Merge branch 'carry-every-date-through-an-adjustment'

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>

CLAUDE.md

@@ -408,6 +408,18 @@ Turning a region back into slices re-derives, per cell, the same filters Perspec
 
 All three operations follow the same structure: insert a `pf.log` row in a CTE, then insert forecast rows referencing its id. `{{where_clause}}` is built from the slice; `{{exclude_clause}}` blocks `exclude_iters` rows.
 
+**Every date column travels, not just the first.** `dataCols` is
+`[...dims, ...dateCols, value, units]`. It used to be `dateCols[0]`, so on a
+source with order, requested and ship dates, scale and recode wrote rows whose
+`rdate` and `sdate_e` were **null** — and because the derived period dimensions
+(`rseas`, `smon_e`) are dimensions and were copied with the rest, the labels
+read correctly while the dates under them were gone. Both columns are
+`role = 'date'` and therefore sliceable, so an adjustment scoped to a ship date
+matched no adjustment row that had ever been written. Clone and the loads were
+always right. The wider GROUP BY costs almost nothing on `osm_skinny`
+(971,185 → 971,352 groups) because `ordnum`/`ordline` already make a row
+near-unique.
+
 - **Scale** — distributes `value_incr`/`units_incr` proportionally across rows in the slice using window functions
 - **Recode** — inserts negative rows (zero out original) + positive rows with `{{set_clause}}` dimension overrides; both share the same logid
 - **Clone** — copies the slice with `{{set_clause}}` overrides and `{{scale_factor}}` multiplier; original untouched
@@ -539,6 +551,13 @@ column.
 
 ## Known issues / active work
 
+- **Rows written before 2026-09-21 have null `rdate`/`sdate_e`.** The generator
+  fix above changes what gets written from here on; it does not repair what is
+  there. On `fc_osm_skinny_29` that is ~270k scale and recode rows. A backfill
+  would have to re-derive each from the baseline rows at the same coordinate,
+  which is possible but is inference, not recovery — deleting and replaying
+  those log entries is the honest repair
+
 - **Zero-row operations report success.** Scale refuses with "Nothing to
   scale…" when its slice matches nothing; recode and clone commit an empty log
   entry and return `rows_affected: 0`. A recode of a rep whose rows are all

lib/sql_generator.js

@@ -198,19 +198,31 @@ function generateSQL(source, colMeta) {
 
     const valueCol = valueCols[0];
     const unitsCol = unitsCols[0];
-    const dateCol  = dateCols[0];
 
     if (!valueCol) throw new Error('No value column defined in col_meta');
-    if (!dateCol)  throw new Error('No date column defined in col_meta');
+    if (!dateCols.length) throw new Error('No date column defined in col_meta');
     if (dims.length === 0) throw new Error('No dimension columns defined in col_meta');
 
     const srcTable        = `"${source.schema}"."${source.tname}"`;
-    const dataCols        = [...dims, dateCol, valueCol, unitsCol].filter(Boolean);
+    // Every date column, not just the primary one. Scale and recode used to
+    // carry dateCols[0] alone, so a source with order, requested and ship dates
+    // wrote adjustment rows whose rdate and sdate_e were *null* -- not stale,
+    // absent. Those columns are role 'date' and therefore sliceable, so a later
+    // adjustment scoped to a ship date matched no adjustment row ever written,
+    // and any reader that dated the forecast by ship date lost every
+    // adjustment silently. The derived period dimensions (rseas, smon_e) were
+    // fine throughout, being dimensions and copied with the rest -- which is
+    // what made it invisible: the labels were right and the dates underneath
+    // them were gone.
+    const dataCols        = [...dims, ...dateCols, valueCol, unitsCol].filter(Boolean);
     const effectiveValue  = dataCols.includes(valueCol) ? valueCol : null;
     const effectiveUnits  = dataCols.includes(unitsCol) ? unitsCol : null;
     const insertCols      = [...dataCols.map(q), 'pf_iter', 'pf_logid', 'pf_user', 'pf_created_at'].join(', ');
     const selectData      = dataCols.map(q).join(', ');
     const dimsJoined      = dims.map(q).join(', ');
+    // The date columns as a select list, in the same order dataCols lists them,
+    // so it lines up with insertCols positionally.
+    const datesJoined     = dateCols.map(q).join(', ');
 
