gongxiangp2/lib/performance-conversion-source.ts

import mssql, { type ConnectionPool } from 'mssql'
import type { PerformanceConversionBrand } from '@/components/department-dashboard/performance-conversion'

export const TMALL_STORE_SOURCE_PREFIX = 'tmall-store-v1:'
export const TMALL_STORE_BRANDS = ['顾家', '索菲亚', '朴美'] as const
export type TmallStoreBrand = typeof TMALL_STORE_BRANDS[number]
const STORES: Record<TmallStoreBrand, string> = {
  顾家: '顾家家居小件家具旗舰店',
  索菲亚: '索菲亚实木风旗舰店',
  朴美: '朴美家具旗舰店',
}
const MAX_SOURCE_ROWS = 5000

export type MetricSource = {
  kind: 'legacy'
} | {
  kind: 'tmall-store'
  brand: TmallStoreBrand
  store: string
  keyPrefix: string
}

export type SourceMetricRow = {
  sourceRowId: string | null
  metricDate: Date | string | null
  productId: string | null
  productName: string | null
  sourceBrand: string | null
  category1: string | null
  category2: string | null
  category3: string | null
  paymentAmount: string | null
  paymentUsers: string | null
  cartUsers: string | null
  visitors: string | null
  conversionRate: string | null
  favorites: string | null
  impressions: string | null
  clicks: string | null
  clickRate: string | null
  promotionSpend: string | null
  promotionRevenue: string | null
  roi: string | null
  promotionSourceRowId?: string | null
}

export function metricSourceForBrand(brand: PerformanceConversionBrand): MetricSource {
  if (!Object.prototype.hasOwnProperty.call(STORES, brand)) return { kind: 'legacy' }
  const storeBrand = brand as TmallStoreBrand
  return { kind: 'tmall-store', brand: storeBrand, store: STORES[storeBrand], keyPrefix: `${TMALL_STORE_SOURCE_PREFIX}${storeBrand}:` }
}

export function supportsMetricPlatform(source: MetricSource, platform: string | null) {
  // A legacy missing platform is still resolved by the exact store/product key.
  // An explicitly non-Tmall workflow must never consume a coincidentally equal ID.
  return source.kind === 'legacy' || !platform || /天猫|淘宝|tmall|taobao/i.test(platform)
}

export function sourceSnapshotFilter(source: MetricSource) {
  return source.kind === 'tmall-store'
    ? { sourceKey: { startsWith: source.keyPrefix } }
    : { NOT: { sourceKey: { startsWith: TMALL_STORE_SOURCE_PREFIX } } }
}

export function sourceMetricDateKey(value: Date | string | null) {
  if (!value) return null
  if (typeof value === 'string' && /^\d{4}-\d{2}-\d{2}/.test(value)) return value.slice(0, 10)
  const date = value instanceof Date ? value : new Date(value)
  return Number.isNaN(date.getTime()) ? null : date.toISOString().slice(0, 10)
}

export type StoreSourceRange = { firstDate: string; lastDate: string; correctionThrough: string | null }

// Monthly views drop older months. Never delete cached dates outside the
// currently retained Overall range, or advance past a delayed ROI source.
export async function readTmallStoreSourceRanges(pool: ConnectionPool, today: string) {
  const request = pool.request().input('today', mssql.NVarChar(10), today)
  TMALL_STORE_BRANDS.forEach((brand, index) => request.input(`store${index}`, mssql.NVarChar(200), STORES[brand]))
  const result = await request.query<{
    sourceKind: string; sourceStore: string; firstDate: Date | string; lastDate: Date | string
  }>(`
    SELECT N'overall' AS sourceKind, [店铺名称] AS sourceStore,
      MIN([统计日期]) AS firstDate, MAX([统计日期]) AS lastDate
    FROM [rpt].[TmallStoreOverall]
    WHERE [店铺名称] IN (@store0, @store1, @store2) AND [统计日期] <= TRY_CONVERT(date, @today)
    GROUP BY [店铺名称]
    UNION ALL
    SELECT N'roi' AS sourceKind, [店铺名称] AS sourceStore,
      MIN([统计日期]) AS firstDate, MAX([统计日期]) AS lastDate
    FROM [rpt].[TmallStoreBusinessRoi]
    WHERE [店铺名称] IN (@store0, @store1, @store2) AND [统计日期] <= TRY_CONVERT(date, @today)
    GROUP BY [店铺名称]
  `)
  const ranges = new Map<TmallStoreBrand, StoreSourceRange>()
  for (const brand of TMALL_STORE_BRANDS) {
    const overall = result.recordset.find((row) => row.sourceKind === 'overall' && row.sourceStore === STORES[brand])
    const roi = result.recordset.find((row) => row.sourceKind === 'roi' && row.sourceStore === STORES[brand])
    const firstDate = sourceMetricDateKey(overall?.firstDate || null)
    const lastDate = sourceMetricDateKey(overall?.lastDate || null)
    const roiLastDate = sourceMetricDateKey(roi?.lastDate || null)
    if (firstDate && lastDate && firstDate <= lastDate) {
      ranges.set(brand, { firstDate, lastDate, correctionThrough: roiLastDate ? (roiLastDate < lastDate ? roiLastDate : lastDate) : null })
    }
  }
  return ranges
}

