优化动作，网站流量详情接口算法，动作增加drop，loop
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zhanghongqing
@@ -286,10 +286,13 @@ public class DashboardService extends BaseService {
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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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/*
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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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String sqlDrop = "((service1040 and service<=1042) or (service=3) or (service=5) or (service=25) or (service=28) or (service=274))"; // 丢弃
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String sqlLoop = "((service=4) or (service>=832 and service<=834))"; // 回流
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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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@@ -298,6 +301,12 @@ public class DashboardService extends BaseService {
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if (serviceType.equalsIgnoreCase("monitor")) {
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sql = sqlMonitor;
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}
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if (serviceType.equalsIgnoreCase("drop")) {
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sql = sqlDrop;
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}
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if (serviceType.equalsIgnoreCase("loop")) {
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sql = sqlLoop;
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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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@@ -363,13 +372,107 @@ public class DashboardService extends BaseService {
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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("count", sumList2);//
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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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/**
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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> getActionTrans2(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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String sqlDrop = "((service1040 and service<=1042) or (service=3) or (service=5) or (service=25) or (service=28) or (service=274))"; // 丢弃
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String sqlLoop = "((service=4) or (service>=832 and service<=834))"; // 回流
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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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if (serviceType.equalsIgnoreCase("drop")) {
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sql = sqlDrop;
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}
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if (serviceType.equalsIgnoreCase("loop")) {
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sql = sqlLoop;
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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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Map<String, Comparable> m = new HashMap<String, Comparable>();
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Date beginDate = DateUtils.parseDate(begin);
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Date endDate = DateUtils.parseDate(end);
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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("MM-dd HH:mm");
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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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//存放每个时间点的总数
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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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List sumList1 =new ArrayList();
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List sumList2 =new ArrayList();
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for (int i = 0; i < dateRangeList.size(); i++) {
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//存放一个时间点中总数
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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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Long num1 = 0L;
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Long num2 = 0L;
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for (int j = index; j < entrance1.size(); j++) {
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NtcEntranceReport ipInfo = entrance1.get(j);
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if (ipInfo.getReportTime()!=null){
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if(ipInfo.getReportTime().compareTo(date)>=0&&(i+1<dateRangeList.size()&&ipInfo.getReportTime().compareTo(dateRangeList.get(i+1))<0)) {
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num1=num1+ipInfo.getSum();
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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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sumList1.add(num1);
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for (int j = index; j < entrance2.size(); j++) {
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NtcEntranceReport ipInfo = entrance2.get(j);
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if (ipInfo.getReportTime()!=null){
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if(ipInfo.getReportTime().compareTo(date)>=0&&(i+1<dateRangeList.size()&&ipInfo.getReportTime().compareTo(dateRangeList.get(i+1))<0)) {
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num2=num2+ipInfo.getSum();
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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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sumList2.add(num2);
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}
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//整合 count time
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m1.put("count", sumList1);
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m1.put("statTime", strDateRangeList);
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m1.put("entranceId", 1);
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m2.put("count", sumList2);//
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m2.put("statTime", strDateRangeList);
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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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@@ -1291,52 +1394,81 @@ public class DashboardService extends BaseService {
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* @param entranceId
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* @return
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*/
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public List<HashMap> getDomainTrans(String beginDate, String endDate, Integer domain, Integer entranceId) {
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List<HashMap> listMap = new ArrayList<HashMap>();
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HashMap resulMap = new HashMap();
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/*
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* public List<HashMap> getDomainTrans(String beginDate, String endDate,
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* Integer domain, Integer entranceId) { List<HashMap> listMap = new
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* ArrayList<HashMap>(); HashMap resulMap = new HashMap();
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* List<TrafficHttpFocusStatistic> domainList = new
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* ArrayList<TrafficHttpFocusStatistic>(); domainList =
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* trafficHttpStatisticDao.getDomainTrans(entranceId, beginDate, endDate,
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* domain); List timeList = new ArrayList(); List countList = new
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* ArrayList(); if (domainList != null && domainList.size() > 0) {
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* Map<String, Comparable> m = new HashMap<String, Comparable>(); int inter
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* = 1000 * 60 * 30;// 间隔时间为30分钟 // 开始时间，结束时间 时间戳 Long b =
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* dateToStamp(beginDate); Long e = dateToStamp(endDate); int num = 0; Long
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* pointTime = b; while (pointTime < e) { Map rm = new HashMap(); Long sumL
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* = 0l; if (pointTime >= e) { break; // 停止 } for (TrafficHttpFocusStatistic
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* tt : domainList) { // 实际时间 String time = tt.getTime(); Long t =
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* dateToStamp(time); if (t >= pointTime && t < pointTime + inter) { //
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* 范围之内分到此pointTime组 sumL = sumL + tt.getCount(); } } //
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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 if (pointTime >= e - inter && sumL > 0) {
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* countList.add(sumL); timeList.add(stampToDate(pointTime)); } if
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* (pointTime < e - inter) { timeList.add(stampToDate(pointTime));
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* countList.add(sumL); } num = num + 1; pointTime = b + inter * num; }
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* resulMap.put("count", countList); resulMap.put("statTime", timeList);
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* listMap.add(resulMap); } return listMap; }
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*/
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/**
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* 优化后的网站详情域名趋势查询
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* @param beginDate
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* @param endDate
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* @param domain
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* @param entranceId
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* @return
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*/
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public List<HashMap> getDomainTrans2(String begin, String end, Integer domain, Integer entranceId) {
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List<TrafficHttpFocusStatistic> domainList = new ArrayList<TrafficHttpFocusStatistic>();
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domainList = trafficHttpStatisticDao.getDomainTrans(entranceId, beginDate, endDate, domain);
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List timeList = new ArrayList();
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List countList = new ArrayList();
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if (domainList != null && domainList.size() > 0) {
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Map<String, Comparable> m = new HashMap<String, Comparable>();
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int inter = 1000 * 60 * 30;// 间隔时间为30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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if (pointTime >= e) {
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break; // 停止
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}
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for (TrafficHttpFocusStatistic tt : domainList) {
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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.getCount();
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domainList = trafficHttpStatisticDao.getDomainTrans(entranceId, begin, end, domain);
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Date beginDate = DateUtils.parseDate(begin);
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Date endDate = DateUtils.parseDate(end);
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List<HashMap> listMap = new ArrayList<HashMap>();
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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("MM-dd HH:mm");
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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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//存放每个时间点的总数
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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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List countList =new ArrayList();
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for (int i = 0; i < dateRangeList.size(); i++) {
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//存放一个时间点中总数
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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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Long num = 0L;
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for (int j = index; j < domainList.size(); j++) {
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TrafficHttpFocusStatistic ipInfo = domainList.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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num=num+ipInfo.getCount();
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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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// 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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countList.add(sumL);
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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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countList.add(sumL);
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}
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num = num + 1;
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pointTime = b + inter * num;
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countList.add(num);
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}
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resulMap.put("count", countList);
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resulMap.put("statTime", timeList);
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listMap.add(resulMap);
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}
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//整合 count time
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HashMap ipTrafficMap = new HashMap();
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ipTrafficMap.put("count", countList);
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ipTrafficMap.put("statTime", strDateRangeList);
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listMap.add(ipTrafficMap);
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return listMap;
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}
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