Ship rows pre-aggregated to the grain the pivot displays instead of raw
forecast rows. This is Path B from pf_perspective_options.md: it keeps
Perspective's native WASM engine — so expand/collapse/depth/sort/filter
all still work — and fixes load time by cutting rows, not transport.
Measured on pf.fc_osm_stack_20 at pending_rep x customer x smon:
534,902 -> 6,154 rows (~87x), pf_gkey unique across all 6,154, and both
measures reconcile exactly to the raw totals.
The grain is static: flagged once per source in Setup and baked into the
stored pf.sql templates, so load and operations agree by construction.
Sources with no flagged column keep the previous raw-row behaviour, so
this is backward compatible.
- pf.col_meta gains in_grain; grainOf() in lib/sql_generator.js is the
single definition of the grain and is reused by routes/log.js.
- New get_agg template + GET /api/versions/:id/agg, generated only when a
grain is defined. Regenerating drops templates no longer produced, so
clearing the grain falls back to /data.
- scale/recode/clone now aggregate their own new rows to grain before
returning. Because pf_logid is part of pf_gkey those keys are always
new, so table.update() appends and the view re-sums — the Excel
pivot-cache pattern, no bucket recomputation.
- Undo reports pf_gkeys (RETURNING cannot take DISTINCT, so the delete
feeds a CTE that reduces to distinct keys); the client removes those
index values and the view re-sums.
- pf_gkey is concat_ws(chr(31), COALESCE(col::text, chr(30)), ...).
The separator and NULL sentinel are load-bearing: plain concat_ws skips
NULLs, so ('a',NULL) and (NULL,'a') would collide and silently merge two
groups into one indexed row.
- Forecast.jsx reads col_meta first to pick /agg vs /data; the Arrow
streaming logic is extracted to fetchArrow() since both share it.
- Setup.jsx gains a grain checkbox and shows the resulting grain.
- 01_schema.sql: move the col_meta ALTERs after its CREATE TABLE — they
referenced the table before it existed on a fresh install.
All six generated statements verified to plan against the real forecast
table; the in_grain column has been added to the dev database.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
- col_meta gets dim_period_col field: maps a dimension column to its pf.dim_period counterpart (e.g. year -> cal_year, month -> cal_month)
- When the date column is is_key of a dim_group and any sibling dimension has dim_period_col set, baseline and reference SQL JOIN pf.dim_period on the shifted date instead of copying raw source values
- No dim_period config = identical SQL to before (fully backwards compatible)
- Setup UI: period col input in col_meta editor, enabled for dimension columns with a dim_group set
- Schema migration applied: dim_period_col text null on pf.col_meta
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- col_meta: add dim_group field to group related columns (dimension hierarchies, date-adjacent columns); is_key now enabled for date role to mark group parent
- sources.js: upsert includes dim_group
- Setup.jsx: group column in col_meta editor, key checkbox enabled for date role
- gen_dim_period.sql: create and populate pf.dim_period with calendar and fiscal period cuts (monthly grain, 2018-2035)
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Forecast falls back to a saved per-source layout when no version-local
layout is cached, so new versions of a source open with a sensible pivot
without each user reconfiguring it.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