export async function fetchPerformanceSourceRows(
  pool: ConnectionPool, source: MetricSource, productId: string, startDate: string, endDate: string,
): Promise<SourceMetricRow[]> {
  const request = pool.request()
    .input('productId', mssql.NVarChar(255), productId)
    .input('startDate', mssql.NVarChar(10), startDate)
    .input('endDate', mssql.NVarChar(10), endDate)
  if (source.kind === 'tmall-store') request.input('store', mssql.NVarChar(200), source.store)
  const result = await request.query<SourceMetricRow>(source.kind === 'tmall-store' ? `
    SELECT TOP (5001)
      CONVERT(nvarchar(255), o.[RowId]) AS sourceRowId,
      o.[统计日期] AS metricDate,
      CONVERT(nvarchar(255), o.[商品ID]) AS productId,
      CONVERT(nvarchar(2000), o.[商品名称]) AS productName,
      CONVERT(nvarchar(500), o.[店铺名称]) AS sourceBrand,
      CONVERT(nvarchar(500), o.[一级类目名称]) AS category1,
      CONVERT(nvarchar(500), o.[二级类目名称]) AS category2,
      CONVERT(nvarchar(500), o.[叶子类目名称]) AS category3,
      CONVERT(nvarchar(255), o.[支付金额]) AS paymentAmount,
      CONVERT(nvarchar(255), o.[支付买家数]) AS paymentUsers,
      CONVERT(nvarchar(255), o.[加购人数]) AS cartUsers,
      CONVERT(nvarchar(255), o.[商品访客数]) AS visitors,
      CONVERT(nvarchar(255), o.[支付转化率]) AS conversionRate,
      CONVERT(nvarchar(255), o.[商品收藏人数]) AS favorites,
      CONVERT(nvarchar(255), o.[主图整体点击率]) AS clickRate,
      CONVERT(nvarchar(255), r.[RowId]) AS promotionSourceRowId,
      CONVERT(nvarchar(255), r.[展现量]) AS impressions,
      CAST(NULL AS nvarchar(255)) AS clicks,
      CONVERT(nvarchar(255), r.[推广消耗金额]) AS promotionSpend,
      CONVERT(nvarchar(255), r.[推广引导总成交金额]) AS promotionRevenue,
      CONVERT(nvarchar(255), r.[推广ROI]) AS roi
    FROM [rpt].[TmallStoreOverall] o
    LEFT JOIN [rpt].[TmallStoreBusinessRoi] r
      ON r.[店铺名称] = o.[店铺名称] AND r.[统计日期] = o.[统计日期]
      AND LTRIM(RTRIM(r.[商品ID])) = LTRIM(RTRIM(o.[商品ID]))
    WHERE o.[店铺名称] = @store AND LTRIM(RTRIM(o.[商品ID])) = @productId
      AND o.[统计日期] >= TRY_CONVERT(date, @startDate)
      AND o.[统计日期] <= TRY_CONVERT(date, @endDate)
    ORDER BY o.[统计日期] ASC, o.[RowId] ASC
  ` : `
    SELECT TOP (5001)
      CONVERT(nvarchar(255), [RowId]) AS sourceRowId,
      [统计日期] AS metricDate,
      CONVERT(nvarchar(255), [商品ID]) AS productId,
      CONVERT(nvarchar(2000), [商品名称]) AS productName,
      CONVERT(nvarchar(500), [品牌名称]) AS sourceBrand,
      CONVERT(nvarchar(500), [一级类目名称]) AS category1,
      CONVERT(nvarchar(500), [二级类目名称]) AS category2,
      CONVERT(nvarchar(500), [叶子类目名称]) AS category3,
      CONVERT(nvarchar(255), [支付金额]) AS paymentAmount,
      CONVERT(nvarchar(255), [支付人数]) AS paymentUsers,
      CONVERT(nvarchar(255), [加购人数]) AS cartUsers,
      CONVERT(nvarchar(255), [商品访客数]) AS visitors,
      CONVERT(nvarchar(255), [支付转化率]) AS conversionRate,
      CONVERT(nvarchar(255), [商品收藏人数]) AS favorites,
      CONVERT(nvarchar(255), [展现量]) AS impressions,
      CONVERT(nvarchar(255), [点击量]) AS clicks,
      CONVERT(nvarchar(255), [点击率]) AS clickRate,
      CONVERT(nvarchar(255), [推广消耗金额]) AS promotionSpend,
      CONVERT(nvarchar(255), [推广引导总成交金额]) AS promotionRevenue,
      CONVERT(nvarchar(255), [推广ROI]) AS roi
    FROM [rpt].[TmallSrcBusinessRoi]
    WHERE LTRIM(RTRIM(CONVERT(nvarchar(255), [商品ID]))) = @productId
      AND [统计日期] >= TRY_CONVERT(date, @startDate)
      AND [统计日期] <= TRY_CONVERT(date, @endDate)
    ORDER BY [统计日期] ASC, [RowId] ASC
  `)
  const rows = result.recordset || []
  if (rows.length > MAX_SOURCE_ROWS) throw new Error('经营数据来源行数超出安全上限，本轮不替换快照')
  if (source.kind === 'tmall-store') {
    const dates = new Set<string>()
    for (const row of rows) {
      const date = sourceMetricDateKey(row.metricDate)
      if (!date || date < startDate || date > endDate || row.productId?.trim() !== productId || row.sourceBrand !== source.store) {
        throw new Error('天猫经营数据关联键或日期无效，本轮不替换快照')
      }
      if (dates.has(date)) throw new Error('天猫视图同一店铺、商品、日期有重复记录，本轮不替换快照')
      dates.add(date)
    }
  }
  return rows
}