845 lines
34 KiB
TypeScript
845 lines
34 KiB
TypeScript
import { randomUUID } from 'node:crypto'
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import { hostname } from 'node:os'
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import type { Session } from 'next-auth'
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import mssql from 'mssql'
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import {
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fetchPerformanceSourceRows,
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metricSourceForBrand,
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readTmallStoreSourceRanges,
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sourceMetricDateKey as metricDateKey,
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sourceSnapshotFilter,
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supportsMetricPlatform,
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TMALL_STORE_BRANDS,
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type MetricSource,
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type SourceMetricRow,
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type StoreSourceRange,
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type TmallStoreBrand,
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} from '@/lib/performance-conversion-source'
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import { assertBrandCenterDashboardAccess } from '@/lib/brand-center-dashboard-access'
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import { prisma } from '@/lib/prisma'
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import {
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DING_WORKFLOW_ALLOWED_PROCESS_CODES,
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DING_WORKFLOW_STARTED_AT_CUTOFF_ISO,
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getDingWorkflowSyncMetadata,
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isDingWorkflowApprovedCompletion,
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} from '@/lib/ding-workflow-sync'
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import {
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BUSINESS_TREND_BRANDS,
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addCalendarMonths,
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compareDateKeys,
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daysBetweenInclusive,
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extractValidProductIds,
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isValidDateKey,
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toShanghaiDateKey,
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type PerformanceConversionBrand,
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type PerformanceConversionDailyMetric,
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type PerformanceConversionTimeseries,
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type PerformanceConversionWorkflowItem,
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type PerformanceConversionWorkflowList,
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} from '@/components/department-dashboard/performance-conversion'
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const ART_PROCESS_CODE = DING_WORKFLOW_ALLOWED_PROCESS_CODES[0]
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const VALID_BRANDS = new Set<string>(BUSINESS_TREND_BRANDS)
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const DEFAULT_PAGE_SIZE = 20
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const MAX_PAGE_SIZE = 50
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const SOURCE_CACHE_TTL_MS = 5 * 60 * 1000
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const PERFORMANCE_CONVERSION_SYNC_STATE_ID = 'performance-conversion-daily-v1'
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const SYNC_LEASE_DURATION_MS = 20 * 60 * 1000
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const SYNC_INITIAL_DELAY_MS = 30 * 1000
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const SYNC_DAY_MS = 24 * 60 * 60 * 1000
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const SYNC_LOOKBACK_DAYS = 2
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export class PerformanceConversionError extends Error {
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status: number
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constructor(message: string, status = 400) {
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super(message)
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this.name = 'PerformanceConversionError'
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this.status = status
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}
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}
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type SnapshotRow = {
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processInstanceId: string
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businessId: string | null
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title: string | null
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result: string | null
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bizAction: string | null
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status: string
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processCode: string | null
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brand: string | null
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sourceFinishedAtRaw: string | null
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formFields: unknown
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}
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type CachedSourceRows = { expiresAt: number; rows: SourceMetricRow[] }
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const sourceCache = new Map<string, CachedSourceRows>()
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type PerformanceConversionSourceCursor = {
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version: 2
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lastSourceDate: string | null
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tmallStoreDates: Partial<Record<TmallStoreBrand, string | null>>
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}
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export type PerformanceConversionSyncStatus = 'pending' | 'syncing' | 'ready' | 'error'
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export type PerformanceConversionSyncMetadata = {
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status: PerformanceConversionSyncStatus
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lastCompletedAt: string | null
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lastSourceDate: string | null
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}
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function clean(value: unknown) {
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const normalized = String(value ?? '').trim()
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return normalized && normalized.toUpperCase() !== 'NULL' && normalized !== '--' ? normalized : null
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}
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function formRecord(value: unknown): Record<string, unknown> {
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return value && typeof value === 'object' && !Array.isArray(value)
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? value as Record<string, unknown>
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: {}
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}
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function workflowItems(row: SnapshotRow): PerformanceConversionWorkflowItem[] {
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const brand = clean(row.brand)
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const completedAt = clean(row.sourceFinishedAtRaw)
