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ZHHT-IRN-BD-ANALYSIS
Commit c5b088a5 by 芮蒙
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ID:2023-01-03 MSG:行车情况提交最新代码,修改连接池大小

parent 8b3bc8dc
Showing with 190 additions and 199 deletions
realtime/hologram-streaming/src/main/java/com/zhht/irn/entity/dto/TravelInfo.java
......@@ -31,6 +31,7 @@ public class TravelInfo implements Comparable<TravelInfo> {
private Long arrivedTime ;//可选 到达时间，毫秒级别时间戳
private Double arrivedSpeed ;//可选 到达时速度，单位km/h
private String inCrossLineId ;//可选 进入路口时车道编号
private String flowDirection ;//流向
private Long inCrossTime ;//可选 进入路口时间，毫秒级别时间戳
private Double inSpeed ;//可选 进入时速度，单位km/h
private String outCrossLineId ;//可选 通过路口时车道编号
......
realtime/hologram-streaming/src/main/java/com/zhht/irn/functions/TravelCarInfoCoProcessFunction.java
......@@ -30,6 +30,7 @@ public class TravelCarInfoCoProcessFunction extends CoProcessFunction<TravelInfo
private static Logger logger = Logger.getLogger(TravelCarInfoCoProcessFunction.class);
//定义状态，用于存储旅行信息，当周期信号数据过来的时候，触发计算
//状态数据存储结构为 Map（路口id--》（Map（车道id-》（List（旅行信息））））） 一辆车只有一条旅行信息
// 这样就把每个路口的数据进行分流，同时，对每个路口的数据，也按照了不同的车道进行了分流，同一个路口，同一个车道的数据存在一个list中
......@@ -39,7 +40,7 @@ public class TravelCarInfoCoProcessFunction extends CoProcessFunction<TravelInfo
private MapState<Integer, CycleSignalData> alreadyHandleCycleSignalDataState; //已经处理过的周期数据，避免重复触发
private ListState<Long> cycleSectionState ;
private ListState<Long> cycleSectionState ; //周期数据切片 ，记录每个周期的开始时间，以便于进行对locations切分到不同周期，计算停车次数
private static Map<String, Map<String, String>> dim_cnt_cross_lane_position;
SimpleDateFormat sdf = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
......@@ -62,6 +63,7 @@ public class TravelCarInfoCoProcessFunction extends CoProcessFunction<TravelInfo
ListStateDescriptor cycleSectionStateDescriptor = new ListStateDescriptor("cycleSectionState", TypeInformation.of(Long.class));
//待计算的周期数据
StateTtlConfig stateTtlConfig4CycleData = StateTtlConfig
// 状态有效时间 3小时
.newBuilder(Time.hours(3))
......@@ -73,6 +75,7 @@ public class TravelCarInfoCoProcessFunction extends CoProcessFunction<TravelInfo
.cleanupFullSnapshot()
.build();
cycleSignalDataStateDescriptor.enableTimeToLive(stateTtlConfig4CycleData);
alreadyHandleCycleSignalDataStateDescriptor.enableTimeToLive(stateTtlConfig4CycleData);
travelInfoState = getRuntimeContext().getMapState(travelInfoStateDescriptor);
cycleSignalDataState = getRuntimeContext().getMapState(cycleSignalDataStateDescriptor);
......@@ -94,9 +97,13 @@ public class TravelCarInfoCoProcessFunction extends CoProcessFunction<TravelInfo
public void processElement1(TravelInfo value, CoProcessFunction<TravelInfo, CycleSignalData, List<TravelLineSinkInfo>>.Context ctx,
Collector<List<TravelLineSinkInfo>> out) throws Exception {
// System.out.println("路口id"+value.getCrossId() +"车辆id"+value.getCarId() + "进入路口时间："+sdf.format(value.getInCrossTime()));
logger.info("路口id"+value.getCrossId() +"车辆id"+value.getCarId() + "进入路口时间："+sdf.format(value.getInCrossTime()));
if(value.getInCrossTime() < 0 || value.getArrivedTime() < 0){
