579cd007c2
2:修改trafficTopicList和trafficTopicAndDomainChart接口的返回值 3:修改asn统计的返回值单位(兆) 4:修改ip范围查询使用end>=searchIp and start<=searchIp
1294 lines
44 KiB
Java
1294 lines
44 KiB
Java
package com.nis.web.service.restful;
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import com.beust.jcommander.internal.Maps;
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import com.nis.domain.restful.NtcEntranceReport;
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import com.nis.domain.restful.dashboard.*;
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import com.nis.util.DateUtils;
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import com.nis.util.StringUtils;
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import com.nis.web.dao.dashboard.*;
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import com.nis.web.service.BaseService;
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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.SimpleDateFormat;
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import java.util.*;
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import java.util.Map.Entry;
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@Service
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public class DashboardService extends BaseService {
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@Autowired
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public TrafficIpActiveStatisticDao trafficIpActiveStatisticDao;
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@Autowired
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public TrafficProtocolStatisticDao trafficProtocolStatisticDao;
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@Autowired
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public TrafficAppStatisticDao trafficAppStatisticDao;
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@Autowired
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public TrafficUaStatisticDao trafficUaStatisticDao;
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@Autowired
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public TrafficHttpStatisticDao trafficHttpStatisticDao;
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@Autowired
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public NtcTotalReportDao ntcTotalReportDao;
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@Autowired
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public TrafficPortActiveStatisticDao trafficPortActiveStatisticDao;
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/**
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* 流量统计 数据显示 info：先查询最近时间，根据时间条件查询数据 效率提高
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*/
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public List<Map> getTotalReportList() {
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List<Map> totalReportList = new ArrayList<Map>();
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List<Map> newData = new ArrayList<Map>();
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// 流量统计阻断丢弃回流等数据显示最近时间
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NtcTotalReport maxReportTime = ntcTotalReportDao.getMaxReportTime();
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if (maxReportTime != null && maxReportTime.getReportTime() != null) {
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Date reportTime = maxReportTime.getReportTime();
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totalReportList = ntcTotalReportDao.getTotalReportList(reportTime);// 返回阻断，监测等結果
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}
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Map maxRecvtTime = ntcTotalReportDao.getMaxStatTime();
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if (maxRecvtTime != null && maxRecvtTime.get("statTime") != null) {
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Date recvTime = (Date) maxRecvtTime.get("statTime");
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newData = ntcTotalReportDao.getNetFlowPortInfoNew(recvTime);
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}
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// 统计带宽的流入流出 单位 五分钟 的 byte
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if (StringUtil.isNotEmpty(newData)) {
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Double inoctets = Double.parseDouble(newData.get(0).get("inoctets").toString());
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Double outoctets = Double.parseDouble(newData.get(0).get("outoctets").toString());
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if (StringUtil.isEmpty(totalReportList)) {
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Map valueMap = Maps.newHashMap();
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valueMap.put("inoctets", inoctets);
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valueMap.put("outoctets", outoctets);
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totalReportList.add(valueMap);
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} else {
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totalReportList.get(0).put("inoctets", inoctets);
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totalReportList.get(0).put("outoctets", outoctets);
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}
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}
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return totalReportList;
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}
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/**
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* 根据ip46,协议tcp，udp查询带宽
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*
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* @param addrType
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* @param transType
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* @return
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*/
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/*
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* public List<HashMap> getBandwidthTrans(String addrType, Integer
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* transType,String beginDate,String endDate) { ArrayList<HashMap> listMap = new
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* ArrayList<HashMap>(); List<TrafficTransStatistic> bandwidthList = new
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* ArrayList<TrafficTransStatistic>(); Map maxStatTime =
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* ntcTotalReportDao.getMaxStatTime(); if (maxStatTime != null &&
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* maxStatTime.get("statTime") != null) { Date stat = (Date)
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* maxStatTime.get("statTime"); HashMap m = new HashMap(); bandwidthList =
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* ntcTotalReportDao.getBandwidthTrans(stat, addrType, transType); List timeList
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* = new ArrayList(); List linkList = new ArrayList(); List gbpsList = new
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* ArrayList(); List ppsList = new ArrayList(); if (bandwidthList != null &&
