优化 sql : SELECT /*aggregation_path_type=single_agg*/ `company_code`, `company_name`, `sale_id`, `sale_name`, round(sum(`checkin_uv`), 2) AS peopleSum, round(sum(`cash_pay`), 2) AS cashPay, round(sum(`account_pay`), 2) AS accountPay, round(sum(`salecard_pay`), 2) AS saleCardPay, round(sum(`online_pay`), 2) AS onlinePay, round(sum(`pay_amount_final`), 2) AS payAmount, round(sum(`total_original_price`), 2) AS originalPrice, CASE WHEN sum(`total_original_price`) = 0 THEN 0 ELSE Round( sum(`pay_amount_final`) / sum(`total_original_price`) * 100, 2 ) END AS discount, CASE WHEN sum(`checkin_uv`) = 0 THEN 0 ELSE Round(sum(`pay_amount_final`) / sum(`checkin_uv`), 2) END AS priceAvg, round(SUM(`settlement_pice_exclude_add`), 2) AS saleExcludeAdd, round(SUM(`original_pice_exclude_add`), 2) AS originalExcludeAdd, CASE WHEN sum(`total_original_price`) = 0 THEN 0 ELSE Round( ( SUM(`settlement_pice_exclude_add`) / sum(`total_original_price`) * 100 ), 2 ) END AS excludeAddDis, CASE WHEN sum(`checkin_uv`) = 0 THEN 0 ELSE Round( SUM(`settlement_pice_exclude_add`) / sum(`checkin_uv`), 2 ) END AS excludeAddPriceAvg FROM `salesman_confim_revenue_v2` WHERE sale_region_code = '8' and DATE_FORMAT(checkin_time, '%Y-%m-%d') >= DATE_FORMAT('2023-04-01', '%Y-%m-%d') and DATE_FORMAT(checkin_time, '%Y-%m-%d') <= DATE_FORMAT('2023-05-22', '%Y-%m-%d') GROUP BY `company_code`, `sale_id` ORDER BY `company_code` DESC

可以尝试对该 SQL 进行如下优化：

1. 使用索引：在 `salesman_confim_revenue_v2` 表中创建 `sale_region_code` 和 `checkin_time` 字段的联合索引，可以提高查询效率。

2. 使用 BETWEEN 代替两个 DATE_FORMAT：可以将 `DATE_FORMAT(checkin_time, '%Y-%m-%d') >= DATE_FORMAT('2023-04-01', '%Y-%m-%d')` 和 `DATE_FORMAT(checkin_time, '%Y-%m-%d') <= DATE_FORMAT('2023-05-22', '%Y-%m-%d')` 替换为 `checkin_time BETWEEN '2023-04-01' AND '2023-05-22'`，可以减少函数的使用，提高查询效率。

3. 减少聚合函数的使用：可以将 `sum` 和 `round` 函数的使用减少，避免重复计算，提高查询效率。

优化后的 SQL 如下：

SELECT 
    /*aggregation_path_type=single_agg*/ 
    `company_code`, 
    `company_name`, 
    `sale_id`, 
    `sale_name`, 
    ROUND(SUM(`checkin_uv`), 2) AS peopleSum, 
    ROUND(SUM(`cash_pay`), 2) AS cashPay, 
    ROUND(SUM(`account_pay`), 2) AS accountPay, 
    ROUND(SUM(`salecard_pay`), 2) AS saleCardPay, 
    ROUND(SUM(`online_pay`), 2) AS onlinePay, 
    ROUND(SUM(`pay_amount_final`), 2) AS payAmount, 
    ROUND(SUM(`total_original_price`), 2) AS originalPrice, 
    CASE 
        WHEN SUM(`total_original_price`) = 0 THEN 0 
        ELSE ROUND(SUM(`pay_amount_final`) / SUM(`total_original_price`) * 100, 2) 
    END AS discount, 
    CASE 
        WHEN SUM(`checkin_uv`) = 0 THEN 0 
        ELSE ROUND(SUM(`pay_amount_final`) / SUM(`checkin_uv`), 2) 
    END AS priceAvg, 
    ROUND(SUM(`settlement_pice_exclude_add`), 2) AS saleExcludeAdd, 
    ROUND(SUM(`original_pice_exclude_add`), 2) AS originalExcludeAdd, 
    CASE 
        WHEN SUM(`total_original_price`) = 0 THEN 0 
        ELSE ROUND((SUM(`settlement_pice_exclude_add`) / SUM(`total_original_price`) * 100), 2) 
    END AS excludeAddDis, 
    CASE 
        WHEN SUM(`checkin_uv`) = 0 THEN 0 
        ELSE ROUND(SUM(`settlement_pice_exclude_add`) / SUM(`checkin_uv`), 2) 
    END AS excludeAddPriceAvg 
FROM 
    `salesman_confim_revenue_v2` 
WHERE 
    sale_region_code = '8' 
    AND checkin_time BETWEEN '2023-04-01' AND '2023-05-22' 
GROUP BY 
    `company_code`, 
    `sale_id` 
ORDER BY 
    `company_code` DESC