logger.info("路口id"+value.getCrossId() +"车辆id"+value.getCarId() + "进入路口时间："+sdf.format(value.getInCrossTime())+"数据存在异常-作废");
return ;
}
// System.out.println("路口id"+value.getCrossId() +"车辆id"+value.getCarId() + "进入路口时间："+sdf.format(value.getInCrossTime()));
logger.info("路口id"+value.getCrossId() +"车辆id"+value.getCarId() +
"进入路口时间："+sdf.format(value.getInCrossTime())+"到达时间"+sdf.format(value.getArrivedTime()));
String crossId = value.getCrossId();
Iterator<Map<String, List<TravelInfo>>> iterator = travelInfoState.values().iterator();
//如果状态为空，则进行初始化
......@@ -151,7 +158,7 @@ public class TravelCarInfoCoProcessFunction extends CoProcessFunction<TravelInfo
Collector<List<TravelLineSinkInfo>> out) {
try {
// System.out.println("路口id"+value.getCrossCode() +"周期id"+value.getCycleOrder() + "周期时间："+sdf.format(value.getBeginDateTime())+"~"+sdf.format(value.getEndDateTime()));
//System.out.println("路口id"+value.getCrossCode() +"周期id"+value.getCycleOrder() + "周期时间："+sdf.format(value.getBeginDateTime())+"~"+sdf.format(value.getEndDateTime()));
logger.info("路口id"+value.getCrossCode() +"周期id"+value.getCycleOrder() + "周期时间："+sdf.format(value.getBeginDateTime())+"~"+sdf.format(value.getEndDateTime()));
//判断当前周期是否执行过了,存在周期数据重复下发的情况，只触发一次计算
......@@ -159,10 +166,11 @@ public class TravelCarInfoCoProcessFunction extends CoProcessFunction<TravelInfo
logger.info("周期数据重复----当前路口id是" + value.getCrossCode() + "当前周期已经计算完成了" + value.getCycleOrder());
return;
}
//记录周期数据时间切片，以便划分locations
cycleSectionState.add(value.getBeginDateTime());
String crossCode = value.getCrossCode();
// System.out.println("当前路口是---->"+crossCode);
// System.out.println("当前路口是---->"+crossCode);
Integer cycleOrder = value.getCycleOrder();
//周期开始时间，周期结束时间
Long beginDateTime = value.getBeginDateTime();
......@@ -178,12 +186,17 @@ public class TravelCarInfoCoProcessFunction extends CoProcessFunction<TravelInfo
if (beforeCycleDataListMap != null) {
List<TravelLineSinkInfo> travelLineSinkInfos = handTwoStreamData(beforeCycleDataListMap, beforeCycle.getCycleOrder(),
crossCode, beforeCycle.getBeginDateTime(), beforeCycle.getEndDateTime());
out.collect(travelLineSinkInfos);
// 当前周期已经处理完成了，kafka中再次来了该周期的数据不需要再次触发计算了
alreadyHandleCycleSignalDataState.put(beforeCycle.getCycleOrder(), beforeCycle);
listToRemove.add(beforeCycle.getCycleOrder());
// TODO 只有当前周期有数据sink，才算计算完成，否则继续等待触发
if(travelLineSinkInfos.size()>0){
out.collect(travelLineSinkInfos);
// 当前周期已经处理完成了，kafka中再次来了该周期的数据不需要再次触发计算了
alreadyHandleCycleSignalDataState.put(beforeCycle.getCycleOrder(), beforeCycle);
listToRemove.add(beforeCycle.getCycleOrder());
}
}
}
// 清理待计算的周期数据，计算完成后进行移除
for (Integer i:listToRemove) {
cycleSignalDataState.remove(i);
}
......@@ -194,10 +207,13 @@ public class TravelCarInfoCoProcessFunction extends CoProcessFunction<TravelInfo
//如果，有旅行信息数据就计算，否则就不计算
if (thisCycleDataListMap!=null && !thisCycleDataListMap.values().isEmpty()) {
List<TravelLineSinkInfo> travelLineSinkInfos = handTwoStreamData(thisCycleDataListMap, cycleOrder, crossCode, beginDateTime, endDateTime);
out.collect(travelLineSinkInfos);
// 当前周期已经处理完成了，，kafka中再次来了该周期的数据不需要再次触发计算了
