I'm super new to time series database and I've just approached the use of InfluxDB with Python.
I'm trying to understand what's the best way to organize data.
The system I need to monitor is basically a cluster of sensors. The data acquisition will be in real-time but not 24/7. The user will be able to start/stop the acquisition and every acquisition must be grouped.
Having read the documentation and the examples with Python my idea of gerarchy organization is something like
- Measurement: My Cluster Sensor
-- Tag: My Acquisition #1
--- Field: My Sensor #1
--- Field: My Sensor #2
...... etc
A similar python code would be
point = (
Point("MyClusterSensor")
.tag("Acquisition", var_acquisitionNumber)
.field("Sensor1", var_sensor1,"Sensor2",var_sensor2)
)
write_api.write(bucket=MyBucket, org="[email protected]", record=point)
Does it make sense and it is in line with the idea of InfluxDB and how it should be used?
Is there a better way to store the data?
It turned out to be the right choice but field is used as
point = (
Point("MyClusterSensor")
.tag("Acquisition", var_acquisitionNumber)
.field("Sensor1", var_sensor1)
.field("Sensor2",var_sensor2)
)
write_api.write(bucket=MyBucket, org="[email protected]", record=point)