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* bandwidthList.size() > 0) { for (TrafficTransStatistic tt : bandwidthList) {
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* if (tt.getTime() != null) { timeList.add(tt.getTime()); if (tt.getLinkNum()
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* != null) { linkList.add(tt.getLinkNum()); } if (tt.getPps() != null) {
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* ppsList.add(tt.getPps()); } if (tt.getGbps() != null) {
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* gbpsList.add(tt.getGbps()); } } } } m.put("linkNum", linkList); m.put("gbps",
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* gbpsList); m.put("pps", ppsList); m.put("statTime", timeList);
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* listMap.add(m); } return listMap; }
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*/
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/**
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* 根据ip46,协议tcp，udp查询带宽
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*
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* @param addrType
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* @param transType
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* @return
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*/
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public List<HashMap> getBandwidthTrans(String addrType, Integer transType, String beginDate, String endDate) {
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ArrayList<HashMap> listMap = new ArrayList<HashMap>();
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HashMap m1 = getBandwidthTransEntrance(addrType, transType, beginDate, endDate, 1);
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if (m1 != null && m1.size() > 0) {
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m1.put("entranceId", 1);// 局点1.2 不同来源
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listMap.add(m1);
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}
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return listMap;
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}
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/**
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* 根据ip46,协议tcp，udp查询带宽
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*
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* @param addrType
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* @param transType
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* @return
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*/
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public List<HashMap> getBandwidthTrans2(String addrType, Integer transType, String beginDate, String endDate) {
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ArrayList<HashMap> listMap = new ArrayList<HashMap>();
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HashMap m2 = getBandwidthTransEntrance(addrType, transType, beginDate, endDate, 2);
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if (m2 != null && m2.size() > 0) {
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m2.put("entranceId", 2);
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listMap.add(m2);
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}
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return listMap;
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}
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/**
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* 查询单个局点流量的数据信息
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*
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* @param addrType
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* @param transType
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* @param beginDate
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* @param endDate
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* @param entranceId
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* @return
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*/
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public HashMap getBandwidthTransEntrance(String addrType, Integer transType, String beginDate, String endDate,
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Integer entranceId) {
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long start = System.currentTimeMillis();
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ArrayList<HashMap> listMap = new ArrayList<HashMap>();
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List<TrafficTransStatistic> bandwidthList = new ArrayList<TrafficTransStatistic>();
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HashMap resulMap = new HashMap();
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bandwidthList = ntcTotalReportDao.getBandwidthTrans(entranceId, beginDate, endDate, addrType, transType);
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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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Map rm = new HashMap();
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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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}
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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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}
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if (pointTime >= e - inter && sumP > 0) {
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ppsList.add(sumP);
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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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}
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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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}
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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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}
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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 resulMap;
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}
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/**
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* 将结果格式为时间间隔相同，数量补0数据
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*
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* @param begin
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* @param end
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* @param li
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* @return
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*/
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public static List<Map> formatDateData(String begin, String end, List<Map> li) {
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List<Map> resList = new ArrayList<Map>();
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Map<String, Comparable> m = new HashMap<String, Comparable>();
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int inter = 1000 * 60 * 60;// 间隔时间为一小时
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// 开始时间，结束时间 时间戳
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Long b = dateToStamp(begin);
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Long e = dateToStamp(end);
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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 sum = 0l;
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if (pointTime >= e) {
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break; // 停止
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}
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for (Map<?, ?> map : li) {
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// 实际时间
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String time = (String) map.get("time");
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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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sum = sum + (Long) map.get("count");
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}
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}
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rm.put("time", stampToDate(pointTime));
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rm.put("sum", sum);
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num = num + 1;
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pointTime = b + inter * num;
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resList.add(rm);
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}
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return resList;
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}
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/**
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* 日期格式字符串转换成时间戳
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*
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* @param date 字符串日期
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* @param format 如：yyyy-MM-dd HH:mm:ss
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* @return
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*/
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public static Long dateToStamp(String date_str) {
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try {
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SimpleDateFormat sdf = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
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return sdf.parse(date_str).getTime();
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} catch (Exception e) {
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e.printStackTrace();
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}
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return 0l;
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}
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/**
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* 时间戳 换成日期格式字符串转
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*
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* @param 时间 1544602212000
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* @param format 如：yyyy-MM-dd HH:mm:ss
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* @return
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*/
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public static String stampToDate(long timeStamp) {
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SimpleDateFormat sdf = new SimpleDateFormat("MM-dd HH:mm");// 这个是你要转成后的时间的格式
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String sd = sdf.format(new Date(timeStamp)); // 时间戳转换成时间
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return sd;
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}
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/**
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* 根据service 动作查询近五分钟变化趋势 entrance 默认为1,2
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*/
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public List<HashMap> getActionTrans(String begin, String end, String serviceType) {
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String sql = "";
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String sqlBlock = "((service>=16 and service<=40) or (service>=258 and service<=273) or (service=576))"; // 阻断
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String sqlMonitor = "((service>=128 and service<=152) or (service>=384 and service<=513) or (service=592) or (service>=848 and service<=1030) or (service=1152))"; // 监测
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// 区分动作
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if (StringUtils.isNotBlank(serviceType)) {
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if (serviceType.equalsIgnoreCase("block")) {
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sql = sqlBlock;
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}
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if (serviceType.equalsIgnoreCase("monitor")) {
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sql = sqlMonitor;
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}
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}
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ArrayList<HashMap> listMap = new ArrayList<HashMap>();
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List<NtcEntranceReport> entrance1 = new ArrayList<NtcEntranceReport>();
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List<NtcEntranceReport> entrance2 = new ArrayList<NtcEntranceReport>();
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HashMap m1 = new HashMap();
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HashMap m2 = new HashMap();
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entrance1 = ntcTotalReportDao.getActionTrans(begin, end, 1, sql);
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entrance2 = ntcTotalReportDao.getActionTrans(begin, end, 2, sql);
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List timeList = new ArrayList();
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List sumList1 = new ArrayList();
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List sumList2 = 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(begin);
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Long e = dateToStamp(end);
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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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Long sum2 = 0l;
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if (pointTime >= e) {
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break; // 停止
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}
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for (NtcEntranceReport e1 : entrance1) {
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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.getSum();
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}
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}
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for (NtcEntranceReport e2 : entrance2) {
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// 实际时间
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String time = e2.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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sum2 = sum2 + e2.getSum();
