const fs = require('fs');
const path = require('path');
const dayjs = require('dayjs');
const cloudDb = require('../config/cloudDatabase');

const PICKUP_EXCLUDED_LABEL_KEYWORDS = [
  '配件',
  '经管大单',
  '不发',
  '等通知',
  '延期',
  '延迟',
  '武进安能',
  '中铁',
  '物流',
  '自提',
  '外贸',
  '采购单',
  '备货',
  '定制',
  '中转集运',
  '中转订单',
  '新疆西藏单',
  'ECLP订单',
];

const PICKUP_EXCLUDED_COURIER_KEYWORDS = [
  '武进安能',
  '中铁',
  '物流',
  '自提',
  '线下快递',
  '专线',
];

const PICKUP_EXCLUDED_REMARK_KEYWORDS = [
  'bbff',
  'ccdd',
  '转X00006',
];

const PICKUP_TIMELY_NO_FETCH_COURIER_KEYWORDS = [
  '京东快运',
  '京东自营',
  '顺丰',
];

const PICKUP_TIMELY_LABEL_KEYWORDS = [
  'CLPS订单',
  'ECLP订单',
];

const UNKNOWN_WAREHOUSE = '未知仓库';
const UNKNOWN_SUPPLIER = '未知供应商';
const UNKNOWN_PURCHASER = '未配置';
const SNAPSHOT_DIR = path.resolve(__dirname, '../../runtime-cache/logistics-pickup-board');

function q(value) {
  return `N'${String(value).replace(/'/g, "''")}'`;
}

function buildSqlLikeAny(column, keywords) {
  return keywords
    .map((keyword) => `${column} LIKE ${q(`%${keyword}%`)}`)
    .join(' OR ');
}

const excludedLabelSql = buildSqlLikeAny(`ISNULL(src.order_labels, N'')`, PICKUP_EXCLUDED_LABEL_KEYWORDS);
const excludedCourierSql = buildSqlLikeAny(`ISNULL(src.courier_name, N'')`, PICKUP_EXCLUDED_COURIER_KEYWORDS);
const excludedRemarkSql = buildSqlLikeAny(
  `ISNULL(src.buyer_message, N'') + N' ' + ISNULL(src.remark, N'') + N' ' + ISNULL(src.remark_content, N'')`,
  PICKUP_EXCLUDED_REMARK_KEYWORDS
);
const timelyNoFetchCourierSql = buildSqlLikeAny(`ISNULL(src.courier_name, N'')`, PICKUP_TIMELY_NO_FETCH_COURIER_KEYWORDS);
const timelyLabelSql = buildSqlLikeAny(`ISNULL(src.order_labels, N'')`, PICKUP_TIMELY_LABEL_KEYWORDS);

const PICKUP_BOARD_SQL = `
SET NOCOUNT ON;

DECLARE @payStart DATETIME = DATEADD(DAY, -1, CAST(@startDate AS DATETIME));
DECLARE @payEnd DATETIME = DATEADD(DAY, -1, CAST(@endDate AS DATETIME));

SELECT
  CAST(DATEADD(DAY, 1, TRY_CONVERT(datetime, REPLACE(undefined5, '/', '-'))) AS date) AS stat_date,
  NULLIF(LTRIM(RTRIM(undefined1)), '') AS inner_order_id,
  NULLIF(LTRIM(RTRIM(undefined2)), '') AS order_id,
  NULLIF(LTRIM(RTRIM(undefined10)), '') AS sku_id,
  TRY_CONVERT(datetime, REPLACE(undefined5, '/', '-')) AS pay_time,
  TRY_CONVERT(datetime, REPLACE(undefined6, '/', '-')) AS afs_send_time,
  NULLIF(LTRIM(RTRIM(undefined8)), '') AS shop_name,
  NULLIF(LTRIM(RTRIM(undefined62)), '') AS order_labels,
  NULLIF(LTRIM(RTRIM(undefined72)), '') AS express_no,
  NULLIF(LTRIM(RTRIM(undefined73)), '') AS afs_courier_name,
  NULLIF(LTRIM(RTRIM(undefined74)), '') AS province,
  NULLIF(LTRIM(RTRIM(undefined75)), '') AS city,
  NULLIF(LTRIM(RTRIM(undefined66)), '') AS afs_warehouse_name,
  NULLIF(LTRIM(RTRIM(undefined32)), '') AS order_type,
  TRY_CONVERT(datetime, REPLACE(undefined33, '/', '-')) AS aftersale_apply_time
INTO #afs_raw
FROM dbo.jst_goods_profit_kpi_items_afs
WHERE TRY_CONVERT(datetime, REPLACE(undefined5, '/', '-')) >= @payStart
  AND TRY_CONVERT(datetime, REPLACE(undefined5, '/', '-')) < DATEADD(DAY, 1, @payEnd);

