databrickslabs · tombonfert · Aug 13, 2026 · Aug 6, 2026 · Aug 6, 2026 · Aug 7, 2026
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@@ -428,6 +407,11 @@
     "        \"container_id\", \"vehicle_key\",\n",
     "        \"start_ts\", \"stop_ts\",\n",
     "    ],\n",
+    "    \"calculated_channels\": {\n",
+    "        \"emit_channel_metrics\": True,\n",
+    "        \"attribute_columns\": [],\n",
+    "        \"kpis\": [\"duration\", \"min\", \"max\", \"mean\"],\n",
+    "    },\n",
     "}\n",
     "\n",
     "report = Report(\n",
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@@ -751,6 +723,36 @@
     "print(f\"{len(page.aggregations)} aggregations added\")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 0,
+   "metadata": {
+    "application/vnd.databricks.v1+cell": {
+     "cellMetadata": {
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+     "nuid": "41b9398e-6cc2-44e7-9320-0b47d55536a9",
+     "showTitle": true,
+     "tableResultSettingsMap": {},
+     "title": "Register Calculated Channel"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "from impulse_reporting.channels.calculated_channel import CalculatedChannel\n",
+    "\n",
+    "avg_temp_channel = CalculatedChannel(\n",
+    "    name=\"avg_temp\",\n",
+    "    expr=avg_temp,\n",
+    "    identity={\"channel_name\": \"avg_temp\", \"data_key\": \"CALC\"},\n",
+    "    desc=\"Average of ambient and intake air temperature\",\n",
+    ")\n",
+    "report.add_calculated_channel(avg_temp_channel)\n",
+    "print(\"Calculated channel 'avg_temp' registered\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
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      "title": "Visualize Gold Layer Results"
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@@ -1144,7 +1137,7 @@
      }
     },
     "schema": {
-     "currentValue": "default",
+     "currentValue": "thomas_bonfert",
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@@ -352,6 +352,40 @@ mode-resolution rules and what counts as a definition change.
 
 ---
 
+## calculated_channels (optional)
+
+Controls the optional `calculated_channel_metrics` output. By default a report
+writes calculated channels to `calculated_channel_fact` (the derived signal) and
+`calculated_channel_dimension` (the definitions). Setting `emit_channel_metrics`
+adds a third table, `calculated_channel_metrics`, shaped like the silver
+`channel_metrics` table so the fact + metrics pair can serve as an Impulse silver
+source. See the [Channels reference](../references/report/channel.md) for the
+output schema.
+
+| Field                 | Type        | Default                              | Description                                                                                       |
+|-----------------------|-------------|--------------------------------------|---------------------------------------------------------------------------------------------------|
+| `emit_channel_metrics`| `bool`      | `false`                              | Turns on the `calculated_channel_metrics` table.                                                  |
+| `attribute_columns`   | `list[str]` | `[]`                                 | Calculated-channel `attributes` keys to surface as columns on the metrics table (e.g. `["unit"]`). |
+| `kpis`                | `list[str]` | `["duration", "min", "max", "mean"]` | KPIs computed per `(container_id, channel_id)`, one column each. Must be registered KPI names.     |
+
+When enabled, each row of `calculated_channel_metrics` is one
+`(container_id, channel_id)` pair, carrying the selected `kpis` plus dynamic
+identity columns (the union of `identity` keys across the report's channels) and
+the configured `attribute_columns`. A channel that omits an identity or attribute
+key gets `null` for that column; an identity key wins over an attribute key of the
+same name.
+
+The available `kpis` are `duration`, `min`, `max`, and `mean` (all
+duration-weighted, matching the silver ingestion semantics). An unknown KPI name is
+rejected at config validation with a `ValueError` naming the valid KPIs.
+
+:::note Off by default
+When `emit_channel_metrics` is `false` (the default), no metrics table is written
+and `attribute_columns` / `kpis` have no effect.
+:::
+
+---
+
 ## measurement_dimensions (optional)
 
 List of `container_metrics` column names to surface into the gold-layer

@@ -186,6 +186,17 @@ calculated_channel_fact {
     timestamp _created_at
 }
 
+calculated_channel_metrics {
+    int container_id
+    long channel_id
+    string value_type
+    double duration
+    double min
+    double max
+    double mean
+    timestamp _created_at
+}
+
 histogram_fact }o--|| event_dimension: event_id
 histogram2d_fact }o--|| event_dimension: event_id
 stats_aggregator_fact }o--|| event_instance_fact: event_instance_id
@@ -221,7 +232,8 @@ guaranteed.
 | `{prefix}_histogram2d_fact`      | `container_id`, `visual_id`, `event_id`, `x_bin_id`, `y_bin_id`                        | 2D histogram bin values per container.                       |
 | `{prefix}_stats_aggregator_fact` | `container_id`, `visual_id`, `event_instance_id`, `channel_name`, `aggregation_label`  | Statistics values per signal, event instance, and container. |
 | `{prefix}_event_instance_fact`   | `container_id`, `event_id`, `event_instance_id`                                        | Materialized event occurrences with start/end timestamps.    |
-| `{prefix}_calculated_channel_fact` | `container_id`, `channel_id`, `tstart`                                               | Materialized derived signal — one row per sample interval, in the silver `channels` shape (`tstart`, `tend`, `value`). The channel's identity lives on `calculated_channel_dimension`, joined via `channel_id`. |
+| `{prefix}_calculated_channel_fact` | `container_id`, `channel_id`, `tstart`                                               | Materialized derived signal, one row per sample interval, in the silver `channels` shape (`tstart`, `tend`, `value`). The channel's identity lives on `calculated_channel_dimension`, joined via `channel_id`. |
+| `{prefix}_calculated_channel_metrics` | `container_id`, `channel_id`                                                       | Optional per-channel metrics in the silver `channel_metrics` shape, so the fact + metrics pair can serve as an Impulse silver source. Written only when [`config.calculated_channels.emit_channel_metrics`](../config/configuration.md#calculated_channels-optional) is set. Carries the configured `kpis` plus dynamic identity/attribute columns. See [Channels](../references/report/channel.md). |
 
