Help with cumulative sum please!

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@Marion_Akagi I simplified your query a little bit and it should be much more performant. You don’t need a join and I condensed the mulitple map() calls down to a single map() call. In that, I explicitly map only the columns you want returned so it drops everything else. It also duplicates the discharge_cycles columns as discharge_cycles_total. I then run cumulativeSum() on the discharge_cycles_total column:

from(bucket: "rdata")
    |> range(start: v.timeRangeStart, stop: v.timeRangeStop)
    |> filter(fn: (r) => r["_measurement"] == "site")
    |> filter(fn: (r) => r["point_name"] == "kW")
    |> aggregateWindow(every: 1d, fn: sum)
    |> map(
        fn: (r) => {
            dischargemwhs = if r._value > 0.0 then r._value / 3600000.0 else 0.0
            chargemwh = if r._value < 0.0 then r._value / (-3600000.0) else 0.0
            discharge_cycles = dischargemwhs / 15.0

            return {
                time: r._time,
                dischargemwhs: dischargemwhs,
                chargemwh: chargemwh,
                discharge_cycles: discharge_cycles,
                discharge_cycles_total: discharge_cycles,
            }
        },
    )
    |> cumulativeSum(columns: ["discharge_cycles_total"])

Let me know if this solves your problem.

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