new HashMap();
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List timeList = new ArrayList();
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List linkList = new ArrayList();
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List gbpsList = new ArrayList();
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List ppsList = new ArrayList();
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if (bandwidthList != null && bandwidthList.size() > 0) {
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Map<String, Comparable> m = new HashMap<String, Comparable>();
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int inter = 1000 * 60 * 5;// 间隔时间为五分钟
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// 开始时间，结束时间 时间戳
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Long b = dateToStamp(beginDate);
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Long e = dateToStamp(endDate);
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int num = 0;
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Long pointTime = b;
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while (pointTime < e) {
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Long sumL = 0l;
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Long sumP = 0l;
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Long sumG = 0l;
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if (pointTime >= e) {
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break; // 停止
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}
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for (TrafficTransStatistic tt : bandwidthList) {
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// 实际时间
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String time = tt.getTime();
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Long t = dateToStamp(time);
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if (t >= pointTime && t < pointTime + inter) {
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// 范围之内分到此pointTime组
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sumL = sumL + tt.getLinkNum();
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sumP = sumP + tt.getPps();
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sumG = sumG + tt.getGbps();
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String[] addrTypes = getFiledTypeByName("addr_type");
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String[] transTypes = getFiledTypeByName("trans_type");
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String[] entranceIds = getFiledTypeByName("entrance_id");
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if(bandwidthListIPvx!=null&&bandwidthListIPvx.size()>0&&bandwidthListProtocol!=null&&bandwidthListProtocol.size()>0&&addrTypes!=null&&addrTypes.length>0&&transTypes!=null&&transTypes.length>0
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&&entranceIds!=null&&entranceIds.length>0){
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//按区域和类型构建Map
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for (String entranceId : entranceIds) {
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for (String addrType : addrTypes) {
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listMap.put("ipv" + addrType + "Type" + entranceId, new ArrayList<TrafficTransStatistic>());
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}
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}
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// 在结束时间只有当值大于0时才记录数据，防止折线降为0引起误会
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if (pointTime >= e - inter && sumL > 0) {
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linkList.add(sumL);
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for (String entranceId : entranceIds) {
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for (String transType : transTypes) {
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listMap.put("trans" + transType + "Type" + entranceId, new ArrayList<TrafficTransStatistic>());
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}
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}
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if (pointTime >= e - inter && sumP > 0) {
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ppsList.add(sumP);
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//按区域和类型提取数据到列表中
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for (TrafficTransStatistic tts : bandwidthListIPvx) {
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String addrType = tts.getAddrType();
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Integer entranceId = tts.getEntranceId();
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Integer transType = tts.getTransType();
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String key = "ipv" + addrType + "Type" + entranceId;
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listMap.get(key).add(tts);
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}
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if (pointTime >= e - inter && sumG > 0) {
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gbpsList.add(sumG);
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for (TrafficTransStatistic tts : bandwidthListProtocol) {
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String addrType = tts.getAddrType();
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Integer entranceId = tts.getEntranceId();
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Integer transType = tts.getTransType();
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String key = "trans" + transType + "Type" + entranceId;
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listMap.get(key).add(tts);
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}
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if (pointTime >= e - inter && (sumL > 0 || sumG > 0 || sumP > 0)) {
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timeList.add(stampToDate(pointTime));
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Set<Entry<String, ArrayList<TrafficTransStatistic>>> entrySet = listMap.entrySet();
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for (Entry<String, ArrayList<TrafficTransStatistic>> entry : entrySet) {
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String key = entry.getKey();
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String entranceId = key.substring(key.length() - 1);
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ArrayList<TrafficTransStatistic> value = entry.getValue();
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resultMap.put(key, getNewData(dateRangeList,strDateRangeList,value));
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}
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if (pointTime < e - inter) {
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timeList.add(stampToDate(pointTime));
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linkList.add(sumL);
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gbpsList.add(sumG);
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ppsList.add(sumP);
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}
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num = num + 1;
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pointTime = b + inter * num;
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return resultMap;
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}
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resulMap.put("linkNum", linkList);
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resulMap.put("gbps", gbpsList);
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resulMap.put("pps", ppsList);
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resulMap.put("statTime", timeList);
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}
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return null;
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}
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private Map getNewData(List<Date> dateRangeList,List<String> timeList, List<TrafficTransStatistic> bandwidthList) {
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Map<String,List> resulMap = new HashMap<String,List>();
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int index = 0;
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for (int i = 0; i < dateRangeList.size(); i++) {
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Date date = dateRangeList.get(i);
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Map<String, Long> countMap = new HashMap<String, Long>();
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Long linkNum = 0L;
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Long ppsNum = 0L;
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Long gbpsNum = 0L;
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for (int j = index; j < bandwidthList.size(); j++) {
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TrafficTransStatistic info = bandwidthList.get(j);
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if (info.getStatTime()!=null){
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if(info.getStatTime().compareTo(date)>=0&&(i+1<dateRangeList.size()&&info.getStatTime().compareTo(dateRangeList.get(i+1))<0)) {
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linkNum =info.getLinkNum() +linkNum;
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ppsNum = info.getPps()+ppsNum;
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gbpsNum = info.getGbps()+gbpsNum;
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}else{
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index = j;
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break;
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}
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}
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}
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countMap.put("linkNum", linkNum);
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countMap.put("pps", ppsNum);
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countMap.put("gbps", gbpsNum);
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Iterator iterator = countMap.keySet().iterator();
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while (iterator.hasNext()) {
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String key = iterator.next()+"";
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if (resulMap.containsKey(key)) {
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resulMap.get(key).add(countMap.get(key));
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}else {
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List<Long> list = new ArrayList<Long>();
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list.add(countMap.get(key));
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resulMap.put(key, list);
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}
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}
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}
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resulMap.put("statTime", timeList);
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return resulMap;
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}
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