jared
0fbae00e27
cog_spending(), cog_revenue() and cog_balances() gain optional state/type
arguments. Both default to NULL, so every existing govid-based call is
unchanged.
The verbs took a cohort only as a govid vector, which .sql_lit_chr()
rendered into a quoted IN list and .verb_spendrev() embedded into 5-8
separate statements per call: the scope check, the main aggregate, the
per-capita join, the harmonization block, and the suggestion and
suppression queries. For type = "city" that list is 301,589 characters,
parsed and planned from scratch every time it appears.
Passing state/type instead expresses the cohort as a subquery against
canonical_fips_xwalk, so its size never enters the SQL string at all.
Measured on the production corpus, same FY2022 aggregate over the
20,106-government city cohort, DUCKDB_THREADS=2, median of 5:
IN (20,106 literals) -- 0.3.0 432 ms
join against a temp cohort table 132 ms
predicate on canonical_fips_xwalk 102 ms
no cohort filter at all (the floor) 105 ms
The predicate reaches the no-filter floor: the cohort restriction is
now free. End to end through cog_spending(category = "Police"),
1080 ms -> 271 ms, 3.99x -- larger than the single-query saving,
because the repetition across statements is what actually cost.
Design decisions, both made explicitly rather than left implicit:
- govid AND state/type INTERSECT. "These ids, narrowed to that
state/type" is a real query, and an error here could never be
relaxed later without breaking callers.
- A predicate cohort has no id list to report, so
provenance$scope$govids_found/govids_missing stay empty and a new
scope$cohort block carries state, type and n_governments. Resolving
the ids just to report them would put 20,000 govids in every
fleet-scale response body -- the cost this change removes. A
govid-named cohort's provenance is untouched.
state/type are coerced with .coerce_state_to_fips()/.coerce_type(), the
same helpers cog_gov_search() uses. That is load-bearing: the argument
is a postal abbreviation ("WI") while fips_state holds a FIPS code
("55"), and a predicate on the raw parameter matches nothing and returns
an empty result indistinguishable from "reported nothing". cog-api hit
exactly this trap optimizing the same path.
.attach_per_capita() now keys its population lookup on the govids present
in the result rather than the requested cohort. Those are the only ones
its LEFT JOIN can match, so the output is identical -- but it needs no id
list, and on a paginated call it looks up one page instead of the fleet.
Fixes uscogdata#58.
88 lines
3.4 KiB
R
88 lines
3.4 KiB
R
# R/basis.R
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# basis= resolution (harmonized/raw, with v4/v5 dual-accept) and the
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# harmonization exclusion-count block attached to provenance.
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#' Resolve the requested `basis` against the active corpus's schema_version.
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#'
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#' On a `schema_version >= 5` corpus, the requested basis is used as-is. On
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#' an older (`schema_version == 4`) corpus, which has no harmonization
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#' tables: a caller who left `basis` at its default (`"harmonized"`, so
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#' `explicit` is `FALSE`) silently gets `"raw"` back, with a note recorded
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#' for provenance; a caller who explicitly asked for
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#' `basis = "harmonized"` gets a hard abort instead of a silent downgrade.
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#'
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#' @param basis `"harmonized"` or `"raw"` (already resolved via `match.arg`).
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#' @param explicit `TRUE` if the caller passed `basis` explicitly (as
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#' opposed to relying on the default `c("harmonized", "raw")`).
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#' @param manifest The active session's parsed manifest list.
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#' @return List with `basis` (the resolved value) and `note` (character or
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#' `NA_character_`).
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#' @noRd
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.resolve_basis <- function(basis, explicit, manifest) {
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schema_version <- suppressWarnings(as.integer(manifest$schema_version %||% 0L))
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if (schema_version >= 5L) {
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return(list(basis = basis, note = NA_character_))
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}
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if (identical(basis, "harmonized") && explicit) {
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cli::cli_abort(c(
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"basis = \"harmonized\" requires corpus schema_version >= 5.",
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x = "Active corpus has schema_version {schema_version}.",
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i = "Use basis = \"raw\" (the default on this corpus), or point USCOGDATA_URL at a schema_version >= 5 corpus."
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), class = "uscogdata_basis_unsupported")
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}
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list(
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basis = "raw",
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note = sprintf(
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"basis resolved to \"raw\": corpus schema_version %d < 5 (harmonization tables unavailable)",
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schema_version
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)
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)
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}
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#' Count + sum item-level rows that basis="harmonized" excludes because they
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#' carry no harmonized_code (discontinued / not-yet-ruled codes) within the
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#' calling verb's crosswalk scope (`subtype_col` values in `subtype_scope` --
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#' the same subtype-membership classification the verb SQL uses, never
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#' item-code prefixes), govids, and years. Only meaningful when the resolved
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#' basis is "harmonized"; returns an applied = FALSE stub otherwise (raw
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#' basis never excludes rows this way).
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#'
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#' The intergovernmental leg is deliberately outside this count even for
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#' expenditure_concept = "total": ig_long_harmonized COALESCEs rather than
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#' drops NULL-harmonized rows, so harmonization never excludes an IG row.
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#' @noRd
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.build_harmonization_block <- function(con, cohort, years, resolved,
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subtype_col, subtype_scope) {
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if (!identical(resolved$basis, "harmonized")) {
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return(list(
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applied = FALSE,
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na_rows_excluded = 0L,
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na_amount_excluded = 0,
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note = resolved$note
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))
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}
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sql <- sprintf(
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"SELECT COUNT(*) AS n, COALESCE(SUM(amt), 0) * 1000.0 AS amt
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FROM long
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WHERE %s AND year IN (%s)
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AND NOT is_aggregate AND harmonized_code IS NULL
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AND item_code IN (
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SELECT item_code FROM summary_categories WHERE %s IN (%s)
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)",
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.cohort_sql(cohort), paste(as.integer(years), collapse = ","),
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subtype_col, .sql_lit_chr(subtype_scope)
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)
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na <- DBI::dbGetQuery(con, sql)
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list(
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applied = TRUE,
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na_rows_excluded = as.integer(na$n),
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na_amount_excluded = as.numeric(na$amt),
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note = resolved$note
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)
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}
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