Hi I am using Grafana Cloud and InfluxDB cloud. I have some sensor data, an upon errors these sensors send a value of 99.99. I managed to map these values to show error using value mappings, as in this image:
Now this works okay, but the usual values in my panel are between 0 and 20, so having these outliers at 99.99 makes the non-error data difficult to view. One idea I got is to replace the values = 99.99 with a negative number like -0.1, so the graph looks much better.
However the only way in which I managed to achieve this is through the query itself. Using flux (the influxDB query language) I used the map function:
|> map(fn: (r) => ({ r with _value: if r._value > 99 then float(v: "-0.1") else r._value }))
This works fine for small datasets, but if I try to view the last 30 days performance is not great, loading a visualization takes a lot of time.
I am wondering if there’s a grafana transformation I could use to achieve the same thing? I tried testing transformations and googled but was unsuccessful. Also perhaps someone has better advice as to how to show errors without distorting the whole graph.
exclude errors from “values” timeseries and select only errors (>99.9 in your case) as another timeseries + use overrides to customize it for your needs (e. g. right axis, bars, red colors with 50% trasnparency,…)
I just use the influxdb library for Arduino with an ESP32. So there’s an instance of an InfluxDB point which I call sensor, and then every 5s or so the following code is called:
sensor.clearFields();
sensor.addField("Pressure NEG", DPT_E.NG);
// other fields such as pressure in other locations
published = (client.writePoint(sensor));
Not much design is into the bucket, I literally just adapted the Arduino client library example to my needs.
