@@ -277,11 +277,15 @@ FROM (SELECT
GROUP BY t1 . perYear , t1 . goods_barcode
ORDER BY t1 . perYear , SUM ( t1 . goods_amt ) DESC ;
- - SELECT * FROM custom_online_sale_bill_local WHERE goods_barcode = ' 000000009918000001 ' ;
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - --
-- 2.1线上每年各省份销售金额、订单数量及其占比
-- 1234791条平台订单没有省份
SELECT COUNT ( DISTINCT platform_order_no ) FROM custom_online_sale_order_local WHERE province = ' ' ;
SELECT source_system , COUNT ( DISTINCT platform_order_no ) FROM custom_online_sale_order_local WHERE province = ' ' GROUP BY source_system ;
SELECT brand_code , COUNT ( ) FROM custom_online_sale_order_local WHERE province = ' ' AND source_system = ' E3PLUS_NEW2 ' GROUP BY brand_code ;
SELECT brand_code , COUNT ( ) FROM custom_online_sale_order_local WHERE source_system = ' E3PLUS_NEW2 ' GROUP BY brand_code ;
-- 只能计算有订单的,账单的不能算(没有省份)
-- 考虑店铺单号重复问题 非换货单有946单重复, 加上换货单有1229条重复
-- 忽略省份为空的平台订单
@@ -415,7 +419,7 @@ SELECT * FROM custom_online_sale_order_local WHERE city = '湖北';
-- 1236382条平台订单没有城市
SELECT source_system , COUNT ( DISTINCT platform_order_no ) FROM custom_online_sale_order_local WHERE city = ' ' GROUP BY source_system ;
-- 城市和等级关联到的只有5695单 需要手工调整
-- 城市和等级关联到的只有5695单 需要手工调整 已调整
SELECT DISTINCT city FROM custom_online_sale_order_local ;
-- 只能计算有订单的,账单的不能算(没有城市)
-- 忽略城市为空的平台订单
@@ -664,38 +668,407 @@ ORDER BY SUBSTR(order_time, 1, 4), SUM(goods_amt) DESC;
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - --
-- 3.4线上每年大促期间店铺销售金额、订单数量和占比
/*
* 2022:
* 618: 0531-0620
* 1111: 1031-1111
* 2023:
* 618: 0531-0620
* 1111: 1020-1111
* 2024:
* 618: 0520-0620
* 1111: 1017-1111
* 2025:
* 618: 0516-0620
* 1111: 1008-1114
*/
SELECT
store_code AS " 店铺编码 " ,
MAX ( store_name_t) AS " 店铺名称 " ,
SUM ( goods_amt_t ) AS " 销售金额(元 ) " ,
SUM ( order_freight_amt_t ) AS " 运费金额(元) " ,
SUM ( goods_amt_t ) + SUM ( order_freight_amt_t ) AS " 销售金额(元)(包含运费) " ,
COUNT ( DISTINCT platform_ order_no ) AS " 订单数量 "
t1 . store_code AS " 店铺编码 " ,
t1 . store_name_t_t AS " 店铺名称 " ,
t3 . sale_money AS " 2022年618销售金额( 元) ( 包含运费 ) " ,
t3 . order_count AS " 2022年618订单数量 " ,
t2 . sale_money AS " 2022年双11 销售金额(元)(包含运费)" ,
t2 . order_count AS " 2022年双11 订单数量" ,
t1 . all_sale_money AS " 2022年总销售金额( 元) ( 包含运费) " ,
t1 . all_order_count AS " 2022年总订单数量 " ,
CASE WHEN t1 . all_sale_money = 0 THEN 0 ELSE ROUND ( t3 . sale_money / t1 . all_sale_money , 4 ) END AS " 2022年618销售金额占比 " ,
CASE WHEN t1 . all_sale_money = 0 THEN 0 ELSE ROUND ( t3 . order_count / t1 . all_order_count , 4 ) END AS " 2022年618订单数量占比 " ,
CASE WHEN t1 . all_sale_money = 0 THEN 0 ELSE ROUND ( t2 . sale_money / t1 . all_sale_money , 4 ) END AS " 2022年双11销售金额占比 " ,
CASE WHEN t1 . all_sale_money = 0 THEN 0 ELSE ROUND ( t2 . order_count / t1 . all_order_count , 4 ) END AS " 2022年双11订单数量占比 "
FROM ( SELECT
store_code ,
MAX ( store_name ) AS store_name_t ,
system_order_no ,
platform_order_no ,
MIN ( min_order_time ) AS order_time_t ,
MAX ( order_freight_amt ) AS order_freight_amt_t ,
SUM ( goods_qty ) AS goods_qty _t,
SUM ( goods_amt ) AS goods_amt_t
FROM custom_online_sale_order_local
WHERE SUBSTR ( min_order_time , 1 , 10 ) > = ' 2022-06-01 ' AND SUBSTR ( min_order_time , 1 , 10 ) < = ' 2022-06-30 '
G ROUP BY store_code , system_order_no , platform_order_no
)
GROUP BY store_code