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if (!brand || !VALID_BRANDS.has(brand) || !completedAt) return []
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const monitorStartDate = toShanghaiDateKey(completedAt)
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if (!monitorStartDate) return []
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const fields = formRecord(row.formFields)
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const ids = extractValidProductIds(fields.productId, fields.currentProductId)
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const monitorEndDate = addCalendarMonths(monitorStartDate, 6)
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const today = toShanghaiDateKey(new Date()) || monitorStartDate
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return ids.map((productId) => ({
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key: `${row.processInstanceId}:${productId}`,
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workflowId: row.processInstanceId,
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approvalNumber: clean(row.businessId),
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processCode: clean(row.processCode) || ART_PROCESS_CODE,
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title: clean(row.title) || '未命名流程',
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brand: brand as PerformanceConversionBrand,
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productId,
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spu: clean(fields.spu),
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platform: clean(fields.platform),
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completedAt,
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monitorStartDate,
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monitorEndDate,
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monitoringStatus: compareDateKeys(today, monitorEndDate) <= 0 ? 'monitoring' : 'complete',
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}))
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}
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function isEligibleSnapshot(row: SnapshotRow) {
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return row.processCode === ART_PROCESS_CODE
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&& Boolean(row.sourceFinishedAtRaw)
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&& isDingWorkflowApprovedCompletion(row.status, row.result, row.bizAction)
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}
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async function readEligibleSnapshots(): Promise<SnapshotRow[]> {
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const rows = await prisma.dingWorkflowSnapshot.findMany({
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where: {
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processCode: ART_PROCESS_CODE,
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sourceCreatedAtRaw: { gte: DING_WORKFLOW_STARTED_AT_CUTOFF_ISO },
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sourceFinishedAtRaw: { not: null },
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},
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select: {
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processInstanceId: true,
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businessId: true,
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title: true,
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result: true,
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bizAction: true,
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status: true,
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processCode: true,
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brand: true,
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sourceFinishedAtRaw: true,
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formFields: true,
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},
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orderBy: [
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{ sourceFinishedAtRaw: 'desc' },
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{ processInstanceId: 'desc' },
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],
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})
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return rows.filter(isEligibleSnapshot)
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}
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export async function getPerformanceConversionWorkflows(
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session: Session | null,
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input: {
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brand?: string | null
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page?: number
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pageSize?: number
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query?: string | null
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completedFrom?: string | null
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completedTo?: string | null
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} = {},
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): Promise<PerformanceConversionWorkflowList> {
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await assertBrandCenterDashboardAccess(session)
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const brand = clean(input.brand) || BUSINESS_TREND_BRANDS[0]
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if (!VALID_BRANDS.has(brand)) throw new PerformanceConversionError('品牌参数无效')
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const page = Math.max(1, Math.floor(Number(input.page) || 1))
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const pageSize = Math.max(1, Math.min(MAX_PAGE_SIZE, Math.floor(Number(input.pageSize) || DEFAULT_PAGE_SIZE)))
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const query = clean(input.query)?.toLocaleLowerCase('zh-CN') || ''
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const completedFrom = clean(input.completedFrom)
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const completedTo = clean(input.completedTo)
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if (completedFrom && !isValidDateKey(completedFrom)) throw new PerformanceConversionError('完结开始日期格式无效')
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if (completedTo && !isValidDateKey(completedTo)) throw new PerformanceConversionError('完结结束日期格式无效')
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if (completedFrom && completedTo && compareDateKeys(completedFrom, completedTo) > 0) {
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throw new PerformanceConversionError('完结开始日期不能晚于结束日期')
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}
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const [snapshots, workflowSync, performanceSync] = await Promise.all([
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readEligibleSnapshots(),
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getDingWorkflowSyncMetadata(),
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getPerformanceConversionSyncMetadata(brand as PerformanceConversionBrand),
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])
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const rangeSnapshots = snapshots.filter((row) => {
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const completedDate = row.sourceFinishedAtRaw ? toShanghaiDateKey(row.sourceFinishedAtRaw) : null
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if (!completedDate) return false
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return (!completedFrom || compareDateKeys(completedDate, completedFrom) >= 0)
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&& (!completedTo || compareDateKeys(completedDate, completedTo) <= 0)
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})
