PR3 of Phase B. Replaces the no-op stubs in analytics.service.ts with
working drizzle queries and adds the recurring BullMQ job that warms
the cache.
Computations:
- computePipelineFunnel: groups interests by pipeline_stage filtered by
port + range + not archived; emits 8-row stages array with conversion
pct relative to 'open' as the funnel top.
- computeOccupancyTimeline: per day in range, counts berths covered by
an active reservation (start_date ≤ day, end_date IS NULL OR ≥ day);
emits {date, occupied, total, occupancyPct}.
- computeRevenueBreakdown: sums invoices.total grouped by status +
currency; filters out archived rows.
- computeLeadSourceAttribution: counts interests by source descending;
null source bucketed as 'unspecified'.
Public API (getPipelineFunnel, getOccupancyTimeline, etc.) reads
analytics_snapshots first; falls back to compute + writeSnapshot. TTL
15 minutes (matches the cron interval).
Cron:
- queue/scheduler.ts registers 'analytics-refresh' on maintenance with
pattern '*/15 * * * *'.
- queue/workers/maintenance.ts dispatches to refreshSnapshotsForPort
for every port; per-port try/catch so one bad port doesn't kill the
sweep.
Tests: tests/integration/analytics-service.test.ts (9 cases). Pipeline
funnel math (incl. zero state), occupancy timeline shape/percentages
with seeded reservations, revenue grouped by status + currency, lead
source attribution incl. null bucketing, cache hit (mutate snapshot
directly → next read returns mutated value), refreshSnapshotsForPort
warms every metric×range combo.
Vitest 690/690 (+9). tsc + lint clean.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
321 lines
10 KiB
TypeScript
321 lines
10 KiB
TypeScript
/**
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* Phase B analytics service. Reads pre-computed snapshots from
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* `analytics_snapshots`; recomputes on demand if older than `SNAPSHOT_TTL_MS`.
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* The recurring `analytics-refresh` BullMQ job (PR3) warms the table
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* every 15 minutes per port × per metric.
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*/
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import { and, eq, gte, isNull, sql } from 'drizzle-orm';
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import { db } from '@/lib/db';
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import { analyticsSnapshots } from '@/lib/db/schema/insights';
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import { interests } from '@/lib/db/schema/interests';
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import { invoices } from '@/lib/db/schema/financial';
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import { berthReservations } from '@/lib/db/schema/reservations';
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export type DateRange = '7d' | '30d' | '90d' | 'today';
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export type MetricBase =
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| 'pipeline_funnel'
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| 'occupancy_timeline'
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| 'revenue_breakdown'
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| 'lead_source_attribution';
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export type MetricId = `${MetricBase}.${DateRange}`;
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export const ALL_RANGES: readonly DateRange[] = ['today', '7d', '30d', '90d'] as const;
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export const ALL_METRICS: readonly MetricBase[] = [
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'pipeline_funnel',
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'occupancy_timeline',
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'revenue_breakdown',
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'lead_source_attribution',
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] as const;
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export const SNAPSHOT_TTL_MS = 15 * 60 * 1000; // 15 minutes
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// ─── Output shapes ────────────────────────────────────────────────────────────
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export interface PipelineFunnelData {
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stages: Array<{ stage: string; count: number; conversionPct: number }>;
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}
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export interface OccupancyTimelineData {
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points: Array<{ date: string; occupied: number; total: number; occupancyPct: number }>;
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}
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export interface RevenueBreakdownData {
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bars: Array<{ status: string; amount: number; currency: string }>;
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}
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export interface LeadSourceAttributionData {
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slices: Array<{ source: string; count: number }>;
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}
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export type SnapshotData =
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| PipelineFunnelData
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| OccupancyTimelineData
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| RevenueBreakdownData
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| LeadSourceAttributionData;
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// ─── Cache layer ──────────────────────────────────────────────────────────────
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export async function readSnapshot<T extends SnapshotData>(
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portId: string,
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metricId: MetricId,
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): Promise<T | null> {
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const row = await db.query.analyticsSnapshots.findFirst({
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where: and(eq(analyticsSnapshots.portId, portId), eq(analyticsSnapshots.metricId, metricId)),
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});
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if (!row) return null;
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const age = Date.now() - row.computedAt.getTime();
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if (age > SNAPSHOT_TTL_MS) return null;
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return row.data as T;
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}
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export async function writeSnapshot(