ORDER BY SUM ( goods_amt_t ) + SUM ( order_freight_amt_t ) DESC ;
MAX ( store_name_t ) AS store_name_t_t ,
SUM ( goods_amt_t ) + SUM ( order_freight_amt_t ) AS all_sale_money ,
COUNT ( DISTINCT platform_order_no ) AS all_order_count
FROM ( SELECT
store_code ,
MAX ( store_name ) AS store_name _t,
platform_order_no ,
MAX ( order_freight_amt ) AS order_freight_amt_t ,
SUM ( goods_amt ) AS goods_amt_t
F ROM cu stom_online_sale_order_local
WHERE SUBSTR ( min_order_time , 1 , 10 ) > = ' 2022-01-01 ' AND SUBSTR ( min_order_time , 1 , 10 ) < = ' 2022-12-31 '
GROUP BY store_code , system_order_no , platform_order_no
) GROUP BY store_code
) t1 LEFT JOIN ( SELECT
store_code ,
SUM ( goods_amt_t ) + SUM ( order_freight_amt_t ) AS sale_money ,
COUNT ( DISTINCT platform_order_no ) AS order_count
FROM ( SELECT
store_code ,
platform_order_no ,
MAX ( order_freight_amt ) AS order_freight_amt_t ,
SUM ( goods_amt ) AS goods_amt_t
FROM custom_online_sale_order_local
WHERE SUBSTR ( min_order_time , 1 , 10 ) > = ' 2022-10-31 ' AND SUBSTR ( min_order_time , 1 , 10 ) < = ' 2022-11-11 '
GROUP BY store_code , system_order_no , platform_order_no
) GROUP BY store_code
) t2 ON t1 . store_code = t2 . store_code LEFT JOIN (
SELECT
store_code ,
SUM ( goods_amt_t ) + SUM ( order_freight_amt_t ) AS sale_money ,
COUNT ( DISTINCT platform_order_no ) AS order_count
FROM ( SELECT
store_code ,
platform_order_no ,
MAX ( order_freight_amt ) AS order_freight_amt_t ,
SUM ( goods_amt ) AS goods_amt_t
FROM custom_online_sale_order_local
WHERE SUBSTR ( min_order_time , 1 , 10 ) > = ' 2022-05-31 ' AND SUBSTR ( min_order_time , 1 , 10 ) < = ' 2022-06-20 '
GROUP BY store_code , system_order_no , platform_order_no
) GROUP BY store_code
) t3 ON t1 . store_code = t3 . store_code
ORDER BY t1 . all_sale_money DESC ;
SELECT
t1 . store_code AS " 店铺编码 " ,
t1 . store_name_t_t AS " 店铺名称 " ,
t3 . sale_money AS " 2023年618销售金额( 元) ( 包含运费) " ,
t3 . order_count AS " 2023年618订单数量 " ,
t2 . sale_money AS " 2023年双11销售金额( 元) ( 包含运费) " ,
t2 . order_count AS " 2023年双11订单数量 " ,
t1 . all_sale_money AS " 2023年总销售金额( 元) ( 包含运费) " ,
t1 . all_order_count AS " 2023年总订单数量 " ,
CASE WHEN t1 . all_sale_money = 0 THEN 0 ELSE ROUND ( t3 . sale_money / t1 . all_sale_money , 4 ) END AS " 2023年618销售金额占比 " ,
CASE WHEN t1 . all_sale_money = 0 THEN 0 ELSE ROUND ( t3 . order_count / t1 . all_order_count , 4 ) END AS " 2023年618订单数量占比 " ,
CASE WHEN t1 . all_sale_money = 0 THEN 0 ELSE ROUND ( t2 . sale_money / t1 . all_sale_money , 4 ) END AS " 2023年双11销售金额占比 " ,
CASE WHEN t1 . all_sale_money = 0 THEN 0 ELSE ROUND ( t2 . order_count / t1 . all_order_count , 4 ) END AS " 2023年双11订单数量占比 "
FROM ( SELECT
store_code ,
MAX ( store_name_t ) AS store_name_t_t ,
SUM ( goods_amt_t ) + SUM ( order_freight_amt_t ) AS all_sale_money ,
COUNT ( DISTINCT platform_order_no ) AS all_order_count
FROM ( SELECT
store_code ,
MAX ( store_name ) AS store_name_t ,
platform_order_no ,
MAX ( order_freight_amt ) AS order_freight_amt_t ,
SUM ( goods_amt ) AS goods_amt_t
FROM custom_online_sale_order_local
WHERE SUBSTR ( min_order_time , 1 , 10 ) > = ' 2023-01-01 ' AND SUBSTR ( min_order_time , 1 , 10 ) < = ' 2023-12-31 '
GROUP BY store_code , system_order_no , platform_order_no
) GROUP BY store_code
) t1 LEFT JOIN ( SELECT
store_code ,