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const allItems = rangeSnapshots.flatMap(workflowItems)
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const brandCounts = new Map<PerformanceConversionBrand, number>(
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BUSINESS_TREND_BRANDS.map((item) => [item, 0]),
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)
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allItems.forEach((item) => brandCounts.set(item.brand, (brandCounts.get(item.brand) || 0) + 1))
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const brandSnapshots = rangeSnapshots.filter((row) => row.brand === brand)
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const invalidProductIdCount = brandSnapshots.filter((row) => workflowItems(row).length === 0).length
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const filtered = allItems.filter((item) => item.brand === brand && (!query || [
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item.productId,
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item.spu,
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item.approvalNumber,
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item.workflowId,
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item.title,
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].some((value) => String(value || '').toLocaleLowerCase('zh-CN').includes(query))))
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const offset = (page - 1) * pageSize
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return {
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brands: BUSINESS_TREND_BRANDS.map((item) => ({ brand: item, count: brandCounts.get(item) || 0 })),
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items: filtered.slice(offset, offset + pageSize),
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total: filtered.length,
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invalidProductIdCount,
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page,
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pageSize,
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hasMore: offset + pageSize < filtered.length,
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workflowSync,
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performanceSync,
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}
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}
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function sourceDbConfigured() {
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return Boolean(
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process.env.REPORT_DB_SERVER
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&& process.env.REPORT_DB_DATABASE
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&& process.env.REPORT_DB_USER
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&& process.env.REPORT_DB_PASSWORD,
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)
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}
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function sourceConfig() {
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if (!sourceDbConfigured()) throw new PerformanceConversionError('经营数据源尚未配置', 503)
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return {
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server: process.env.REPORT_DB_SERVER as string,
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database: process.env.REPORT_DB_DATABASE as string,
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user: process.env.REPORT_DB_USER as string,
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password: process.env.REPORT_DB_PASSWORD as string,
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port: Number(process.env.REPORT_DB_PORT || 1433),
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options: {
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encrypt: process.env.REPORT_DB_ENCRYPT === 'true',
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trustServerCertificate: process.env.REPORT_DB_TRUST_SERVER_CERTIFICATE !== 'false',
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enableArithAbort: true,
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},
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connectionTimeout: 15_000,
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requestTimeout: 60_000,
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pool: { max: 4, min: 0, idleTimeoutMillis: 10_000 },
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}
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}
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function dateKeyToUtcDate(value: string) {
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return new Date(`${value}T00:00:00.000Z`)
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}
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function shiftDateKey(value: string, days: number) {
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const date = dateKeyToUtcDate(value)
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date.setUTCDate(date.getUTCDate() + days)
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return date.toISOString().slice(0, 10)
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}
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function maxDateKey(left: string, right: string) {
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return compareDateKeys(left, right) >= 0 ? left : right
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}
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function parsePerformanceConversionSourceCursor(value: string | null): PerformanceConversionSourceCursor {
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const empty: PerformanceConversionSourceCursor = { version: 2, lastSourceDate: null, tmallStoreDates: {} }
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if (!value) return empty
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try {
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const parsed = JSON.parse(value) as Partial<PerformanceConversionSourceCursor>
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const tmallStoreDates: PerformanceConversionSourceCursor['tmallStoreDates'] = {}
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if (parsed.version === 2 && parsed.tmallStoreDates && typeof parsed.tmallStoreDates === 'object') {
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for (const brand of TMALL_STORE_BRANDS) {
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const date = parsed.tmallStoreDates[brand]
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if (date === null || isValidDateKey(date)) tmallStoreDates[brand] = date
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}
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}
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return {
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version: 2,
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lastSourceDate: typeof parsed.lastSourceDate === 'string' && isValidDateKey(parsed.lastSourceDate)
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? parsed.lastSourceDate
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: null,
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tmallStoreDates,
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}
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} catch {
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return empty
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}
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}
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function serializePerformanceConversionSourceCursor(cursor: PerformanceConversionSourceCursor) {
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return JSON.stringify(cursor)
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}
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function normalizePerformanceConversionSyncStatus(state: { status: string; lastCompletedAt: Date | null } | null): PerformanceConversionSyncStatus {
