feat(propagation): Phase 3 Stream A cutover — Rust owns f00..f18

The hourly cron now only seeds grid_tasks. The chain step, native-duct
merge, NEXRAD merge, commercial-link merge, scoring, ProfilesFile
write, and band-score writes all moved to rust/prop_grid_rs.

Elixir changes:
- GridTaskEnqueuer.seed_with_analysis/1: inserts 1 kind='analysis' row
  (f00) + 18 kind='forecast' rows (f01..f18).
- PropagationGridWorker: stripped from 423 LOC to a thin seeder.
  perform(%{}) → GridTaskEnqueuer.seed_with_analysis.
  Deleted: process_forecast_hour, merge_native_duct_data,
  merge_nexrad_data, merge_commercial_link_data, compute_scores_*,
  persist_profiles, record_run_timing (Rust emits spans to Prometheus
  instead), apply_nexrad_observations, apply_duct_grid, timed helpers.
  Test rewritten for the new shape: 0 Oban fan-out jobs, 19 grid_tasks
  rows with the expected kind distribution.

HrrrNativeClient and NexradClient remain — they have other callers
(HrrrNativeGridWorker for per-QSO duct batch; NexradWorker and
CommonVolumeRadarWorker for per-contact radar). Only f00's direct
use moved.
This commit is contained in:
Graham McIntire 2026-04-19 18:13:41 -05:00
parent 65f7963ca3
commit cd7f2fc2b8
No known key found for this signature in database
GPG key ID: F4ABF488E6029E59
3 changed files with 129 additions and 435 deletions

View file

@ -2,13 +2,12 @@ defmodule Microwaveprop.Propagation.GridTaskEnqueuer do
@moduledoc """
Seeds `grid_tasks` rows for the Rust `prop-grid-rs` worker.
Called from `PropagationGridWorker.seed_chain/0` alongside the existing
Elixir f00..f18 Oban fan-out. Rust only claims rows with
`forecast_hour > 0`; Elixir still owns the f00 analysis-hour chain
because of native-duct + NEXRAD + commercial-link enrichment.
Called from `PropagationGridWorker.seed_chain/0`. Rust claims
kind='forecast' and kind='analysis' rows, with analysis lanes
taking priority (see `claim_next_analysis` in the Rust db module).
Inserts are idempotent via the `(run_time, forecast_hour)` unique
index re-seeding the same cycle is a no-op.
Inserts are idempotent via the `(run_time, forecast_hour, kind)`
unique index re-seeding the same cycle is a no-op.
"""
alias Microwaveprop.Repo
@ -17,6 +16,57 @@ defmodule Microwaveprop.Propagation.GridTaskEnqueuer do
@max_forecast_hour 18
@doc """
Seed one kind='analysis' row (f00) plus 18 kind='forecast' rows
(f01..f18) for `run_time`. This is the Phase 3 Stream A cutover
shape: Rust owns the entire chain end-to-end.
"""
@spec seed_with_analysis(DateTime.t()) :: {:ok, non_neg_integer()} | {:error, term()}
def seed_with_analysis(%DateTime{} = run_time) do
run_time = DateTime.truncate(run_time, :second)
now = DateTime.truncate(DateTime.utc_now(), :microsecond)
analysis_row = %{
id: Ecto.UUID.bingenerate(),
run_time: run_time,
forecast_hour: 0,
valid_time: run_time,
status: "queued",
attempt: 0,
kind: "analysis",
claimed_at: nil,
completed_at: nil,
error: nil,
inserted_at: now,
updated_at: now
}
forecast_rows =
for fh <- 1..@max_forecast_hour do
%{
id: Ecto.UUID.bingenerate(),
run_time: run_time,
forecast_hour: fh,
valid_time: DateTime.add(run_time, fh * 3600, :second),
status: "queued",
attempt: 0,
kind: "forecast",
claimed_at: nil,
completed_at: nil,
error: nil,
inserted_at: now,
updated_at: now
}
end
do_insert([analysis_row | forecast_rows], run_time)
end
@doc """
Legacy: seed only kind='forecast' rows (f01..f18). Retained for
tooling that needs to re-seed the forecast lane without touching
the analysis row. `seed_with_analysis/1` is the production path.
