anchor.diff:  <6> Within each group, all the measurements of that station are aggregated, by keeping track of minimum and maxium values and calculating the average value of all measurements of that station (see the `Aggregation` type)
   <7> The results of the pipeline are written out to the `temperatures-aggregated` topic
   <8> The Quarkus `StartupEvent` and `ShutdownEvent` lifecycle events are used for starting and stopping the pipeline; as it may only be started once the topics exist, the Kafka admin client is used to check for their existence continuously, until they have been set up
  -
  -Lastly, create the Quarkus configuration file `aggregator/src/main/resources/application.properties` with the following contents:
  -
  -[source]
  -----
  -org.acme.quarkus.sample.kafkastreams.bootstrap.servers=localhost:9092
  -----
   
   == Building and Running the Applications
   
  
positive.code: 
      private static final Logger LOG = LoggerFactory.getLogger(KafkaStreamsPipeline.class);
  
      @ConfigProperty(name="org.acme.quarkus.sample.kafkastreams.bootstrap.servers", defaultValue="localhost:9092")
      String bootstrapServers;
  
      @ConfigProperty(name="HOSTNAME")                            // <1>
  
negative.code:     public int count;
      public double avg;
  
      private WeatherStationData(int stationId, String stationName, double min, double max,
              int count, double avg) {
          this.stationId = stationId;
          this.stationName = stationName;
          this.min = min;
  