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if (!state?.lastCompletedAt) {
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return state?.status === 'syncing' ? 'syncing' : state?.status === 'error' ? 'error' : 'pending'
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}
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if (state.status === 'syncing') return 'syncing'
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if (state.status === 'error') return 'error'
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return 'ready'
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}
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export async function getPerformanceConversionSyncMetadata(brand?: PerformanceConversionBrand): Promise<PerformanceConversionSyncMetadata> {
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// Keep isolated unit tests and pre-migration local shells readable while the
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// additive table is being introduced. Production Prisma clients always have
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// this delegate after the migration has been applied.
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const syncState = (prisma as typeof prisma & {
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performanceConversionSyncState?: typeof prisma.performanceConversionSyncState
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}).performanceConversionSyncState
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if (!syncState) {
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return { status: 'pending', lastCompletedAt: null, lastSourceDate: null }
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}
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try {
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const state = await syncState.findUnique({
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where: { id: PERFORMANCE_CONVERSION_SYNC_STATE_ID },
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select: { status: true, lastCompletedAt: true, sourceCursorRaw: true },
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})
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const cursor = parsePerformanceConversionSourceCursor(state?.sourceCursorRaw || null)
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const source = brand ? metricSourceForBrand(brand) : { kind: 'legacy' as const }
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if (source.kind === 'tmall-store' && !(source.brand in cursor.tmallStoreDates)) {
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return { status: state?.status === 'error' ? 'error' : state?.status === 'syncing' ? 'syncing' : 'pending', lastCompletedAt: null, lastSourceDate: null }
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}
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return {
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status: normalizePerformanceConversionSyncStatus(state),
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lastCompletedAt: state?.lastCompletedAt?.toISOString() || null,
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lastSourceDate: source.kind === 'tmall-store' ? cursor.tmallStoreDates[source.brand] || null : cursor.lastSourceDate,
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}
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} catch (error) {
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console.warn('[performance-conversion-sync] 同步状态读取失败，暂按首次同步处理：', error)
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return { status: 'pending', lastCompletedAt: null, lastSourceDate: null }
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}
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}
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async function readSnapshotRows(source: MetricSource, productId: string, startDate: string, endDate: string) {
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const rows = await prisma.performanceConversionMetricSnapshot.findMany({
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where: {
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productId,
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...sourceSnapshotFilter(source),
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metricDate: {
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gte: dateKeyToUtcDate(startDate),
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lte: dateKeyToUtcDate(endDate),
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},
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},
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orderBy: [{ metricDate: 'asc' }, { sourceRowId: 'asc' }],
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})
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return rows.map((row) => ({
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sourceRowId: row.sourceRowId,
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metricDate: row.metricDate,
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productId: row.productId,
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productName: row.productName,
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sourceBrand: row.sourceBrand,
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category1: row.category1,
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category2: row.category2,
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category3: row.category3,
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paymentAmount: row.paymentAmount,
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paymentUsers: row.paymentUsers,
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cartUsers: row.cartUsers,
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visitors: row.visitors,
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conversionRate: row.conversionRate,
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favorites: row.favorites,
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impressions: row.impressions,
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clicks: row.clicks,
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clickRate: row.clickRate,
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promotionSpend: row.promotionSpend,
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promotionRevenue: row.promotionRevenue,
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roi: row.roi,
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})) satisfies SourceMetricRow[]
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}
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async function readUpstreamSourceRows(source: MetricSource, productId: string, startDate: string, endDate: string) {
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const cacheKey = `upstream:${source.kind === 'tmall-store' ? source.keyPrefix : 'legacy'}:${productId}:${startDate}:${endDate}`
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const cached = sourceCache.get(cacheKey)
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if (cached && cached.expiresAt > Date.now()) return cached.rows
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const pool = new mssql.ConnectionPool(sourceConfig())
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try {
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await pool.connect()
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const rows = await fetchPerformanceSourceRows(pool, source, productId, startDate, endDate)
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sourceCache.set(cacheKey, { rows, expiresAt: Date.now() + SOURCE_CACHE_TTL_MS })
|
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return rows
|
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} finally {
|
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await pool.close().catch(() => undefined)
|