CREATE NONCLUSTERED INDEX IX_afs_raw_stat_dedup ON #afs_raw(stat_date, inner_order_id, sku_id);

WITH ranked AS (
  SELECT
    *,
    ROW_NUMBER() OVER (
      PARTITION BY stat_date, inner_order_id, sku_id
      ORDER BY
        CASE WHEN express_no IS NULL OR express_no = '' THEN 1 ELSE 0 END,
        CASE WHEN afs_send_time IS NULL THEN 1 ELSE 0 END,
        afs_send_time DESC,
        pay_time DESC
    ) AS rn
  FROM #afs_raw
  WHERE stat_date BETWEEN @startDate AND @endDate
    AND inner_order_id IS NOT NULL
    AND inner_order_id <> ''
    AND sku_id IS NOT NULL
    AND sku_id <> ''
)
SELECT
  stat_date,
  inner_order_id,
  order_id,
  sku_id,
  pay_time,
  afs_send_time,
  shop_name,
  order_labels,
  express_no,
  afs_courier_name,
  province,
  city,
  afs_warehouse_name,
  order_type,
  aftersale_apply_time
INTO #afs_dedup
FROM ranked
WHERE rn = 1;

CREATE NONCLUSTERED INDEX IX_afs_dedup_order_id ON #afs_dedup(order_id);
CREATE NONCLUSTERED INDEX IX_afs_dedup_sku_id ON #afs_dedup(sku_id);
CREATE NONCLUSTERED INDEX IX_afs_dedup_express_no ON #afs_dedup(express_no);

SELECT DISTINCT express_no
INTO #express_keys
FROM #afs_dedup
WHERE express_no IS NOT NULL
  AND express_no <> '';

SELECT DISTINCT order_id
INTO #order_keys
FROM #afs_dedup
WHERE order_id IS NOT NULL
  AND order_id <> '';

CREATE UNIQUE CLUSTERED INDEX IX_order_keys ON #order_keys(order_id);

SELECT DISTINCT sku_id
INTO #sku_keys
FROM #afs_dedup
WHERE sku_id IS NOT NULL
  AND sku_id <> '';

CREATE UNIQUE CLUSTERED INDEX IX_sku_keys ON #sku_keys(sku_id);

SELECT
  NULLIF(LTRIM(RTRIM(e.logistic_id)), '') AS logistic_id,
  MAX(NULLIF(LTRIM(RTRIM(e.so_id)), '')) AS so_id,
  MAX(NULLIF(LTRIM(RTRIM(e.logistic_company_name)), '')) AS logistic_company_name,
  MAX(NULLIF(LTRIM(RTRIM(e.order_status_name)), '')) AS order_status_name,
  MAX(NULLIF(LTRIM(RTRIM(e.aftersale_status_name)), '')) AS aftersale_status_name,
  MAX(NULLIF(LTRIM(RTRIM(e.remark)), '')) AS remark,
  MAX(NULLIF(LTRIM(RTRIM(e.buyer_message)), '')) AS buyer_message,
  MAX(NULLIF(LTRIM(RTRIM(e.remark_content)), '')) AS remark_content,
  MAX(NULLIF(LTRIM(RTRIM(e.shop_name)), '')) AS shop_name,
  MAX(NULLIF(LTRIM(RTRIM(e.warehouse_name)), '')) AS warehouse_name,
  MIN(e.send_time) AS send_time,
  MIN(e.fetch_time) AS fetch_time,
  MAX(NULLIF(LTRIM(RTRIM(e.receiver_address)), '')) AS receiver_address
INTO #express_by_logistic
FROM dbo.jst_order_express_details e
INNER JOIN #express_keys k
  ON k.express_no = NULLIF(LTRIM(RTRIM(e.logistic_id)), '')
GROUP BY NULLIF(LTRIM(RTRIM(e.logistic_id)), '');

