Your organization runs a solar thermal power system that uses sensors to monitor the system's health. Currently, each sensor is identified by its location. Instead, you want to identify each sensor using an ID to simplify future analytics on the data.
You collect the following data on sensor readings:
SensorLocation
LastReadingTime
Area A
7/9/2019 11:36:09
Area B
7/9/2019 16:43:42
Area C
7/9/2019 13:23:53
To add an ID column and assign ID values to each sensor, complete the following steps:
Step 1. Create a Python transformation.
Create a passive Python transformation.
Step 2. Pass data to the Python transformation.
Pass data from upstream transformations in the mapping to the Python transformation.
After you pass the data to the Python transformation, the Python transformation contains the following input ports:
SensorLocation
LastReadingTime
Step 3. Create output ports.
Use the Ports tab in the Python transformation to create the output port
SensorID_out
to represent the ID column.
Additionally, create the following output ports to pass incoming data to downstream transformations:
SensorLocation_out
LastReadingTime_out
Step 4. Set the ID value for each row.
On the On Input tab, set the ID value for each row that is processed and write the data to the output ports using the following code:
SensorID="".join(str(x) for x in map(ord, SensorLocation))
SensorID_out = SensorID
SensorLocation_out = SensorLocation
LastReadingTime_out = LastReadingTime
Step 5. Run the mapping.
If the output ports in the Python transformation are linked directly to a Write transformation, the target contains the following data after you run the mapping: