youruo
62cac712db
4 个销量来源 union all 后各分支各自 GROUP BY，同一个 仓库+商品 命中多个 分支时外层层 LEFT JOIN 没有二次聚合，一个仓位行被拆成多行、每行只带某一 个分支的销量（实测 SJ038411 同时出现 sales=0 与 sales=44 两行）。 新增 shipAgg CTE：按 仓库+商品 对各来源求和成一行，再与仓位行 join。 SalesQty/分摊销量/日销/等级随之统一。
244 lines
11 KiB
JavaScript
244 lines
11 KiB
JavaScript
'use strict';
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/**
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* 拣选库位动销分析 —— 业务库取数
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*
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* 库存：rpt.jst_packInventoryInfo 按 wms_co_id + 仓位 + sku_id 汇总 qty（仓位为空的行不参与）
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* 范围：只统计真实拣选仓位（pack_type=Bin 且 bin_group 为空）；
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* 箱记录（pack_type=Pack）与存货位（bin_group=存货）不纳入
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* 销量（4 个来源分支，均按 send_date 窗口）：
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* 1) rpt.jst_Orders × jst_OrderItem 普通行（sku_type<>combine），排除 Delete/Cancelled
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* 2) rpt.jst_Orders 组合装行（sku_id 为 ZH-... 拼接串）→ JOIN jst_comboProductItem 展开为子件×数量
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* 3) rpt.jst_qmcust_orderlist（全民客户 B2B 分销）普通行，排除 Delete/Cancelled/Split/Question
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* （Split 是拆单父单，与拆出的子单重复，必须排除）
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* 4) rpt.jst_qmcust_orderlist 组合装行 → 同样按映射表展开
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* 粒度：仓位 × 商品编码（一个仓位有 N 个商品就输出 N 行），列表与导出共用
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*
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* 【日销与动销等级口径】按「商品日销」判定，不做仓位分摊：
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* 商品日销 = 该商品在窗口内的整档销量 ÷ 窗口天数
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* 同一件商品无论占用几个仓位，各行显示的销量 / 日销 / 动销等级完全一致 ——
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* 不会因为货放得散就被算成滞销。
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*
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* 附带输出「分摊销量」= 商品销量 ÷ 该商品占用的同类型仓位数，用于需要按行求和的场景：
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* 恒等式（已实测校验，差异 0）：全部行分摊销量之和 = 有库位记录的那些 SKU 的销量之和。
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* 注意它小于「全仓销量」：jst_packInventoryInfo 只覆盖部分 SKU 的仓位数据，
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* 没有仓位记录的 SKU 的销量不会体现在任何库位上。
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*/
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const { PICKING_BIN_GRADE_RULES, BIN_TYPE_PICKING } = require('../config/pickingBinSalesAnalysis');
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/** mssql 不支持数组参数，按位展开成 @p0,@p1... */
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function buildInClause(values, prefix) {
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const params = {};
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const clause = values
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.map((v, i) => {
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const key = `${prefix}${i}`;
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params[key] = v;
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return `@${key}`;
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})
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.join(',');
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return { clause, params };
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}
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/**
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* 日销分档表达式：从高档往低档依次命中，最后一档「销售=0」由 salesQty <= 0 兜底。
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* 传入的 salesExpr 是窗口销量（商品整档销量），除以天数得到日销。
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*/
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function buildGradeCase(salesExpr = 'ISNULL(s.salesQty, 0)', daysParam = '@days') {
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const branches = PICKING_BIN_GRADE_RULES
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.filter((rule) => rule.lower > 0)
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.map((rule) => {
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const daily = `(${salesExpr} / ${daysParam})`;
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const lower = `${daily} >= ${rule.lower}`;
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const upper = rule.upper == null ? null : `${daily} < ${rule.upper}`;
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const cond = upper ? `${lower} AND ${upper}` : lower;
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return `WHEN ${cond} THEN '${rule.key}'`;
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});
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return `
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CASE
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${branches.join('\n ')}
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WHEN ${salesExpr} > 0 THEN 'slow2'
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ELSE 'zero'
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END`;
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}
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/**
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* 拉取「仓位 × 商品编码」粒度明细（列表与导出共用）。
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*
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* - stockQty：该商品在此仓位的实际库存
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* - salesQty：该商品在此仓库的窗口销量（整档，不按仓位分摊），动销等级的判定依据
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* - dailySales：salesQty / 窗口天数 = 商品日销
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* - allocatedSalesQty：salesQty ÷ 该商品占用的同类型仓位数，用于需要按行求和的场景
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* - skuCount：该仓位内存放的商品数（仓位粒度，同一仓位多行重复）
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*
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* @param {object} cloudDb 业务库实例
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* @param {string[]} wmsCoIds 仓库编码
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* @param {{shipFrom:string, shipTo:string, days:number}} options
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* @returns {Promise<Array<{wmsCoId:string, binName:string, binType:string, skuId:string,
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* stockQty:number, skuCount:number, salesQty:number, allocatedSalesQty:number,
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* dailySales:number, gradeKey:string}>>}
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*/
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async function fetchPickingBinSkuRows(cloudDb, wmsCoIds, options = {}) {
