sum(t1.quantity_init_advise) as 'quantity_init_advise', -- 原始采购建议数量 new
( sum(t1.quantity_out_stock) - ( sum((case when t1.quantity_out_stock>0 then 0 else t1.quantity_inventory end )) + sum(t1.quantity_transfer) + sum(t1.quantity_purchase) ) ) as 'quantity_final_advise', -- 计算moq之后的数量 new
t6.product_inner_code as 'product_inner_code', -- 内部商品编码 new
0 as 'goods_quantity_init_advise', -- 商品本次的建议下单数量 new
0 as 'goods_moq', -- 商品的moq new
0 as 'good_sku_codes', -- 商品涉及的下单所有sku new
0 as 'goods_history_fourteenday_sales', -- 商品的最近14日总日均销量
t1.history_fourteenday_sales as 'history_fourteenday_sales', -- sku的最近14日日均
0 as 'quantity_actual', -- 真实下单数量
@main_id as 'main_id',
t2.forecast_formula as 'forecast_formula',
t2.fit_forecast_formula as 'fit_forecast_formula',
t1.turnover_days,
t1.supplier_delivery,
t1.inspection_delivery,
t1.transfer_delivery,
t1.sales_upper_limit,
0 as 'ispush',
1 as 'type',
t6.suppliers_id
from dc_auto_turnover as t1
left join dc_auto_sales as t2 on t1.bailun_sku = t2.bailun_sku and t1.warehouse_code = t2.warehouse_code
left join dc_auto_config_sku_warehouse as t5 on t1.bailun_sku = t5.bailun_sku and t1.warehouse_code = t5.warehouse_code
left join dc_base_sku as t6 on t1.bailun_sku = t6.bailun_sku
where t6.buyer_name in ('赵美聪','张莹霞','张莹霞1','冯兆欣')
and t1.warehouse_code in ('GZBLWH','GZBLYS')
GROUP BY t1.bailun_sku
HAVING ( sum((case when t1.quantity_out_stock>0 then 0 else t1.quantity_inventory end )) + sum(t1.quantity_transfer) + sum(t1.quantity_purchase) < sum(t1.quantity_out_stock) )
) ",new{main_id=mainID},commandTimeout:0);
// 凑单sku(初始建议数没有) 如果下单数只有一个,改为2 ( 只补缺货的不管 )
_connection.Execute(@" update dc_auto_purchase_advise_detailed as t1,
...
...
@@ -152,10 +111,7 @@ where t1.bailun_sku = t2.bailun_sku and quantity_final_advise=1 and quantity_ini
sum(t1.quantity_init_advise) as 'quantity_init_advise', -- 原始采购建议数量 new
( sum(t1.quantity_out_stock) - ( sum((case when t1.quantity_out_stock>0 then 0 else t1.quantity_inventory end )) + sum(t1.quantity_transfer) + sum(t1.quantity_purchase) ) ) as 'quantity_final_advise', -- 计算moq之后的数量 new
t6.product_inner_code as 'product_inner_code', -- 内部商品编码 new
0 as 'goods_quantity_init_advise', -- 商品本次的建议下单数量 new
0 as 'goods_moq', -- 商品的moq new
0 as 'good_sku_codes', -- 商品涉及的下单所有sku new
0 as 'goods_history_fourteenday_sales', -- 商品的最近14日总日均销量
t1.history_fourteenday_sales as 'history_fourteenday_sales', -- sku的最近14日日均
0 as 'quantity_actual', -- 真实下单数量
@main_id as 'main_id',
t2.forecast_formula as 'forecast_formula',
t2.fit_forecast_formula as 'fit_forecast_formula',
t1.turnover_days,
t1.supplier_delivery,
t1.inspection_delivery,
t1.transfer_delivery,
t1.sales_upper_limit,
0 as 'ispush',
1 as 'type',
t6.suppliers_id
from dc_auto_turnover as t1
left join dc_auto_sales as t2 on t1.bailun_sku = t2.bailun_sku and t1.warehouse_code = t2.warehouse_code
left join dc_auto_config_sku_warehouse as t5 on t1.bailun_sku = t5.bailun_sku and t1.warehouse_code = t5.warehouse_code
left join dc_base_sku as t6 on t1.bailun_sku = t6.bailun_sku
where t6.buyer_name in ('赵美聪','张莹霞','张莹霞1','冯兆欣')
and t1.warehouse_code in ('GZBLWH','GZBLYS')
GROUP BY t1.bailun_sku
HAVING ( sum((case when t1.quantity_out_stock>0 then 0 else t1.quantity_inventory end )) + sum(t1.quantity_transfer) + sum(t1.quantity_purchase) < sum(t1.quantity_out_stock) )