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portId: string,
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metricId: MetricId,
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data: SnapshotData,
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): Promise<void> {
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await db
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.insert(analyticsSnapshots)
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.values({ portId, metricId, data })
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.onConflictDoUpdate({
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target: [analyticsSnapshots.portId, analyticsSnapshots.metricId],
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set: { data, computedAt: new Date() },
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});
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}
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// ─── Range helpers ────────────────────────────────────────────────────────────
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function rangeToCutoff(range: DateRange): Date {
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const now = Date.now();
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switch (range) {
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case 'today':
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return new Date(now - 1 * 86_400_000);
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case '7d':
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return new Date(now - 7 * 86_400_000);
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case '30d':
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return new Date(now - 30 * 86_400_000);
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case '90d':
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return new Date(now - 90 * 86_400_000);
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}
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}
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function rangeToDays(range: DateRange): number {
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switch (range) {
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case 'today':
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return 1;
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case '7d':
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return 7;
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case '30d':
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return 30;
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case '90d':
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return 90;
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}
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}
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// ─── Computations ─────────────────────────────────────────────────────────────
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const PIPELINE_STAGES = [
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'open',
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'details_sent',
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'in_communication',
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'visited',
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'signed_eoi_nda',
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'deposit_10pct',
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'contract',
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'completed',
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] as const;
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export async function computePipelineFunnel(
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portId: string,
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range: DateRange,
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): Promise<PipelineFunnelData> {
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const cutoff = rangeToCutoff(range);
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const rows = await db
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.select({ stage: interests.pipelineStage, count: sql<number>`count(*)::int` })
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.from(interests)
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.where(
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and(
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eq(interests.portId, portId),
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isNull(interests.archivedAt),
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gte(interests.createdAt, cutoff),
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),
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)
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.groupBy(interests.pipelineStage);
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const counts = new Map(rows.map((r) => [r.stage, r.count]));
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const top = counts.get('open') ?? 0;
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const stages = PIPELINE_STAGES.map((stage) => {
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const count = counts.get(stage) ?? 0;
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const conversionPct = top === 0 ? 0 : Math.round((count / top) * 1000) / 10;
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return { stage, count, conversionPct };
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});
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return { stages };
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}
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export async function computeOccupancyTimeline(
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portId: string,
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range: DateRange,
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): Promise<OccupancyTimelineData> {
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const days = rangeToDays(range);
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// Total berths per port (current count — assumes no churn).
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const totalRow = await db.execute<{ total: number }>(
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sql`SELECT count(*)::int AS total FROM berths WHERE port_id = ${portId}`,
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);
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const total = totalRow[0]?.total ?? 0;
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// For each day in range, count berths that have an active reservation
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// covering that day. A reservation is "covering" if start_date <= day
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// AND (end_date IS NULL OR end_date >= day).