CREATE UNIQUE CLUSTERED INDEX IX_express_by_logistic ON #express_by_logistic(logistic_id);

SELECT
  NULLIF(LTRIM(RTRIM(e.so_id)), '') AS so_id,
  MAX(NULLIF(LTRIM(RTRIM(e.logistic_id)), '')) AS logistic_id,
  MAX(NULLIF(LTRIM(RTRIM(e.logistic_company_name)), '')) AS logistic_company_name,
  MAX(NULLIF(LTRIM(RTRIM(e.order_status_name)), '')) AS order_status_name,
  MAX(NULLIF(LTRIM(RTRIM(e.aftersale_status_name)), '')) AS aftersale_status_name,
  MAX(NULLIF(LTRIM(RTRIM(e.remark)), '')) AS remark,
  MAX(NULLIF(LTRIM(RTRIM(e.buyer_message)), '')) AS buyer_message,
  MAX(NULLIF(LTRIM(RTRIM(e.remark_content)), '')) AS remark_content,
  MAX(NULLIF(LTRIM(RTRIM(e.shop_name)), '')) AS shop_name,
  MAX(NULLIF(LTRIM(RTRIM(e.warehouse_name)), '')) AS warehouse_name,
  MIN(e.send_time) AS send_time,
  MIN(e.fetch_time) AS fetch_time,
  MAX(NULLIF(LTRIM(RTRIM(e.receiver_address)), '')) AS receiver_address
INTO #express_by_order
FROM dbo.jst_order_express_details e
INNER JOIN #order_keys k
  ON k.order_id = NULLIF(LTRIM(RTRIM(e.so_id)), '')
GROUP BY NULLIF(LTRIM(RTRIM(e.so_id)), '');

CREATE UNIQUE CLUSTERED INDEX IX_express_by_order ON #express_by_order(so_id);

SELECT
  NULLIF(LTRIM(RTRIM(s.sku_id)), '') AS sku_id,
  NULLIF(LTRIM(RTRIM(s.supplier_name)), '') AS supplier_name,
  NULLIF(LTRIM(RTRIM(s.other_1)), '') AS spu_key,
  NULLIF(LTRIM(RTRIM(s.other_3)), '') AS default_warehouse
INTO #sku_meta
FROM dbo.jst_sku s
INNER JOIN #sku_keys k
  ON k.sku_id = NULLIF(LTRIM(RTRIM(s.sku_id)), '');

CREATE UNIQUE CLUSTERED INDEX IX_sku_meta ON #sku_meta(sku_id);

