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Update Task05：SQL高级处理.md

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Task05：SQL高级处理.md
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@ -27,7 +27,7 @@ SELECT product_name
,sale_price
,RANK() OVER (PARTITION BY product_type
ORDER BY sale_price) AS ranking
FROM Product  
FROM product  
```
得到的结果是:
@ -84,7 +84,7 @@ SELECT product_name
,RANK() OVER (ORDER BY sale_price) AS ranking
,DENSE_RANK() OVER (ORDER BY sale_price) AS dense_ranking
,ROW_NUMBER() OVER (ORDER BY sale_price) AS row_num
FROM Product  
FROM product  
```
![图片](https://github.com/datawhalechina/team-learning-sql/blob/main/img/ch05/ch0503.png)
@ -102,7 +102,7 @@ SELECT product_id
,sale_price
,SUM(sale_price) OVER (ORDER BY product_id) AS current_sum
,AVG(sale_price) OVER (ORDER BY product_id) AS current_avg  
FROM Product;  
FROM product;  
```
![图片](https://github.com/datawhalechina/team-learning-sql/blob/main/img/ch05/ch0504.png)
@ -142,7 +142,7 @@ SELECT product_id
,AVG(sale_price) OVER (ORDER BY product_id
ROWS BETWEEN 1 PRECEDING
AND 1 FOLLOWING) AS moving_avg
FROM Product  
FROM product  
```
**执行结果：**
@ -171,7 +171,7 @@ ROWS BETWEEN 1 PRECEDING AND 1 FOLLOWING：
SELECT product_type
,regist_date
,SUM(sale_price) AS sum_price
FROM Product
FROM product
GROUP BY product_type, regist_date WITH ROLLUP  
```
得到的结果为：
@ -190,18 +190,18 @@ ROLLUP 可以对多列进行汇总求小计和合计。
## **5.1**
请说出针对本章中使用的 Product（商品）表执行如下 SELECT 语句所能得到的结果。
请说出针对本章中使用的 product（商品）表执行如下 SELECT 语句所能得到的结果。
```sql
SELECT product_id
,product_name
,sale_price
,MAX(sale_price) OVER (ORDER BY product_id) AS Current_max_price
FROM Product
FROM product
```
## **5.2**
继续使用Product表，计算出按照登记日期（regist_date）升序进行排列的各日期的销售单价（sale_price）的总额。排序是需要将登记日期为NULL 的“运动 T 恤”记录排在第 1 位（也就是将其看作比其他日期都早）
继续使用product表，计算出按照登记日期（regist_date）升序进行排列的各日期的销售单价（sale_price）的总额。排序是需要将登记日期为NULL 的“运动 T 恤”记录排在第 1 位（也就是将其看作比其他日期都早）
## **5.3**