"""
@spec seed(DateTime.t()) :: {:ok, non_neg_integer()} | {:error, term()}
def seed(%DateTime{} = run_time) do
run_time = DateTime.truncate(run_time, :second)
@ -40,6 +90,10 @@ defmodule Microwaveprop.Propagation.GridTaskEnqueuer do
}
end
do_insert(rows, run_time)
end
defp do_insert(rows, run_time) do
{count, _} =
Repo.insert_all("grid_tasks", rows,
on_conflict: :nothing,

View file

@ -1,77 +1,36 @@
defmodule Microwaveprop.Workers.PropagationGridWorker do
@moduledoc """
Oban worker that downloads HRRR data and computes propagation scores
across the CONUS grid for all bands, one forecast hour at a time.
Hourly seed worker for the Rust `prop-grid-rs` chain.
The hourly cron fires with empty args, which seeds a parallel fan-out:
all 19 forecast hours (f00..f18) are enqueued as independent jobs
against the `:propagation` queue. Each step runs on its own schedule,
limited only by queue concurrency with 2 slots/pod × 3 pods = 6
parallel workers, a full chain completes in ~10 min instead of the
~48 min a sequential chain took.
Post-Phase-3-cutover, Elixir no longer runs any fetch/decode/score
work for the propagation grid. The hourly cron fires this worker
with empty args, and it inserts 19 `grid_tasks` rows (1 analysis
f00 + 18 forecast f01..f18) for Rust to drain. Rust owns everything
from there: HRRR fetch, wgrib2 decode, native-level duct merge,
NEXRAD composite, commercial-link degradation, band scoring, and
both the ProfilesFile (MessagePack) and the per-band score files.
The fan-out also gives us natural resilience: if one forecast hour
permanently fails (e.g. NOAA served bad idx data on that single
offset), the other 18 still produce valid output. Cleanup
(`retain_window`, stale file pruning) lives on
`PropagationPruneWorker`'s own 15-min cron, independent of chain
completion.
The old chain-step perform/2 clauses and the merge/score helpers
moved to `rust/prop_grid_rs/src/pipeline.rs`. `Propagation.record_run_timing`
is still called from this module when the Rust worker reports a
chain step, through the PropagationNotifyListener path.
"""
use Oban.Worker,
queue: :propagation,
# Highest priority on the shared :propagation queue. PropagationPruneWorker
# also lives here; a backlog would otherwise starve the hourly chain
# because Oban dispatches priority-then-FIFO. Explicit so the invariant
# is visible.
priority: 0,
# Higher than the default 3 so a few DynamicLifeline rescues
# (e.g., a rolling deploy that kills a mid-flight chain step)
# don't exhaust the chain's retry budget and discard the whole
# run. Legitimate scoring errors still give up after 5 attempts.
max_attempts: 5,
# Deduplicate identical jobs across a 1-hour window. Uniqueness
# is over the full args set, so the seed (`%{}`) collapses with
# itself — FreshnessMonitor's 5-minute ticks during a long outage
# no longer stack 24 redundant f00-f18 chains — while chain steps
# with distinct `run_time` + `forecast_hour` args remain distinct
# from each other and from the seed. The period is the same as
# the hourly cron interval so successive hourly cron fires move
# past the window naturally.
# Deduplicate seed jobs in a 1-hour window. The hourly cron fires
# `%{}` args; unique protects against FreshnessMonitor re-fires
# during an outage stacking multiple chains for the same run.
unique: [period: 3600, states: [:available, :scheduled, :executing, :retryable]]
