Weigh-ins: Garmin's document has no samplePk and gives kilograms, the live
service sends a samplePk and grams. A weigh-in now takes its id from
samplePk or else its own GMT instant, reads each mass by magnitude (above
1000 is grams), and is written whole or not at all: a missing weight, a
missing instant or one implausible value drops every row of it, counted
on the wide event by reason.
Refused resources: a lasting 4xx on one resource (a cycle summary for an
account that tracks no cycle) is noted once on the progress column,
counts as done for the backfill, is skipped by the hourly sync and is
listed in the card's details. It no longer holds the backfill open or
turns the connection red. The cycle leg never parks the connection,
whatever it is refused with.
Backfill: weigh-ins walk back to the start of Garmin Connect on their
own, so history before the first watch day and a scale-only account
arrive. Progress and the completion stamp are written only while the
connection the slice started on is still the stored one.
Key: connect sends the key to the one service the person picks (Garmin
Connect or Garmin Connect China), never to both. A parked key is asked
about again once a day with a single token exchange and reconnected when
Garmin accepts it. The key's end is read from the token's own iat and
exp, an estimate the key outlived is cleared after an accepted exchange,
and the validity can be corrected from the card's menu (PATCH
/api/garmin/key-expiry, with the day the key was created) without
pasting it again.
Sync: an incremental run reaches back to the last successful sync, up to
a year, so an outage longer than the 30-day window leaves no gap; a night
Garmin no longer reports (deleted, or turned into a nap) is retired.
Card: connect errors are translated from meta.errorCode in every locale.
Types: BODY_BATTERY, STRESS_LEVEL, TRAINING_READINESS and
ACUTE_TRAINING_LOAD get source ladders of their own (the device or the
bridge first, then the hand-entered sources in their usual order), join
the ranked types and the provenance picker, and the recovery-empty
description names them.
The canonical-source pick grouped the window to (type, day, source),
chose each day's source with DISTINCT ON, and joined the choices back to
the rows. Whether that join ran as a hash join or as a nested loop that
rescanned the whole pick for every row was the planner's call, made from
table statistics. On a measurements table without them (a new install,
or an import still under the autoanalyze threshold) it estimated one row
on each side and took the nested loop.
Binding the request's clock as a parameter instead of reading NOW()
flipped which side of that loop the pick landed on: the analytics read
over 6,000 freshly written blood-pressure rows went from 1.6 s to 8.4 s,
and the demo seed's dashboard headline to 20 s. On a ten-year account
without statistics the 90-day read took 4 s with either clock and the
all-time read ran past two minutes.
The pick is now one window function over one scan: FIRST_VALUE of the
source per (type, UTC day) in ladder order, keeping the rows of that
source. Same rows, same order of preference, so every day keeps its
source; the parity suite against the DISTINCT ON statement holds that.
The analytics read on the fixture above takes about 0.1 s, the headline
0.4 s. On the analysed ten-year account the 90-day and all-time reads
are as fast as the join was, and they no longer depend on statistics.
The rows carry one extra column, canonical_source; every reader selects
its columns by name.
A new integration test runs every reader shape under EXPLAIN ANALYZE on
a table with no statistics and bounds the rows the plan produces or
discards per row seeded. The statement count never moved, so a statement
budget could not see this; the join measured 200 to 8,600 row visits
per row seeded and the window stays at 4.
The summaries slice and the comprehensive aggregator took their JS windows
(the DAY-bucket bounds, the rollup slope anchors, lastSeen staleness) from
the process clock and their SQL windows (avg7, avg30, the month before, the
median, the 90-day canonical pick, the cold-path slope evidence) from
NOW(), the database's clock. One response mixed two clocks, so a reading
on a window's edge fell in or out with whichever host answered, and with
the process clock pinned the analytics parity walk changed its avg7 with
the hour it ran at.
Each read now takes one `now` and binds it into its statements
(`request-clock-sql.ts`): `$N::timestamp`, which keeps the driver's
offset-free UTC string as written in any session zone. The canonical-pick
helper takes its window as an instant plus an interval instead of reading
NOW(); the series and calendar readers anchor it on their own `since`, the
BP-in-target read on its 365-day start. The window-mean and live-slope
columns the two aggregates each spelled out now come from one builder.