 ---
 

@@ -62,6 +62,7 @@ The Gold layer uses a **star schema** with fact and dimension tables. All table
 | `histogram2d_fact`     | One row per (x, y) bin per container     | 2D histogram bin values, duration-weighted.               |
 | `stats_aggregator_fact` | One row per statistic label per signal per event instance | Descriptive statistics (built-in min/max/mean/median and any custom statistics). |
 | `calculated_channel_fact` | One row per sample interval per container | Materialized derived signal (a *channel*, not a summary), in the silver `channels` shape. |
+| `calculated_channel_metrics` | One row per calculated channel per container | Optional per-channel metrics in the silver `channel_metrics` shape. Written only when `config.calculated_channels.emit_channel_metrics` is set. |
 
 ### Dimension tables
 

@@ -20,4 +20,6 @@ Enumeration of supported statistic types for aggregations.
 - `MAX` (`str`): Maximum value statistic.
 - `MEAN` (`str`): Mean (average) value statistic.
 - `MEDIAN` (`str`): Median value statistic.
+- `START` (`str`): First value in the interval.
+- `END` (`str`): Last value in the interval.
 
@@ -190,14 +190,16 @@ Only includes computation-affecting attributes:
 - input_expressions
 - statistics to be calculated
 - event expression if there is any
-- custom statistics (name, kind, declared input indices, and function
-  bytecode, so implementation or input-wiring changes invalidate cached
-  results; only appended when custom statistics are configured so
-  aggregators without them keep their previous hash)
-
-Excludes: name, desc, signal_name, units, page_number, report_id, and the
-cross-channel descriptors' channel_name (presentation metadata, like
-channel_names).
+- channel_names, and each cross-channel descriptor's channel_name. These
+  are the fact table's ``channel_name`` merge key, so a rename must force
+  a recompute (a changed definition recomputes and prunes all containers);
+  otherwise, in incremental mode, already-processed containers would keep
+  rows under the old name.
+- custom statistics (labels, kind, declared input indices, params, and
+  function bytecode, so implementation or input-wiring changes invalidate
+  cached results; only appended when custom statistics are configured)
+
+Excludes: name, desc, units, page_number, report_id.
 
 **Returns**:
 

@@ -178,3 +178,50 @@ Create the dimension DataFrame for the given channels.
 which ``createDataFrame`` builds directly from the plain dict returned by
 
 
+#### determine\_channel\_metrics
+
+```python
+def determine_channel_metrics(
+        cls,
+        spark: SparkSession,
+        channels: list[CalculatedChannel],
+        fact_df: DataFrame | None,
+        *,
+        attribute_columns: list[str] | None = None,
+        kpis: list[str] | None = None) -> DataFrame | None
+```
+
+Derive a silver-shaped ``channel_metrics`` DataFrame from the fact rows.
+
+The calculated-channel fact table already matches the silver ``channels``
+table; this builds its companion ``channel_metrics`` so the pair can serve
+as an Impulse silver source.  Metrics are aggregated **directly from the
+narrow fact rows** (``container_id, channel_id, tstart, tend, value``),
+grouped by ``(container_id, channel_id)``.
+
+The output schema is **dynamic**: fixed columns ``container_id,
+channel_id, value_type`` plus one column per configured KPI (see ``kpis``),
+one per identity key (the union across all ``channels``), and one per
+configured attribute key.  Identity/attribute values are pulled from
+each channel's in-memory ``identity`` / ``attributes`` dicts (null where a
+channel omits a key).  On an identity/attribute key collision, identity wins
+and the attribute is skipped.
+
+**Arguments**:
+
+- `spark` (`SparkSession`): Session used to build the per-channel metadata frame.
+- `channels` (`list of CalculatedChannel`): The channels whose fact rows are in ``fact_df``; supply identity and
+attributes.
+- `fact_df` (`DataFrame or None`): Narrow fact DataFrame (output of :meth:`determine_calculated_channels`).
+``None`` returns ``None``.
+- `attribute_columns` (`list of str`): Attribute keys to surface as columns.  Default/empty → no attribute
+columns.  A key no channel defines yields an all-null column.
+- `kpis` (`list of str`): KPI names to compute (see ``calculated_channel_kpis.KPI_BUILDERS``); the
+output carries one column per name, in order.  ``None`` → the default
+KPIs (``duration, min, max, mean``).
+
+**Returns**:
+
+`DataFrame or None`: The dynamic-schema metrics DataFrame, or ``None`` when ``fact_df`` is
+``None``.
+