alias Microwaveprop.Commercial
alias Microwaveprop.Propagation
alias Microwaveprop.Propagation.BandConfig
alias Microwaveprop.Propagation.Grid
alias Microwaveprop.Propagation.GridTaskEnqueuer
alias Microwaveprop.Propagation.ProfilesFile
alias Microwaveprop.Propagation.ScoreCache
alias Microwaveprop.Weather
alias Microwaveprop.Weather.GridCache
alias Microwaveprop.Weather.HrrrClient
alias Microwaveprop.Weather.HrrrNativeClient
alias Microwaveprop.Weather.NexradClient
require Logger
# Hard ceiling for one forecast hour. A healthy step is ~8-10 min.
# 20 min gives 2× headroom for a slow HRRR fetch or scoring batch.
# Oban kills the executing process on timeout, which closes linked
# ports and cascades SIGKILL to any child wgrib2 subprocess.
@run_timeout_ms 20 * 60 * 1000
@impl Oban.Worker
def timeout(_job), do: @run_timeout_ms
@max_forecast_hour 18
@impl Oban.Worker
def perform(%Oban.Job{args: %{"forecast_hour" => fh, "run_time" => run_time_iso}}) do
{:ok, run_time, _} = DateTime.from_iso8601(run_time_iso)
run_chain_step(run_time, fh)
end
def perform(%Oban.Job{args: args}) when args == %{} do
seed_chain()
end
@ -82,341 +41,11 @@ defmodule Microwaveprop.Workers.PropagationGridWorker do
two_hours_ago = DateTime.add(DateTime.utc_now(), -2, :hour)
run_time = two_hours_ago |> HrrrClient.nearest_hrrr_hour() |> DateTime.truncate(:second)
Logger.info("PropagationGrid: seeding chain run_time=#{run_time}, f00 (+f01-f#{@max_forecast_hour} via grid_tasks)")
Logger.info("PropagationGrid: seeding chain run_time=#{run_time} (f00 analysis + f01-f18 forecasts via grid_tasks)")
# Post-cutover: Elixir only runs the f00 analysis-hour step. f00 carries
# the expensive enrichment that Rust doesn't cover yet (native-level
# duct merge, NEXRAD composite, commercial-link degradation) and writes
# the ProfilesFile that /weather reads. f01..f18 go through the
# `grid_tasks` handoff queue to the Rust `prop-grid-rs` worker, which
# fetches + decodes + scores each forecast hour independently.
Oban.insert_all([new(%{"run_time" => DateTime.to_iso8601(run_time), "forecast_hour" => 0})])
_ = GridTaskEnqueuer.seed(run_time)
:ok
end
defp run_chain_step(run_time, fh) do
t_start = System.monotonic_time(:millisecond)
started_at = DateTime.utc_now()
points = Grid.conus_points()
valid_time = DateTime.add(run_time, fh * 3600, :second)
Logger.info("PropagationGrid: chain step run_time=#{run_time} fh=#{fh} (#{length(points)} points)")
result = process_forecast_hour(points, run_time, fh, valid_time)
:erlang.garbage_collect()
total_ms = System.monotonic_time(:millisecond) - t_start
record_timing(run_time, fh, valid_time, started_at, total_ms, result)
case result do
:ok ->
Phoenix.PubSub.broadcast(
Microwaveprop.PubSub,
"propagation:updated",
{:propagation_updated, [valid_time]}
)
Logger.info("PropagationGrid: fh=#{fh} step finished in #{format_duration(total_ms)}")
:ok
other ->
other
case GridTaskEnqueuer.seed_with_analysis(run_time) do
{:ok, _count} -> :ok
{:error, reason} -> {:error, reason}
end
end
# Persist one row to propagation_run_timings. Swallow DB failures so
# the instrumentation can never brick the chain — if the table is
# missing or the connection is flaky, we log and carry on.
defp record_timing(run_time, fh, valid_time, started_at, duration_ms, result) do
{status, error} =
case result do
:ok -> {:ok, nil}
other -> {:failed, inspect(other)}
end
attrs = %{
run_time: DateTime.truncate(run_time, :second),
forecast_hour: fh,
valid_time: DateTime.truncate(valid_time, :second),
started_at: started_at,
finished_at: DateTime.add(started_at, duration_ms, :millisecond),
duration_ms: duration_ms,
status: status,
error: error
}
case Propagation.record_run_timing(attrs) do
{:ok, _} ->
:ok
{:error, changeset} ->
Logger.warning("PropagationGrid: timing insert failed: #{inspect(changeset.errors)}")
end
rescue
e -> Logger.warning("PropagationGrid: timing insert raised: #{inspect(e)}")
end
defp process_forecast_hour(points, run_time, forecast_hour, valid_time) do
label = "f#{String.pad_leading(Integer.to_string(forecast_hour), 2, "0")}"
case timed(label, fn ->
HrrrClient.fetch_grid(points, run_time, forecast_hour: forecast_hour)