SELECT
  d.stat_date,
  d.inner_order_id,
  d.order_id,
  d.sku_id,
  d.pay_time,
  COALESCE(el.send_time, eo.send_time, d.afs_send_time) AS send_time,
  COALESCE(el.fetch_time, eo.fetch_time) AS fetch_time,
  COALESCE(el.shop_name, eo.shop_name, d.shop_name) AS shop_name,
  COALESCE(el.warehouse_name, eo.warehouse_name, d.afs_warehouse_name) AS raw_warehouse_name,
  COALESCE(el.logistic_company_name, eo.logistic_company_name, d.afs_courier_name) AS courier_name,
  COALESCE(d.express_no, el.logistic_id, eo.logistic_id, N'') AS express_no,
  COALESCE(el.order_status_name, eo.order_status_name, N'') AS order_status_name,
  COALESCE(el.aftersale_status_name, eo.aftersale_status_name, N'') AS aftersale_status_name,
  COALESCE(el.remark, eo.remark, N'') AS remark,
  COALESCE(el.buyer_message, eo.buyer_message, N'') AS buyer_message,
  COALESCE(el.remark_content, eo.remark_content, N'') AS remark_content,
  COALESCE(d.order_labels, N'') AS order_labels,
  COALESCE(d.province, N'') AS province,
  COALESCE(d.city, N'') AS city,
  COALESCE(el.receiver_address, eo.receiver_address, N'') AS receiver_address,
  COALESCE(d.order_type, N'') AS order_type,
  d.aftersale_apply_time,
  COALESCE(s.supplier_name, N'') AS supplier_name,
  COALESCE(s.spu_key, N'') AS spu_key,
  COALESCE(s.default_warehouse, N'') AS default_warehouse,
  COALESCE(cfg.purchaser, N'') AS purchaser_name,
  COALESCE(shop_meta.responsible_department, N'') AS shop_responsible_department
INTO #pickup_enriched
FROM #afs_dedup d
LEFT JOIN #express_by_logistic el ON d.express_no = el.logistic_id
LEFT JOIN #express_by_order eo ON d.order_id = eo.so_id
LEFT JOIN #sku_meta s ON d.sku_id = s.sku_id
OUTER APPLY (
  SELECT TOP 1 purchaser
  FROM dbo.fys_SkuDataLibrary_SpuConfig
  WHERE COALESCE(NULLIF(s.spu_key, N''), d.sku_id) LIKE spu + N'%'
    AND purchaser IS NOT NULL AND purchaser != N''
  ORDER BY LEN(spu) DESC
) cfg
OUTER APPLY (
  SELECT TOP 1 NULLIF(LTRIM(RTRIM(responsibleDepartment)), N'') AS responsible_department
  FROM dbo.fys_shopInfo
  WHERE NULLIF(LTRIM(RTRIM(erpShopName)), N'') = COALESCE(el.shop_name, eo.shop_name, d.shop_name)
) shop_meta;

SELECT
  src.stat_date,
  ISNULL(NULLIF(src.shop_name, N''), N'未知店铺') AS shop_name,
  CASE
    WHEN ISNULL(NULLIF(src.raw_warehouse_name, N''), N'') = N'常州简尚家居有限公司'
         AND ISNULL(NULLIF(src.default_warehouse, N''), N'') <> N''
      THEN src.default_warehouse
    WHEN ISNULL(NULLIF(src.raw_warehouse_name, N''), N'') <> N''
      THEN src.raw_warehouse_name
    WHEN ISNULL(NULLIF(src.default_warehouse, N''), N'') <> N''
      THEN src.default_warehouse
    ELSE ${q(UNKNOWN_WAREHOUSE)}
  END AS warehouse_name,
  ISNULL(NULLIF(src.purchaser_name, N''), ${q(UNKNOWN_PURCHASER)}) AS purchaser_name,
  ISNULL(NULLIF(src.supplier_name, N''), ${q(UNKNOWN_SUPPLIER)}) AS supplier_name,
  src.sku_id,
  CASE
    WHEN (${excludedLabelSql}) THEN 1
    WHEN ISNULL(src.shop_responsible_department, N'') LIKE N'%灞变笢椤圭洰缁?%' THEN 1
    WHEN src.supplier_name IN (${q('虚拟')}, ${q('景瓴十方')}) THEN 1
    WHEN src.order_status_name IN (${q('被拆分')}, ${q('被合并')}) THEN 1
    WHEN (${excludedCourierSql}) THEN 1
    WHEN ISNULL(src.express_no, N'') LIKE ${q('%F800%')} THEN 1
    WHEN (${excludedRemarkSql}) THEN 1
    WHEN ISNULL(src.shop_name, N'') LIKE ${q('%京喜%')}
         AND ISNULL(src.aftersale_status_name, ${q('暂无售后')}) <> ${q('暂无售后')} THEN 1
    WHEN ISNULL(src.shop_name, N'') LIKE ${q('%样品专用店铺%')} THEN 1
    WHEN ISNULL(src.order_status_name, N'') LIKE ${q('%取消%')}
         AND src.send_time IS NULL
         AND ISNULL(src.aftersale_status_name, ${q('暂无售后')}) IN (N'', ${q('暂无售后')}, ${q('未申请退款')}) THEN 1
    WHEN src.aftersale_apply_time IS NOT NULL
         AND src.pay_time IS NOT NULL
         AND src.aftersale_apply_time >= src.pay_time
         AND DATEDIFF(SECOND, src.pay_time, src.aftersale_apply_time) <= 24 * 3600 THEN 1
    WHEN ISNULL(src.order_type, N'') LIKE ${q('%预售%')}
         OR ISNULL(src.order_status_name, N'') LIKE ${q('%预售%')} THEN 1
    ELSE 0
  END AS is_excluded,
  CASE
    WHEN src.pay_time IS NULL THEN 1
    WHEN ISNULL(src.shop_name, N'') LIKE ${q('%京喜%')}
         AND src.send_time IS NOT NULL
         AND src.send_time >= src.pay_time
         AND DATEDIFF(SECOND, src.pay_time, src.send_time) <= 24 * 3600 THEN 0
    WHEN (${timelyNoFetchCourierSql})
         AND src.fetch_time IS NULL
         AND src.send_time IS NOT NULL
         AND src.send_time >= src.pay_time
         AND DATEDIFF(SECOND, src.pay_time, src.send_time) <= 24 * 3600 THEN 0
    WHEN (${timelyLabelSql})
         AND src.send_time IS NOT NULL
         AND src.send_time >= src.pay_time
         AND DATEDIFF(SECOND, src.pay_time, src.send_time) <= 24 * 3600 THEN 0
    WHEN src.fetch_time IS NOT NULL
         AND src.fetch_time >= src.pay_time
         AND DATEDIFF(SECOND, src.pay_time, src.fetch_time) <= 24 * 3600 THEN 0
    ELSE 1
  END AS is_timeout
INTO #pickup_scored
FROM #pickup_enriched src;