alreadyHandleCycleSignalDataState.put(cycleOrder, value);
cycleSignalDataState.remove(cycleOrder);
// TODO 只有当前周期有数据sink，才算计算完成，否则继续等待触发
if(travelLineSinkInfos.size()>0){
out.collect(travelLineSinkInfos);
// 当前周期已经处理完成了，，kafka中再次来了该周期的数据不需要再次触发计算了
alreadyHandleCycleSignalDataState.put(cycleOrder, value);
cycleSignalDataState.remove(cycleOrder);
}
} else {
cycleSignalDataState.put(cycleOrder, value);
}
......@@ -236,108 +252,108 @@ public class TravelCarInfoCoProcessFunction extends CoProcessFunction<TravelInfo
,Long beginDateTime ,Long endDateTime) throws Exception {
Set<String> laneIds = thisCycleDataListMap.keySet();
Set<String> laneIds = thisCycleDataListMap.keySet();
List<TravelLineSinkInfo> sinkList = new ArrayList<>();
List<TravelLineSinkInfo> sinkList = new ArrayList<>();
for (String laneId : laneIds) {
// 当前车道的所有的旅行信息 ，一辆车对应1条信息
List<TravelInfo> travelInfos = thisCycleDataListMap.get(laneId);
//需要将这个车道上的所有的车辆，按照进入路口的时间依次排序才能计算出车头时距
List<TravelInfo> orderedTravelInfoList = orderByInCrossTime(travelInfos);
List<TravelCarInfo> list = new ArrayList<>();
//这里的旅行信息的数据，一定是完成了从路口出现到丢失的整个过程的数据，一辆车只有一条数据
//根据周期数据及旅行信息，查询维表，将每一条旅行信息转换为行车情况明细数据(1对1转换)
for (int i = 0; i < orderedTravelInfoList.size(); i++) {
TravelInfo travel = orderedTravelInfoList.get(i);
Long beforeCarInCrossTime;
if (i != 0) {
beforeCarInCrossTime = travelInfos.get(i - 1).getInCrossTime();
} else {
beforeCarInCrossTime = 0L;
}
TravelCarInfo travelCarInfo = trunTravelAndCycleToTravelCarInfo(travel, cycleOrder, beforeCarInCrossTime,beginDateTime,endDateTime);
list.add(travelCarInfo);
for (String laneId : laneIds) {
// 当前车道的所有的旅行信息 ，一辆车对应1条信息
List<TravelInfo> travelInfos = thisCycleDataListMap.get(laneId);
//需要将这个车道上的所有的车辆，按照进入路口的时间依次排序才能计算出车头时距
List<TravelInfo> orderedTravelInfoList = orderByInCrossTime(travelInfos);
List<TravelCarInfo> list = new ArrayList<>();
//这里的旅行信息的数据，一定是完成了从路口出现到丢失的整个过程的数据，一辆车只有一条数据
//根据周期数据及旅行信息，查询维表，将每一条旅行信息转换为行车情况明细数据(1对1转换)
for (int i = 0; i < orderedTravelInfoList.size(); i++) {
TravelInfo travel = orderedTravelInfoList.get(i);
Long beforeCarInCrossTime;
if (i != 0) {
beforeCarInCrossTime = travelInfos.get(i - 1).getInCrossTime();
} else {
beforeCarInCrossTime = 0L;
}
TravelCarInfo travelCarInfo = trunTravelAndCycleToTravelCarInfo(travel, cycleOrder, beforeCarInCrossTime,beginDateTime,endDateTime);
list.add(travelCarInfo);
}
// list存的是一个周期内的当前车道 旅行信息数据 行车情况的明细数据
// 根据一个车道内一个周期的行车情况的明细数据，计算具体的指标值，这里按照流向进行预聚合统计
//对当前list中的数据按照流向进行拆分
// list存的是一个周期内的当前车道 旅行信息数据 行车情况的明细数据
// 根据一个车道内一个周期的行车情况的明细数据，计算具体的指标值，这里按照流向进行预聚合统计
//对当前list中的数据按照流向进行拆分
Map<String, List<TravelCarInfo>> map = new HashMap<>();
Map<String, List<TravelCarInfo>> map = new HashMap<>();
for (TravelCarInfo t : list) {
List<TravelCarInfo> lineList;
if (!map.containsKey(t.getFlowDirection())) {
lineList = new ArrayList<>();
} else {
lineList = map.get(t.getFlowDirection());
}
lineList.add(t);
map.put(t.getFlowDirection(), lineList);
for (TravelCarInfo t : list) {
List<TravelCarInfo> lineList;
if (!map.containsKey(t.getFlowDirection())) {
lineList = new ArrayList<>();
} else {