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}
|
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}
|
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async function readSourceRows(brand: PerformanceConversionBrand, productId: string, startDate: string, endDate: string) {
|
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const source = metricSourceForBrand(brand)
|
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const sync = await getPerformanceConversionSyncMetadata(brand)
|
||
if (sync.lastCompletedAt) {
|
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const localRows = await readSnapshotRows(source, productId, startDate, endDate)
|
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if (localRows.length > 0) {
|
||
return localRows
|
||
}
|
||
// A newly synced workflow may not be included in the previous daily run.
|
||
// Keep the old direct read only for that bootstrap gap; the next scheduled
|
||
// run will persist the same product into the local snapshot.
|
||
}
|
||
return readUpstreamSourceRows(source, productId, startDate, endDate)
|
||
}
|
||
|
||
type MetricProductWindow = {
|
||
source: MetricSource
|
||
productId: string
|
||
startDate: string
|
||
endDate: string
|
||
}
|
||
|
||
function getMetricProductWindows(snapshots: SnapshotRow[], today: string): MetricProductWindow[] {
|
||
const windows = new Map<string, MetricProductWindow>()
|
||
snapshots.flatMap(workflowItems).forEach((item) => {
|
||
const source = metricSourceForBrand(item.brand)
|
||
if (!supportsMetricPlatform(source, item.platform)) return
|
||
const key = `${source.kind === 'tmall-store' ? source.keyPrefix : 'legacy'}:${item.productId}`
|
||
const endDate = compareDateKeys(today, item.monitorEndDate) <= 0 ? today : item.monitorEndDate
|
||
const existing = windows.get(key)
|
||
if (!existing) {
|
||
windows.set(key, { source, productId: item.productId, startDate: item.monitorStartDate, endDate })
|
||
return
|
||
}
|
||
existing.startDate = compareDateKeys(item.monitorStartDate, existing.startDate) < 0
|
||
? item.monitorStartDate
|
||
: existing.startDate
|
||
existing.endDate = maxDateKey(existing.endDate, endDate)
|
||
})
|
||
return Array.from(windows.values()).filter((item) => compareDateKeys(item.startDate, item.endDate) <= 0)
|
||
}
|
||
|
||
async function acquirePerformanceConversionSyncLease(leaseOwner: string, startedAt: Date) {
|
||
await prisma.performanceConversionSyncState.upsert({
|
||
where: { id: PERFORMANCE_CONVERSION_SYNC_STATE_ID },
|
||
create: { id: PERFORMANCE_CONVERSION_SYNC_STATE_ID },
|
||
update: {},
|
||
})
|
||
const claimed = await prisma.performanceConversionSyncState.updateMany({
|
||
where: {
|
||
id: PERFORMANCE_CONVERSION_SYNC_STATE_ID,
|
||
OR: [
|
||
{ leaseExpiresAt: null },
|
||
{ leaseExpiresAt: { lt: startedAt } },
|
||
{ leaseOwner },
|
||
],
|
||
},
|
||
data: {
|
||
status: 'syncing',
|
||
lastStartedAt: startedAt,
|
||
lastError: null,
|
||
leaseOwner,
|
||
leaseExpiresAt: new Date(startedAt.getTime() + SYNC_LEASE_DURATION_MS),
|
||
},
|
||
})
|
||
if (claimed.count !== 1) return null
|
||
return prisma.performanceConversionSyncState.findUniqueOrThrow({
|
||
where: { id: PERFORMANCE_CONVERSION_SYNC_STATE_ID },
|
||
})
|
||
}
|
||
|
||
async function renewPerformanceConversionSyncLease(leaseOwner: string) {
|
||
const renewed = await prisma.performanceConversionSyncState.updateMany({
|
||
where: { id: PERFORMANCE_CONVERSION_SYNC_STATE_ID, leaseOwner },
|
||
data: { leaseExpiresAt: new Date(Date.now() + SYNC_LEASE_DURATION_MS) },
|
||
})
|
||
if (renewed.count !== 1) throw new Error('经营数据同步租约已失效，本轮停止写入')
|
||
}
|
||
|
||
function toMetricSnapshotData(row: SourceMetricRow, source: MetricSource, productId: string, syncedAt: Date, index: number) {
|
||
const metricDate = metricDateKey(row.metricDate)
|
||
if (!metricDate) return null
|
||
const sourceRowId = clean(row.sourceRowId)
|
||
return {
|
||
id: randomUUID(),
|
||
sourceKey: source.kind === 'tmall-store'
|
||
? `${source.keyPrefix}${productId}:${metricDate}`
|
||
: `${productId}:${metricDate}:${sourceRowId || `row-${index}`}`,
|
||
sourceRowId,
|
||
productId,
|
||
metricDate: dateKeyToUtcDate(metricDate),
|
||
productName: clean(row.productName),
|
||
sourceBrand: clean(row.sourceBrand),
|
||
category1: clean(row.category1),
|
||
category2: clean(row.category2),
|
||
category3: clean(row.category3),
|
||
paymentAmount: clean(row.paymentAmount),
|
||
paymentUsers: clean(row.paymentUsers),
|
||
cartUsers: clean(row.cartUsers),
|
||
visitors: clean(row.visitors),
|
||
conversionRate: clean(row.conversionRate),
|
||
favorites: clean(row.favorites),
|
||
impressions: clean(row.impressions),
|
||
clicks: clean(row.clicks),
|
||
clickRate: clean(row.clickRate),
|
||
promotionSpend: clean(row.promotionSpend),
|
||
promotionRevenue: clean(row.promotionRevenue),
|
||
roi: clean(row.roi),
|
||
syncedAt,
|
||
createdAt: syncedAt,
|
||
updatedAt: syncedAt,
|
||
}
|
||
}
|
||
|
||
export async function syncPerformanceConversionMetrics() {
|
||
if (!sourceDbConfigured()) throw new Error('未配置上游报表库（REPORT_DB_*），无法同步经营数据')
|
||
|
||
const startedAt = new Date()
|
||
const leaseOwner = `${hostname()}:${process.pid}:${randomUUID()}`
|
||
const state = await acquirePerformanceConversionSyncLease(leaseOwner, startedAt)
|
||
if (!state) return { skipped: true, rowsUpserted: 0, productsSynced: 0 }
|
||
|
||
const pool = new mssql.ConnectionPool(sourceConfig())
|
||
let rowsUpserted = 0
|
||
let productsSynced = 0
|
||
try {
|
||
await pool.connect()
|
||
const cursor = parsePerformanceConversionSourceCursor(state.sourceCursorRaw)
|
||
const today = toShanghaiDateKey(new Date())
|
||
if (!today) throw new Error('无法确定上海时区的当前日期')
|
||
const snapshots = await readEligibleSnapshots()
|
||
const windows = getMetricProductWindows(snapshots, today)
|
||
const storeRanges = windows.some((window) => window.source.kind === 'tmall-store')
|
||
? await readTmallStoreSourceRanges(pool, today)
|
||
: new Map<TmallStoreBrand, StoreSourceRange>()
|
||
const tmallStoreDates = { ...cursor.tmallStoreDates }
|
||
const syncStartedAt = new Date()
|
||
|
||
for (const window of windows) {
|
||
await renewPerformanceConversionSyncLease(leaseOwner)
|
||
const source = window.source
|
||
const scopeFilter = sourceSnapshotFilter(source)
|
||
const existing = await prisma.performanceConversionMetricSnapshot.findFirst({
|
||
where: { productId: window.productId, ...scopeFilter },
|
||
select: { id: true },
|
||
})
|
||
// The legacy cursor cannot stand in for the first sync of a new source.
|
||
const lastSourceDate = source.kind === 'tmall-store' ? cursor.tmallStoreDates[source.brand] : cursor.lastSourceDate
|
||
const incrementalStart = lastSourceDate
|
||
? shiftDateKey(lastSourceDate, -SYNC_LOOKBACK_DAYS)
|
||
: window.startDate
|
||
let startDate = existing ? maxDateKey(window.startDate, incrementalStart) : window.startDate
|
||
let endDate = window.endDate
|
||
if (source.kind === 'tmall-store') {
|
||
const retainedRange = storeRanges.get(source.brand)
|
||
// An empty/missing store must not purge its previously retained history.
|
||
if (!retainedRange) continue
|
||
startDate = maxDateKey(startDate, retainedRange.firstDate)
|
||
endDate = compareDateKeys(endDate, retainedRange.lastDate) < 0 ? endDate : retainedRange.lastDate
|
||
tmallStoreDates[source.brand] = retainedRange.correctionThrough
|
||
}
|
||
if (compareDateKeys(startDate, endDate) > 0) continue
|
||
|
||
const sourceRows = await fetchPerformanceSourceRows(pool, source, window.productId, startDate, endDate)
|
||
const snapshotsToWrite = sourceRows
|
||
.map((row, index) => toMetricSnapshotData(row, source, window.productId, syncStartedAt, index))
|
||
.filter((row): row is NonNullable<ReturnType<typeof toMetricSnapshotData>> => row !== null)
|
||
|
||
await prisma.$transaction(async (tx) => {
|
||
// The supplemental ROI view can lag the Overall view or roll away a
|
||
// month. Preserve only prior supplemental values when its row is absent;
|
||
// a present row with an explicit null/zero remains authoritative.