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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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}
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if (pointTime >= e - inter && sum2 > 0) {
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sumList2.add(sum2);
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}
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if (pointTime >= e - inter && (sum1 > 0 || sum2 > 0)) {
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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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sumList2.add(sum2);
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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("count", sumList1);
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m1.put("statTime", timeList);
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m1.put("entranceId", 1);
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m2.put("count", sumList2);// [{link1:[],time:[],entrance:"1"},]
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m2.put("statTime", timeList);
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m2.put("entranceId", 2);
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listMap.add(m1);
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listMap.add(m2);
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return listMap;
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}
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/**
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* 最近活跃端口时间五分钟数据
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*
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* @return List
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*/
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public List<Map> getPortActiveList() {
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List<Map> list = new ArrayList<Map>();
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TrafficPortActiveStatistic maxStatTime = trafficPortActiveStatisticDao.getMaxStatTime();
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if (maxStatTime != null && maxStatTime.getStatTime() != null) {
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Date statTime = maxStatTime.getStatTime();
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List<TrafficPortActiveStatistic> portActiveList = trafficPortActiveStatisticDao.getPortActiveList(statTime);
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// 上个时间五分钟数据
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if (portActiveList != null && portActiveList.size() > 0) {
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for (TrafficPortActiveStatistic port : portActiveList) {
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if (port.getPort() != null) {
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Map map = new HashMap();
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map.put("port", port.getPort());
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map.put("sum", port.getSum());
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TrafficPortActiveStatistic portActiveOld = trafficPortActiveStatisticDao
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.getPortActiveOld(port.getPort(), statTime);
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if (portActiveOld != null && portActiveOld.getSum() != null) {
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map.put("preSum", portActiveOld.getSum());
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} else {
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map.put("preSum", 0);
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}
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list.add(map);
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}
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}
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}
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}
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return list;
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}
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/**
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* 活跃IP最近五分钟数据TOP10
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*
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* @return
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*/
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/*
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* public List<HashMap> ipActiveFiveMinute(Date beginDate,Date endDate) {
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* TrafficIpActiveStatistic maxStatTime =
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* trafficIpActiveStatisticDao.getMaxStatTime(); ArrayList<HashMap> listMap =
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* new ArrayList<HashMap>(); if (maxStatTime != null &&
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* maxStatTime.getStatTime() != null) { Date statTime =
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* maxStatTime.getStatTime(); // 查询最近五分钟TOP10 ArrayList<LinkedHashMap>
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* ipListTop10 = trafficIpActiveStatisticDao.ipActiveChart(beginDate,endDate);
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* if (ipListTop10 != null && ipListTop10.size() > 0) { for (LinkedHashMap map :
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* ipListTop10) { HashMap m = new HashMap(); if (map.get("ipAddr") != null) {
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* String ipAddr = (String) map.get("ipAddr"); m.put("ipAddr", ipAddr); //
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* 根据五分钟TOP10IP，查询TOP10中每个IP最近一小时的变化 long beforeTime = beginDate.getTime(); long
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* afterTime = endDate.getTime(); Long inter=(afterTime - beforeTime) / (1000 *
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* 60 * 5); ArrayList<TrafficIpActiveStatistic> ipList =
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* trafficIpActiveStatisticDao.ipActiveFiveMinute(inter,ipAddr,
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* beginDate,endDate); List linkList = new ArrayList(); List timeList = new
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||
* ArrayList(); if (ipList != null && ipList.size() > 0) { for
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* (TrafficIpActiveStatistic ip : ipList) { if (ip.getLinkNum() != null &&
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||
* ip.getTime() != null) { linkList.add(ip.getLinkNum());
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||
* timeList.add(ip.getTime()); } } } m.put("linkNum", linkList);
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* m.put("statTime", timeList); listMap.add(m); } } } }
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*
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* return listMap; }
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*/
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/**
|
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* 获取活跃IPtop10 的趋势图
|
||
*/
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public List<HashMap> ipActiveFiveMinute(Date beginDate, Date endDate) {