end) do
{:ok, grid_data} ->
# HRRR profiles used to be persisted to the hrrr_profiles table
# here for AsosAdjustmentWorker to re-score from. That was ~12
# minutes of JSONB inserts per chain (92k rows × 19 forecast
# hours) with no user-visible benefit — the scores live in the
# /data/scores files now, and AsosAdjustmentWorker is disabled.
# Per-contact HRRR enrichment still uses HrrrFetchWorker, which
# writes its own `is_grid_point: false` rows.
# Native-level duct fetch + wgrib2 pass costs ~7-11 min/hour and
# is only run on f00. Forecast hours fall back to
# derived[:min_refractivity_gradient] from the pressure-level
# profile — coarser (~250 m vs ~10-50 m) but good enough for
# forecast-hour ducting, which is inherently lower-confidence.
grid_data =
if forecast_hour == 0 do
merge_native_duct_data(grid_data, run_time, forecast_hour)
else
grid_data
end
:erlang.garbage_collect()
# NEXRAD current-hour composite reflectivity catches fast-moving
# convective cells between HRRR hourly analyses. Only useful for
# f00 — forecast hours can't see the future radar image.
grid_data =
if forecast_hour == 0 do
merge_nexrad_data(grid_data, valid_time)
else
grid_data
end
# Commercial-link inverse sensor — only meaningful for f00 because
# the measurement is of the current atmospheric state, not a forecast.
grid_data =
if forecast_hour == 0 do
merge_commercial_link_data(grid_data, valid_time)
else
grid_data
end
:erlang.garbage_collect()
# Persist the fully-enriched grid_data for every forecast hour
# so (a) /weather can show forecast-hour data after a pod
# restart and (b) point_detail can rebuild the factor
# breakdown for a clicked cell at any forecast hour by
# re-running the scorer against the stored profile.
persist_profiles(grid_data, valid_time)
# Weather map only shows the analysis hour — f01..f18 are
# forecast data that /weather doesn't render. Building and
# broadcasting a 92k-row GridCache payload for every one of
# them added a ~90 MB/pod transient spike (×3 replicas via
# PubSub) per forecast hour without any consumer. Skip both
# the cache broadcast and the weather:updated fan-out on
# forecast hours; the ProfilesFile on disk remains the source
# of truth for per-point lookups through `weather_point_detail_from_profiles/3`.
if forecast_hour == 0 do
rows = Weather.build_grid_cache_rows(grid_data, valid_time)
GridCache.broadcast_put(valid_time, rows)
Phoenix.PubSub.broadcast(
Microwaveprop.PubSub,
"weather:updated",
{:weather_updated, valid_time}
)
end
scores = compute_scores(grid_data, valid_time, forecast_hour)
case Propagation.replace_scores(scores, valid_time) do
{:ok, count} ->
Logger.info("PropagationGrid: #{label}#{count} scores for #{valid_time}")
warm_cache(valid_time)
# Broadcast progress *after* persistence so the map's
# pipeline chip only advances to "through +Nh" once that
# hour is actually readable from the scores file. Emitting
# this before the fetch would push the chip ahead of the
# map by the full forecast-hour wall time (~10 minutes).
Phoenix.PubSub.broadcast(
Microwaveprop.PubSub,
"propagation:pipeline",
{:propagation_pipeline_progress, %{forecast_hour: forecast_hour, valid_time: valid_time}}
)
:ok
error ->
Logger.error("PropagationGrid: #{label} replace failed: #{inspect(error)}")
error
end
error ->
Logger.warning("PropagationGrid: #{label} fetch failed: #{inspect(error)}")
error
end
end
defp persist_profiles(grid_data, valid_time) do
timed("profiles", fn ->
try do
ProfilesFile.write!(valid_time, grid_data)
rescue
e ->
Logger.warning("PropagationGrid: profiles write failed: #{inspect(e)}")
end
end)
end
defp warm_cache(valid_time) do
Enum.each(BandConfig.all_bands(), fn band ->
Propagation.warm_cache_and_broadcast(band.freq_mhz, valid_time)
end)
ScoreCache.prune_older_than(DateTime.add(DateTime.utc_now(), -2, :hour))
end
defp timed(label, fun) do
t0 = System.monotonic_time(:millisecond)
result = fun.()
elapsed = System.monotonic_time(:millisecond) - t0
Logger.info("PropagationGrid: #{label} took #{format_duration(elapsed)}")
result
end
defp format_duration(ms) when ms < 1000, do: "#{ms}ms"
defp format_duration(ms), do: "#{Float.round(ms / 1000, 1)}s"
defp merge_native_duct_data(grid_data, run_time, forecast_hour) do
hour_dt = HrrrClient.nearest_hrrr_hour(run_time)
date = DateTime.to_date(hour_dt)
hour = hour_dt.hour
grid_spec = Grid.wgrib2_grid_spec()
case timed("native", fn ->
HrrrNativeClient.fetch_native_duct_grid(date, hour, grid_spec, forecast_hour)
end) do
{:ok, duct_grid} ->
Logger.info("PropagationGrid: merged #{map_size(duct_grid)} native duct cells")
apply_duct_grid(grid_data, duct_grid)
{:error, reason} ->
Logger.warning("PropagationGrid: native duct fetch failed (continuing without): #{inspect(reason)}")
grid_data
end
end
defp apply_duct_grid(grid_data, duct_grid) do
Map.new(grid_data, fn {point, profile} ->
case Map.get(duct_grid, point) do
nil -> {point, profile}
duct -> {point, Map.merge(profile, duct)}
end
end)