SELECT
  stat_date,
  shop_name,
  warehouse_name,
  purchaser_name,
  supplier_name,
  sku_id,
  COUNT_BIG(*) AS total_count,
  SUM(CASE WHEN is_timeout = 1 THEN 1 ELSE 0 END) AS timeout_count
FROM #pickup_scored
WHERE is_excluded = 0
GROUP BY stat_date, shop_name, warehouse_name, purchaser_name, supplier_name, sku_id
ORDER BY stat_date, total_count DESC;
`;

function parseListParam(value) {
  if (!value) {
    return [];
  }

  if (Array.isArray(value)) {
    return [...new Set(value.flatMap((item) => String(item).split(',')).map((item) => item.trim()).filter(Boolean))];
  }

  return [...new Set(String(value).split(',').map((item) => item.trim()).filter(Boolean))];
}

function toNum(value) {
  return Number(value) || 0;
}

function calcRate(totalCount, timeoutCount) {
  if (!totalCount) {
    return null;
  }

  return Number((((totalCount - timeoutCount) / totalCount) * 100).toFixed(2));
}

function clampEndDateToYesterday(endDate) {
  const requestedEnd = dayjs(endDate);
  const yesterday = dayjs().subtract(1, 'day').startOf('day');
  return requestedEnd.isAfter(yesterday, 'day') ? yesterday.format('YYYY-MM-DD') : requestedEnd.format('YYYY-MM-DD');
}

function buildPeriods(startDate, endDate, mode) {
  const start = dayjs(startDate);
  const end = dayjs(endDate);
  const periods = [];
  let cursor = start.startOf(mode === 'monthly' ? 'month' : 'day');

  while (cursor.isSame(end, mode === 'monthly' ? 'month' : 'day') || cursor.isBefore(end, mode === 'monthly' ? 'month' : 'day')) {
    periods.push(
      mode === 'monthly'
        ? {
            key: cursor.format('YYYY-MM'),
            label: cursor.format('YYYY年M月'),
          }
        : {
            key: cursor.format('YYYY-MM-DD'),
            label: cursor.format('M月D日'),
          }
    );
    cursor = cursor.add(1, mode === 'monthly' ? 'month' : 'day');
  }

  return periods;
}

function bucketKey(statDate, mode) {
  return mode === 'monthly' ? dayjs(statDate).format('YYYY-MM') : dayjs(statDate).format('YYYY-MM-DD');
}

