sample_query_input.json

{
  "query_json": {
    "from": "1755422054728",
    "to": "1756026854728",
    "queries": [
      {
        "refId": "A",
        "datasource": {
          "type": "influxdb",
          "uid": "cetae2ecaiwowa"
        },
        "datasourceId": 1,
        "intervalMs": 900000,
        "maxDataPoints": 790,
        "hide": false,
        "query": "base =\n  from(bucket: \"pms_bucket\")\n    |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n    |> filter(fn: (r) => r[\"_measurement\"] == \"2206600812\")\n    // treat 0 as \"no data\"\n    |> filter(fn: (r) => exists r._value and r._value != 0.0)\n    |> keep(columns: [\"_measurement\", \"_field\", \"_value\"])\n    |> group(columns: [\"_measurement\", \"_field\"])\n\nstats =\n  base\n    |> reduce(\n        fn: (r, accumulator) => ({\n          count: accumulator.count + 1.0,\n          sum:   accumulator.sum + r._value,\n          min:   if accumulator.count == 0.0 or r._value < accumulator.min then r._value else accumulator.min,\n          max:   if accumulator.count == 0.0 or r._value > accumulator.max then r._value else accumulator.max\n        }),\n        identity: {count: 0.0, sum: 0.0, min: 0.0, max: 0.0}\n    )\n    |> map(fn: (r) => ({\n        Metric:      r._field,\n        Min:         r.min,\n        Mean:        if r.count > 0.0 then r.sum / r.count else 0.0,\n        Max:         r.max,\n        Measurement: r._measurement\n    }))\n\n// --- Clean names (good for further calculations)\nstats\n  |> rename(columns: {Metric: \"KPI Name\", Measurement: \"Radio Serial Number\"})\n  |> keep(columns: [\"KPI Name\", \"Min\", \"Mean\", \"Max\", \"Radio Serial Number\"])\n  |> sort(columns: [\"KPI Name\"]) \n  |> yield(name: \"kpi_numeric\")\n\n// --- Pinned display (forces KPI Name left-most in a Table panel)\nstats\n  |> rename(columns: {Metric: \"KPI_Name\", Measurement: \"Radio_Serial_Number\"})\n  |> map(fn: (r) => ({\n      \"00_KPI Name\":            r.KPI_Name,\n      \"01_Min\":                 string(v: r.Min),\n      \"02_Mean\":                string(v: r.Mean),\n      \"03_Max\":                 string(v: r.Max),\n      \"04_Radio Serial Number\": r.Radio_Serial_Number\n  }))\n  |> yield(name: \"kpi_display_pinned\")"
      }
    ]
  },
  "range": {
    "from_date": "2025-08-17T09:14:14.728Z",
    "to_date": "2025-08-24T09:14:14.728Z"
  },
  "grafana_url": "http://192.168.9.112:3001"
}