The streak's local day series read its bounds through `::timestamptz`,
which follows the session zone: outside a UTC session today's reading fell
out of the streak. It reads them as UTC first.
The parity walks for analytics, the dashboard summary and the
comprehensive overview pin a fixed day instead of today: their records are
laid out from the anchor day, so the chronotype's work and free nights and
the weight-by-weekday points moved with the weekday the walk ran on. The
snapshots are unchanged. A new suite pins the clock to four times of day,
far from the database clock, with readings ten minutes either side of
every edge, on both read paths, in a UTC and an Auckland session.
The shared canonical-source CTE sorted every raw reading in its window by
a CASE expression no index can supply; on the benchmark account the pulse
pick over ten years sorted 260,000 rows and spilled to disk. Its order
depends only on (type, source), so the pick now groups the window to its
distinct (type, day, source) triples first and runs DISTINCT ON over
those. The picked source per day is the same by construction; an
integration test runs the old statement beside the new one over a fixture
with overlapping sources, sources off the ladder, tombstones, empty days
and readings either side of midnight, under default and reordered ladders,
for every reader shape, and requires identical rows.
Every app session now sets jit=off. Postgres compiled the larger folds to
machine code, which took 100 to 140 ms of a 220 ms statement and saved
nothing for statements that run once and are bound by reading rows. JIT
never changes a result.
Output of `node scripts/strip-planning-tags.mjs --write`: 3,157 comment
lines in 1,308 files lose the work-item identifier at their head. Release
versions and issue references stay; nothing outside comment text
changes, which the script checks per file against a comment-free
printout. healthlog/no-planning-tags is enabled at error level with this
commit, so the tree it lands on is clean.
Every raw-SQL clock read against a timestamp column without a zone now
writes NOW() AT TIME ZONE 'UTC', so passkey and login challenges, rate
limits, provider pauses, coach usage stamps, tombstone and measurement
windows no longer pass through the session time zone even where the
per-connection pin cannot apply. The regression-window bounds stay naive
UTC timestamps instead of being turned into timestamptz. A structural
guard keeps bare NOW() / CURRENT_TIMESTAMP out of raw SQL outside a short
list of timestamptz targets. The integration test sets the database
default to Europe/Berlin and drives challenge claims, session expiry, the
native sign-in handoff freshness check and the rate-limit window through
the app's client, plus the challenge claim through an unpinned client.
Self-hosting docs describe the pin for an existing or shared Postgres.
iOS and watchOS 27 add `HKQuantityTypeIdentifierHeartRateVariabilityRMSSD`
(Apple's symbol `c:@HKQuantityTypeIdentifierHeartRateVariabilityRMSSD`,
available from 27.0). The live batch and the export.zip import now store it
as `HRV_RMSSD`, the type WHOOP, Oura and Polar already write, in
milliseconds, mean-aggregated and flagged privacy-sensitive like SDNN. The
accepted range is 1 to 300 ms.
RMSSD ranks on its own `hrvRmssd` ladder in the SQL source collapse, so a
day holding it from Apple Health and a strap resolves to one source
instead of a name tiebreak.
SDNN and RMSSD are different statistics and are kept apart once one
account holds both. The HRV page charts each on its own, titled with its
measure, instead of hiding RMSSD behind SDNN. The Coach's HRV section
carries one timeline per measure under `byMeasure` (same section key, so
every reader still finds it) rather than one daily series averaging the
two; the budget pass condenses and sheds each measure's timeline like a
glucose context.
The rollup tier and sleep resolve every (type, day) to the source the person's
ladder picks before they aggregate. The dense and raw reads of
/api/measurements/series filtered on user and type only, so with a second
provider a day's value blended the two, a reading present in both showed
twice, and the configured ladder had no effect on those charts.
Both reads now take the ladder-winning source per day through the shared
canonicalMeasurementsCte helper, as the other live readers do:
- the day and hour bucket read of the dense kinds (pulse, glucose, HRV, SpO2),
and the stats strip over its rows;
- the generic raw read (weight, body fat, steps, resting heart rate, ...).