|
||
if (source.kind === 'tmall-store' && sourceRows.some((row) => !row.promotionSourceRowId)) {
|
||
const previous = await tx.performanceConversionMetricSnapshot.findMany({
|
||
where: {
|
||
productId: window.productId, ...scopeFilter,
|
||
metricDate: { gte: dateKeyToUtcDate(startDate), lte: dateKeyToUtcDate(endDate) },
|
||
},
|
||
select: { sourceKey: true, impressions: true, promotionSpend: true, promotionRevenue: true, roi: true },
|
||
})
|
||
const byKey = new Map(previous.map((row) => [row.sourceKey, row]))
|
||
snapshotsToWrite.forEach((snapshot, index) => {
|
||
const prior = byKey.get(snapshot.sourceKey)
|
||
if (prior && !sourceRows[index].promotionSourceRowId) {
|
||
snapshot.impressions = prior.impressions
|
||
snapshot.promotionSpend = prior.promotionSpend
|
||
snapshot.promotionRevenue = prior.promotionRevenue
|
||
snapshot.roi = prior.roi
|
||
}
|
||
})
|
||
}
|
||
// Fence the replacement in the same transaction as its writes.
|
||
const lease = await tx.performanceConversionSyncState.updateMany({
|
||
where: { id: PERFORMANCE_CONVERSION_SYNC_STATE_ID, leaseOwner, leaseExpiresAt: { gt: new Date() } },
|
||
data: { leaseExpiresAt: new Date(Date.now() + SYNC_LEASE_DURATION_MS) },
|
||
})
|
||
if (lease.count !== 1) throw new Error('经营数据同步租约已失效，本轮停止写入')
|
||
await tx.performanceConversionMetricSnapshot.deleteMany({
|
||
where: {
|
||
productId: window.productId,
|
||
...scopeFilter,
|
||
metricDate: { gte: dateKeyToUtcDate(startDate), lte: dateKeyToUtcDate(endDate) },
|
||
// Monthly views are not a deletion feed: missing source dates must
|
||
// not remove already ingested daily history.
|
||
...(source.kind === 'tmall-store' ? { AND: { sourceKey: { in: snapshotsToWrite.map((row) => row.sourceKey) } } } : {}),
|
||
},
|
||
})
|
||
if (snapshotsToWrite.length > 0) {
|
||
await tx.performanceConversionMetricSnapshot.createMany({ data: snapshotsToWrite })
|
||
}
|
||
})
|
||
rowsUpserted += snapshotsToWrite.length
|
||
productsSynced += 1
|
||
}
|
||
|
||
sourceCache.clear()
|
||
const sourceCursorRaw = serializePerformanceConversionSourceCursor({ version: 2, lastSourceDate: today, tmallStoreDates })
|
||
const completed = await prisma.performanceConversionSyncState.updateMany({
|
||
where: { id: PERFORMANCE_CONVERSION_SYNC_STATE_ID, leaseOwner },
|
||
data: {
|
||
status: 'ready',
|
||
sourceCursorRaw,
|
||
lastCompletedAt: syncStartedAt,
|
||
lastError: null,
|
||
leaseOwner: null,
|
||
leaseExpiresAt: null,
|
||
rowsUpserted,
|
||
productsSynced,
|
||
},
|
||
})
|
||
if (completed.count !== 1) throw new Error('经营数据同步租约已失效，本轮不能标记为成功')
|
||
return { skipped: false, rowsUpserted, productsSynced }
|
||
} catch (error) {
|
||
const message = error instanceof Error ? error.message : String(error)
|
||
await prisma.performanceConversionSyncState.updateMany({
|
||
where: { id: PERFORMANCE_CONVERSION_SYNC_STATE_ID, leaseOwner },
|
||
data: {
|
||
status: 'error',
|
||
lastError: message.slice(0, 2_000),
|
||
leaseOwner: null,
|
||
leaseExpiresAt: null,
|
||
},
|
||
}).catch(() => undefined)
|
||
throw error
|
||
} finally {
|
||
await pool.close().catch(() => undefined)
|
||
}
|
||
}
|
||
|
||
type PerformanceConversionSyncGlobal = typeof globalThis & {
|
||
__performanceConversionDailySyncStarted?: boolean
|
||
}
|
||
|
||
export function ensureDailyPerformanceConversionSyncStarted() {
|
||
const schedulerGlobal = globalThis as PerformanceConversionSyncGlobal
|
||
if (schedulerGlobal.__performanceConversionDailySyncStarted) return
|
||
schedulerGlobal.__performanceConversionDailySyncStarted = true
|
||
|
||
if (!sourceDbConfigured()) {
|
||
console.info('[performance-conversion-sync] 未配置上游报表库，跳过每日经营数据同步')
|
||
return
|
||
}
|
||
|
||
const runOnce = () => {
|
||
void syncPerformanceConversionMetrics()
|
||
.then((result) => {
|
||
if (result.skipped) {
|
||
console.info('[performance-conversion-sync] 另一实例正在同步，本轮跳过')
|
||
return
|
||
}
|
||
console.info(`[performance-conversion-sync] 同步完成：更新 ${result.rowsUpserted} 条，商品 ${result.productsSynced} 个`)
|
||
})
|
||
.catch((error) => console.warn('[performance-conversion-sync] 同步失败：', error))
|
||
}
|
||
|
||
const initialTimer = setTimeout(runOnce, SYNC_INITIAL_DELAY_MS)
|
||
initialTimer.unref?.()
|
||
const scheduleNext = () => {
|
||
const timer = setTimeout(() => {
|
||
runOnce()
|
||
scheduleNext()
|
||
}, nextPerformanceConversionSyncDelay(new Date()))
|
||
timer.unref?.()
|
||
}
|
||
scheduleNext()
|
||
console.info('[performance-conversion-sync] 已调度经营数据每日增量同步：上海时间 15:00（上游视图 14:30 刷新），按来源日期回看两天校准')
|
||
}
|
||
|
||
export function nextPerformanceConversionSyncDelay(now: Date) {
|
||
// 15:00 Asia/Shanghai is 07:00 UTC, independent of the host timezone.