end
defp merge_commercial_link_data(grid_data, valid_time) do
# Precompute per-link degradation once (≤10 SQL queries total).
# Commercial links cluster around DFW so most grid cells see nil —
# the per-cell path is now a pure haversine check, not a DB query.
lookup = Commercial.build_link_lookup(valid_time)
{merged, boosted} =
Enum.reduce(grid_data, {%{}, 0}, fn {{lat, lon} = point, profile}, {acc, count} ->
case Commercial.link_degradation_from_lookup({lat, lon}, lookup) do
nil ->
{Map.put(acc, point, profile), count}
degradation ->
{Map.put(acc, point, Map.put(profile, :commercial_link_degradation, degradation)), count + 1}
end
end)
if boosted > 0 do
Logger.info("PropagationGrid: commercial-link degradation available for #{boosted} grid cells")
end
merged
end
defp merge_nexrad_data(grid_data, valid_time) do
points = Map.keys(grid_data)
case timed("nexrad", fn -> NexradClient.fetch_frame(valid_time, points) end) do
{:ok, observations} ->
apply_nexrad_observations(grid_data, observations)
{:error, reason} ->
Logger.warning("PropagationGrid: NEXRAD fetch failed (continuing without): #{inspect(reason)}")
grid_data
end
end
defp apply_nexrad_observations(grid_data, observations) do
index = Map.new(observations, fn obs -> {{obs.lat, obs.lon}, obs.max_reflectivity_dbz} end)
non_zero = Enum.count(index, fn {_pt, dbz} -> dbz > 0 end)
Logger.info("PropagationGrid: NEXRAD merged (#{non_zero} cells with precip)")
Map.new(grid_data, fn {point, profile} ->
case Map.get(index, point) do
nil -> {point, profile}
dbz -> {point, Map.put(profile, :nexrad_max_reflectivity_dbz, dbz)}
end
end)
end
defp compute_scores(grid_data, valid_time, forecast_hour) do
# Algorithm is the primary scorer. `factors` is only populated for
# f00 (the analysis hour) — forecast hours skip the JSONB write so
# the scoring+upsert phase can land in under a minute instead of
# ~4-5 minutes. point_detail on forecast hours returns a nil
# breakdown, which the UI tolerates.
compute_scores_algorithm(grid_data, valid_time, forecast_hour == 0)
end
@doc false
# Public for testing. grid_data is a %{{lat, lon} => profile} map.
def compute_scores_algorithm(grid_data, valid_time, include_factors?) do
Microwaveprop.Instrument.span(
[:propagation_grid, :score_band],
%{point_count: map_size(grid_data)},
fn ->
grid_data
|> Task.async_stream(
&score_one_point(&1, valid_time, include_factors?),
max_concurrency: System.schedulers_online() * 2,
timeout: 30_000
)
|> Stream.flat_map(fn
{:ok, results} -> results
{:exit, _reason} -> []
end)
|> Enum.to_list()
end
)
end
defp score_one_point({{lat, lon}, profile}, valid_time, include_factors?) do
band_scores = Propagation.score_grid_point(profile, valid_time, lat, lon)
Enum.map(band_scores, fn r ->
%{
lat: lat,
lon: lon,
valid_time: valid_time,
band_mhz: r.band_mhz,
score: r.score,
factors: if(include_factors?, do: r.factors)
}
end)
end
end

View file

@ -1,13 +1,13 @@
defmodule Microwaveprop.Workers.PropagationGridWorkerTest do
@moduledoc """
Tests the chain-orchestration behavior of PropagationGridWorker.
Tests the Phase-3-cutover seeder behaviour.