lineList = map.get(t.getFlowDirection());
}
lineList.add(t);
map.put(t.getFlowDirection(), lineList);
}
// 按照流向分组完成后，对每个流向的数据进行聚合统计操作，并记录数据，准备写入数据库
Set<String> flowDirections = map.keySet();
for (String flowDirection : flowDirections) {
//当前流向 所有的车辆行车情况信息
List<TravelCarInfo> next = map.get(flowDirection);
//在循环一个车道某个流向过程中需要计算的数据
//1、通过时间之和
//2、每辆车通过平均车速之和
//3、控制延误之和
//4、停车次数之和
//5、停车延误之和
//6、车头时距之和
//7、最后一辆车进入路口的时间（即inCrossTime最大值，记录此值是为了，后续有迟到数据，计算车头时距的时候用的）
Long sumPassTime = 0L;
double sumSpeed = 0.0;
Long sumControlDelay = 0L;
Integer sumStopTimes = 0;
Long sumStopDelay = 0L;
Long sumCarHeadTimeGap = 0L;
Long maxInCrossTime = 0L;
for (TravelCarInfo t : next) {
sumPassTime = sumPassTime + t.getPassTime();
sumSpeed = sumSpeed + t.getAverageSpeed();
sumControlDelay = sumControlDelay + t.getControlDelayTime();
sumStopTimes = sumStopTimes + t.getStopTimes();
sumStopDelay = sumStopDelay + t.getStopDelayTime();
sumCarHeadTimeGap = sumCarHeadTimeGap + t.getCarHeadTimeGap();
if (t.getInCrossTime() > maxInCrossTime) {
maxInCrossTime = t.getInCrossTime();
}
// 按照流向分组完成后，对每个流向的数据进行聚合统计操作，并记录数据，准备写入数据库
Set<String> flowDirections = map.keySet();
for (String flowDirection : flowDirections) {
//当前流向 所有的车辆行车情况信息
List<TravelCarInfo> next = map.get(flowDirection);
//在循环一个车道某个流向过程中需要计算的数据
//1、通过时间之和
//2、每辆车通过平均车速之和
//3、控制延误之和
//4、停车次数之和
//5、停车延误之和
//6、车头时距之和
//7、最后一辆车进入路口的时间（即inCrossTime最大值，记录此值是为了，后续有迟到数据，计算车头时距的时候用的）
Long sumPassTime = 0L;
double sumSpeed = 0.0;
Long sumControlDelay = 0L;
Integer sumStopTimes = 0;
Long sumStopDelay = 0L;
Long sumCarHeadTimeGap = 0L;
Long maxInCrossTime = 0L;
for (TravelCarInfo t : next) {
sumPassTime = sumPassTime + t.getPassTime();
sumSpeed = sumSpeed + t.getAverageSpeed();
sumControlDelay = sumControlDelay + t.getControlDelayTime();
sumStopTimes = sumStopTimes + t.getStopTimes();
sumStopDelay = sumStopDelay + t.getStopDelayTime();
sumCarHeadTimeGap = sumCarHeadTimeGap + t.getCarHeadTimeGap();
if (t.getInCrossTime() > maxInCrossTime) {
maxInCrossTime = t.getInCrossTime();
}
int size = next.size();
TravelLineSinkInfo travelLineSinkInfo = new TravelLineSinkInfo();
travelLineSinkInfo.setCross_id(crossCode);
travelLineSinkInfo.setCycle_id(cycleOrder);
travelLineSinkInfo.setDirection(next.get(0).getDirection());
travelLineSinkInfo.setFlow_direction(flowDirection);
travelLineSinkInfo.setLane_id(next.get(0).getInCrossLineId());
travelLineSinkInfo.setPass_numbers(next.size());
travelLineSinkInfo.setAverage_pass_time(sumPassTime/(size*1.000*1000));
travelLineSinkInfo.setAverage_pass_speed(sumSpeed / (size));
travelLineSinkInfo.setAverage_control_delay(-1.0);
travelLineSinkInfo.setAverage_stop_times(sumStopTimes/(size*1.000));
travelLineSinkInfo.setAverage_stop_delay(sumStopDelay/(size*1.000*1000));
travelLineSinkInfo.setAverage_car_head_time_gap(sumCarHeadTimeGap/(size*1.000*1000));
travelLineSinkInfo.setLast_car_inCross_time(maxInCrossTime);
travelLineSinkInfo.setCycle_begin_time(beginDateTime);
travelLineSinkInfo.setCycle_end_time(endDateTime);
sinkList.add(travelLineSinkInfo);
}
int size = next.size();
TravelLineSinkInfo travelLineSinkInfo = new TravelLineSinkInfo();
