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fix(dashboardAPI): clean stat panels — dedup stray-tag series, value-only text, meter units

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Three display defects surfaced when rendering the live PS/pump/MGC dashboards:

1. Doubled values everywhere. EVOLV telemetry historically carried stray tags
   (tagcode="undefined"/uuid="null") that newer writes dropped, so InfluxDB holds
   two series per field and last() returned two of everything (e.g. Time Left,
   Runtime, Heights). Add |> group(columns:["_field"]) before last()/aggregateWindow
   in every template query so each field collapses to one value/line regardless of
   tag-set history.

2. fields:"/.*/" also rendered the _time column as a stat value. For single-field
   string panels (Direction, Flow Source, Mode, State, Prediction Quality) append
   |> keep(columns:["_value"]); for mixed string+numeric panels (valve/vgc/monster)
   drop _time/_start/_stop instead.

3. Level/Heights showed "0.12 min" — Grafana unit id "m" means minutes, not meters.
   Change to lengthm; normalize m³->m3, m³/h->m3/h on pumpingStation.

Verified live via headless screenshots: PS, pump, and measurement dashboards now
show single clean values with correct units.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
znetsixe
2026-05-27 21:42:47 +02:00
parent 8bfc67c610
commit c4f5b68c6a
11 changed files with 409 additions and 157 deletions
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12
config/machineGroup.json
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@@ -69,7 +69,7 @@
},
"targets": [
{
"query": "from(bucket: \"${bucket}\")\n |> range(start: -7d)\n |> filter(fn:(r) => r._measurement==\"${measurement}\" and r._field==\"mode\")\n |> last()",
"query": "from(bucket: \"${bucket}\")\n |> range(start: -7d)\n |> filter(fn:(r) => r._measurement==\"${measurement}\" and r._field==\"mode\")\n |> group(columns:[\"_field\"])\n |> last()\n |> keep(columns:[\"_value\"])",
"refId": "A"
}
],
@@ -118,7 +118,7 @@
},
"targets": [
{
"query": "from(bucket: \"${bucket}\")\n |> range(start: -7d)\n |> filter(fn:(r) => r._measurement==\"${measurement}\" and r._field==\"scaling\")\n |> last()",
"query": "from(bucket: \"${bucket}\")\n |> range(start: -7d)\n |> filter(fn:(r) => r._measurement==\"${measurement}\" and r._field==\"scaling\")\n |> group(columns:[\"_field\"])\n |> last()",
"refId": "A"
}
],
@@ -175,7 +175,7 @@
},
"targets": [
{
"query": "from(bucket: \"${bucket}\")\n |> range(start: -7d)\n |> filter(fn:(r) => r._measurement==\"${measurement}\" and r._field==\"absDistFromPeak\")\n |> last()",
"query": "from(bucket: \"${bucket}\")\n |> range(start: -7d)\n |> filter(fn:(r) => r._measurement==\"${measurement}\" and r._field==\"absDistFromPeak\")\n |> group(columns:[\"_field\"])\n |> last()",
"refId": "A"
}
],
@@ -233,7 +233,7 @@
},
"targets": [
{
"query": "from(bucket: \"${bucket}\")\n |> range(start: -7d)\n |> filter(fn:(r) => r._measurement==\"${measurement}\" and r._field==\"relDistFromPeak\")\n |> last()",
"query": "from(bucket: \"${bucket}\")\n |> range(start: -7d)\n |> filter(fn:(r) => r._measurement==\"${measurement}\" and r._field==\"relDistFromPeak\")\n |> group(columns:[\"_field\"])\n |> last()",
"refId": "A"
}
],
@@ -340,7 +340,7 @@
},
"targets": [
{
"query": "from(bucket: \"${bucket}\")\n |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n |> filter(fn:(r) => r._measurement==\"${measurement}\" and r._field =~ /predicted_flow|flow/)\n |> aggregateWindow(every: v.windowPeriod, fn: mean, createEmpty: false)",
"query": "from(bucket: \"${bucket}\")\n |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n |> filter(fn:(r) => r._measurement==\"${measurement}\" and r._field =~ /predicted_flow|flow/)\n |> group(columns:[\"_field\"])\n |> aggregateWindow(every: v.windowPeriod, fn: mean, createEmpty: false)",
"refId": "A"
}
],
@@ -437,7 +437,7 @@
},
"targets": [
{
"query": "from(bucket: \"${bucket}\")\n |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n |> filter(fn:(r) => r._measurement==\"${measurement}\" and r._field =~ /predicted_power|power/)\n |> aggregateWindow(every: v.windowPeriod, fn: mean, createEmpty: false)",
"query": "from(bucket: \"${bucket}\")\n |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n |> filter(fn:(r) => r._measurement==\"${measurement}\" and r._field =~ /predicted_power|power/)\n |> group(columns:[\"_field\"])\n |> aggregateWindow(every: v.windowPeriod, fn: mean, createEmpty: false)",
"refId": "A"
}
],