SUM ( goods_amt_t ) + SUM ( order_freight_amt_t ) AS sale_money ,
COUNT ( DISTINCT platform_order_no ) AS order_count
FROM ( SELECT
store_code ,
platform_order_no ,
MAX ( order_freight_amt ) AS order_freight_amt_t ,
SUM ( goods_amt ) AS goods_amt_t
FROM custom_online_sale_order_local
WHERE SUBSTR ( min_order_time , 1 , 10 ) > = ' 2023-10-20 ' AND SUBSTR ( min_order_time , 1 , 10 ) < = ' 2023-11-11 '
GROUP BY store_code , system_order_no , platform_order_no
) GROUP BY store_code
) t2 ON t1 . store_code = t2 . store_code LEFT JOIN (
SELECT
store_code ,
SUM ( goods_amt_t ) + SUM ( order_freight_amt_t ) AS sale_money ,
COUNT ( DISTINCT platform_order_no ) AS order_count
FROM ( SELECT
store_code ,
platform_order_no ,
MAX ( order_freight_amt ) AS order_freight_amt_t ,
SUM ( goods_amt ) AS goods_amt_t
FROM custom_online_sale_order_local
WHERE SUBSTR ( min_order_time , 1 , 10 ) > = ' 2023-05-31 ' AND SUBSTR ( min_order_time , 1 , 10 ) < = ' 2023-06-20 '
GROUP BY store_code , system_order_no , platform_order_no
) GROUP BY store_code
) t3 ON t1 . store_code = t3 . store_code
ORDER BY t1 . all_sale_money DESC ;
SELECT
t1 . store_code AS " 店铺编码 " ,
t1 . store_name_t_t AS " 店铺名称 " ,
t3 . sale_money AS " 2024年618销售金额( 元) ( 包含运费) " ,
t3 . order_count AS " 2024年618订单数量 " ,
t2 . sale_money AS " 2024年双11销售金额( 元) ( 包含运费) " ,
t2 . order_count AS " 2024年双11订单数量 " ,
t1 . all_sale_money AS " 2024年总销售金额( 元) ( 包含运费) " ,
t1 . all_order_count AS " 2024年总订单数量 " ,
CASE WHEN t1 . all_sale_money = 0 THEN 0 ELSE ROUND ( t3 . sale_money / t1 . all_sale_money , 4 ) END AS " 2024年618销售金额占比 " ,
CASE WHEN t1 . all_sale_money = 0 THEN 0 ELSE ROUND ( t3 . order_count / t1 . all_order_count , 4 ) END AS " 2024年618订单数量占比 " ,
CASE WHEN t1 . all_sale_money = 0 THEN 0 ELSE ROUND ( t2 . sale_money / t1 . all_sale_money , 4 ) END AS " 2024年双11销售金额占比 " ,
CASE WHEN t1 . all_sale_money = 0 THEN 0 ELSE ROUND ( t2 . order_count / t1 . all_order_count , 4 ) END AS " 2024年双11订单数量占比 "
FROM ( SELECT
store_code ,
MAX ( store_name_t ) AS store_name_t_t ,
SUM ( goods_amt_t ) + SUM ( order_freight_amt_t ) AS all_sale_money ,
COUNT ( DISTINCT platform_order_no ) AS all_order_count
FROM ( SELECT
store_code ,
MAX ( store_name ) AS store_name_t ,
platform_order_no ,
MAX ( order_freight_amt ) AS order_freight_amt_t ,
SUM ( goods_amt ) AS goods_amt_t
FROM custom_online_sale_order_local
WHERE SUBSTR ( min_order_time , 1 , 10 ) > = ' 2024-01-01 ' AND SUBSTR ( min_order_time , 1 , 10 ) < = ' 2024-12-31 '
GROUP BY store_code , system_order_no , platform_order_no
) GROUP BY store_code
) t1 LEFT JOIN ( SELECT
store_code ,
SUM ( goods_amt_t ) + SUM ( order_freight_amt_t ) AS sale_money ,
COUNT ( DISTINCT platform_order_no ) AS order_count
FROM ( SELECT
store_code ,
platform_order_no ,
MAX ( order_freight_amt ) AS order_freight_amt_t ,
SUM ( goods_amt ) AS goods_amt_t
FROM custom_online_sale_order_local
WHERE SUBSTR ( min_order_time , 1 , 10 ) > = ' 2024-10-17 ' AND SUBSTR ( min_order_time , 1 , 10 ) < = ' 2024-11-11 '
GROUP BY store_code , system_order_no , platform_order_no
) GROUP BY store_code
) t2 ON t1 . store_code = t2 . store_code LEFT JOIN (
SELECT
store_code ,
SUM ( goods_amt_t ) + SUM ( order_freight_amt_t ) AS sale_money ,
COUNT ( DISTINCT platform_order_no ) AS order_count
FROM ( SELECT
store_code ,
