Query to count values per day

I created a query that will count the number of occurrences of the Offset field in a range of four days aggregated day by day:

from(bucket: "my_bucket")
	|> range(start: -4d, stop: today())
	|> filter(fn: (r) => 
		r[\"_measurement\"] == "measurement1" 
		and r[\"SuitId\"] == "xxxyyyzzzvvv"
		and r._field == "Offset"
	|> group(columns: ["_start"])
	|> aggregateWindow(every: 1d, fn: count)
	|> sort(columns: ["_time"], desc: true)"

the result i get is something like this

_value=90010 _time=today   
_value=50 _time=yesterday    
_value=0 _time=the day before

Witch looks fabulous, except the days are not matching the data. In the table the 90010 corresponds to yesterday and 50 corresponds to the day before. I don’t understand what i’m doing wrong. Can someone point at where i’m wrong. many thanks.

@rucaza When you use aggregateWindow(), the aggregate function (count) actually drops the _time column because it isn’t part of the group key and it doesn’t know how to aggregate the time value. By default aggregateWindow() duplicates the _stop column as the new _time column to give each row a _time value for the window the row represents.

You can control which column aggregateWindow() duplicates as the output time with the timeSrc parameter. In your case, I’d suggest setting timeSrc: "_start":

// ...
    |> aggregateWindow(every: 1d, fn: count, timeSrc: "_start")
// ...