travelLineSinkInfo.setCross_id(crossCode);
travelLineSinkInfo.setCycle_id(cycleOrder);
travelLineSinkInfo.setDirection(next.get(0).getDirection());
travelLineSinkInfo.setFlow_direction(flowDirection);
travelLineSinkInfo.setLane_id(next.get(0).getInCrossLineId());
travelLineSinkInfo.setPass_numbers(next.size());
travelLineSinkInfo.setAverage_pass_time(sumPassTime/(size*1.000*1000));
travelLineSinkInfo.setAverage_pass_speed(sumSpeed / (size));
travelLineSinkInfo.setAverage_control_delay(-1.0);
travelLineSinkInfo.setAverage_stop_times(sumStopTimes/(size*1.000));
travelLineSinkInfo.setAverage_stop_delay(sumStopDelay/(size*1.000*1000));
travelLineSinkInfo.setAverage_car_head_time_gap(sumCarHeadTimeGap/(size*1.000*1000));
travelLineSinkInfo.setLast_car_inCross_time(maxInCrossTime);
travelLineSinkInfo.setCycle_begin_time(beginDateTime);
travelLineSinkInfo.setCycle_end_time(endDateTime);
sinkList.add(travelLineSinkInfo);
}
}
return sinkList ;
return sinkList ;
// sinkTravelLineSinkInfoToMysql(sinkList);
// sinkTravelLineSinkInfoToMysql(sinkList);
}
......@@ -361,14 +377,14 @@ public class TravelCarInfoCoProcessFunction extends CoProcessFunction<TravelInfo
List<TravelInfo> thisData = new ArrayList<>(); //属于当前周期的数据
for (TravelInfo t : allTravelInfos) {
//进入路口的时间属于这个周期
if (t.getInCrossTime() >= beginDateTime && t.getInCrossTime() <= endDateTime) {
if (t.getInCrossTime() >= beginDateTime && t.getInCrossTime() <= endDateTime && t.getLocations()!=null) {
//当前周期用到的数据
thisData.add(t);
//如果，进入路口时距小于周期开始时间，且已经超过30min，则清理这个数据
}
else if(t.getInCrossTime()<beginDateTime && beginDateTime - t.getInCrossTime() > 1000*60*60 ) {
logger.info("移除当前旅行信息-超过30分钟都没有触发计算"+t);
else if(t.getInCrossTime()<beginDateTime && beginDateTime - t.getInCrossTime() > 1000*60*60*3 ) {
logger.info("移除当前旅行信息-超过30分钟都没有触发计算"+"车辆id"+t.getCarId() + "进入路口时间："+sdf.format(t.getInCrossTime()));
}
else {
//当前周期没有用的的数据
......@@ -411,7 +427,7 @@ public class TravelCarInfoCoProcessFunction extends CoProcessFunction<TravelInfo
//1、计算进入时间
long arriveTime = travel.getInCrossTime() - travel.getArrivedTime();
long passTime = travel.getInCrossTime() - travel.getArrivedTime();
//2、获取方向
String direction = dim_cnt_cross_lane_position.get(travel.getCrossId()).get(travel.getInCrossLineId()+"direction");
......@@ -433,12 +449,13 @@ public class TravelCarInfoCoProcessFunction extends CoProcessFunction<TravelInfo
if (beforeCarInCrossTime == 0L) {
carHeadTimeGap = 0L;
} else {
carHeadTimeGap = travel.getInCrossTime() - beforeCarInCrossTime;
// 取绝对值，避免出现插队导致车头时距变成负数
carHeadTimeGap = Math.abs(travel.getInCrossTime() - beforeCarInCrossTime);
}
TravelCarInfo travelCarInfo = new TravelCarInfo(travel.getCrossId(), cycleOrder,
travel.getCarId()
, arriveTime,travel.getInCrossTime(), travel.getInCrossLineId(), direction, flow_direction,averageSpeed,
, passTime,travel.getInCrossTime(), travel.getInCrossLineId(), direction, flow_direction,averageSpeed,
controlDelayTime, stopTimes, stopDelayTime, carHeadTimeGap);
return travelCarInfo;
......@@ -493,18 +510,18 @@ public class TravelCarInfoCoProcessFunction extends CoProcessFunction<TravelInfo
