2022-12-13 切换使用旅行信息进行计算行车情况相关指标

realtime/hologram-streaming/src/main/java/com/zhht/irn/entity/dto/Location.java

@@ -2,6 +2,8 @@ package com.zhht.irn.entity.dto;
 
 import lombok.AllArgsConstructor;
 import lombok.Data;
+import lombok.Getter;
+import lombok.NoArgsConstructor;
 
 /**
  * 位置信息
@@ -11,6 +13,7 @@ import lombok.Data;
  **/
 @Data
 @AllArgsConstructor
+@NoArgsConstructor
 public class Location implements Comparable<Location>{
 
    private Double longitude  ;//可选 经度

realtime/hologram-streaming/src/main/java/com/zhht/irn/entity/dto/TravelInfo.java

@@ -11,7 +11,7 @@ import java.util.List;
  * @create 2022-11-14 13:33{
  **/
 @Data
-public class TravelInfo {
+public class TravelInfo implements Comparable<TravelInfo>  {
 
     private Integer id  ;//必填 ID
     private String crossId  ;//必填 路口ID
@@ -45,4 +45,9 @@ public class TravelInfo {
     private Double crossingTime  ;//可选 旅行时长，单位 秒 (s)（驶离时刻-到达时刻）
     private List<Location> locations  ;//必填 数组，参考 位置信息字段
     private String remark  ;//可选 备注
+
+    @Override
+    public int compareTo(TravelInfo o) {
+        return (int)(inCrossTime-o.getInCrossTime());
+    }
 }

realtime/hologram-streaming/src/main/java/com/zhht/irn/job/TravelSituationAnalysisJob.java

@@ -2,9 +2,12 @@ package com.zhht.irn.job;
 
 import com.zhht.irn.entity.dto.CycleSignalData;
 import com.zhht.irn.entity.dto.TravelEvent;
+import com.zhht.irn.entity.dto.TravelInfo;
+import com.zhht.irn.functions.TravelCarInfoCoProcessFunction;
 import com.zhht.irn.functions.TravelEventAndCycleCoProcessFunction;
 import com.zhht.irn.schema.CycleSignalKafkaSchema;
 import com.zhht.irn.schema.TravelEventKafkaSchema;
+import com.zhht.irn.schema.TravelInfoKafkaSchema;
 import org.apache.flink.api.common.restartstrategy.RestartStrategies;
 import org.apache.flink.api.common.time.Time;
 import org.apache.flink.api.java.functions.KeySelector;
@@ -14,8 +17,9 @@ import org.apache.flink.streaming.api.datastream.DataStreamSource;
 import org.apache.flink.streaming.api.environment.CheckpointConfig;
 import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
 import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer;
-import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumerBase;
 import org.apache.kafka.clients.consumer.ConsumerConfig;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
 
 import java.util.Properties;
 
@@ -26,7 +30,6 @@ import java.util.Properties;
  * @create 2022-11-14 11:43
  **/
 public class TravelSituationAnalysisJob {
-
     public static void main(String[] args)  {
 
         try {
@@ -46,7 +49,7 @@ public class TravelSituationAnalysisJob {
             env.getCheckpointConfig().setCheckpointingMode(CheckpointingMode.EXACTLY_ONCE);
 
             //设置重启策略
-            env.setRestartStrategy( RestartStrategies.fixedDelayRestart(5, Time.seconds(10)));
+            env.setRestartStrategy( RestartStrategies.fixedDelayRestart(1, Time.seconds(10)));
 
 /*
            关于flink checkpoint存储的设置统一在集群配置文件中设置
@@ -55,52 +58,57 @@ public class TravelSituationAnalysisJob {
 
 
             Properties kafkaProperties = new Properties();
-         kafkaProperties.setProperty("bootstrap.servers", "dn1.zhht:9092,dn2.zhht:9092,dn3.zhht:9092");
-         //  kafkaProperties.setProperty("bootstrap.servers", "172.25.1.251:9092,172.25.1.122:9092,172.25.1.67:9092");
-            kafkaProperties.setProperty("group.id", "travel_event");
+        // kafkaProperties.setProperty("bootstrap.servers", "dn3.zhht:9092");
+           kafkaProperties.setProperty("bootstrap.servers", "139.9.157.176:9092");
+          //  kafkaProperties.setProperty("group.id", "travel_event");
+            kafkaProperties.setProperty("group.id", "trips_info2");
             kafkaProperties.setProperty(ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG, "true");
             kafkaProperties.setProperty(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "latest");
 