platform_order_no ,
MAX ( order_freight_amt ) AS order_freight_amt_t ,
SUM ( goods_amt ) AS goods_amt_t
FROM custom_online_sale_order_local
WHERE SUBSTR ( min_order_time , 1 , 10 ) > = ' 2024-05-20 ' AND SUBSTR ( min_order_time , 1 , 10 ) < = ' 2024-06-20 '
GROUP BY store_code , system_order_no , platform_order_no
) GROUP BY store_code
) t3 ON t1 . store_code = t3 . store_code
ORDER BY t1 . all_sale_money DESC ;
SELECT
t1 . store_code AS " 店铺编码 " ,
t1 . store_name_t_t AS " 店铺名称 " ,
t2 . sale_money AS " 2025年618销售金额( 元) ( 包含运费) " ,
t2 . order_count AS " 2025年618订单数量 " ,
t1 . all_sale_money AS " 20250630总销售金额( 元) ( 包含运费) " ,
t1 . all_order_count AS " 20250630总订单数量 " ,
CASE WHEN t1 . all_sale_money = 0 THEN 0 ELSE ROUND ( t2 . sale_money / t1 . all_sale_money , 4 ) END AS " 到20250630·618销售金额占比 " ,
CASE WHEN t1 . all_sale_money = 0 THEN 0 ELSE ROUND ( t2 . order_count / t1 . all_order_count , 4 ) END AS " 到20250630·618订单数量占比 "
FROM ( SELECT
store_code ,
MAX ( store_name_t ) AS store_name_t_t ,
SUM ( goods_amt_t ) + SUM ( order_freight_amt_t ) AS all_sale_money ,
COUNT ( DISTINCT platform_order_no ) AS all_order_count
FROM ( SELECT
store_code ,
MAX ( store_name ) AS store_name_t ,
platform_order_no ,
MAX ( order_freight_amt ) AS order_freight_amt_t ,
SUM ( goods_amt ) AS goods_amt_t
FROM custom_online_sale_order_local
WHERE SUBSTR ( min_order_time , 1 , 10 ) > = ' 2025-01-01 ' AND SUBSTR ( min_order_time , 1 , 10 ) < = ' 2025-06-30 '
GROUP BY store_code , system_order_no , platform_order_no
) GROUP BY store_code
) t1 LEFT JOIN (
SELECT
store_code ,
SUM ( goods_amt_t ) + SUM ( order_freight_amt_t ) AS sale_money ,
COUNT ( DISTINCT platform_order_no ) AS order_count
FROM ( SELECT
store_code ,
platform_order_no ,
MAX ( order_freight_amt ) AS order_freight_amt_t ,
SUM ( goods_amt ) AS goods_amt_t
FROM custom_online_sale_order_local
WHERE SUBSTR ( min_order_time , 1 , 10 ) > = ' 2025-05-16 ' AND SUBSTR ( min_order_time , 1 , 10 ) < = ' 2025-06-20 '
GROUP BY store_code , system_order_no , platform_order_no
) GROUP BY store_code
) t2 ON t1 . store_code = t2 . store_code
ORDER BY t1 . all_sale_money DESC ;
-- 不区分店铺算总的
- - SELECT
-- a.sale_money AS "2022年618销售金额( 元) ( 包含运费) ",
-- a.order_count AS "2022年618订单数量",
-- b.sale_money AS "2022年双11销售金额( 元) ( 包含运费) ",
-- b.order_count AS "2022年双11订单数量",
-- c.all_sale_money AS "2022年总销售金额( 元) ( 包含运费) ",
-- c.all_order_count AS "2022年总订单数量",
-- ROUND(a.sale_money / c.all_sale_money, 4) AS "2022年618销售金额占比",
-- ROUND(a.order_count / c.all_order_count, 4) AS "2022年618订单数量占比",
-- ROUND(b.sale_money / c.all_sale_money, 4) AS "2022年双11销售金额占比",
-- ROUND(b.order_count / c.all_order_count, 4) AS "2022年双11订单数量占比"
- - FROM ( SELECT
-- SUM(sale_amt) AS sale_money,
-- SUM(order_amt) AS order_count
-- FROM (SELECT
-- SUM(goods_amt_t) + SUM(order_freight_amt_t) AS sale_amt,
-- COUNT(DISTINCT platform_order_no) AS order_amt
-- FROM (SELECT
-- store_code,
-- platform_order_no,
-- MAX(order_freight_amt) AS order_freight_amt_t,
-- SUM(goods_amt) AS goods_amt_t
-- FROM custom_online_sale_order_local
-- WHERE SUBSTR(min_order_time, 1, 10) >= '2022-05-31' AND SUBSTR(min_order_time, 1, 10) <= '2022-06-20'
-- GROUP BY store_code, system_order_no, platform_order_no
-- ) GROUP BY store_code) -- 为了不同店铺同一平台单算多条,再包一层