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if (!cloudDb || typeof cloudDb.query !== 'function') {
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throw new TypeError('fetchPickingBinSkuRows 的第一个参数必须是业务库实例');
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}
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const { shipFrom, shipTo, days } = options;
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if (!Array.isArray(wmsCoIds) || wmsCoIds.length === 0) return [];
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if (!shipFrom || !shipTo || !days) return [];
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const binIn = buildInClause(wmsCoIds, 'w');
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const shipIn = buildInClause(wmsCoIds, 'v');
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// 统计范围固定为真实拣选仓位：pack_type=Bin 且 bin_group 为空。
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// 仅过滤 bin_group 会把同样为空的 Pack 箱记录误标为拣选位。
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const sqlText = `
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WITH bin AS (
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SELECT p.wms_co_id AS wmsCoId,
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LTRIM(RTRIM(p.bin)) AS binName,
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N'${BIN_TYPE_PICKING}' AS binType,
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p.sku_id AS skuId,
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SUM(CAST(ISNULL(p.qty, 0) AS DECIMAL(18, 2))) AS binSkuQty
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FROM rpt.jst_packInventoryInfo p
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WHERE p.wms_co_id IN (${binIn.clause})
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AND ISNULL(p.bin, '') <> ''
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AND ISNULL(p.qty, 0) <> 0
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AND p.pack_type = N'Bin'
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AND ISNULL(p.bin_group, '') = ''
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GROUP BY p.wms_co_id,
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LTRIM(RTRIM(p.bin)),
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p.sku_id
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),
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binSpan AS (
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SELECT wmsCoId, skuId, binType, COUNT(DISTINCT binName) AS binCount
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FROM bin
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GROUP BY wmsCoId, skuId, binType
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),
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ship AS (
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-- 1) 线上店铺订单：普通商品行（sku_type<>combine，组合装行在下一分支展开）
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SELECT o.wms_co_id AS wmsCoId,
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oi.sku_id AS skuId,
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SUM(CAST(ISNULL(oi.qty, 0) AS DECIMAL(18, 2))) AS salesQty
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FROM rpt.jst_OrderItem oi
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JOIN rpt.jst_Orders o ON o.o_id = oi.o_id
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WHERE o.wms_co_id IN (${shipIn.clause})
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AND o.send_date >= @shipFrom
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AND o.send_date < @shipTo
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AND ISNULL(o.status, '') NOT IN ('Delete', 'Cancelled')
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AND ISNULL(oi.sku_type, 'normal') <> 'combine'
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GROUP BY o.wms_co_id, oi.sku_id
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UNION ALL
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-- 2) 线上店铺订单：组合装行（sku_id 为 ZH-子件A-N-子件B-M 拼接串）→ 按映射表展开为子件
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SELECT o.wms_co_id AS wmsCoId,
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ci.src_sku_id AS skuId,
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SUM(CAST(ISNULL(oi.qty, 0) * ISNULL(ci.qty, 0) AS DECIMAL(18, 2))) AS salesQty
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FROM rpt.jst_OrderItem oi
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JOIN rpt.jst_Orders o ON o.o_id = oi.o_id
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JOIN rpt.jst_comboProductItem ci ON ci.combine_sku_id = oi.sku_id
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WHERE o.wms_co_id IN (${shipIn.clause})
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AND o.send_date >= @shipFrom
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AND o.send_date < @shipTo
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AND ISNULL(o.status, '') NOT IN ('Delete', 'Cancelled')
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AND oi.sku_type = 'combine'
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GROUP BY o.wms_co_id, ci.src_sku_id
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UNION ALL
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-- 3) 全民客户（B2B 分销）订单：普通商品行（拆单父单 Split 与子单重复，需排除）
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SELECT o.wms_co_id AS wmsCoId,
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oi.sku_id AS skuId,
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SUM(CAST(ISNULL(oi.qty, 0) AS DECIMAL(18, 2))) AS salesQty
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FROM rpt.jst_qmcust_orderlist_item oi
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JOIN rpt.jst_qmcust_orderlist o ON o.o_id = oi.o_id
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WHERE o.wms_co_id IN (${shipIn.clause})
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AND o.send_date >= @shipFrom
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AND o.send_date < @shipTo
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AND ISNULL(o.status, '') NOT IN ('Delete', 'Cancelled', 'Split', 'Question')
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AND ISNULL(oi.sku_type, 'normal') <> 'combine'
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GROUP BY o.wms_co_id, oi.sku_id
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UNION ALL
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-- 4) 全民客户订单：组合装行展开为子件
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SELECT o.wms_co_id AS wmsCoId,
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ci.src_sku_id AS skuId,