|
||
const next = new Date(now)
|
||
next.setUTCHours(7, 0, 0, 0)
|
||
if (next.getTime() <= now.getTime()) next.setTime(next.getTime() + SYNC_DAY_MS)
|
||
return next.getTime() - now.getTime()
|
||
}
|
||
|
||
function numberValue(value: unknown) {
|
||
const normalized = clean(value)?.replace(/[,%￥¥\s]/g, '')
|
||
if (!normalized) return null
|
||
const parsed = Number(normalized)
|
||
if (!Number.isFinite(parsed)) return null
|
||
return String(value).includes('%') ? parsed / 100 : parsed
|
||
}
|
||
|
||
function sum(values: Array<number | null>) {
|
||
const present = values.filter((value): value is number => value !== null)
|
||
return present.length ? present.reduce((total, value) => total + value, 0) : null
|
||
}
|
||
|
||
function average(values: Array<number | null>) {
|
||
const present = values.filter((value): value is number => value !== null)
|
||
return present.length ? present.reduce((total, value) => total + value, 0) / present.length : null
|
||
}
|
||
|
||
function ratio(numerator: number | null, denominator: number | null, fallback: number | null) {
|
||
return denominator !== null && denominator > 0 && numerator !== null ? numerator / denominator : fallback
|
||
}
|
||
|
||
function aggregateRows(rows: SourceMetricRow[], source: MetricSource) {
|
||
const grouped = new Map<string, SourceMetricRow[]>()
|
||
rows.forEach((row) => {
|
||
const key = metricDateKey(row.metricDate)
|
||
if (key) grouped.set(key, [...(grouped.get(key) || []), row])
|
||
})
|
||
return Array.from(grouped.entries()).sort(([left], [right]) => left.localeCompare(right)).map(([date, dayRows]): PerformanceConversionDailyMetric => {
|
||
const impressions = sum(dayRows.map((row) => numberValue(row.impressions)))
|
||
const clicks = sum(dayRows.map((row) => numberValue(row.clicks)))
|
||
const visitors = sum(dayRows.map((row) => numberValue(row.visitors)))
|
||
const paymentUsers = sum(dayRows.map((row) => numberValue(row.paymentUsers)))
|
||
const promotionSpend = sum(dayRows.map((row) => numberValue(row.promotionSpend)))
|
||
const promotionRevenue = sum(dayRows.map((row) => numberValue(row.promotionRevenue)))
|
||
return {
|
||
date,
|
||
impressions,
|
||
visitors,
|
||
clickRate: source.kind === 'tmall-store'
|
||
? average(dayRows.map((row) => numberValue(row.clickRate)))
|
||
: ratio(clicks, impressions, average(dayRows.map((row) => numberValue(row.clickRate)))),
|
||
favorites: sum(dayRows.map((row) => numberValue(row.favorites))),
|
||
cartUsers: sum(dayRows.map((row) => numberValue(row.cartUsers))),
|
||
paymentConversionRate: source.kind === 'tmall-store'
|
||
? average(dayRows.map((row) => numberValue(row.conversionRate)))
|
||
: ratio(paymentUsers, visitors, average(dayRows.map((row) => numberValue(row.conversionRate)))),
|
||
paymentAmount: sum(dayRows.map((row) => numberValue(row.paymentAmount))),
|
||
roi: source.kind === 'tmall-store'
|
||
? average(dayRows.map((row) => numberValue(row.roi)))
|
||
: ratio(promotionRevenue, promotionSpend, average(dayRows.map((row) => numberValue(row.roi)))),
|
||
}
|
||
})
|
||
}
|
||
|
||
function expandDailyRange(
|
||
source: PerformanceConversionDailyMetric[],
|
||
startDate: string,
|
||
endDate: string,
|
||
) {
|
||
const byDate = new Map(source.map((item) => [item.date, item]))
|
||
const expanded: PerformanceConversionDailyMetric[] = []
|
||
const cursor = new Date(`${startDate}T00:00:00Z`)
|
||
const end = new Date(`${endDate}T00:00:00Z`)
|
||
while (cursor <= end) {
|
||
const date = cursor.toISOString().slice(0, 10)
|
||
expanded.push(byDate.get(date) || {
|
||
date,
|
||
impressions: null,
|
||