|
||
ArrayList<HashMap> listMap = new ArrayList<HashMap>();
|
||
ArrayList<LinkedHashMap> ipListTop10 = trafficIpActiveStatisticDao.ipActiveChart(beginDate, endDate);
|
||
if (ipListTop10 != null && ipListTop10.size() > 0) {
|
||
for (LinkedHashMap map : ipListTop10) {
|
||
HashMap m1 = new HashMap();
|
||
String ipAddr = (String) map.get("ipAddr");
|
||
m1.put("ipAddr", ipAddr);
|
||
ArrayList<TrafficIpActiveStatistic> ipList = trafficIpActiveStatisticDao.ipActiveFiveMinute(ipAddr,
|
||
beginDate, endDate);
|
||
List timeList = new ArrayList();
|
||
List sumList1 = new ArrayList();
|
||
|
||
Map<String, Comparable> m = new HashMap<String, Comparable>();
|
||
int inter = 1000 * 60 * 5;// 间隔时间为五分钟
|
||
// 开始时间，结束时间 时间戳
|
||
Long b = dateToStamp(DateUtils.formatDateTime(beginDate));
|
||
Long e = dateToStamp(DateUtils.formatDateTime(endDate));
|
||
int num = 0;
|
||
Long pointTime = b;
|
||
while (pointTime < e) {
|
||
Map rm = new HashMap();
|
||
Long sum1 = 0l;
|
||
if (pointTime >= e) {
|
||
break; // 停止
|
||
}
|
||
for (TrafficIpActiveStatistic e1 : ipList) {
|
||
// 实际时间
|
||
String time = e1.getTime();
|
||
Long t = dateToStamp(time);
|
||
if (t >= pointTime && t < pointTime + inter) {
|
||
// 范围之内分到此pointTime组
|
||
sum1 = sum1 + e1.getCount();
|
||
}
|
||
}
|
||
// 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
|
||
if (pointTime >= e - inter && sum1 > 0) {
|
||
sumList1.add(sum1);
|
||
timeList.add(stampToDate(pointTime));
|
||
}
|
||
if (pointTime < e - inter) {
|
||
sumList1.add(sum1);
|
||
timeList.add(stampToDate(pointTime));
|
||
}
|
||
num = num + 1;
|
||
pointTime = b + inter * num;
|
||
}
|
||
m1.put("linkNum", sumList1);
|
||
m1.put("statTime", timeList);
|
||
listMap.add(m1);
|
||
}
|
||
}
|
||
return listMap;
|
||
}
|
||
|
||
/**
|
||
* 根据活跃IP最近五分钟TOP10，查询近1小时最大值
|
||
*
|
||
* @return
|
||
*/
|
||
public List<HashMap> ipActiveOneHour(Date beginDate, Date endDate) {
|
||
TrafficIpActiveStatistic maxStatTime = trafficIpActiveStatisticDao.getMaxStatTime();
|
||
ArrayList<HashMap> listMap = new ArrayList<HashMap>();
|
||
if (maxStatTime != null && maxStatTime.getStatTime() != null) {
|
||
Date statTime = maxStatTime.getStatTime();
|
||
ArrayList<LinkedHashMap> list = trafficIpActiveStatisticDao.ipActiveChart(beginDate, endDate);
|
||
if (list != null && list.size() > 0) {
|
||
for (LinkedHashMap map : list) {
|
||
if (map.get("ipAddr") != null) {
|
||
String ipAddr = (String) map.get("ipAddr");
|
||
ArrayList<HashMap> iplList = trafficIpActiveStatisticDao.ipActiveOneHour(ipAddr, beginDate,
|
||
endDate);
|
||
listMap.add(iplList.get(0));
|
||
}
|
||
}
|
||
}
|
||
}
|
||
|
||
return listMap;
|
||
}
|
||
|
||
/**
|
||
* 活跃IP首页top10
|
||
*
|
||
* @param beginDate
|
||
* @param endDate
|
||
* @return
|
||
*/
|
||
@SuppressWarnings("rawtypes")
|
||
public List<LinkedHashMap> ipActiveChart(Date beginDate, Date endDate) {
|
||
// TrafficIpActiveStatistic maxStatTime = trafficIpActiveStatisticDao.getMaxStatTime();
|
||
ArrayList<LinkedHashMap> list = new ArrayList<>();
|
||
// if (maxStatTime != null && maxStatTime.getStatTime() != null) {
|
||
// Date statTime = maxStatTime.getStatTime();
|
||
list = trafficIpActiveStatisticDao.ipActiveChart(beginDate, endDate);
|
||
if (list != null && list.size() > 0) {
|
||
for (LinkedHashMap map : list) {
|
||
if (map.get("ipAddr") != null) {
|
||
Map m = new LinkedHashMap();
|
||
map.put("pktNum", 0);
|
||
map.put("byteLen", 0);
|
||
}
|
||
}
|
||
}
|
||
// }
|
||
return list;
|
||
}
|
||
|
||
/**
|
||
* 协议统计
|
||
*
|
||
* @return
|
||
*/
|
||
public List<Map> protocolChart() {
|
||
TrafficProtocolStatistic maxStatTime = trafficProtocolStatisticDao.getMaxStatTime();
|
||
List<Map> list = new ArrayList<Map>();
|
||
if (maxStatTime != null && maxStatTime.getStatTime() != null) {
|
||
Date statTime = maxStatTime.getStatTime();
|
||
list = trafficProtocolStatisticDao.protocolChart(statTime);
|
||
// 当不查询包，字节时 设为0
|
||
if (list != null && list.size() > 0) {
|
||
Map map = new HashMap();
|
||
map.put("pktNum", 0);
|
||
map.put("byteLen", 0);
|
||
}
|
||
}
|
||
return list;
|
||
}
|
||
|
||
/**
|
||
* 协议统计报表
|
||
*
|
||
* @return
|
||
*/
|
||
public List<Map> getProtocolList(String startTime, String endTime) {
|
||
TrafficProtocolStatistic maxStatTime = trafficProtocolStatisticDao.getMaxStatTime();
|
||
List<Map> list = new ArrayList<Map>();
|
||
if (maxStatTime != null && maxStatTime.getStatTime() != null) {
|
||
Date statTime = maxStatTime.getStatTime();
|
||
list = trafficProtocolStatisticDao.getProtocolList(statTime, startTime, endTime);
|
||
}
|
||
return list;
|
||
}
|
||
|
||
/**
|
||
* app应用top10 图
|
||
*
|
||
* @return
|
||
*/
|
||
public List<Map> appChart() {
|
||
List<Map> list = new ArrayList<Map>();
|
||
TrafficAppStatistic maxStatTime = trafficAppStatisticDao.getMaxStatTime();
|
||
if (maxStatTime != null && maxStatTime.getStatTime() != null) {
|
||
Date statTime = maxStatTime.getStatTime();
|
||
list = trafficAppStatisticDao.appChart(statTime);
|
||
// 当不查询包，字节时 设为0
|
||
if (list != null && list.size() > 0) {
|
||
Map map = new HashMap();
|
||
map.put("pktNum", 0);
|
||
map.put("byteLen", 0);
|
||
}
|
||
}
|
||
return list;
|
||
}
|
||
|
||
/**
|
||
* App统计报表
|
||
*
|
||
* @return
|
||
*/
|
||
public List<Map> getAppList(String startTime, String endTime, Integer appType) {
|
||
// TrafficAppStatistic maxStatTime = trafficAppStatisticDao.getMaxStatTime();
|
||
List<Map> list = new ArrayList<Map>();
|
||
// if (maxStatTime != null && maxStatTime.getStatTime() != null) {
|
||
// Date statTime = maxStatTime.getStatTime();
|
||
list = trafficAppStatisticDao.getAppList(startTime, endTime, appType);
|
||
// }
|
||
return list;
|
||
}
|
||
|
||
// 操作系统列表 排名TOP10
|
||
@SuppressWarnings({ "unchecked", "rawtypes" })
|
||
public List<Map> systemList() {
|
||
List<Map> result = new ArrayList<Map>();
|
||
TrafficUaStatistic maxStatTime = trafficUaStatisticDao.getMaxStatTime();
|
||
if (maxStatTime != null) {
|
||
Date statTime = maxStatTime.getStatTime();
|
||
List<TrafficUaStatistic> list = trafficUaStatisticDao.systemList(statTime);
|
||
Long preCount = 0l;
|
||
for (TrafficUaStatistic ua : list) {
|
||
Map map = new HashMap();
|
||
map.put("osType", ua.getOsType());
|
||
map.put("count", ua.getCount());
|
||
map.put("pktNum", 0);
|
||
map.put("byteLen", 0);
|
||
preCount = trafficUaStatisticDao.preSystemListCount(ua.getOsType(), statTime);// 上个时段的量 用于与现在对比
|
||
if (preCount != null) {
|
||
map.put("preCount", preCount);
|
||
} else {
|
||
map.put("preCount", 0);
|
||
}
|
||
result.add(map);
|
||
}
|
||
}
|
||
return result;
|
||
}
|
||
|
||
public List<Map> getBrowserBySystem(Integer osType) {
|
||
List<Map> list = new ArrayList<Map>();
|
||
TrafficUaStatistic maxStatTime = trafficUaStatisticDao.getMaxStatTime();
|
||
if (maxStatTime != null) {
|
||
Date statTime = maxStatTime.getStatTime();
|
||
list = trafficUaStatisticDao.getBrowserBySystem(osType, statTime);
|
||
List bsType = new ArrayList();
|
||
// 查新固定操系统下的除了TOP10以外的others
|
||
if (list != null && list.size() > 0) {
|
||
for (Map map : list) {
|
||
bsType.add(map.get("bsType"));
|
||
}
|
||
if (list.size() > 10) {
|
||
Map others = new HashMap();
|
||
others = trafficUaStatisticDao.systemOthers(bsType, osType, statTime);
|
||
if (others != null && others.size() > 0) {
|
||
others.put("bsType", "-1");
|
||
list.add(others);
|
||
}
|
||
}
|
||
}
|
||
}
|
||
return list;
|
||
}
|
||
|
||
public List<Map> browserList() {
|
||
List<Map> result = new ArrayList<Map>();
|
||
TrafficUaStatistic maxStatTime = trafficUaStatisticDao.getMaxStatTime();
|
||
if (maxStatTime != null) {
|
||
Date statTime = maxStatTime.getStatTime();
|
||
List<TrafficUaStatistic> list = trafficUaStatisticDao.browserList(statTime);
|
||
Long preCount = 0l;
|
||
if (list != null && list.size() > 0) {
|
||
for (TrafficUaStatistic ua : list) {
|
||
Map map = new HashMap();
|
||
map.put("bsType", ua.getBsType());
|
||
map.put("count", ua.getCount());
|
||
map.put("pktNum", 0);
|
||
map.put("byteLen", 0);
|
||
preCount = trafficUaStatisticDao.preBrowserListCount(ua.getBsType(), statTime);// 上个时段的量 用于与现在对比
|
||
if (preCount != null) {
|
||
map.put("preCount", preCount);
|
||
} else {
|
||
map.put("preCount", 0);
|
||
}
|
||
result.add(map);
|
||
}
|
||
}
|
||
}
|
||
return result;
|
||
}
|
||
|
||
public List<Map> getSystemBybrowser(Integer bsType) {
|
||
List<Map> list = new ArrayList<Map>();
|
||
TrafficUaStatistic maxStatTime = trafficUaStatisticDao.getMaxStatTime();
|
||
if (maxStatTime != null) {
|
||
Date statTime = maxStatTime.getStatTime();
|
||
list = trafficUaStatisticDao.getSystemBybrowser(bsType, statTime);
|
||
List osType = new ArrayList();
|
||
// 查询固定操系统下的除了TOP10以外的others
|
||
if (list != null && list.size() > 0) {
|
||
for (Map map : list) {
|
||
osType.add(map.get("osType"));
|
||
}
|
||
if (list.size() > 10) {
|
||
Map others = new HashMap();
|
||
others = trafficUaStatisticDao.browserOthers(osType, bsType, statTime);
|
||
if (others != null && others.size() > 0) {
|
||
others.put("osType", "-1");
|
||
list.add(others);
|
||
}
|
||
}
|
||
}
|
||
}
|
||
return list;
|
||
}
|
||
|
||
/**
|
||
*
|
||
* 网站子域名详情
|
||
*
|
||
* @param beginDate
|
||
* @param endDate
|
||
* @return
|
||
*/
|
||
public List<Map> getWebsiteDetailsById(Integer websiteServiceId, Date beginDate, Date endDate) {
|
||
List<Map> list = null;
|
||
if (beginDate != null && endDate != null) {
|
||
list = getDomainByWebsiteServiceId(websiteServiceId, beginDate, endDate, null);
|
||
} else {
|
||
Date startTime = getBeforeByHourTime(1);// 获取上一个小时
|
||
list = getDomainByWebsiteServiceId(websiteServiceId, startTime, new Date(), "top");
|
||
}
|
||
return list;
|
||
}
|
||
|
||
/**
|
||
* 根据网站服务查询子域名
|
||
*
|
||
* @param websiteServiceId
|
||
* @return list
|
||
*/
|
||
public List<Map> getDomainByWebsiteServiceId(Integer websiteServiceId, Date beginDate, Date endDate, String top) {
|
||
|
||
// Date statTime = getBeforeByHourTime(1);// 获取上一个小时
|
||
|
||
List idList = trafficHttpStatisticDao.getIdByWebSiteId(websiteServiceId);
|
||
|
||
List<Map> matchList = trafficHttpStatisticDao.getDomainByWebsiteServiceId(idList, beginDate, endDate);// 获取webid和count的对应关系,key是webid,val是count
|
||
// 获取webid和count的对应关系,key是webid,val是count
|
||
Set<Long> set = new HashSet<>();
|
||
Map<Long, List<Map>> countMap = new HashMap();// 存储count和map的对应关系,后面根据count过滤,获取top10的count
|
||
for (Map map : matchList) {
|
||
String countStr = String.valueOf(map.get("count"));
|
||
long count = Long.parseLong(countStr);
|
||
set.add(count);
|
||
if (countMap.containsKey(count)) {// 将每个count和对应的viewmap放到map中,count可能相同所以value是list
|
||
countMap.get(count).add(map);
|
||
} else {
|
||
List<Map> listMap = new ArrayList<>();
|
||
listMap.add(map);
|
||
countMap.put(count, listMap);
|
||
}
|
||
}
|
||
List<Map> top10Data = new ArrayList();
|
||
if (top != null) {
|
||
top10Data = getTop10Data(set, countMap, 1);
|
||
} else {
|
||
top10Data = getTop10Data(set, countMap, 2);
|
||
}
|
||
List<String> notTop10List = new ArrayList<>();// 获取不在top10中的webid,用来查询标记为orther
|
||
for (Map map : matchList) {
|
||
String webIdStr = String.valueOf(map.get("webId"));
|
||
boolean exist = false;
|
||
for (Map map1 : top10Data) {
|
||
String webIdStr1 = String.valueOf(map1.get("webId"));
|
||
if (webIdStr1 != null && webIdStr != null && webIdStr1.equals(webIdStr)) {
|
||
exist = true;
|
||
}
|
||
if (!exist) {
|
||
notTop10List.add(webIdStr);
|
||
}
|
||
}
|
||
}
|
||
|
||
// 查询固定网站下的域名除了TOP10以外的others域名
|
||
if (matchList != null && matchList.size() > 10) {
|
||
Map others = trafficHttpStatisticDao.websiteDomainOthers(notTop10List, beginDate, endDate);
|
||
if (others != null && others.size() > 0) {
|
||
others.put("webId", "-1");
|
||
top10Data.add(others);
|
||
}
|
||
}
|
||
return top10Data;
|
||
|
||
}
|
||
|
||
/**
|
||
*
|
||
* 网站详情
|
||
*
|
||
* @param beginDate
|
||
* @param endDate
|
||
* @return
|
||
*/
|
||
public List<Map> getWebsiteDetails(Date beginDate, Date endDate, Integer domain, Integer entranceId) {
|
||
List<Map> list = trafficHttpStatisticDao.getTrafficHttpDomain(beginDate, endDate, domain, entranceId);
|
||
return list;
|
||
}
|
||
|
||
/**
|
||
*
|
||
* 网站TOP10 默认一小时
|
||
*
|
||
* @param beginDate
|
||
* @param endDate
|
||
* @return
|
||
*/
|
||
public List<Map> getWebsiteTop10() {
|
||
Date startTime = getBeforeByHourTime(1);// 获取上一个小时
|
||
List<Map> list = getDomainByWebsiteList(startTime, new Date(), "top");
|
||
return list;
|
||
}
|
||
|
||
/**
|
||
* 获取网站列表
|
||
*
|
||
* @return
|
||
*/
|
||
@SuppressWarnings("unchecked")
|
||
public List<Map> getDomainByWebsiteList(Date beginDate, Date endDate, String top) {
|
||
Map<String, List<String>> websiteIdAndIdMap = new HashMap<>();// 存储websiteServiceId和id的对应关系,一个websiteServiceId有多个id
|
||
List<Map> websiteIdAndidList = trafficHttpStatisticDao.getDomainByWebsiteList(beginDate, endDate);// 获取website_service_id和id的对应关系,group
|
||
// by
|
||
// website_service_id,id
|
||
for (Map map : websiteIdAndidList) {
|
||
Object websiteServiceIdObj = map.get("websiteServiceId");
|
||
Object idObj = map.get("id");
|
||
if (websiteServiceIdObj != null && idObj != null) {
|
||
if (websiteIdAndIdMap.containsKey(String.valueOf(websiteServiceIdObj))) {
|
||
websiteIdAndIdMap.get(String.valueOf(websiteServiceIdObj)).add(String.valueOf(idObj));
|
||
} else {
|
||
List<String> list = new ArrayList<>();
|
||
list.add(String.valueOf(idObj));
|
||
websiteIdAndIdMap.put(String.valueOf(websiteServiceIdObj), list);
|
||
}
|
||
}
|
||
}
|
||
|
||
Set<Long> set = new HashSet<>();
|
||
Map<Long, List<Map>> countAndViewMap = new HashMap<>();// 存储count和map的对应关系,后面根据count过滤,获取top10的count
|
||
List<Map> webIdAndCountList = trafficHttpStatisticDao.getHttpStatisticNoLinkAndPkt(beginDate, endDate);// 获取最近一小时的webid和count的关系
|
||
List<Map> prevWebIdAndCountList = trafficHttpStatisticDao.getHttpStatisticNoLinkAndPkt(getBeforeByHourTime(2),
|
||
beginDate);// 获取最近一小时的webid和count的关系
|
||
for (String websiteServiceId : websiteIdAndIdMap.keySet()) {// 遍历上面获取的websiteServiceId和id的对应关系,拼接json
|
||
Map viewMap = new HashMap<>();
|
||
long count = 0l;// 记录当前websiteServiceId所有的count
|
||
long prevCount = 0l;// 记录当前websiteServiceId所有的count
|
||
List<String> idList = websiteIdAndIdMap.get(websiteServiceId);// 根据websiteServiceId获取对应的id
|
||
for (String id : idList) {
|
||
for (Map webIdAndCountMap : webIdAndCountList) {// 遍历webid和count
|
||
String webId = String.valueOf(webIdAndCountMap.get("webId"));
|
||
if (webId != null && webId.equals(id)) {// 如果webid和id相等则获取count数据并统计