- - ) a , ( SELECT
-- SUM(sale_amt) AS sale_money,
-- SUM(order_amt) AS order_count
-- FROM (SELECT
-- SUM(goods_amt_t) + SUM(order_freight_amt_t) AS sale_amt,
-- COUNT(DISTINCT platform_order_no) AS order_amt
-- FROM (SELECT
-- store_code,
-- platform_order_no,
-- MAX(order_freight_amt) AS order_freight_amt_t,
-- SUM(goods_amt) AS goods_amt_t
-- FROM custom_online_sale_order_local
-- WHERE SUBSTR(min_order_time, 1, 10) >= '2022-10-31' AND SUBSTR(min_order_time, 1, 10) <= '2022-11-11'
-- GROUP BY store_code, system_order_no, platform_order_no
-- ) GROUP BY store_code)
- - ) b , ( SELECT
-- SUM(sale_amt) AS all_sale_money,
-- SUM(order_amt) AS all_order_count
-- FROM (SELECT
-- SUM(goods_amt_t) + SUM(order_freight_amt_t) AS sale_amt,
-- COUNT(DISTINCT platform_order_no) AS order_amt
-- FROM (SELECT
-- store_code,
-- platform_order_no,
-- MAX(order_freight_amt) AS order_freight_amt_t,
-- SUM(goods_amt) AS goods_amt_t
-- FROM custom_online_sale_order_local
-- WHERE SUBSTR(min_order_time, 1, 10) >= '2022-01-01' AND SUBSTR(min_order_time, 1, 10) <= '2022-12-31'
-- GROUP BY store_code, system_order_no, platform_order_no
-- ) GROUP BY store_code)
- - ) c ;
-- 账单店铺金额
SELECT
store_code AS " 店铺编码 " ,
MAX ( store_name) AS " 店铺名称 " ,
SUM ( goods _amt) AS " 销售金额(元) "
FROM custom_online_sale_bill_local
WHERE goods_amt > = 0 AND SUBSTR ( order_time , 1 , 10 ) > = ' 2022-06-01 ' AND SUBSTR ( order_time , 1 , 10 ) < = ' 2022-06-30 '
GROUP BY store_code
ORDER BY SUM ( goods_amt ) DESC ;
t1 . store_code AS " 店铺编码 " ,
t1 . store_name_t AS " 店铺名称 " ,
t3 . sale _amt AS " 2022年618 销售金额(元)" ,
t2 . sale_amt AS " 2022年双11销售金额( 元) " ,
t1 . all_sale_amt AS " 2022年总销售金额( 元) " ,
CASE WHEN t1 . all_sale_amt = 0 THEN 0 ELSE ROUND ( t3 . sale_amt / t1 . all_sale_amt , 4 ) END AS " 2022年618销售金额占比 " ,
CASE WHEN t1 . all_sale_amt = 0 THEN 0 ELSE ROUND ( t2 . sale_amt / t1 . all_sale_amt , 4 ) END AS " 2022年双11销售金额占比 "
FROM ( SELECT
store_code ,
MAX ( store_name ) AS store_name_t ,
SUM ( goods_amt ) AS all_sale_amt
FROM custom_online_sale_bill_local
WHERE goods_amt > = 0 AND SUBSTR ( order_time , 1 , 10 ) > = ' 2022-01-01 ' AND SUBSTR ( order_time , 1 , 10 ) < = ' 2022-12-31 '
GROUP BY store_code
) t1 LEFT JOIN ( SELECT
store_code ,
SUM ( goods_amt ) AS sale_amt
FROM custom_online_sale_bill_local
WHERE goods_amt > = 0 AND SUBSTR ( order_time , 1 , 10 ) > = ' 2022-10-31 ' AND SUBSTR ( order_time , 1 , 10 ) < = ' 2022-11-11 '
GROUP BY store_code
) t2 ON t1 . store_code = t2 . store_code LEFT JOIN ( SELECT
store_code ,
SUM ( goods_amt ) AS sale_amt
FROM custom_online_sale_bill_local
WHERE goods_amt > = 0 AND SUBSTR ( order_time , 1 , 10 ) > = ' 2022-05-31 ' AND SUBSTR ( order_time , 1 , 10 ) < = ' 2022-06-20 '
GROUP BY store_code
) t3 ON t1 . store_code = t3 . store_code
ORDER BY t1 . all_sale_amt DESC ;
SELECT
t1 . store_code AS " 店铺编码 " ,
t1 . store_name_t AS " 店铺名称 " ,
t3 . sale_amt AS " 2023年618销售金额( 元) " ,
t2 . sale_amt AS " 2023年双11销售金额( 元) " ,
t1 . all_sale_amt AS " 2023年总销售金额( 元) " ,
CASE WHEN t1 . all_sale_amt = 0 THEN 0 ELSE ROUND ( t3 . sale_amt / t1 . all_sale_amt , 4 ) END AS " 2023年618销售金额占比 " ,
CASE WHEN t1 . all_sale_amt = 0 THEN 0 ELSE ROUND ( t2 . sale_amt / t1 . all_sale_amt , 4 ) END AS " 2023年双11销售金额占比 "
FROM ( SELECT
store_code ,
