趁大钱 发表于 2023-4-2 12:37:44

读SQL进阶教程笔记05_关联子查询


1. 关联子查询

1.1. 关联子查询和自连接在很多时候都是等价的
1.2. 使用SQL进行行间比较时,发挥主要作用的技术是关联子查询,特别是与自连接相结合的“自关联子查询”
1.3. 缺点

[*]1.3.1. 代码的可读性不好

[*]1.3.1.1. 特别是在计算累计值和移动平均值的例题里,与聚合一起使用后,其内部处理过程非常难理解

[*]1.3.2. 性能不好

[*]1.3.2.1. 特别是在SELECT子句里使用标量子查询时,性能可能会变差

2. 增长、减少、维持现状

2.1. 使用基于时间序列的表进行时间序列分析
2.2. 示例

[*]2.2.1. --求与上一年营业额一样的年份(1):使用关联子查询
   SELECT year, sale
     FROM Sales S1
    WHERE sale = (SELECT sale
                   FROM Sales S2
                   WHERE S2.year = S1.year -1)
    ORDER BY year;

[*]2.2.2. S2.year = S1.year -1这个条件起到了将要比较的数据偏移一行的作用
[*]2.2.3. --求与上一年营业额一样的年份(2):使用自连接
   SELECT S1.year, S1.sale
     FROM Sales S1,
         Sales S2
    WHERE S2.sale = S1.sale
     AND S2.year = S1.year -1
    ORDER BY year;3. 用列表展示与上一年的比较结果

3.1. 示例

[*]3.1.1. --求出是增长了还是减少了,抑或是维持现状(1):使用关联子查询
   SELECT S1.year, S1.sale,
         CASE WHEN sale =
               (SELECT sale
                   FROM Sales S2
                 WHERE S2.year = S1.year -1) THEN'→'--持平
               WHEN sale >
               (SELECT sale
                   FROM Sales S2
                 WHERE S2.year = S1.year -1) THEN'↑'--增长
               WHEN sale <
               (SELECT sale
                   FROM Sales S2
                 WHERE S2.year = S1.year -1) THEN'↓'--减少
         ELSE'—'END AS var
     FROM Sales S1
    ORDER BY year;

[*]3.1.2. --求出是增长了还是减少了,抑或是维持现状(2):使用自连接查询(最早的年份不会出现在结果里)
   SELECT S1.year, S1.sale,
         CASE WHEN S1.sale = S2.sale THEN'→'
               WHEN S1.sale > S2.sale THEN'↑'
               WHEN S1.sale < S2.sale THEN'↓'
         ELSE'—'END AS var
     FROM Sales S1, Sales S2
    WHERE S2.year = S1.year -1
    ORDER BY year;4. 时间轴有间断时

4.1. 和过去最临近的时间进行比较
4.2. 示例

[*]4.2.1. --查询与过去最临近的年份营业额相同的年份
   SELECT year, sale
     FROM Sales2 S1
    WHERE sale =
     (SELECT sale
         FROM Sales2 S2
       WHERE S2.year =
         (SELECT MAX(year)  --条件2:在满足条件1的年份中,年份最早的一个
             FROM Sales2 S3
           WHERE S1.year > S3.year))  --条件1:与该年份相比是过去的年份
    ORDER BY year;

[*]4.2.2.  自连接版本
SELECT S1.year AS year,

         S1.year AS year
     FROM Sales2 S1, Sales2 S2
    WHERE S1.sale = S2.sale
     AND S2.year = (SELECT MAX(year)
                       FROM Sales2 S3
                     WHERE S1.year > S3.year)
    ORDER BY year;

[*]4.2.3. --求每一年与过去最临近的年份之间的营业额之差(1):结果里不包含最早的年份
   SELECT S2.year AS pre_year,
         S1.year AS now_year,
         S2.sale AS pre_sale,
         S1.sale AS now_sale,
         S1.sale - S2.sale  AS diff
     FROM Sales2 S1, Sales2 S2
    WHERE S2.year = (SELECT MAX(year)
                       FROM Sales2 S3
                     WHERE S1.year > S3.year)
    ORDER BY now_year;