visitors: null,
|
||
clickRate: null,
|
||
favorites: null,
|
||
cartUsers: null,
|
||
paymentConversionRate: null,
|
||
paymentAmount: null,
|
||
roi: null,
|
||
})
|
||
cursor.setUTCDate(cursor.getUTCDate() + 1)
|
||
}
|
||
return expanded
|
||
}
|
||
|
||
function normalizeSourceBrand(value: unknown): PerformanceConversionBrand | null {
|
||
const normalized = clean(value)?.toLowerCase()
|
||
if (!normalized) return null
|
||
return BUSINESS_TREND_BRANDS.find((brand) => normalized.includes(brand.toLowerCase())) || null
|
||
}
|
||
|
||
function latestClean(rows: SourceMetricRow[], field: keyof SourceMetricRow) {
|
||
for (let index = rows.length - 1; index >= 0; index -= 1) {
|
||
const value = clean(rows[index][field])
|
||
if (value) return value
|
||
}
|
||
return null
|
||
}
|
||
|
||
export async function getPerformanceConversionTimeseries(
|
||
session: Session | null,
|
||
input: { workflowId?: string | null; productId?: string | null },
|
||
): Promise<PerformanceConversionTimeseries> {
|
||
await assertBrandCenterDashboardAccess(session)
|
||
const workflowId = clean(input.workflowId)
|
||
const productId = extractValidProductIds(input.productId)[0]
|
||
if (!workflowId || !productId) throw new PerformanceConversionError('流程或商品 ID 参数无效')
|
||
|
||
const row = await prisma.dingWorkflowSnapshot.findUnique({
|
||
where: { processInstanceId: workflowId },
|
||
select: {
|
||
processInstanceId: true,
|
||
businessId: true,
|
||
title: true,
|
||
result: true,
|
||
bizAction: true,
|
||
status: true,
|
||
processCode: true,
|
||
brand: true,
|
||
sourceFinishedAtRaw: true,
|
||
formFields: true,
|
||
syncedAt: true,
|
||
},
|
||
})
|
||
if (!row || !isEligibleSnapshot(row)) throw new PerformanceConversionError('未找到可监控的已完结美术流程', 404)
|
||
const workflow = workflowItems(row).find((item) => item.productId === productId)
|
||
if (!workflow) throw new PerformanceConversionError('商品 ID 不属于该流程', 403)
|
||
|
||
const today = toShanghaiDateKey(new Date()) || workflow.monitorStartDate
|
||
const queryEndDate = compareDateKeys(today, workflow.monitorEndDate) < 0 ? today : workflow.monitorEndDate
|
||
const source = metricSourceForBrand(workflow.brand)
|
||
const rows = compareDateKeys(queryEndDate, workflow.monitorStartDate) >= 0 && supportsMetricPlatform(source, workflow.platform)
|
||
? await readSourceRows(workflow.brand, productId, workflow.monitorStartDate, queryEndDate)
|
||
: []
|
||
const sourceDaily = aggregateRows(rows, source)
|
||
const daily = compareDateKeys(queryEndDate, workflow.monitorStartDate) >= 0
|
||
? expandDailyRange(sourceDaily, workflow.monitorStartDate, queryEndDate)
|
||
: []
|
||
const sourceBrand = normalizeSourceBrand(latestClean(rows, 'sourceBrand'))
|
||
const category = [latestClean(rows, 'category1'), latestClean(rows, 'category2'), latestClean(rows, 'category3')]
|
||
.filter(Boolean).join(' / ') || null
|
||
|
||
return {
|
||
workflow,
|
||
product: {
|
||
id: productId,
|
||
name: latestClean(rows, 'productName'),
|
||
sourceBrand: latestClean(rows, 'sourceBrand'),
|
||
category,
|
||
brandMatchesWorkflow: sourceBrand ? sourceBrand === workflow.brand : null,
|
||
},
|
||
latest: sourceDaily[sourceDaily.length - 1] || null,
|
||
daily,
|
||
coverage: {
|
||
sourceFirstDate: sourceDaily[0]?.date || null,
|
||
sourceLatestDate: sourceDaily[sourceDaily.length - 1]?.date || null,
|
||
coveredDays: sourceDaily.length,
|
||
expectedDaysToDate: daysBetweenInclusive(workflow.monitorStartDate, queryEndDate),
|
||
monitorStartDate: workflow.monitorStartDate,
|
||
monitorEndDate: workflow.monitorEndDate,
|
||
},
|
||
}
|
||
}
|