Double sumSpeed = 0.0;
if(travelBeginTime!=null && travelEndTime!=null) {
int i =0 ;
for (Location location : locations) {
int i =0 ;
for (Location location : locations) {
if(location.getDtTranjectory()>=travelBeginTime && location.getDtTranjectory()<=travelEndTime) {
sumSpeed = location.getSpeed() + sumSpeed;
i++;
}
}
return sumSpeed / i;
//如果，没有旅行开始和结束时间，就算全部的
//如果，没有旅行开始和结束时间，就算全部的
} else {
for (Location location : locations) {
sumSpeed = location.getSpeed() + sumSpeed;
sumSpeed = location.getSpeed() + sumSpeed;
}
return sumSpeed / locations.size();
}
......@@ -532,6 +549,7 @@ public class TravelCarInfoCoProcessFunction extends CoProcessFunction<TravelInfo
list.add(l);
}
// 这个会对周期切片的数据进行更新操作，最多保留最近3个周期的时间片
if(list.size() > 3) {
beginTimes = list.subList(list.size() - 3, list.size());
cycleSectionState.update(beginTimes);
......@@ -617,32 +635,32 @@ public class TravelCarInfoCoProcessFunction extends CoProcessFunction<TravelInfo
}
for (int i=0;i<beginTimes.size();i++) {
List<Location> list = new ArrayList<>();
if(i==0){
for (Location location:locations) {
if (location.getDtTranjectory()<beginTimes.get(i)){
list.add(location);
}
for (int i=0;i<beginTimes.size();i++) {
List<Location> list = new ArrayList<>();
if(i==0){
for (Location location:locations) {
if (location.getDtTranjectory()<beginTimes.get(i)){
list.add(location);
}
map.put(beginTimes.get(i),list);
}
map.put(beginTimes.get(i),list);
// 最后一个周期的数据
} else if(i==(beginTimes.size()-1)){
for (Location location:locations) {
if (location.getDtTranjectory()>beginTimes.get(i)){
list.add(location);
}
// 最后一个周期的数据
} else if(i==(beginTimes.size()-1)){
for (Location location:locations) {
if (location.getDtTranjectory()>beginTimes.get(i)){
list.add(location);
}
map.put(beginTimes.get(i),list);
} else {
for (Location location:locations) {
if (location.getDtTranjectory()<beginTimes.get(i)&&location.getDtTranjectory()>beginTimes.get(i-1)){
list.add(location);
}
}
map.put(beginTimes.get(i),list);
} else {
for (Location location:locations) {
if (location.getDtTranjectory()<beginTimes.get(i)&&location.getDtTranjectory()>beginTimes.get(i-1)){
list.add(location);
}
map.put(beginTimes.get(i),list);
}
map.put(beginTimes.get(i),list);
}
}
return map ;
}
......@@ -666,7 +684,8 @@ public class TravelCarInfoCoProcessFunction extends CoProcessFunction<TravelInfo
Iterator<Location> iterator = set.iterator();
List<Location> speedList = new ArrayList<>();
while (iterator.hasNext()) {
speedList.add(iterator.next());
Location next = iterator.next();
speedList.add(next);
}
Long stopDelayTime = 0L;
Long stopStart = 0L;
......@@ -677,15 +696,16 @@ public class TravelCarInfoCoProcessFunction extends CoProcessFunction<TravelInfo
stopStart = speedList.get(i).getDtTranjectory();
//从第二帧开始，只有前一帧速度大于10，且这一帧数据小于10的才算一次停车，连续小于3的视为一次停车
} else {
//发生停车事件
if (speedList.get(i).getSpeed() < 3.0 && speedList.get(i - 1).getSpeed() >= 10.0) {
//发生停车事件 车速小于3.0视为停车
// if (speedList.get(i).getSpeed() < 3.0 && speedList.get(i - 1).getSpeed() >= 10.0) {
if (speedList.get(i).getSpeed() < 3.0 && speedList.get(i - 1).getSpeed() >= 3.0) {
stopStart = speedList.get(i).getDtTranjectory();
}
//开始正常行驶
else {
if (stopStart != 0L && speedList.get(i).getSpeed() >= 3.0) {
stopDelayTime = (speedList.get(i).getDtTranjectory() - stopStart) + stopDelayTime;
//开始正常行驶了，把这个停止起始时间置为0L
stopStart = 0L;
}
// 如果，是最后一帧数据并且是停止状态，且前面也是停止状态，则进行计算延迟时间
......@@ -713,6 +733,21 @@ public class TravelCarInfoCoProcessFunction extends CoProcessFunction<TravelInfo
String inDirection = dim_cnt_cross_lane_position.get(travel.getCrossId()).get(inLineId+"direction");
String outDirection = dim_cnt_cross_lane_position.get(travel.getCrossId()).get(outLineId+"direction");
if(inDirection==null || outDirection==null) {
String flowDirection = travel.getFlowDirection();
if(flowDirection==null){
return "未知";
} else {
String[] split = flowDirection.split("-");
inDirection=split[0];
outDirection=split[1];
}
}
if(inDirection!=null&&inDirection.equals(outDirection)){
return inDirection+"掉头";
} else {
......@@ -737,61 +772,6 @@ public class TravelCarInfoCoProcessFunction extends CoProcessFunction<TravelInfo
}
return "未知";
}
}
}
/**
* 将每个车道流向预聚合的数据存入mysql中去
* @param list
* @throws SQLException
*//*
private void sinkTravelLineSinkInfoToMysql(List<TravelLineSinkInfo> list) throws SQLException {
String sql = "INSERT INTO app_cross_line_travel_car_info" +
"(record_date,cross_id,statistic_time,cycle_begin_time,cycle_end_time, lane_id, cycle_order, direction," +
" flow_direction, pass_numbers," +
" last_car_inCross_time, average_pass_time, average_pass_speed, average_control_delay, " +
"average_stop_delay, average_stop_times, average_car_head_time_gap" +
")" +
"VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?,?,?,?,?) ";
PreparedStatement preparedStatement = connection.prepareStatement(sql);
//TODO 这里的时间使用数据携带的时间，使用最后进入路口车辆的时间，这样在补数据时，可以补充到对应的分区下
Date date = new Date();
SimpleDateFormat sdf = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
SimpleDateFormat sdf2 = new SimpleDateFormat("yyyy-MM-dd");
String statistic_time = sdf.format(date);
for (TravelLineSinkInfo t :list) {
// 使用事件数据的时间划分数据分区，这样可以进行补数操作
String record_date = sdf2.format(t.getLast_car_inCross_time());
preparedStatement.setString(1, record_date);
preparedStatement.setString(2, t.getCross_id());
preparedStatement.setString(3, statistic_time);
preparedStatement.setString(4, sdf.format(t.getCycle_begin_time()));
preparedStatement.setString(5, sdf.format(t.getCycle_end_time()));
preparedStatement.setString(6, t.getLane_id());
preparedStatement.setString(7, t.getCycle_id().toString());
preparedStatement.setString(8, t.getDirection());
preparedStatement.setString(9, t.getFlow_direction());
preparedStatement.setInt(10, t.getPass_numbers());
preparedStatement.setLong(11, t.getLast_car_inCross_time());
preparedStatement.setDouble(12, t.getAverage_pass_time());
preparedStatement.setDouble(13, t.getAverage_pass_speed());
preparedStatement.setDouble(14, t.getAverage_control_delay());
preparedStatement.setDouble(15, t.getAverage_stop_delay());
preparedStatement.setDouble(16, t.getAverage_stop_times());
preparedStatement.setDouble(17, t.getAverage_car_head_time_gap());