The collapse is per day for the hour grain too, as everywhere else. The helper
gains an optional single-type scope so a series scans one metric, not every row
the person has in the window.
Only a type that has a ladder is collapsed. For a type without one (glucose,
body water, bone mass) the helper breaks the tie by source name, which would
silently hide one of two real sources, so those keep every source as before.
A single-source account reads exactly what is stored.
Tests: a real-database test covering the ladder in both directions, the
per-day fallback, a reading mirrored into two sources, the day-bucket, hour-
bucket and raw reads, a type with no ladder and a single-source account. The
route's unit test file reads its fixtures through a small adapter for the new
raw statements, and the dense-read guard drops the exception for the removed
findMany. The OpenAPI description states the rule.
Refs #1108
The rollup writer keeps one row per bucket and source. Collapsing the stored
WEEK / MONTH / YEAR rows picked one source for the whole bucket, so a month
of manual blood-pressure readings plus one synced reading reported the synced
day alone, and a step month that switched devices lost every day the losing
device carried. The live weekly and monthly chart fold made the same pick.
Every coarse bucket is now folded from the canonical DAY buckets: the source
ladder picks one source per day, then the week, month or year counts every
one of its days. Spread, slope and r² are composed from the summed day
accumulators. The live fold picks per local day before folding into weeks
and months. Ties between sources without a ladder rank break alphabetically
on the SQL paths too, matching the rollup reader.
The warm narrow query and the cold heavy query each referenced the
canonical-source subquery twice — once in the window_stats CTE and once in
the outer body — so the DISTINCT-ON pick over the live 90-day rows ran twice
per rebuild. Extract canonicalMeasurementsCte (the SELECT body without the
alias wrapper), bind it once as WITH cm AS (...), and select FROM cm m from
both window_stats and the outer aggregate. Output is identical; the dominant
self-join runs once.
canonicalMeasurementsFrom now wraps the same body, byte-stable for the
single-reference call sites (pinned by a new parity test).
STRESS_SCORE has no source-priority ladder, so metricKeyForType returns null
and the SQL source collapse falls to an alphabetical rank-90 tiebreak. It is
safe today because the only producer is the COMPUTED HRV-derived proxy, but
the instant a device-native producer (Oura daily_stress) is enabled both rows
survive and blend nondeterministically.
Add a stress metric key with an OURA-above-COMPUTED default ladder, wire it
through metricKeyForType and RANKED_TYPES, and surface it in the Sources
settings (all six locales). A guard test asserts every RANKED_TYPES member
resolves to a non-null metric key so a future ranked type can't ship unladdered.
Regenerate the OpenAPI for the additive source-priority key.
- conversation-summary: fault-isolate the per-message decrypt in the
fold loop so one undecryptable historic turn (e.g. mid key-rotation)
no longer permanently stalls a conversation's summary refresh.
- source collapse: unify the no-ladder tiebreak on alphabetically
smallest source across the JS reader and the all-time rollup SQL, so a
ranked vital whose day carries only off-ladder sources resolves to the
same canonical source on the warm and the live-SQL read paths.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Complete the source-aware rollup read path: the slim summaries slice
(rollup + live), the comprehensive aggregator (both paths, including the
dailyByType correlation feed), and the /api/measurements route (rollup
read + the live date_trunc fallback) now resolve overlapping sources to
the source-priority ladder's canonical reading per (type, day) before
aggregating. A dual-source vital (e.g. WHOOP + Apple Watch resting heart
rate) surfaces one canonical series instead of a blend or a doubled
count; cumulative metrics keep summing per canonical source.
The collapse runs in SQL where the aggregate must stay a single
round-trip (buildSourceRankCase emits a per-user ladder-rank CASE;
canonicalMeasurementsFrom restricts a live read to canonical-source rows)
and in application code (collapseRollupRowsBySource) for the row readers,
both driven by the same resolved ladders so live and rollup agree.
Also widens the enum-literal SQL whitelist to accept digits so VO2_MAX
no longer throws on the typed write-hook recompute or the rank CASE.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Marc-André Bombeck