|
||
String countStr = String.valueOf(webIdAndCountMap.get("byteCount"));
|
||
if (countStr != null) {
|
||
count += Long.parseLong(countStr);// 将count累加
|
||
}
|
||
}
|
||
}
|
||
for (Map webIdAndCountMap : prevWebIdAndCountList) {// 遍历webid和count
|
||
String webId = String.valueOf(webIdAndCountMap.get("webId"));
|
||
if (webId != null && webId.equals(id)) {// 如果webid和id相等则获取count数据并统计
|
||
String countStr = String.valueOf(webIdAndCountMap.get("byteCount"));
|
||
if (countStr != null) {
|
||
prevCount += Long.parseLong(countStr);// 将count累加
|
||
}
|
||
}
|
||
}
|
||
|
||
}
|
||
viewMap.put("websiteServiceId", websiteServiceId);
|
||
viewMap.put("count", count);
|
||
viewMap.put("pktNum", 0);
|
||
viewMap.put("byteLen", 0);
|
||
viewMap.put("preCount", prevCount);
|
||
|
||
if (countAndViewMap.containsKey(count)) {// 将每个count和对应的viewmap放到map中,count可能相同所以value是list
|
||
countAndViewMap.get(count).add(viewMap);
|
||
} else {
|
||
List<Map> listMap = new ArrayList<>();
|
||
listMap.add(viewMap);
|
||
countAndViewMap.put(count, listMap);
|
||
}
|
||
set.add(count);
|
||
}
|
||
List<Map> dataList = new ArrayList();
|
||
if (top != null) {
|
||
dataList = getTop10Data(set, countAndViewMap, 1);// 取top10
|
||
} else {
|
||
dataList = getTop10Data(set, countAndViewMap, 2);
|
||
}
|
||
return dataList;
|
||
}
|
||
|
||
/**
|
||
*
|
||
* 主题详情
|
||
*
|
||
* @param beginDate
|
||
* @param endDate
|
||
* @return
|
||
*/
|
||
public List<Map> getTopicDetails(Date beginDate, Date endDate) {
|
||
List<Map> topicAndDomainList = getTopicAndDomainList(beginDate, endDate, null);
|
||
return topicAndDomainList;
|
||
}
|
||
|
||
/**
|
||
*
|
||
* 主题TOP10 默认一小时
|
||
*
|
||
* @param beginDate
|
||
* @param endDate
|
||
* @return
|
||
*/
|
||
public List<Map> getTopicTop10() {
|
||
Date startTime = getBeforeByHourTime(1);// 获取上一个小时
|
||
List<Map> topicAndDomainList = getTopicAndDomainListNoLink(startTime, new Date(), "top");
|
||
return topicAndDomainList;
|
||
}
|
||
|
||
/**
|
||
* 主题网站分类，域名
|
||
*
|
||
**/
|
||
public List<Map> getTopicAndDomainListNoLink(Date beginDate, Date endDate, String top) {
|
||
|
||
Map<String, List<String>> topicIdAndIdMap = new HashMap<>();// 存储topicid和id的对应关系,一个topicid有多个id
|
||
List<Map> topicIdAndIdList = trafficHttpStatisticDao.getDomainByTopicList(beginDate, endDate);// 获取最近一个小时topicId和id的对应关系,group
|
||
for (Map map : topicIdAndIdList) {
|
||
Object topicIdObj = map.get("topicId");
|
||
Object idObj = map.get("id");
|
||
if (topicIdObj != null && idObj != null) {
|
||
if (topicIdAndIdMap.containsKey(String.valueOf(topicIdObj))) {
|
||
topicIdAndIdMap.get(String.valueOf(topicIdObj)).add(String.valueOf(idObj));
|
||
} else {
|
||
List<String> list = new ArrayList<>();
|
||
list.add(String.valueOf(idObj));
|
||
topicIdAndIdMap.put(String.valueOf(topicIdObj), list);
|
||
}
|
||
}
|
||
}
|
||
|
||
Set<Long> set = new HashSet<>();
|
||
Map<Long, List<Map>> countAndViewMap = new HashMap<>();// 存储count和map的对应关系,后面根据count过滤,获取top10的count
|
||
List<Map> webIdAndCountList = trafficHttpStatisticDao.getHttpStatisticNoLinkAndPkt(beginDate, endDate);// 获取最近一小时的webid和count的关系
|
||
for (String topicId : topicIdAndIdMap.keySet()) {// 遍历上面获取的topicid和id的对应关系,拼接json
|
||
Map viewMap = new HashMap<>();
|
||
|
||
List<Map> list = new ArrayList<>();
|
||
long count = 0l;// 记录当前topicid所有的count
|
||
// long linkNum = 0l;
|
||
// long packets = 0l;
|
||
List<String> idList = topicIdAndIdMap.get(topicId);// 根据topicid获取对应的id
|
||
for (String id : idList) {
|
||
for (Map webIdAndCountMap : webIdAndCountList) {// 遍历webid和count
|
||
String webId = String.valueOf(webIdAndCountMap.get("webId"));
|
||
if (webId != null && webId.equals(id)) {// 如果webid和id相等则获取count数据并统计
|
||
String countStr = String.valueOf(webIdAndCountMap.get("byteCount"));
|
||
// String linkNumStr = String.valueOf(webIdAndCountMap.get("linkNum"));
|
||
// String packetsStr = String.valueOf(webIdAndCountMap.get("pktCount"));
|
||
if (countStr != null) {
|
||
count += Long.parseLong(countStr);// 将count累加
|
||
}
|
||
// if (linkNumStr != null) {
|
||
// linkNum += Long.parseLong(linkNumStr);// 将count累加
|
||
// }
|
||
// if (packetsStr != null) {
|
||
// packets += Long.parseLong(packetsStr);// 将count累加
|
||
// }
|
||
// webIdAndCountMap.remove("linkNum");
|
||
// webIdAndCountMap.remove("pktCount");
|
||
list.add(webIdAndCountMap);
|
||
}
|
||
}
|
||
}
|
||
if (list.size() > 0) {
|
||
viewMap.put("count", count);
|
||
// viewMap.put("linkNum", linkNum);
|
||
// viewMap.put("packets", packets);
|
||
viewMap.put("domainData", list);
|
||
viewMap.put("topicId", topicId);
|
||
if (countAndViewMap.containsKey(count)) {// 将每个count和对应的viewmap放到map中,count可能相同所以value是list
|
||
countAndViewMap.get(count).add(viewMap);
|
||
} else {
|
||
List<Map> listMap = new ArrayList<>();
|
||
listMap.add(viewMap);
|
||
countAndViewMap.put(count, listMap);
|
||
}
|
||
set.add(count);
|
||
}
|
||
}
|
||
List<Map> dataList = new ArrayList();
|
||
if (top != null) {
|
||
dataList = getTop10Data(set, countAndViewMap, 1);
|
||
} else {
|
||
dataList = getTop10Data(set, countAndViewMap, 2);
|
||
}
|
||
return dataList;
|
||
}
|
||
|
||
|
||
|
||
|
||
|
||
|
||
public List<Map> getTopicAndDomainList(Date beginDate, Date endDate, String top) {
|
||
|
||
Map<String, List<String>> topicIdAndIdMap = new HashMap<>();// 存储topicid和id的对应关系,一个topicid有多个id
|
||
List<Map> topicIdAndIdList = trafficHttpStatisticDao.getDomainByTopicList(beginDate, endDate);// 获取最近一个小时topicId和id的对应关系,group
|
||
for (Map map : topicIdAndIdList) {
|
||
Object topicIdObj = map.get("topicId");
|
||
Object idObj = map.get("id");
|
||
if (topicIdObj != null && idObj != null) {
|
||
if (topicIdAndIdMap.containsKey(String.valueOf(topicIdObj))) {
|
||
topicIdAndIdMap.get(String.valueOf(topicIdObj)).add(String.valueOf(idObj));
|
||
} else {
|
||
List<String> list = new ArrayList<>();
|
||
list.add(String.valueOf(idObj));
|
||
topicIdAndIdMap.put(String.valueOf(topicIdObj), list);
|
||
}
|
||
}
|
||
}
|
||
|
||
Set<Long> set = new HashSet<>();
|
||
Map<Long, List<Map>> countAndViewMap = new HashMap<>();// 存储count和map的对应关系,后面根据count过滤,获取top10的count
|
||
List<Map> webIdAndCountList = trafficHttpStatisticDao.getTrafficHttpStatistic(beginDate, endDate);// 获取最近一小时的webid和count的关系
|
||
for (String topicId : topicIdAndIdMap.keySet()) {// 遍历上面获取的topicid和id的对应关系,拼接json
|
||
Map viewMap = new HashMap<>();
|
||
List<Map> list = new ArrayList<>();
|
||
long count = 0l;// 记录当前topicid所有的count
|
||
long linkNum = 0l;
|
||
long packets = 0l;
|
||
List<String> idList = topicIdAndIdMap.get(topicId);// 根据topicid获取对应的id
|
||
for (String id : idList) {
|
||
for (Map webIdAndCountMap : webIdAndCountList) {// 遍历webid和count
|
||
String webId = String.valueOf(webIdAndCountMap.get("webId"));
|
||
if (webId != null && webId.equals(id)) {// 如果webid和id相等则获取count数据并统计
|
||
String countStr = String.valueOf(webIdAndCountMap.get("byteCount"));
|
||
String linkNumStr = String.valueOf(webIdAndCountMap.get("linkNum"));
|
||
String packetsStr = String.valueOf(webIdAndCountMap.get("pktCount"));
|
||
if (countStr != null) {
|
||
count += Long.parseLong(countStr);// 将count累加
|
||
}
|
||
if (linkNumStr != null) {
|
||
linkNum += Long.parseLong(linkNumStr);// 将count累加
|
||
}
|
||
if (packetsStr != null) {
|
||
