Each unique "TemperingMachine-" is a // unique instance. Modify the data to be written here // Specify the sensor instance sending the temperature. This is a huge benefit, and we’ll talk about this in greater Several Quality of Service (QoS) policies are applied per-instance. We will go into this in more detail when we talk about the Lifecycle to detect an event such as a flight landing or a chocolate lotįinishing. Instances allow you to model the behavior Requires less memory, and the instances do not need to be discovered the wayĭataWriters and DataReaders discover each other. Using instances to represent unique flights That’s over a thousand flights per day! The problem withĪ one- Topic-per-flight system is that it uses more memory than necessary,Īnd it takes more time for discovery. So why use instances at all?Ĭreating a new instance is lighter-weight than creating a new DataWriter/ DataReader/ Topic.įor example, if you’re representing airline flights, you could create a newĭataWriter, DataReader, and Topic each time a new flight takes off. You’re alreadyĭividing up your data into multiple Topics. Not every data model requires that you use instances. Table 4.1 Examples of Instances and Keys in Distributed Systems ![]() See other examples of keys, instances, and samples in the following table. Samples would be the updated locations of each flight “instance.” Traffic control system, the key fields might be the airline name and flight number. ![]() Long as they uniquely identify the object you are representing. ![]() A key can be composed of multiple fields in your data as Is a unique identifier of something within your data. A key in DDS is similar to a primary key in a database-it When you need to represent multiple objects within a DDS Topic, you use a Publish samples of data for several different objects, such as flights or sensors.Ĭonnext uses “instances” to represent these real-world objects. A DataWriter, for example, publishes samples
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