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SUM(CAST(ISNULL(oi.qty, 0) * ISNULL(ci.qty, 0) AS DECIMAL(18, 2))) AS salesQty
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FROM rpt.jst_qmcust_orderlist_item oi
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JOIN rpt.jst_qmcust_orderlist o ON o.o_id = oi.o_id
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JOIN rpt.jst_comboProductItem ci ON ci.combine_sku_id = oi.sku_id
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WHERE o.wms_co_id IN (${shipIn.clause})
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AND o.send_date >= @shipFrom
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AND o.send_date < @shipTo
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AND ISNULL(o.status, '') NOT IN ('Delete', 'Cancelled', 'Split', 'Question')
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AND oi.sku_type = 'combine'
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GROUP BY o.wms_co_id, ci.src_sku_id
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),
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shipAgg AS (
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-- 同一个 仓库+商品 可能同时命中多个来源分支（线上普通/线上组合装/全民客户普通/全民客户组合装），
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-- 必须先按 仓库+商品 汇总成一行再 join，否则一个仓位行会被拆成多行、每行只带某分支的销量。
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SELECT wmsCoId,
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skuId,
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SUM(CAST(salesQty AS DECIMAL(18, 2))) AS salesQty
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FROM ship
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GROUP BY wmsCoId, skuId
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),
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binAgg AS (
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SELECT wmsCoId,
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binName,
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binType,
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COUNT(DISTINCT skuId) AS skuCount
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FROM bin
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GROUP BY wmsCoId, binName, binType
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)
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SELECT b.wmsCoId,
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b.binName,
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b.binType,
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b.skuId,
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CAST(SUM(CAST(b.binSkuQty AS DECIMAL(18, 2))) AS DECIMAL(18, 2)) AS stockQty,
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CAST(a.skuCount AS INT) AS skuCount,
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CAST(ISNULL(s.salesQty, 0) AS DECIMAL(18, 2)) AS salesQty,
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CAST(ISNULL(s.salesQty, 0) / NULLIF(sp.binCount, 0) AS DECIMAL(18, 4)) AS allocatedSalesQty,
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CAST(ISNULL(s.salesQty, 0) / @days AS DECIMAL(18, 4)) AS dailySales,
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${buildGradeCase('ISNULL(s.salesQty, 0)')} AS gradeKey
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FROM bin b
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JOIN binSpan sp
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ON sp.wmsCoId = b.wmsCoId AND sp.skuId = b.skuId AND sp.binType = b.binType
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JOIN binAgg a
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ON a.wmsCoId = b.wmsCoId AND a.binName = b.binName AND a.binType = b.binType
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LEFT JOIN shipAgg s
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ON s.wmsCoId = b.wmsCoId AND s.skuId = b.skuId
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GROUP BY b.wmsCoId, b.binName, b.binType, b.skuId, a.skuCount, s.salesQty, sp.binCount
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HAVING ABS(SUM(CAST(b.binSkuQty AS DECIMAL(18, 2)))) > 0.0001
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ORDER BY b.wmsCoId, b.binType, b.binName, b.skuId`;
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// 该查询 union 了 4 个销量来源（含 qmcust 全渠道扫描），全仓窗口可能超过默认 60s；
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// mssql 12.x 请求级 timeout 不生效，必须走池级放宽的慢查询入口。
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const runQuery = typeof cloudDb.querySlow === 'function' ? cloudDb.querySlow : cloudDb.query;
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const rows = await runQuery(
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sqlText,
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{
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...binIn.params,
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...shipIn.params,
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shipFrom,
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shipTo,
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days,
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},
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{ requestTimeout: 120000 }
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);
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return rows.map((r) => ({
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wmsCoId: String(r.wmsCoId),
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binName: r.binName || '',
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binType: r.binType || '',
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skuId: r.skuId == null ? '' : String(r.skuId).trim(),
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stockQty: Number(r.stockQty) || 0,
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skuCount: Number(r.skuCount) || 0,
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salesQty: Number(r.salesQty) || 0,
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allocatedSalesQty: Number(r.allocatedSalesQty) || 0,
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dailySales: Number(r.dailySales) || 0,
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gradeKey: r.gradeKey || 'zero',
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}));
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}
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module.exports = {
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buildGradeCase,
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buildInClause,
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fetchPickingBinSkuRows,
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};
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