packets += Long.parseLong(packetsStr);// 将count累加
|
||
}
|
||
webIdAndCountMap.remove("linkNum");
|
||
webIdAndCountMap.remove("pktCount");
|
||
list.add(webIdAndCountMap);
|
||
}
|
||
}
|
||
}
|
||
if (list.size() > 0) {
|
||
viewMap.put("count", count);
|
||
viewMap.put("linkNum", linkNum);
|
||
viewMap.put("packets", packets);
|
||
viewMap.put("domainData", list);
|
||
viewMap.put("topicId", topicId);
|
||
if (countAndViewMap.containsKey(count)) {// 将每个count和对应的viewmap放到map中,count可能相同所以value是list
|
||
countAndViewMap.get(count).add(viewMap);
|
||
} else {
|
||
List<Map> listMap = new ArrayList<>();
|
||
listMap.add(viewMap);
|
||
countAndViewMap.put(count, listMap);
|
||
}
|
||
set.add(count);
|
||
}
|
||
}
|
||
List<Map> dataList = new ArrayList();
|
||
if (top != null) {
|
||
dataList = getTop10Data(set, countAndViewMap, 1);
|
||
} else {
|
||
dataList = getTop10Data(set, countAndViewMap, 2);
|
||
}
|
||
return dataList;
|
||
}
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
public String[] getFiledTypeByName(String fieldName) {
|
||
if (fieldName == null) {
|
||
return null;
|
||
}
|
||
String fieldType = null;
|
||
if ("addr_type".equals(fieldName)) {
|
||
fieldType = ntcTotalReportDao.getAddrType();
|
||
}
|
||
if ("trans_type".equals(fieldName)) {
|
||
fieldType = ntcTotalReportDao.getTransType();
|
||
}
|
||
if ("entrance_id".equals(fieldName)) {
|
||
fieldType = ntcTotalReportDao.getEntranceId();
|
||
}
|
||
return fieldType == null ? null : fieldType.split(",");
|
||
}
|
||
|
||
public Map<String, List<HashMap>> getBandwidthTransEntrance(String beginDate, String endDate) {
|
||
long start = System.currentTimeMillis();
|
||
Map<String, List<TrafficTransStatistic>> listMap = new HashMap<String, List<TrafficTransStatistic>>();
|
||
List<TrafficTransStatistic> bandwidthList = new ArrayList<TrafficTransStatistic>();
|
||
bandwidthList = ntcTotalReportDao.getBandwidthTrans2(beginDate, endDate);
|
||
String[] addrTypes = getFiledTypeByName("addr_type");
|
||
String[] transTypes = getFiledTypeByName("trans_type");
|
||
String[] entranceIds = getFiledTypeByName("entrance_id");
|
||
for (String entranceId : entranceIds) {
|
||
for (String addrType : addrTypes) {
|
||
listMap.put("ipv" + addrType + "Type" + entranceId, new ArrayList<TrafficTransStatistic>());
|
||
}
|
||
}
|
||
for (String entranceId : entranceIds) {
|
||
for (String transType : transTypes) {
|
||
listMap.put("trans" + transType + "Type" + entranceId, new ArrayList<TrafficTransStatistic>());
|
||
}
|
||
}
|
||
for (TrafficTransStatistic tts : bandwidthList) {
|
||
String addrType = tts.getAddrType();
|
||
Integer entranceId = tts.getEntranceId();
|
||
Integer transType = tts.getTransType();
|
||
String key1 = "ipv" + addrType + "Type" + entranceId;
|
||
String key2 = "trans" + transType + "Type" + entranceId;
|
||
listMap.get(key1).add(tts);
|
||
listMap.get(key2).add(tts);
|
||
}
|
||
Map<String, List<HashMap>> resultMap = new HashMap<String, List<HashMap>>();
|
||
Set<Entry<String, List<TrafficTransStatistic>>> entrySet = listMap.entrySet();
|
||
for (Entry<String, List<TrafficTransStatistic>> entry : entrySet) {
|
||
String key = entry.getKey();
|
||
String entranceId = key.substring(key.length() - 1);
|
||
List<TrafficTransStatistic> value = entry.getValue();
|
||
HashMap newData = getNewData(beginDate, endDate, value);
|
||
newData.put("entranceId", entranceId);
|
||
ArrayList<HashMap> resultList = new ArrayList<HashMap>();
|
||
resultList.add(newData);
|
||
resultMap.put(key, resultList);
|
||
}
|
||
return resultMap;
|
||
}
|
||
|
||
private HashMap getNewData(String beginDate, String endDate, List<TrafficTransStatistic> bandwidthList) {
|
||
HashMap resulMap = new HashMap();
|
||
List timeList = new ArrayList();
|
||
List linkList = new ArrayList();
|
||
List gbpsList = new ArrayList();
|
||
List ppsList = new ArrayList();
|
||
if (bandwidthList != null && bandwidthList.size() > 0) {
|
||
Map<String, Comparable> m = new HashMap<String, Comparable>();
|
||
int inter = 1000 * 60 * 5;// 间隔时间为五分钟
|
||
// 开始时间，结束时间 时间戳
|
||
Long b = dateToStamp(beginDate);
|
||
Long e = dateToStamp(endDate);
|
||
int num = 0;
|
||
Long pointTime = b;
|
||
while (pointTime < e) {
|
||
|
||
Long sumL = 0l;
|
||
Long sumP = 0l;
|
||
Long sumG = 0l;
|
||
if (pointTime >= e) {
|
||
break; // 停止
|
||
}
|
||
for (TrafficTransStatistic tt : bandwidthList) {
|
||
// 实际时间
|
||
String time = tt.getTime();
|
||
Long t = dateToStamp(time);
|
||
if (t >= pointTime && t < pointTime + inter) {
|
||
// 范围之内分到此pointTime组
|
||
sumL = sumL + tt.getLinkNum();
|
||
sumP = sumP + tt.getPps();
|
||
sumG = sumG + tt.getGbps();
|
||
}
|
||
}
|
||
// 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
|
||
if (pointTime >= e - inter && sumL > 0) {
|
||
linkList.add(sumL);
|
||
}
|
||
if (pointTime >= e - inter && sumP > 0) {
|
||
ppsList.add(sumP);
|
||
}
|
||
if (pointTime >= e - inter && sumG > 0) {
|
||
gbpsList.add(sumG);
|
||
}
|
||
if (pointTime >= e - inter && (sumL > 0 || sumG > 0 || sumP > 0)) {
|
||
timeList.add(stampToDate(pointTime));
|
||
}
|
||
if (pointTime < e - inter) {
|
||
timeList.add(stampToDate(pointTime));
|
||
linkList.add(sumL);
|
||
gbpsList.add(sumG);
|
||
ppsList.add(sumP);
|
||
}
|
||
|
||
num = num + 1;
|
||
pointTime = b + inter * num;
|
||
}
|
||
resulMap.put("linkNum", linkList);
|
||
resulMap.put("gbps", gbpsList);
|
||
resulMap.put("pps", ppsList);
|
||
resulMap.put("statTime", timeList);
|
||
}
|
||
return resulMap;
|
||
}
|
||
|
||
/**
|
||
*
|
||
* @param beginDate
|
||
* @param endDate
|
||
* @param domain
|
||
* @param entranceId
|
||
* @return
|
||
*/
|
||
public List<HashMap> getDomainTrans(String beginDate, String endDate, Integer domain, Integer entranceId) {
|
||
List<HashMap> listMap = new ArrayList<HashMap>();
|
||
HashMap resulMap = new HashMap();
|
||
List<TrafficHttpFocusStatistic> domainList = new ArrayList<TrafficHttpFocusStatistic>();
|
||
domainList = trafficHttpStatisticDao.getDomainTrans(entranceId, beginDate, endDate, domain);
|
||
List timeList = new ArrayList();
|
||
List countList = new ArrayList();
|
||
if (domainList != null && domainList.size() > 0) {
|
||
Map<String, Comparable> m = new HashMap<String, Comparable>();
|
||
int inter = 1000 * 60 * 30;// 间隔时间为30分钟
|
||
// 开始时间，结束时间 时间戳
|
||
Long b = dateToStamp(beginDate);
|
||
Long e = dateToStamp(endDate);
|
||
int num = 0;
|
||
Long pointTime = b;
|
||
while (pointTime < e) {
|
||
Map rm = new HashMap();
|
||
Long sumL = 0l;
|
||
if (pointTime >= e) {
|
||
break; // 停止
|
||
}
|
||
for (TrafficHttpFocusStatistic tt : domainList) {
|
||
// 实际时间
|
||
String time = tt.getTime();
|
||
Long t = dateToStamp(time);
|
||
if (t >= pointTime && t < pointTime + inter) {
|
||
// 范围之内分到此pointTime组
|
||
sumL = sumL + tt.getCount();
|
||
}
|
||
}
|
||
// 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
|
||
if (pointTime >= e - inter && sumL > 0) {
|
||
countList.add(sumL);
|
||
timeList.add(stampToDate(pointTime));
|
||
}
|
||
if (pointTime < e - inter) {
|
||
timeList.add(stampToDate(pointTime));
|
||
countList.add(sumL);
|
||
}
|
||
num = num + 1;
|
||
pointTime = b + inter * num;
|
||
}
|
||
resulMap.put("count", countList);
|
||
resulMap.put("statTime", timeList);
|
||
listMap.add(resulMap);
|
||
}
|
||
return listMap;
|
||
}
|
||
|
||
}
|