MAX ( store_name ) AS store_name_t ,
SUM ( goods_amt ) AS all_sale_amt
FROM custom_online_sale_bill_local
WHERE goods_amt > = 0 AND SUBSTR ( order_time , 1 , 10 ) > = ' 2023-01-01 ' AND SUBSTR ( order_time , 1 , 10 ) < = ' 2023-12-31 '
GROUP BY store_code
) t1 LEFT JOIN ( SELECT
store_code ,
SUM ( goods_amt ) AS sale_amt
FROM custom_online_sale_bill_local
WHERE goods_amt > = 0 AND SUBSTR ( order_time , 1 , 10 ) > = ' 2023-10-20 ' AND SUBSTR ( order_time , 1 , 10 ) < = ' 2023-11-11 '
GROUP BY store_code
) t2 ON t1 . store_code = t2 . store_code LEFT JOIN ( SELECT
store_code ,
SUM ( goods_amt ) AS sale_amt
FROM custom_online_sale_bill_local
WHERE goods_amt > = 0 AND SUBSTR ( order_time , 1 , 10 ) > = ' 2023-05-31 ' AND SUBSTR ( order_time , 1 , 10 ) < = ' 2023-06-20 '
GROUP BY store_code
) t3 ON t1 . store_code = t3 . store_code
ORDER BY t1 . all_sale_amt DESC ;
SELECT
t1 . store_code AS " 店铺编码 " ,
t1 . store_name_t AS " 店铺名称 " ,
t3 . sale_amt AS " 2024年618销售金额( 元) " ,
t2 . sale_amt AS " 2024年双11销售金额( 元) " ,
t1 . all_sale_amt AS " 2024年总销售金额( 元) " ,
CASE WHEN t1 . all_sale_amt = 0 THEN 0 ELSE ROUND ( t3 . sale_amt / t1 . all_sale_amt , 4 ) END AS " 2024年618销售金额占比 " ,
CASE WHEN t1 . all_sale_amt = 0 THEN 0 ELSE ROUND ( t2 . sale_amt / t1 . all_sale_amt , 4 ) END AS " 2024年双11销售金额占比 "
FROM ( SELECT
store_code ,
MAX ( store_name ) AS store_name_t ,
SUM ( goods_amt ) AS all_sale_amt
FROM custom_online_sale_bill_local
WHERE goods_amt > = 0 AND SUBSTR ( order_time , 1 , 10 ) > = ' 2024-01-01 ' AND SUBSTR ( order_time , 1 , 10 ) < = ' 2024-12-31 '
GROUP BY store_code
) t1 LEFT JOIN ( SELECT
store_code ,
SUM ( goods_amt ) AS sale_amt
FROM custom_online_sale_bill_local
WHERE goods_amt > = 0 AND SUBSTR ( order_time , 1 , 10 ) > = ' 2024-10-17 ' AND SUBSTR ( order_time , 1 , 10 ) < = ' 2024-11-11 '
GROUP BY store_code
) t2 ON t1 . store_code = t2 . store_code LEFT JOIN ( SELECT
store_code ,
SUM ( goods_amt ) AS sale_amt
FROM custom_online_sale_bill_local
WHERE goods_amt > = 0 AND SUBSTR ( order_time , 1 , 10 ) > = ' 2024-05-20 ' AND SUBSTR ( order_time , 1 , 10 ) < = ' 2024-06-20 '
GROUP BY store_code
) t3 ON t1 . store_code = t3 . store_code
ORDER BY t1 . all_sale_amt DESC ;
SELECT
t1 . store_code AS " 店铺编码 " ,
t1 . store_name_t AS " 店铺名称 " ,
t2 . sale_amt AS " 2025年618销售金额( 元) " ,
t1 . all_sale_amt AS " 20250630总销售金额( 元) " ,
CASE WHEN t1 . all_sale_amt = 0 THEN 0 ELSE ROUND ( t2 . sale_amt / t1 . all_sale_amt , 4 ) END AS " 到20250630·618销售金额占比 "
FROM ( SELECT
store_code ,
MAX ( store_name ) AS store_name_t ,
SUM ( goods_amt ) AS all_sale_amt
FROM custom_online_sale_bill_local
WHERE goods_amt > = 0 AND SUBSTR ( order_time , 1 , 10 ) > = ' 2025-01-01 ' AND SUBSTR ( order_time , 1 , 10 ) < = ' 2025-06-30 '
GROUP BY store_code
) t1 LEFT JOIN ( SELECT
store_code ,
SUM ( goods_amt ) AS sale_amt
FROM custom_online_sale_bill_local
WHERE goods_amt > = 0 AND SUBSTR ( order_time , 1 , 10 ) > = ' 2025-05-16 ' AND SUBSTR ( order_time , 1 , 10 ) < = ' 2025-06-20 '
GROUP BY store_code
) t2 ON t1 . store_code = t2 . store_code
ORDER BY t1 . all_sale_amt DESC ;
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - --
-- 4.1线上每年订单下单和发货间隔的销售金额、订单数量分布
@@ -954,7 +1327,7 @@ SELECT COUNT() FROM dwd_basic_all_vip_point_dd WHERE change_time = '';
--SELECT t2.*