function applyFilters(rows, filters) {
  return rows.filter((row) => {
    if (filters.shops.length > 0 && !filters.shops.includes(row.shopName)) return false;
    if (filters.warehouses.length > 0 && !filters.warehouses.includes(row.warehouseName)) return false;
    if (filters.purchasers.length > 0 && !filters.purchasers.includes(row.purchaserName)) return false;
    if (filters.suppliers.length > 0 && !filters.suppliers.includes(row.supplierName)) return false;
    if (filters.skuIds.length > 0 && !filters.skuIds.includes(row.skuId)) return false;
    return true;
  });
}

function buildFilterOptions(rows) {
  const unique = (selector) => [...new Set(rows.map(selector).filter(Boolean))].sort((a, b) => a.localeCompare(b, 'zh-CN'));

  return {
    shops: unique((row) => row.shopName),
    warehouses: unique((row) => row.warehouseName),
    purchasers: unique((row) => row.purchaserName),
    suppliers: unique((row) => row.supplierName),
    skuIds: unique((row) => row.skuId),
  };
}

function aggregateTable(rows, periods, mode, config) {
  const map = new Map();

  const ensureRow = (key, base) => {
    if (!map.has(key)) {
      const row = {
        key,
        ...base,
        totalCount: 0,
        timeoutCount: 0,
        periodMap: {},
      };
      for (const period of periods) {
        row.periodMap[period.key] = {
          totalCount: 0,
          timeoutCount: 0,
          rate: null,
        };
      }
      map.set(key, row);
    }
    return map.get(key);
  };

  for (const item of rows) {
    const period = bucketKey(item.statDate, mode);
    const key = config.buildKey(item);
    const row = ensureRow(key, config.project(item));
    row.totalCount += item.totalCount;
    row.timeoutCount += item.timeoutCount;
    if (!row.periodMap[period]) {
      row.periodMap[period] = { totalCount: 0, timeoutCount: 0, rate: null };
    }
    row.periodMap[period].totalCount += item.totalCount;
    row.periodMap[period].timeoutCount += item.timeoutCount;
  }

  const finalize = (row) => {
    const orderedRates = periods.map((period) => {
      const bucket = row.periodMap[period.key] || { totalCount: 0, timeoutCount: 0 };
      bucket.rate = calcRate(bucket.totalCount, bucket.timeoutCount);
      return bucket.rate;
    });

    const lastRate = [...orderedRates].reverse().find((value) => value !== null);
    const previousRate = [...orderedRates].reverse().find((value, index, arr) => value !== null && arr.indexOf(value) !== arr.lastIndexOf(value));
    const firstRate = orderedRates.find((value) => value !== null);

    row.totalRate = calcRate(row.totalCount, row.timeoutCount);
    row.trendDelta = firstRate !== null && lastRate !== null ? Number((lastRate - firstRate).toFixed(2)) : null;
    row.momDelta = orderedRates.length >= 2 && orderedRates[orderedRates.length - 2] !== null && orderedRates[orderedRates.length - 1] !== null
      ? Number((orderedRates[orderedRates.length - 1] - orderedRates[orderedRates.length - 2]).toFixed(2))
      : previousRate !== undefined && previousRate !== null && lastRate !== null
        ? Number((lastRate - previousRate).toFixed(2))
        : null;
    return row;
  };

  const dataRows = Array.from(map.values()).map(finalize).sort((a, b) => {
    const rateA = Number.isFinite(a.totalRate) ? a.totalRate : Number.POSITIVE_INFINITY;
    const rateB = Number.isFinite(b.totalRate) ? b.totalRate : Number.POSITIVE_INFINITY;
    if (rateA !== rateB) {
      return rateA - rateB;
    }
    return b.totalCount - a.totalCount;
  });

  const totalRow = ensureRow('__total__', config.totalProject());
  for (const item of rows) {
    totalRow.totalCount += item.totalCount;
    totalRow.timeoutCount += item.timeoutCount;
    const period = bucketKey(item.statDate, mode);
    if (!totalRow.periodMap[period]) {
      totalRow.periodMap[period] = { totalCount: 0, timeoutCount: 0, rate: null };
    }
    totalRow.periodMap[period].totalCount += item.totalCount;
    totalRow.periodMap[period].timeoutCount += item.timeoutCount;
  }