[*]4.2.4. --求每一年与过去最临近的年份之间的营业额之差(1):结果里不包含最早的年份
   SELECT S2.year AS pre_year,
         S1.year AS now_year,
         S2.sale AS pre_sale,
         S1.sale AS now_sale,
         S1.sale - S2.sale  AS diff
     FROM Sales2 S1, Sales2 S2
    WHERE S2.year = (SELECT MAX(year)
                       FROM Sales2 S3
                     WHERE S1.year > S3.year)
    ORDER BY now_year;

[*]4.2.5. 使用极值函数时会发生排序
5. 移动累计值和移动平均值

5.1. 示例

[*]5.1.1. --求累计值:使用窗口函数
   SELECT prc_date, prc_amt,
         SUM(prc_amt) OVER (ORDER BY prc_date) AS onhand_amt
     FROM Accounts;

[*]5.1.2. 引入窗口函数的目的原本就是解决这类问题,因此这里的代码非常简洁

[*]5.1.2.1. 如果选用的数据库支持窗口函数,也可以考虑使用窗口函数

[*]5.1.3. 从性能方面来看,表的扫描和数据排序也都只进行了一次

[*]5.1.3.1. 依赖于具体的数据库的

[*]5.1.4. --求累计值:使用冯·诺依曼型递归集合
   SELECT prc_date, A1.prc_amt,
         (SELECT SUM(prc_amt)
           FROM Accounts A2
           WHERE A1.prc_date >= A2.prc_date ) AS onhand_amt
     FROM Accounts A1
    ORDER BY prc_date;

[*]5.1.5. --求移动累计值(1):使用窗口函数
   SELECT prc_date, prc_amt,
         SUM(prc_amt) OVER (ORDER BY prc_date
                           ROWS 2 PRECEDING) AS onhand_amt
     FROM Accounts;

[*]5.1.6. --求移动累计值(2):不满3行的时间区间也输出
   SELECT prc_date, A1.prc_amt,
         (SELECT SUM(prc_amt)
           FROM Accounts A2
           WHERE A1.prc_date >= A2.prc_date
             AND (SELECT COUNT(*)
                   FROM Accounts A3
                   WHERE A3.prc_date
                     BETWEEN A2.prc_date AND A1.prc_date  ) <= 3 )
                 AS mvg_sum
     FROM Accounts A1
    ORDER BY prc_date;

[*]5.1.7. A3.prc_date在以A2.prc_date为起点,以A1.prc_date为终点的区间内移动
[*]5.1.8. --移动累计值(3):不满3行的区间按无效处理
   SELECT prc_date, A1.prc_amt,
    (SELECT SUM(prc_amt)
       FROM Accounts A2
     WHERE A1.prc_date >= A2.prc_date
       AND (SELECT COUNT(*)
               FROM Accounts A3
             WHERE A3.prc_date
               BETWEEN A2.prc_date AND A1.prc_date  ) <= 3
     HAVING  COUNT(*) =3) AS mvg_sum  --不满3行数据的不显示
     FROM Accounts A1
    ORDER BY prc_date;5.2. 基本思路是使用冯·诺依曼型递归集合
6. 查询重叠的时间区间

6.1. 示例

[*]6.1.1. --求重叠的住宿期间
   SELECT reserver, start_date, end_date
     FROM Reservations R1
    WHERE EXISTS
         (SELECT *
               FROM Reservations R2
              WHERE R1.reserver <> R2.reserver  --与自己以外的客人进行比较
                AND ( R1.start_date BETWEEN R2.start_date AND R2.end_date
                                   --条件(1):自己的入住日期在他人的住宿期间内
                   OR R1.end_date  BETWEEN R2.start_date AND R2.end_date));
                                   --条件(2):自己的离店日期在他人的住宿期间内

[*]6.1.2. --升级版:把完全包含别人的住宿期间的情况也输出
   SELECT reserver, start_date, end_date
    FROM Reservations R1
   WHERE EXISTS
         (SELECT *
             FROM Reservations R2
           WHERE R1.reserver <> R2.reserver
             AND (  (     R1.start_date BETWEEN R2.start_date
                                           AND R2.end_date
                       OR R1.end_date   BETWEEN R2.start_date
                                           AND R2.end_date)
                   OR (    R2.start_date BETWEEN R1.start_date
                                           AND R1.end_date
                       AND R2.end_date   BETWEEN R1.start_date
                                           AND R1.end_date)));
来源:https://www.cnblogs.com/lying7/p/17277869.html
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