     // Baseline and reference copy the source row wholesale, so they carry every
     // measure and every date — not just the primary one the operations act on.
@@ -410,7 +422,7 @@ SELECT count(*) AS rows_affected, (SELECT id FROM ilog) AS log_id FROM ins`.trim
         // comes to the same figure the ungrouped window produced.
         const baseSelectParts = [
             ...dimsJoined ? [dimsJoined] : [],
-            q(dateCol),
+            datesJoined,
             effectiveValue  ? `sum(${q(effectiveValue)}) AS ${q(effectiveValue)}` : null,
             effectiveUnits  ? `sum(${q(effectiveUnits)}) AS ${q(effectiveUnits)}` : null,
             effectiveValue  ? `sum(sum(${q(effectiveValue)})) OVER () AS total_value` : null,
@@ -430,12 +442,12 @@ ilog AS (
     WHERE {{where_clause}}
     {{exclude_clause}}
     GROUP BY
-        ${groupCols([...dims, dateCol])}
+        ${groupCols([...dims, ...dateCols])}
 )
 ,ins AS (
     INSERT INTO {{fc_table}} (${insertCols})
     SELECT
-        ${[dimsJoined, q(dateCol), ...(effectiveValue ? [vSel] : []), ...(effectiveUnits ? [uSel] : [])].join(',\n        ')},
+        ${[dimsJoined, datesJoined, ...(effectiveValue ? [vSel] : []), ...(effectiveUnits ? [uSel] : [])].join(',\n        ')},
         'scale', (SELECT id FROM ilog), '{{pf_user}}', now()
     FROM base
     RETURNING *
@@ -454,23 +466,23 @@ ilog AS (
 ,src AS (
     SELECT
         ${dimsJoined},
-        ${q(dateCol)}${effectiveValue ? `,\n        sum(${q(effectiveValue)}) AS ${q(effectiveValue)}` : ''}${effectiveUnits ? `,\n        sum(${q(effectiveUnits)}) AS ${q(effectiveUnits)}` : ''}
+        ${datesJoined}${effectiveValue ? `,\n        sum(${q(effectiveValue)}) AS ${q(effectiveValue)}` : ''}${effectiveUnits ? `,\n        sum(${q(effectiveUnits)}) AS ${q(effectiveUnits)}` : ''}
     FROM {{fc_table}}
     WHERE {{where_clause}}
     {{exclude_clause}}
     GROUP BY
-        ${groupCols([...dims, dateCol])}
+        ${groupCols([...dims, ...dateCols])}
 )
 ,neg AS (
     INSERT INTO {{fc_table}} (${insertCols})
-    SELECT ${dimsJoined}, ${q(dateCol)}, ${effectiveValue ? `-${q(effectiveValue)}` : '0'}${effectiveUnits ? `, -${q(effectiveUnits)}` : ''},
+    SELECT ${dimsJoined}, ${datesJoined}, ${effectiveValue ? `-${q(effectiveValue)}` : '0'}${effectiveUnits ? `, -${q(effectiveUnits)}` : ''},
            'recode', (SELECT id FROM ilog), '{{pf_user}}', now()
     FROM src
     RETURNING *
 )
 ,ins AS (
     INSERT INTO {{fc_table}} (${insertCols})
-    SELECT {{set_clause}}, ${q(dateCol)}, ${effectiveValue ? q(effectiveValue) : '0'}${effectiveUnits ? `, ${q(effectiveUnits)}` : ''},
+    SELECT {{set_clause}}, ${datesJoined}, ${effectiveValue ? q(effectiveValue) : '0'}${effectiveUnits ? `, ${q(effectiveUnits)}` : ''},
            'recode', (SELECT id FROM ilog), '{{pf_user}}', now()
     FROM src
     RETURNING *