  const finalizedTotalRow = finalize(totalRow);
  const limit = config.limit || dataRows.length;
  return [finalizedTotalRow, ...dataRows.slice(0, limit)];
}

function buildBoard(rows, startDate, endDate, mode) {
  const periods = buildPeriods(startDate, endDate, mode);

  return {
    periods,
    shopRows: aggregateTable(rows, periods, mode, {
      buildKey: (row) => `shop:${row.shopName}`,
      project: (row) => ({ shopName: row.shopName }),
      totalProject: () => ({ shopName: '总计' }),
      limit: 120,
    }),
    warehouseRows: aggregateTable(rows, periods, mode, {
      buildKey: (row) => `warehouse:${row.warehouseName}`,
      project: (row) => ({ warehouseName: row.warehouseName }),
      totalProject: () => ({ warehouseName: '总计' }),
      limit: 80,
    }),
    purchaserRows: aggregateTable(rows, periods, mode, {
      buildKey: (row) => `purchaser:${row.purchaserName}`,
      project: (row) => ({ purchaserName: row.purchaserName }),
      totalProject: () => ({ purchaserName: '总计' }),
      limit: 60,
    }),
    supplierRows: aggregateTable(rows, periods, mode, {
      buildKey: (row) => `supplier:${row.purchaserName}:${row.supplierName}`,
      project: (row) => ({ purchaserName: row.purchaserName, supplierName: row.supplierName }),
      totalProject: () => ({ purchaserName: '', supplierName: '总计' }),
      limit: 200,
    }),
    skuRows: aggregateTable(rows, periods, mode, {
      buildKey: (row) => `sku:${row.purchaserName}:${row.supplierName}:${row.skuId}`,
      project: (row) => ({
        purchaserName: row.purchaserName,
        supplierName: row.supplierName,
        skuId: row.skuId,
      }),
      totalProject: () => ({ purchaserName: '', supplierName: '', skuId: '总计' }),
      limit: 300,
    }),
  };
}

function normalizeSnapshotRows(rows = [], periods = []) {
  const safePeriods = Array.isArray(periods) ? periods : [];
  const recomputeRow = (row) => {
    const nextRow = {
      ...row,
      periodMap: { ...(row.periodMap || {}) },
    };
    let totalCount = 0;
    let timeoutCount = 0;
    const rates = [];

    for (const period of safePeriods) {
      const bucket = nextRow.periodMap[period.key] || { totalCount: 0, timeoutCount: 0, rate: null };
      const normalizedBucket = {
        totalCount: Number(bucket.totalCount || 0),
        timeoutCount: Number(bucket.timeoutCount || 0),
        rate: calcRate(Number(bucket.totalCount || 0), Number(bucket.timeoutCount || 0)),
      };
      nextRow.periodMap[period.key] = normalizedBucket;
      totalCount += normalizedBucket.totalCount;
      timeoutCount += normalizedBucket.timeoutCount;
      rates.push(normalizedBucket.rate);
    }

    nextRow.totalCount = totalCount;
    nextRow.timeoutCount = timeoutCount;
    nextRow.totalRate = calcRate(totalCount, timeoutCount);

    const validRates = rates.filter((value) => value !== null);
    const firstRate = validRates[0] ?? null;
    const lastRate = validRates.length > 0 ? validRates[validRates.length - 1] : null;
    const previousRate = validRates.length > 1 ? validRates[validRates.length - 2] : null;
    nextRow.trendDelta = firstRate !== null && lastRate !== null ? Number((lastRate - firstRate).toFixed(2)) : null;
    nextRow.momDelta = previousRate !== null && lastRate !== null ? Number((lastRate - previousRate).toFixed(2)) : null;
    return nextRow;
  };

