WITH all_orders AS ( SELECT A .create_time AS TIME, A.paid_amount AS amount, 'flower_t_order' AS order_table_name FROM flower_t_order A WHERE A.member_id = 1 AND EXTRACT ( YEAR FROM A.create_time ) = 2023 UNION ALL SELECT B.create_time AS TIME, B.paid_amount AS amount, 'shop_t_order' AS order_table_name FROM shop_t_order B WHERE B.member_id = 1 AND EXTRACT ( YEAR FROM B.create_time ) = 2023 UNION ALL SELECT C .create_time AS TIME, C.paid_amount AS amount, 'ticket_t_order' AS order_table_name FROM ticket_t_order C WHERE C.member_id = 1 AND EXTRACT ( YEAR FROM b.create_time ) = 2023 ) SELECT EXTRACT ( MONTH FROM all_orders."time" ( TIMESTAMP ) ) AS MONTH, SUM ( all_orders.amount ) AS total_order_amount, COUNT ( * ) AS total_order_count, SUM ( CASE WHEN order_table_name = 'flower_t_order' THEN paid_amount ELSE 0 END ) AS order_table_1_amount, SUM ( CASE WHEN order_table_name = 'shop_t_order' THEN paid_amount ELSE 0 END ) AS order_table_2_amount, SUM ( CASE WHEN order_table_name = 'ticket_t_order' THEN paid_amount ELSE 0 END ) AS order_table_3_amount FROM all_orders GROUP BY MONTH ORDER BY MONTH;

SELECT users.username, SUM(orders.order_total) AS total_order_amount, SUM(orders.order_total) / (SELECT SUM(order_total) FROM orders) * 100 AS order_percent FROM users INNER JOIN orders ON users.user_id = orders.user_id GROUP BY users.user_id ORDER BY order_percent DESC; 如何优化

SUM(orders.order_total) AS total_order_amount, SUM(orders.order_total) / total_sum_order_total.sum_order_total * 100 AS order_percent FROM users INNER JOIN orders ON users.user_id = orders....

为什么下面的sql语句会输出重复的结果：SELECT tp.parent_production_orders AS parent_production_orders, tp.production_orders AS production_orders, tp.work_order AS work_order, tp.contract AS contract, tp.sbbh AS sbbh, tp.batch_num AS batch_num, tp.product_code AS product_code, tp.product_number AS product_number, tp.product_name AS product_name, to_char( middle.create_date, 'yyyy-mm-dd' ) AS issued_date, to_char( to_timestamp( tp.delivery_time / 1000 ), 'yyyy-mm-dd' ) AS delivery_time, middle.line_code AS work_area_code, middle.line_name AS work_area_name, tp.workorder_number AS workorder_number, tp.complete_number AS complete_number, tp.part_unit AS part_unit, middle.work_time_type AS work_time_type, middle.process_time AS process_time, CASE WHEN sc.totalSubmitHours IS NULL THEN 0 ELSE sc.totalSubmitHours END AS submit_work_hours, CASE WHEN middle.process_time > 0 AND sc.totalSubmitHours IS NOT NULL THEN round( ( sc.totalSubmitHours / middle.process_time ), 2 ) * 100 ELSE 0 END plan_achievement_rate, CASE WHEN sc.totalSubmitHours IS NULL THEN 0 ELSE round( CAST ( sc.totalSubmitHours AS NUMERIC ) / CAST ( 60 AS NUMERIC ), 1 ) END AS submit_work_hours_h, round( CAST ( middle.process_time AS NUMERIC ) / CAST ( 60 AS NUMERIC ), 1 ) AS process_time_h, pinfo.material_channel AS material_channel FROM hm_model_work_order_report_middle middle LEFT JOIN hm_model_trc_plan tp ON middle.work_order = tp.work_order LEFT JOIN ( SELECT oro.work_order AS orderNo, oro.work_area_code AS lineCode, SUM ( submit_work_hours ) AS totalSubmitHours, '自制' AS workHourType FROM hm_model_trc_order_report_operation_u orou LEFT JOIN hm_model_trc_order_report_operation oro ON orou.work_order_process_id = oro.ID WHERE orou.work_order_process_id IS NOT NULL AND oro.work_area_code IS NOT NULL GROUP BY oro.work_order, oro.work_area_code UNION all SELECT ohs.work_order_no AS orderNo, ohs.line_code AS lineCode, SUM ( receiving_hour ) AS totalSubmitHours, '外委' AS workHourType FROM hm_model_outsourcing_hour_statistics ohs GROUP BY ohs.work_order_no, ohs.line_code ) sc ON middle.work_order = sc.orderNo AND middle.line_code = sc.lineCode AND middle.work_time_type = sc.workHourType LEFT JOIN hm_model_part_info AS pinfo ON tp.product_number = pinfo.part_code WHERE middle.process_time > 0 AND tp.delivery_time IS NOT NULL AND tp.production_orders LIKE'FJ2023051100286' ORDER BY to_char( to_timestamp( tp.delivery_time / 1000 ), 'yyyy-mm-dd' ) DESC, tp.parent_production_orders DESC, tp.node_level ASC

例如：SELECT DISTINCT tp.parent_production_orders AS parent_production_orders, tp.production_orders AS production_orders, ... （省略后面的 SQL 语句）。另外，还可以检查查询条件是否合理，是否需要增加更...

WITH filtered_goods AS ( SELECT model FROM base_goods AS bg WHERE bg.type_one = 1 ), aggregated_orders AS ( SELECT og.goods_model, m.merchant_id, SUM( og.buy_num ) AS amount FROM order_goods AS og JOIN orders AS m ON og.order_id = m.id WHERE m.status IN ( 0, 2, 3, 5, 6, 8, 9, 10, 11, 17 ) AND og.goods_model IN ( SELECT model FROM filtered_goods ) GROUP BY m.merchant_id, og.goods_model ) SELECT m.merchant_id, m.goods_model, m.amount, bg.market_date, bg.short_name, mr.shop_name FROM aggregated_orders AS m JOIN base_goods AS bg ON m.goods_model = bg.model JOIN merchant AS mr ON m.merchant_id = mr.id

具体来说，这个查询语句先用一个子查询过滤出类型为1的商品，然后在orders表和order_goods表中根据一些状态条件和商品型号条件筛选订单，统计出每个商家销售的每个商品数量，最后通过JOIN操作连接base_goods表和...

SELECT users.username, SUM(orders.order_total) AS total_order_amount, SUM(orders.order_total) / total_sum_order_total.sum_order_total * 100 AS order_percent FROM users INNER JOIN orders ON users.user_id = orders.user_id CROSS JOIN (SELECT SUM(order_total) AS sum_order_total FROM orders) AS total_sum_order_total GROUP BY users.user_id ORDER BY order_percent DESC; 为什么要用到cross join

在 SELECT 子句中，我们可以使用 total_sum_order_total 子查询中的 sum_order_total 列来计算每个用户的订单总金额与所有订单总金额的比例。由于只有一个行，我们使用 CROSS JOIN 来将它与 users 表和 orders 表...

SELECT orders.id,orders.user_id,orders.cityarea_id,orders.batchcode,orders.status, orders.pay_status,orders.real_pay,orders.total,orders.money,orders.pay_type, orders.premium,orders.createtime,orders.paytime,orders.confirmtime, orders.is_evaluate,orders.pay_method,orders.exp_user_id, orders.return_score, orders.is_change,orders.reward_money,orders.isvalid,orders.after_sale_status,orders.remark, orders.use_coupon_detail,orders.block_chain_price, users.name,users.weixin_name,users.weixin_fromuser, users.phone,wcoe.diy_area_name ,writes.ActivityStatus,writes.NewMoney,records.Commission,records.ReturnRadio from wsy_o2o.weixin_cityarea_orders orders left join wsy_o2o.weixin_cityarea_supply supply on orders.cityarea_id = supply.id left join wsy_o2o.weixin_cityarea_payonline_orders wcco on orders.batchcode=wcco.batchcode left join wsy_user.weixin_users users on users.id = orders.user_id LEFT JOIN wsy_o2o.weixin_cityarea_orders_extend wcoe ON orders.batchcode = wcoe.batchcode LEFT JOIN wsy_dream.ShopWrite writes on orders.batchcode = writes.Batchcode LEFT JOIN wsy_o2o.weixin_cityarea_supply_commissons_record records ON orders.cityarea_id = records.SupplyId and records.CreateTime < orders.createtime ORDER BY records.CreateTime DESC LIMIT 1 WHERE orders.types=3 and orders.customer_id = 41 AND orders.isvalid=true GROUP BY orders.batchcode ORDER BY orders.id DESC limit 0,20; 以上代码报错，怎么解决

SELECT orders.id, orders.user_id, orders.cityarea_id, orders.batchcode, orders.status, orders.pay_status, orders.real_pay, orders.total, orders.money, orders.pay_type, orders.premium, orders....

SQL 中with get_lot_id as

select lot_id, count(*) as total_orders from orders group by lot_id ) select lot_id, total_orders from get_lot_id where total_orders > 5; 这个查询首先创建了一个名为 get_lot_id 的临时查询结果...

SUM(orders.order_total) / (SELECT SUM(order_total) FROM orders) * 100 AS order_percent

其中，SUM(orders.order_total)用于计算某个订单的总金额，(SELECT SUM(order_total) FROM orders)用于计算所有订单的总金额，最后将两者相除并乘以100得到百分比。结果将被命名为order_percent。

flink sql中for system_time as of是什么意思

Flink SQL中的FOR SYSTEM_TIME AS OF语法是用于查询在某个时间点之前的历史数据版本的。它可以用于支持时间旅行查询（Time Travel Query）。具体来说，FOR SYSTEM_TIME AS OF语法允许用户指定一个时间点，然后...

select count(*) FROM xgb_order_products op LEFT JOIN xgb_orders o ON o.order_id=op.order_id left join xgb_order_after_sales oas on op.order_id = oas.order_id where (op.all_refund = 0 or (oas.type = 2 and oas.status = 5) and o.status = 4 and op.is_comment = 0 and o.user_id = 492740 and op.is_gift = 0

- 订单商品表 xgb_order_products 中的 all_refund 字段等于 0； - 订单表 xgb_orders 中的 status 等于 4，user_id 等于 492740； - 订单商品表 xgb_order_products 中的 is_comment 字段等于 0，is_gift 字段等于 ...

select Customers.cust_name,Orders.oder_num from Customers inner join Orders on Customers.cust_id == Orders.cust_id order by Customers.cust_name desc这句SQL有什么语法错误

SELECT Customers.cust_name, Orders.oder_num FROM Customers INNER JOIN Orders ON Customers.cust_id = Orders.cust_id ORDER BY Customers.cust_name DESC 这将按照顾客的名称（以降序排列）和订单号...

UpdateWrapper<Orders>().eq("order_no", tradeNo)

这是一个 Java 代码片段，它使用 MyBatis-Plus 框架中的 UpdateWrapper 类来构建一个更新操作，更新 Orders 表中 order_no 字段等于 tradeNo 的记录。具体来说，eq 方法表示相等条件，参数 "order_no" 是字段名，...

优化这段代码 select o.cust_id,s.total_ordered from Orders o left join (select order_num,sum(item_pricequantity) as total_ordered from OrderItems group by order_num order by sum(item_pricequantity))s on s.order_num=o.order_num order by s.total_ordered desc;

WITH OrderTotals AS ( SELECT order_num, SUM(item_price * quantity) AS total_ordered FROM OrderItems GROUP BY order_num ) SELECT o.cust_id, s.total_ordered FROM Orders o LEFT JOIN OrderTotals s ON s...

select customer_number from Orders where MAX(order_number)

WHERE order_number = (SELECT MAX(order_number) FROM Orders); 这条 SQL 语句的作用是，首先在 Orders 表中查询最大的 order_number，然后再根据这个最大的 order_number 查询对应的 customer_number。注意，...

select t.id,t.amount from( select row_number() over(partition by amount) rn from users u join orders o on u.id=o.id desc)t where t.rn <=10;

ROW_NUMBER() OVER (PARTITION BY o.amount ORDER BY o.order_date DESC) AS rn FROM users u JOIN orders o ON u.id = o.user_id ) t WHERE t.rn ; 这个查询语句首先使用 INNER JOIN 将用户表和订单表连接...

import datetime import pandas as pd def generate_figure(user_name): with open('./data/orders.txt','r') as f1: orders = [eval(each.strip()) for each in f1.readlines()] users_order = [user for user in orders if user['username'] == user_name] order_list = [] with open('./data/produts.txt','r') as f2: products = [eval(product.strip()) for product in f2.readlines()] for item in users_order: user_all_orders = {} user_all_orders['month'] = datetime.datetime.strftime(datetime.datetime.strptime(item['create_time'],"%Y-%m-%d_%H:%M:%S"),"%B") user_all_orders['pro_id'] = item['pro_id'] user_all_orders['pro_price'] = ''.join([str(each['pro_current_price']) for each in products if each['pro_id'] == item['pro_id']]) order_list.append(user_all_orders) df_orders = pd.DataFrame(order_list)这段代码中我该怎么写才能让df_orders变成group by month并且显示的是该月份消费的proprice的总和

with open('./data/orders.txt', 'r') as f1: orders = [eval(each.strip()) for each in f1.readlines()] users_order = [user for user in orders if user['username'] == user_name] order_list = [] with ...

SELECT a.batchcode,a.createtime,a.real_pay,a.total,a.money,b.ReturnRadio,b.Commission,c.RateBankMoney FROM wsy_o2o.weixin_cityarea_orders a LEFT JOIN wsy_o2o.weixin_cityarea_supply_commissons_record b on a.cityarea_id = b.SupplyId LEFT JOIN taocat.bankhead c on a.batchcode = c.BatchCode WHERE a.batchcode = 1380581689148037 and b.CreateTime < a.createtime GROUP BY CommissionRecordid DESC LIMIT 1; 优化上面的SQL语句

FROM wsy_o2o.weixin_cityarea_orders AS a LEFT JOIN wsy_o2o.weixin_cityarea_supply_commissons_record AS b ON a.cityarea_id = b.SupplyId AND b.CreateTime < a.createtime LEFT JOIN taocat.bankhead AS c ON...

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SELECT users.username, SUM(orders.order_total) AS total_order_amount, SUM(orders.order_total) / (SELECT SUM(order_total) FROM orders) * 100 AS order_percent FROM users INNER JOIN orders ON users.user_id = orders.user_id GROUP BY users.user_id ORDER BY order_percent DESC; 如何优化

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优化这段代码 select o.cust_id,s.total_ordered from Orders o left join (select order_num,sum(item_price*quantity) as total_ordered from OrderItems group by order_num order by sum(item_price*quantity))s on s.order_num=o.order_num order by s.total_ordered desc;

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优化这段代码 select o.cust_id,s.total_ordered from Orders o left join (select order_num,sum(item_pricequantity) as total_ordered from OrderItems group by order_num order by sum(item_pricequantity))s on s.order_num=o.order_num order by s.total_ordered desc;