- - FROM ( SELECT DISTINCT store_code FROM custom_online_sale_order_local WHERE SUBSTR ( min_order_time , 1 , 10 ) > = ' 2022-01-01 ' AND SUBSTR ( min_order_time , 1 , 10 ) < = ' 2025-06-30 ' ) t1
- - INNER JOIN dwd_basic_all_vip_info_dd t2 ON t1 . store_code = t2 . member_register_shop
- - WHERE SUBSTR ( t2 . member_register_time , 1 , 10 ) < = ' 2025-06-30 ' ;
- - WHERE SUBSTR ( t2 . member_register_ti me , 1 , 10 ) < = ' 2025-06-30 ' ;
-- 订单号关联不到积分数据
SELECT * FROM custom_online_sale_order_local WHERE platform_order_no IN ( SELECT bill_no FROM dwd_basic_all_vip_point_dd WHERE bill_no < > ' ' ) ;
@@ -1013,5 +1386,101 @@ ORDER BY SUBSTR(t2.member_register_time, 1, 4);
-- 7.4线上每年会员积分新增、消耗、清零数量
-- 积分类型
SELECT DISTINCT change_kind FROM dwd_basic_all_vip_point_dd ;
-- 积分清零有大于0的
SELECT * FROM dwd_basic_all_vip_point_dd WHERE change_kind = ' 60 ' AND point_change > ' 0 ' ;
-- 正向积分 获取
SELECT SUBSTR ( change_time , 1 , 4 ) AS perYear , SUM ( toDecimal64 ( point_change , 2 ) )
FROM dwd_basic_all_vip_point_dd
WHERE member_id IN ( SELECT DISTINCT member_id
FROM ( SELECT DISTINCT store_code FROM custom_online_sale_order_local WHERE SUBSTR ( min_order_time , 1 , 10 ) > = ' 2022-01-01 ' AND SUBSTR ( min_order_time , 1 , 10 ) < = ' 2025-06-30 ' ) t1
INNER JOIN dwd_basic_all_vip_info_dd t2 ON t1 . store_code = t2 . member_register_shop
WHERE t2 . member_register_time < > ' ' )
AND point_change > ' 0 ' AND change_time < > ' ' AND SUBSTR ( change_time , 1 , 10 ) > = ' 2022-01-01 ' AND SUBSTR ( change_time , 1 , 10 ) < = ' 2025-06-30 '
GROUP BY SUBSTR ( change_time , 1 , 4 )
ORDER BY SUBSTR ( change_time , 1 , 4 ) ;
-- 逆向积分 消耗
SELECT SUBSTR ( change_time , 1 , 4 ) AS perYear , SUM ( toDecimal64 ( point_change , 2 ) )
FROM dwd_basic_all_vip_point_dd
WHERE member_id IN ( SELECT DISTINCT member_id
FROM ( SELECT DISTINCT store_code FROM custom_online_sale_order_local WHERE SUBSTR ( min_order_time , 1 , 10 ) > = ' 2022-01-01 ' AND SUBSTR ( min_order_time , 1 , 10 ) < = ' 2025-06-30 ' ) t1
INNER JOIN dwd_basic_all_vip_info_dd t2 ON t1 . store_code = t2 . member_register_shop
WHERE t2 . member_register_time < > ' ' )
AND point_change < ' 0 ' AND change_time < > ' ' AND SUBSTR ( change_time , 1 , 10 ) > = ' 2022-01-01 ' AND SUBSTR ( change_time , 1 , 10 ) < = ' 2025-06-30 ' AND change_kind < > ' 60 '
GROUP BY SUBSTR ( change_time , 1 , 4 )
ORDER BY SUBSTR ( change_time , 1 , 4 ) ;
-- 积分清零
SELECT SUBSTR ( change_time , 1 , 4 ) AS perYear , SUM ( toDecimal64 ( point_change , 2 ) )
FROM dwd_basic_all_vip_point_dd
WHERE member_id IN ( SELECT DISTINCT member_id
FROM ( SELECT DISTINCT store_code FROM custom_online_sale_order_local WHERE SUBSTR ( min_order_time , 1 , 10 ) > = ' 2022-01-01 ' AND SUBSTR ( min_order_time , 1 , 10 ) < = ' 2025-06-30 ' ) t1
INNER JOIN dwd_basic_all_vip_info_dd t2 ON t1 . store_code = t2 . member_register_shop
WHERE t2 . member_register_time < > ' ' )
AND point_change < ' 0 ' AND change_time < > ' ' AND SUBSTR ( change_time , 1 , 10 ) > = ' 2022-01-01 ' AND SUBSTR ( change_time , 1 , 10 ) < = ' 2025-06-30 ' AND change_kind = ' 60 '
GROUP BY SUBSTR ( change_time , 1 , 4 )
ORDER BY SUBSTR ( change_time , 1 , 4 ) ;
- - SELECT SUBSTR ( change_time , 1 , 4 ) AS perYear , change_kind , MAX ( t2 . point_change_name ) , SUM ( toDecimal64 ( point_change , 2 ) )