  const normalizedRows = rows.map(recomputeRow);
  const [totalRow, ...dataRows] = normalizedRows;
  const sortedRows = dataRows.sort((a, b) => {
    const rateA = Number.isFinite(a.totalRate) ? a.totalRate : Number.POSITIVE_INFINITY;
    const rateB = Number.isFinite(b.totalRate) ? b.totalRate : Number.POSITIVE_INFINITY;
    if (rateA !== rateB) {
      return rateA - rateB;
    }
    return b.totalCount - a.totalCount;
  });
  return totalRow ? [totalRow, ...sortedRows] : sortedRows;
}

function normalizeSnapshotData(data, effectiveEndDate) {
  if (!data) {
    return null;
  }

  const trimPeriods = (board) => {
    const nextPeriods = (board?.periods || []).filter((period) => period.key <= effectiveEndDate);
    return {
      periods: nextPeriods,
      shopRows: normalizeSnapshotRows(board?.shopRows || [], nextPeriods),
      warehouseRows: normalizeSnapshotRows(board?.warehouseRows || [], nextPeriods),
      purchaserRows: normalizeSnapshotRows(board?.purchaserRows || [], nextPeriods),
      supplierRows: normalizeSnapshotRows(board?.supplierRows || [], nextPeriods),
      skuRows: normalizeSnapshotRows(board?.skuRows || [], nextPeriods),
    };
  };

  return {
    ...data,
    daily: trimPeriods(data.daily),
    monthly: trimPeriods(data.monthly),
    meta: {
      ...(data.meta || {}),
      endDate: effectiveEndDate,
    },
  };
}

function normalizeRows(rows) {
  return rows.map((row) => ({
    statDate: dayjs(row.stat_date).format('YYYY-MM-DD'),
    shopName: row.shop_name || '未知店铺',
    warehouseName: row.warehouse_name || UNKNOWN_WAREHOUSE,
    purchaserName: row.purchaser_name || UNKNOWN_PURCHASER,
    supplierName: row.supplier_name || UNKNOWN_SUPPLIER,
    skuId: row.sku_id || '未知商品编码',
    totalCount: toNum(row.total_count),
    timeoutCount: toNum(row.timeout_count),
  }));
}

async function queryLogisticsPickupBoard({ startDate, endDate, shops, warehouses, purchasers, suppliers, skuIds }) {
  const effectiveEndDate = clampEndDateToYesterday(endDate);
  const rawRows = await cloudDb.query(PICKUP_BOARD_SQL, { startDate, endDate: effectiveEndDate });
  const rows = normalizeRows(rawRows);
  const filters = {
    shops: parseListParam(shops),
    warehouses: parseListParam(warehouses),
    purchasers: parseListParam(purchasers),
    suppliers: parseListParam(suppliers),
    skuIds: parseListParam(skuIds),
  };
  const filteredRows = applyFilters(rows, filters);

  return {
    filters: buildFilterOptions(filteredRows.length > 0 ? filteredRows : rows),
    daily: buildBoard(filteredRows, startDate, effectiveEndDate, 'daily'),
    monthly: buildBoard(filteredRows, startDate, effectiveEndDate, 'monthly'),
    meta: {
      startDate,
      endDate: effectiveEndDate,
      requestedEndDate: endDate,
      filteredCount: filteredRows.length,
      totalCount: rows.length,
    },
  };
}

function getSnapshotPath(startDate, endDate) {
  return path.join(SNAPSHOT_DIR, `${startDate}_${endDate}.json`);
}

function readLogisticsPickupBoardSnapshot(startDate, endDate) {
  const filePath = getSnapshotPath(startDate, endDate);
  if (!fs.existsSync(filePath)) {
    return null;
  }

  return JSON.parse(fs.readFileSync(filePath, 'utf8'));
}

function writeLogisticsPickupBoardSnapshot(startDate, endDate, data) {
  fs.mkdirSync(SNAPSHOT_DIR, { recursive: true });
  const filePath = getSnapshotPath(startDate, endDate);
  fs.writeFileSync(filePath, JSON.stringify(data), 'utf8');
  return filePath;
}

module.exports = {
  getSnapshotPath,
  queryLogisticsPickupBoard,
  readLogisticsPickupBoardSnapshot,
  writeLogisticsPickupBoardSnapshot,
  normalizeSnapshotData,
};