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const points: OccupancyTimelineData['points'] = [];
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for (let i = days - 1; i >= 0; i--) {
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const day = new Date(Date.now() - i * 86_400_000);
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const dayStr = day.toISOString().slice(0, 10);
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const occRow = await db
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.select({ occupied: sql<number>`count(distinct ${berthReservations.berthId})::int` })
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.from(berthReservations)
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.where(
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and(
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eq(berthReservations.portId, portId),
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eq(berthReservations.status, 'active'),
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sql`${berthReservations.startDate} <= ${dayStr}::date`,
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sql`(${berthReservations.endDate} IS NULL OR ${berthReservations.endDate} >= ${dayStr}::date)`,
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),
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);
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const occupied = occRow[0]?.occupied ?? 0;
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const occupancyPct = total === 0 ? 0 : Math.round((occupied / total) * 1000) / 10;
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points.push({ date: dayStr, occupied, total, occupancyPct });
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}
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return { points };
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}
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export async function computeRevenueBreakdown(
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portId: string,
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range: DateRange,
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): Promise<RevenueBreakdownData> {
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const cutoff = rangeToCutoff(range);
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const rows = await db
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.select({
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status: invoices.status,
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currency: invoices.currency,
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amount: sql<string>`coalesce(sum(${invoices.total}), 0)::text`,
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})
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.from(invoices)
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.where(
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and(
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eq(invoices.portId, portId),
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isNull(invoices.archivedAt),
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gte(invoices.createdAt, cutoff),
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),
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)
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.groupBy(invoices.status, invoices.currency);
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return {
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bars: rows.map((r) => ({
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status: r.status,
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currency: r.currency,
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amount: Number(r.amount),
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})),
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};
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}
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export async function computeLeadSourceAttribution(
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portId: string,
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range: DateRange,
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): Promise<LeadSourceAttributionData> {
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const cutoff = rangeToCutoff(range);
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const rows = await db
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.select({ source: interests.source, count: sql<number>`count(*)::int` })
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.from(interests)
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.where(
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and(
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eq(interests.portId, portId),
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isNull(interests.archivedAt),
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gte(interests.createdAt, cutoff),
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),
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)
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.groupBy(interests.source);
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return {
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slices: rows
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.map((r) => ({
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source: r.source ?? 'unspecified',
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count: r.count,
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}))
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.sort((a, b) => b.count - a.count),
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};
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}
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// ─── Public read API (cache → compute → write back) ──────────────────────────
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export async function getPipelineFunnel(
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portId: string,
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range: DateRange,
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): Promise<PipelineFunnelData> {
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const metricId = `pipeline_funnel.${range}` as const;
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const cached = await readSnapshot<PipelineFunnelData>(portId, metricId);
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if (cached) return cached;
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const fresh = await computePipelineFunnel(portId, range);
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await writeSnapshot(portId, metricId, fresh);
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return fresh;
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}
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export async function getOccupancyTimeline(
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portId: string,
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range: DateRange,
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): Promise<OccupancyTimelineData> {
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const metricId = `occupancy_timeline.${range}` as const;
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const cached = await readSnapshot<OccupancyTimelineData>(portId, metricId);
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if (cached) return cached;
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const fresh = await computeOccupancyTimeline(portId, range);
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await writeSnapshot(portId, metricId, fresh);
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return fresh;
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}
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export async function getRevenueBreakdown(
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portId: string,
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range: DateRange,
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): Promise<RevenueBreakdownData> {
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const metricId = `revenue_breakdown.${range}` as const;
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const cached = await readSnapshot<RevenueBreakdownData>(portId, metricId);
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if (cached) return cached;
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const fresh = await computeRevenueBreakdown(portId, range);
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await writeSnapshot(portId, metricId, fresh);
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return fresh;
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}
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export async function getLeadSourceAttribution(
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portId: string,
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range: DateRange,
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): Promise<LeadSourceAttributionData> {
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const metricId = `lead_source_attribution.${range}` as const;
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const cached = await readSnapshot<LeadSourceAttributionData>(portId, metricId);
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if (cached) return cached;
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const fresh = await computeLeadSourceAttribution(portId, range);
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await writeSnapshot(portId, metricId, fresh);
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return fresh;
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}
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// ─── Cron entrypoint: warm every (port × metric × range) ────────────────────
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export async function refreshSnapshotsForPort(portId: string): Promise<void> {
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for (const range of ALL_RANGES) {
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const [funnel, occupancy, revenue, leadSource] = await Promise.all([
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computePipelineFunnel(portId, range),
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computeOccupancyTimeline(portId, range),
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computeRevenueBreakdown(portId, range),
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computeLeadSourceAttribution(portId, range),
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]);
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await Promise.all([
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writeSnapshot(portId, `pipeline_funnel.${range}`, funnel),
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writeSnapshot(portId, `occupancy_timeline.${range}`, occupancy),
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writeSnapshot(portId, `revenue_breakdown.${range}`, revenue),
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writeSnapshot(portId, `lead_source_attribution.${range}`, leadSource),
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]);
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}
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}
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