- - FROM dwd_basic_all_vip_point_dd t1 LEFT JOIN custom_point_change_enum_local t2 ON t1 . change_kind = t2 . point_change_kind
- - WHERE member_id IN ( SELECT DISTINCT member_id
-- FROM (SELECT DISTINCT store_code FROM custom_online_sale_order_local WHERE SUBSTR(min_order_time, 1, 10) >= '2022-01-01' AND SUBSTR(min_order_time, 1, 10) <= '2025-06-30') t1
-- INNER JOIN dwd_basic_all_vip_info_dd t2 ON t1.store_code = t2.member_register_shop
-- WHERE t2.member_register_time <> '')
- - AND point_change > ' 0 ' AND change_time < > ' ' AND SUBSTR ( change_time , 1 , 10 ) > = ' 2022-01-01 ' AND SUBSTR ( change_time , 1 , 10 ) < = ' 2025-06-30 '
- - GROUP BY SUBSTR ( change_time , 1 , 4 ) , change_kind
- - ORDER BY SUBSTR ( change_time , 1 , 4 ) ;
- - SELECT SUBSTR ( change_time , 1 , 4 ) AS perYear , change_kind ,
-- CASE
-- WHEN change_kind = '1' THEN '初始积分'
-- WHEN change_kind = '2' THEN '交易送积分-线下'
-- WHEN change_kind = '7' THEN '交易退积分-线下'
-- WHEN change_kind = '9' THEN '调整积分'
-- WHEN change_kind = '13' THEN '接口赠送'
-- WHEN change_kind = '15' THEN '第三方发独立活动扣积分'
-- WHEN change_kind = '16' THEN '第三方活动积分类型'
-- WHEN change_kind = '19' THEN '调整减少积分'
-- WHEN change_kind = '20' THEN '交易基础积分'
-- WHEN change_kind = '21' THEN '交易基础积分-退'
-- WHEN change_kind = '22' THEN '交易活动积分'
-- WHEN change_kind = '23' THEN '交易活动积分-退'
-- WHEN change_kind = '30' THEN '退货'
-- WHEN change_kind = '40' THEN '其他'
-- WHEN change_kind = '50' THEN '交易送积分-线上商城'
-- WHEN change_kind = '51' THEN '交易退积分-线上商城'
-- WHEN change_kind = '52' THEN '交易送积分,三方商城,京东天猫等'
-- WHEN change_kind = '53' THEN '交易退积分.三方商城,京东天猫等'
-- WHEN change_kind = '54' THEN '交易送积分-线上商城'
-- WHEN change_kind = '70' THEN '人工调增'
-- WHEN change_kind = '80' THEN '人工调减'
-- WHEN change_kind = '90' THEN '营销互动奖励积分'
-- WHEN change_kind = '91' THEN '营销互动扣减积分'
-- WHEN change_kind = '92' THEN '生日奖励积分'
-- WHEN change_kind = '93' THEN '注册奖励积分'
-- WHEN change_kind = '94' THEN '完善资料奖励积分'
-- WHEN change_kind = '95' THEN '升降级奖励积分'
-- WHEN change_kind = '96' THEN '通用事件奖励积分'
-- WHEN change_kind = '5' THEN '积分兑换'
-- WHEN change_kind = '6' THEN '积分抵现'
-- WHEN change_kind = '8' THEN '积分抵现-冲正'
-- WHEN change_kind = '10' THEN '积分抵现-退货'
-- WHEN change_kind = '24' THEN '积分兑商品'
-- WHEN change_kind = '25' THEN '积分兑商品-冲正'
-- WHEN change_kind = '60' THEN '积分清零'
-- WHEN change_kind = '97' THEN '生日奖励积分'
-- WHEN change_kind = '98' THEN '交易基础积分'
-- WHEN change_kind = '99' THEN '交易基础积分-退'
-- WHEN change_kind = '100' THEN '交易基础积分'
-- WHEN change_kind = '101' THEN '交易基础积分-退'
-- END AS "积分变动类型值",
-- SUM(toDecimal64(point_change, 2))
- - FROM dwd_basic_all_vip_point_dd
- - WHERE member_id IN ( SELECT DISTINCT member_id
-- FROM (SELECT DISTINCT store_code FROM custom_online_sale_order_local WHERE SUBSTR(min_order_time, 1, 10) >= '2022-01-01' AND SUBSTR(min_order_time, 1, 10) <= '2025-06-30') t1
-- INNER JOIN dwd_basic_all_vip_info_dd t2 ON t1.store_code = t2.member_register_shop
-- WHERE t2.member_register_time <> '')
- - AND point_change > ' 0 ' AND change_time < > ' ' AND SUBSTR ( change_time , 1 , 10 ) > = ' 2022-01-01 ' AND SUBSTR ( change_time , 1 , 10 ) < = ' 2025-06-30 '
- - GROUP BY SUBSTR ( change_time , 1 , 4 ) , change_kind
- - ORDER BY SUBSTR ( change_time , 1 , 4 ) ;
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -