figures predate the row-group rechunk (cog_pipeline#93, published 2026-08-09) and reported the mirrored column as 'local speed' with no number -- hiding the largest difference available to a user. Measured 2026-08-10, fresh R session per arm, against the live corpus at pipeline_commit 3d28ddd. Madison WI, 16-core Linux workstation. Three findings the old table could not express: - A local mirror is 60-80x faster. A one-off question is ~12 s end to end remotely against ~0.15 s mirrored. Stated outright now, because it is a bigger and cheaper win for users than anything in the R code. - Opening the session is the LARGEST remote cost (~7.5 s), bigger than any individual query, and it lands on the user's first query rather than on library(). The old table accounted for it nowhere, so every per-query figure was quietly missing it. - The remote cost is round-trips, not scanning: a repeat query over already-touched partitions is ~1.5 s against ~4 s cold, and a full-history query costs ~7 s whether it runs first or last (verified by running the arms in both orders). This is why #93's 1.4-1.7x, measured through cog-api against a local mount, does not show up on the remote path -- there, network latency swamps scan time. Corpus size corrected to ~201 MB: row-group chunking added ~3.4%, and 190.6 was ambiguous between MB and MiB besides. Measured from the manifest and on disk. The 0.3.0 NEWS section keeps 190.6 -- it was correct for that release. Also documented HTTP 429: a burst of remote queries gets rate-limited by the host. Hit while taking these measurements.
11 KiB
uscogdata 0.4.0
DuckDB's resource budget is configurable
USCOGDATA_DUCKDB_THREADS and USCOGDATA_DUCKDB_MEMORY_LIMIT (with matching
options(uscogdata.duckdb_threads = ) / options(uscogdata.duckdb_memory_limit = )
spellings) cap the DuckDB connection the package opens. Both follow the same
env-var > option > default precedence as USCOGDATA_URL.
Unset, no pragma is issued at all and DuckDB's own defaults apply exactly as before -- every visible core. That is right for one interactive session on a dedicated machine and wrong for a server: where several readers share a host, each otherwise claims the whole machine and they contend. Capping measured ~5% on a single-government all-years query (502 ms at 2 threads vs 475 ms uncapped on 16 cores), which is cheap enough that a server should always cap.
This replaces a workaround in which a consumer reached into the package namespace
at boot -- getFromNamespace(".ensure_session", "uscogdata")() followed by a manual
SET threads -- depending both on a private name and on the session already being
open.
cog_gov_search() and cog_balances() gain limit/offset
Pagination arrived on cog_spending()/cog_revenue() in 0.3.0; the other two
verbs were left materializing everything and slicing in R. Both now take
limit/offset with the same semantics: NULL default, the page applied in
SQL behind a deterministic ORDER BY, and the unpaginated count returned as a
total_rows attribute computed by COUNT(*) OVER() in the same scan rather
than a second query.
cog_gov_search() had no LIMIT at all, which made it the one verb that
returns the entire 40,336-row crosswalk when called with no filter.
Two refusals rather than silent surprises:
cog_balances(recipe = , limit = )aborts with classuscogdata_recipe_pagination_conflict-- a recipe's result comes from a separate query that pagination is not wired into.cog_gov_search()in basket mode (length(name) > 1) aborts with classuscogdata_basket_pagination_conflict. Basket mode returns one resolved row per requested name with a sidecar covering all of them; a page of that is not a page of anything the caller asked for.
Documentation: the corpus-access table is re-measured and honest
The README's "two ways to read the corpus" table carried figures taken before
the corpus was re-chunked into row groups (cog_pipeline#93, published
2026-08-09) and reported the mirrored column as "local speed" with no number at
all. Re-measured 2026-08-10 against the published corpus (pipeline_commit 3d28ddd), fresh R session per arm:
- A local mirror is roughly 60-80x faster. A one-off question costs ~12 s end to end remotely against ~0.15 s mirrored. That is the largest single difference available to a user and it is now stated outright rather than left as "local speed".
- Opening the session is the largest remote cost (~7.5 s -- manifest fetch
plus 23 view registrations over HTTPS), larger than any individual query, and
it lands on the first query rather than on
library(uscogdata). The old table did not account for it anywhere. - The remote cost is round-trips, not scanning. A repeat query over already-touched partitions is ~1.5 s against ~4 s cold, and a full-history query costs ~7 s whether it runs first or last.
- The corpus size is ~201 MB, not 190.6 MB -- row-group chunking added ~3.4% and the old figure was ambiguous between MB and MiB besides.
- Documented that a burst of remote queries can be rate-limited by the host
(
HTTP 429), which is another reason to mirror for real work.
Cohorts can be named by predicate, not just by id
cog_spending(), cog_revenue() and cog_balances() gain optional state
and type arguments. Both default to NULL, so every existing call behaves
exactly as before.
Passing them expresses the cohort as a subquery against canonical_fips_xwalk
inside each statement, instead of round-tripping the ids through R and
rendering them back into a literal IN list:
# before: resolve 20,106 ids in R, then embed them in every statement
ids <- cog_gov_search(NULL, state = "CA", type = "city")$canonical_govid
cog_spending(ids, years = 2022)
# now: the cohort never leaves the database
cog_spending(years = 2022, state = "CA", type = "city")
Measured against the production corpus, same FY2022 aggregate over the
20,106-government type = "city" cohort:
| cohort expressed as | time |
|---|---|
IN (20,106 literals) |
449 ms |
| join against a temp cohort table | 99 ms |
predicate on canonical_fips_xwalk |
94 ms |
| no cohort filter at all (the floor) | 88 ms |
4.8x, within 7% of the floor. The rendered IN list was 301,591
characters and was re-parsed in 5-8 separate statements per call, so the cost
was paid repeatedly; the predicate's size is constant in the cohort.
state and type use the same vocabulary and the same internal coercion as
cog_gov_search() -- state is a postal abbreviation ("WI") even though the
crosswalk column holds a FIPS code ("55").
Supplying govid and state/type intersects them: the governments in
govid that also match the predicate. Naming no cohort at all now aborts with
class uscogdata_no_cohort rather than R's "argument is missing" error.
When the cohort is named by predicate there is no id list to report, so
provenance$scope$govids_found/govids_missing are empty and
provenance$scope$cohort carries state, type and n_governments instead.
A govid-named cohort's provenance is unchanged.
Fixes
-
cog_gov_search()now orders bypopulation_acs DESC NULLS LAST, canonical_govid.population_acsalone is not a total order -- ties, and the entireNULLS LASTblock, came back in whatever order the scan produced. That was invisible while every call returned the full result set, but it makes a paged sweep unsound: two requests can order tied rows differently, so a row is duplicated on one page and missing from the next. Unpaginated results are unchanged except for the relative order of rows that were already tied. -
An unknown
stateabbreviation now aborts with "Unknown state abbreviation" (classuscogdata_unknown_state) instead of base R's "subscript out of bounds"..state_abbrev_to_fipsis a named character vector, so[[on an absent name threw before the curated message could be reached -- making that message unreachable dead code in every verb that takes astate.
uscogdata 0.3.0
First public release.
uscogdata provides curated R verbs over the Civilytics US Census of
Governments finance corpus: unit-level financial profiles, geographic rollups
and peer comparisons, with auditable provenance on every result.
What it covers
Government types 0-3 (state, county, municipality, township), FY1967-FY2024 -- 56 fiscal years, 46,148,034 rows, 190.6 MB. There is no source data for FY1968 or FY1969. Special districts (type 4) and school districts (type 5) are out of scope pending validation.
The verbs
cog_spending(), cog_revenue() and cog_balances() for flows and holdings;
cog_gov_search() to resolve place names (including basket mode for many at
once); cog_find_peers() and cog_peer_compare() for cohorts;
cog_geographic_rollup() for aggregates; cog_categories(), cog_recipes(),
cog_manifest() and cog_explain() for metadata and provenance; and
cog_mirror() for a local copy of the corpus.
Reading the corpus now works out of the box
- The package reads the published corpus over HTTPS with no configuration. Previously the default was a placeholder sentinel and no document in the package supplied a working URL, so a new user had no path to a session.
- Remote reads work at all. The partitioned view used a glob, and DuckDB
cannot expand a glob over generic HTTP -- there is no directory listing to
expand against. Partition paths are now enumerated from the corpus manifest,
which is host-agnostic: an HTTPS mirror, a Nextcloud share and a local
cog_mirror()copy all take the same path. - Nothing is written to disk in remote mode; DuckDB fetches only the row groups a query needs.
Four things to know before your first query
- Amounts are in full US dollars. The raw Census files report thousands; the verbs multiply by 1000 on the way out. Do not multiply again.
- Multi-government aggregates disclose their coverage. The Census is a
complete enumeration only in years ending in 2 and 7; every other year is a
sample. Every such result carries
provenance$coveragewith per-yearn_units_reporting. - Absence means two different things. Before FY2012 an absent cell means
Census published $0; from FY2012 it means not reported.
complete = TRUElabels which. - Series breaks reach you unasked. Catalogued breaks intersecting your
query appear in provenance and in
cog_explain().
Known limits
- Special districts (type 4) and school districts (type 5) are out of scope.
- Per-capita rollups exclude governments with no F-33 population, which is by design but does silently narrow a rollup.
n_units_reportingis category-conditional and is not a response rate.- Employee-retirement (
X) codes stop at FY2016, when those systems moved to the Annual Survey of Public Pensions.
uscogdata 0.2.0
New features
-
cog_spending()andcog_revenue()accept the reserved category"All Categories", returning one summed row per(year, canonical_govid, subtype)across every category inside the requested concept's subtype scope. Filtering the result tospend_subtype == "operations"gives an operating-expenditure total.cog_geographic_rollup()inherits it, which is the efficient way to build a geographic total — previously a caller had to issue one rollup per category and sum the results (cog-api#37)."All Categories"is not the same thing asexpenditure_concept = "total". The concept chooses which subtypes are in scope;"All Categories"chooses whether the rows inside that scope are broken out or summed. -
cog_categories()advertises"All Categories"for the expenditure and revenue vocabularies, so the reserved value is discoverable. -
Coverage signposting (see "Signposting now catches partially-suppressed categories" below) now also works in
category = "All Categories"mode. The recipe-suggestion candidate query used to be scoped bycategory, which is never a match for the reserved"All Categories"value, soprovenance$suggestionsalways came back empty there — the one mode whose whole point is "you cannot sum the wrong scope" was silently unable to signal a wrong scope. The candidate query is now scoped by the concept's subtype allowlist instead, symmetric with how.build_verb_sql()itself scopes the summed total: Los Angeles County FY2011,category = "All Categories"still excludes $271,589,000 of aggregate-published Public Welfare (E68), but now namesrecipe = "welfare_cash_e68_wide"to recover it instead of reporting zero suggestions.
Documentation
cog_geographic_rollup()andcog_peer_compare()now document thatprovenance$coverage'sn_units_reportingis category-conditional and is not a response rate: a government that was surveyed and genuinely spends nothing in the requested category is indistinguishable from one never surveyed (uscogdata#36).