 
             Properties kafkaProperties2 = new Properties();
-           kafkaProperties2.setProperty("bootstrap.servers", "dn1.zhht:9092,dn2.zhht:9092,dn3.zhht:9092");
-         //   kafkaProperties2.setProperty("bootstrap.servers", "172.25.1.251:9092,172.25.1.122:9092,172.25.1.67:9092");
-            kafkaProperties2.setProperty("group.id", "cycle_signal");
+       //   kafkaProperties2.setProperty("bootstrap.servers", "dn3.zhht:9092");
+           kafkaProperties2.setProperty("bootstrap.servers", "139.9.157.176:9092");
+            kafkaProperties2.setProperty("group.id", "cycle_signal2");
             kafkaProperties2.setProperty(ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG, "true");
             kafkaProperties2.setProperty(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "latest");
 
             //旅行事件    
-            FlinkKafkaConsumerBase<TravelEvent> travelEvent =
+/*            FlinkKafkaConsumer<TravelEvent> travelEvent =
                     new FlinkKafkaConsumer<TravelEvent>("trips_event_info",
                             new TravelEventKafkaSchema(),
                             kafkaProperties) {
                     };
-            DataStreamSource<TravelEvent> travelEventStream = env.addSource(travelEvent);
+            DataStreamSource<TravelEvent> travelEventStream = env.addSource(travelEvent).setParallelism(3);*/
+
+
+           // FlinkKafkaConsumer<TravelInfo> travelInfo = new FlinkKafkaConsumer<>("trips_info", new TravelInfoKafkaSchema(), kafkaProperties);
+            FlinkKafkaConsumer<TravelInfo> travelInfo = new FlinkKafkaConsumer<>("t_info2", new TravelInfoKafkaSchema(), kafkaProperties);
+            DataStreamSource<TravelInfo> travelInfoStream = env.addSource(travelInfo).setParallelism(3);
 
-           travelEventStream.print();
+            travelInfoStream.print();
 
             //周期信号
-            FlinkKafkaConsumer<CycleSignalData> cycleSignalData =
-                    new FlinkKafkaConsumer<>("signal_cycle_data",
-                            new CycleSignalKafkaSchema(),
-                            kafkaProperties2);
+           // FlinkKafkaConsumer<CycleSignalData> cycleSignalData = new FlinkKafkaConsumer<>("signal_cycle_data", new CycleSignalKafkaSchema(), kafkaProperties2);
+            FlinkKafkaConsumer<CycleSignalData> cycleSignalData = new FlinkKafkaConsumer<>("s_data2", new CycleSignalKafkaSchema(), kafkaProperties2);
+
             DataStreamSource<CycleSignalData> cycleSignalDataStream = env.addSource(cycleSignalData);
 
            cycleSignalDataStream.print();
 
-
             //2、使用connect，把2个流联合处理
-        ConnectedStreams<TravelEvent, CycleSignalData> connect = travelEventStream
+        ConnectedStreams<TravelInfo, CycleSignalData> connect = travelInfoStream
                 .connect(cycleSignalDataStream);
 
-        ConnectedStreams<TravelEvent, CycleSignalData> travelInfoCycleSignalDataConnectedStreams = connect.keyBy(
-                (KeySelector<TravelEvent, String>) travelInfo1 -> travelInfo1.getCrossId(),
+        ConnectedStreams<TravelInfo, CycleSignalData> travelInfoCycleSignalDataConnectedStreams = connect.keyBy(
+                (KeySelector<TravelInfo, String>) travelInfo1 -> travelInfo1.getCrossId(),
                 (KeySelector<CycleSignalData, String>) cycleSignalData1 -> cycleSignalData1.getCrossCode()
         );
 
-        travelInfoCycleSignalDataConnectedStreams.process(new TravelEventAndCycleCoProcessFunction());
+        travelInfoCycleSignalDataConnectedStreams.process(new TravelCarInfoCoProcessFunction()).setParallelism(3);
+
 
-        env.execute();
+        env.execute("TravelSituationAnalysisJob");
 
         } catch (Exception e){
             e.printStackTrace();