preparedStatement.addBatch();
}
preparedStatement.executeBatch();
}*/
}
realtime/hologram-streaming/src/main/java/com/zhht/irn/job/TravelSituationAnalysisJob.java
......@@ -14,6 +14,7 @@ import org.apache.flink.api.common.restartstrategy.RestartStrategies;
import org.apache.flink.api.common.serialization.SimpleStringSchema;
import org.apache.flink.api.common.time.Time;
import org.apache.flink.api.java.functions.KeySelector;
import org.apache.flink.runtime.state.filesystem.FsStateBackend;
import org.apache.flink.streaming.api.CheckpointingMode;
import org.apache.flink.streaming.api.datastream.ConnectedStreams;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
......@@ -52,8 +53,12 @@ public class TravelSituationAnalysisJob {
env.getCheckpointConfig().setCheckpointingMode(CheckpointingMode.EXACTLY_ONCE);
//设置重启策略
env.setRestartStrategy(RestartStrategies.fixedDelayRestart(10, Time.seconds(30)));
//这如果不指定使用FsStateBackend 则默认使用flink集群中的配置，rocksDB
env.setStateBackend(new FsStateBackend("file:///data/flink/state"));
//设置重启策略 这里不设置重启策略，由平台统一拉起任务
// env.setRestartStrategy(RestartStrategies.fixedDelayRestart(10, Time.seconds(30)));
env.setRestartStrategy(RestartStrategies.noRestart());
......
realtime/hologram-streaming/src/main/java/com/zhht/irn/sink/TravelLaneInfoSink.java
......@@ -49,6 +49,8 @@ public class TravelLaneInfoSink extends RichSinkFunction<List<TravelLineSinkInfo
public void invoke(List<TravelLineSinkInfo> value, Context context) throws Exception {
super.invoke(value, context);
//重新获取连接，避免超时的问题
connection = DruidConnectPoolUtils.getConnection();
String sql = "INSERT INTO app_cross_line_travel_car_info" +
"(record_date,cross_id,statistic_time,cycle_begin_time,cycle_end_time, lane_id, cycle_order, direction," +
" flow_direction, pass_numbers," +
......@@ -92,5 +94,8 @@ public class TravelLaneInfoSink extends RichSinkFunction<List<TravelLineSinkInfo
logger.info("写入数据成功。。。。。"+ints.length+"...");
connection.close();
}
}
realtime/hologram-streaming/src/main/java/com/zhht/irn/utils/DruidConnectPoolUtils.java
......@@ -31,8 +31,8 @@ public class DruidConnectPoolUtils {
dataSource.setUrl(dbHosts);
dataSource.setUsername(username);
dataSource.setPassword(password);
dataSource.setInitialSize(3); //初始连接数，默认0
dataSource.setMaxActive(10); //最大连接数，默认8
dataSource.setInitialSize(5); //初始连接数，默认0
dataSource.setMaxActive(30); //最大连接数，默认8
dataSource.setMinIdle(5); //最小闲置数
dataSource.setMaxWait(3000);//获取连接的最大等待时间，单位毫秒
dataSource.setTestWhileIdle(true); //指明连接是否被空闲连接回收器(如果有)进行检验.如果检测失败,则连接将被从池中去除
......@@ -47,8 +47,8 @@ public class DruidConnectPoolUtils {
dataSource.setUrl(dbHosts);
dataSource.setUsername(username);
dataSource.setPassword(password);
dataSource.setInitialSize(3); //初始连接数，默认0
dataSource.setMaxActive(10); //最大连接数，默认8
dataSource.setInitialSize(5); //初始连接数，默认0
dataSource.setMaxActive(30); //最大连接数，默认8
dataSource.setMinIdle(5); //最小闲置数
dataSource.setMaxWait(3000);//获取连接的最大等待时间，单位毫秒
dataSource.setTestWhileIdle(true); //指明连接是否被空闲连接回收器(如果有)进行检验.如果检测失败,则连接将被从池中去除
......
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