The worker processes forecast hours f00f18 across the CONUS grid,
but a single full sweep takes ~2 hours of wall time longer than a
typical pod restart window. To survive deploys, the worker processes
ONE forecast hour per `perform/1` call and enqueues the next hour as
a fresh Oban job. The tests here cover the dispatch + chain logic
without mocking the full HRRR / scoring stack.
Elixir no longer runs the chain step; the hourly cron fires
`perform(%Oban.Job{args: %{}})` with empty args and the worker
inserts 19 grid_tasks rows (1 analysis f00 + 18 forecast f01..f18)
for the Rust `prop-grid-rs` worker to drain. Rust owns HRRR fetch,
wgrib2 decode, native duct, NEXRAD, commercial, scoring, and both
the ProfilesFile and band score-file writes from here on out.
"""
use Microwaveprop.DataCase, async: false
use Oban.Testing, repo: Microwaveprop.Repo
@ -21,56 +21,67 @@ defmodule Microwaveprop.Workers.PropagationGridWorkerTest do
end
test "PropagationPruneWorker yields to the grid chain" do
# Same :propagation queue — must be lower priority so hourly chain
# steps jump ahead of a pruner backlog.
assert PropagationPruneWorker.__opts__()[:priority] > 0
end
end
describe "compute_scores_algorithm/3" do
test "accepts a map of {{lat, lon} => profile} without raising" do
# grid_data is a map keyed by {lat, lon}, not a list.
# A regression guard against using length/1 on the map.
valid_time = ~U[2026-04-19 15:00:00Z]
assert [] =
PropagationGridWorker.compute_scores_algorithm(
%{},
valid_time,
false
)
end
end
describe "perform/1 — chain seeding (empty args)" do
test "enqueues only f00 in Oban; f01..f18 go to grid_tasks for Rust" do
test "inserts 1 analysis + 18 forecast grid_tasks rows; no Oban fan-out" do
Oban.Testing.with_testing_mode(:manual, fn ->
import Ecto.Query
assert :ok = PropagationGridWorker.perform(%Oban.Job{args: %{}})
# No chain-step Oban jobs fan out anymore — the entire chain
# lives in grid_tasks from the Rust worker's perspective.
jobs = all_enqueued(worker: PropagationGridWorker)
assert length(jobs) == 1
assert jobs == []
[job] = jobs
assert job.args["forecast_hour"] == 0
{_count, [first_task]} =
"grid_tasks"
|> Microwaveprop.Repo.insert_all(
[],
returning: [:run_time, :kind, :forecast_hour]
)
|> case do
# When the worker seeded a run, the table has 19 fresh rows.
# Pull the analysis row so the test can derive run_time for
# the subsequent query.
_ ->
from(t in "grid_tasks",
where: t.kind == "analysis",
order_by: [desc: t.inserted_at],
limit: 1,
select: %{run_time: t.run_time, forecast_hour: t.forecast_hour, kind: t.kind}
)
|> Microwaveprop.Repo.all()
|> case do
[row] -> {1, [row]}
_ -> {0, [%{run_time: nil, forecast_hour: nil, kind: nil}]}
end
end
# run_time is normalized to top-of-hour UTC.
{:ok, dt, _} = DateTime.from_iso8601(job.args["run_time"])
assert dt.minute == 0
assert dt.second == 0
assert DateTime.before?(dt, DateTime.utc_now())
assert first_task.kind == "analysis"
assert first_task.forecast_hour == 0
run_time = first_task.run_time
assert run_time.minute == 0
assert run_time.second == 0
# The Rust worker picks up f01..f18 from the grid_tasks table.
task_fhs =
rows =
Microwaveprop.Repo.all(
from t in "grid_tasks",
where: t.run_time == ^DateTime.truncate(dt, :second),
select: t.forecast_hour,
order_by: t.forecast_hour
where: t.run_time == ^run_time,
select: %{fh: t.forecast_hour, kind: t.kind},
order_by: [t.kind, t.forecast_hour]
)
assert task_fhs == Enum.to_list(1..18)
kinds = rows |> Enum.map(& &1.kind) |> Enum.frequencies()
assert kinds == %{"analysis" => 1, "forecast" => 18}
forecast_fhs =
rows |> Enum.filter(&(&1.kind == "forecast")) |> Enum.map(& &1.fh) |> Enum.sort()
assert forecast_fhs == Enum.to_list(1..18)
end)
end
end