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mysql滑动聚合/年初至今聚合原理与用法实例分析

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本文实例讲述了mysql滑动聚合/年初至今聚合原理与用法。分享给大家供大家参考,具体如下:

滑动聚合是按顺序对滑动窗口范围内的数据进行聚合的操作。下累积聚合不同,滑动聚合并不是统计开始计算的位置到当前位置的数据。

这里以统计最近三个月中员工第月订单情况为例来介绍滑动聚合。

滑动聚合和累积聚合解决方案的主要区别在于连接的条件不同。滑动聚合条件不再是b.ordermonth <= a.ordermonth,而应该是b.ordermonth大于前三个月的月份,并且小于当前月份。因此滑动聚合的解决方案的SQL语句如下

SELECT
 a.empid,
 DATE_FORMAT(a.ordermonth, '%Y-%m') AS ordermonth,
 a.qty AS thismonth,
 SUM(b.qty) AS total,
 CAST(AVG(b.qty) AS DECIMAL(5,2)) AS avg
FROM emporders a
INNER JOIN emporders b
 ON a.empid=b.empid
 AND b.ordermonth > DATE_ADD(a.ordermonth, INTERVAL -3 MONTH)
 AND b.ordermonth <= a.ordermonth
WHERE DATE_FORMAT(a.ordermonth,'%Y')='2015' AND DATE_FORMAT(b.ordermonth,'%Y')='2015'
GROUP BY a.empid,DATE_FORMAT(a.ordermonth, '%Y-%m'),a.qty
ORDER BY a.empid,a.ordermonth

运行结果如下

该解决方案返回的是三个月为一个周期的滑动聚合,但是每个用户包含前两个月并且未满3个月的聚合。如果只希望返回满3个月的聚合,不返回未满3个月的聚合,可以使用HAVING过滤器进行过滤,过滤的条件为MIN(b.ordermonth)=DATE_ADD(a.ordermonth, INTERVAL -2 MONTH),例如

SELECT
 a.empid,
 a.ordermonth AS ordermonth,
 a.qty AS thismonth,
 SUM(b.qty) AS total,
 CAST(AVG(b.qty) AS DECIMAL(5,2)) AS avg
FROM emporders a
INNER JOIN emporders b
 ON a.empid=b.empid
 AND b.ordermonth > DATE_ADD(a.ordermonth, INTERVAL -3 MONTH)
 AND b.ordermonth <= a.ordermonth
WHERE DATE_FORMAT(a.ordermonth,'%Y')='2015' AND DATE_FORMAT(b.ordermonth,'%Y')='2015' AND a.empid=1
GROUP BY a.empid,DATE_FORMAT(a.ordermonth, '%Y-%m'),a.qty
HAVING MIN(b.ordermonth)=DATE_ADD(a.ordermonth, INTERVAL-2 MONTH)
ORDER BY a.empid,a.ordermonth

运行结果如下

年初至今聚合和滑动聚合类似,不同的地方仅在于统计的仅为当前一年的聚合。唯一的区别体现在下限的开始位置上。在年初至今的问题中,下限为该年的第一天,而滑动聚合的下限为N个月的第一天。因此,年初至今的问题的解决方案如下图所示,得到的结果

SELECT
 a.empid,
 DATE_FORMAT(a.ordermonth, '%Y-%m') AS ordermonth,
 a.qty AS thismonth,
 SUM(b.qty) AS total,
 CAST(AVG(b.qty) AS DECIMAL(5,2)) AS avg
FROM emporders a
INNER JOIN emporders b
  ON a.empid=b.empid
  AND b.ordermonth >= DATE_FORMAT(a.ordermonth, '%Y-01-01')
  AND b.ordermonth <= a.ordermonth
  AND DATE_FORMAT(b.ordermonth,'%Y')='2015'
GROUP BY a.empid,a.ordermonth,a.qty
ORDER BY a.empid,a.ordermonth

运行结果如下

希望本文所述对大家MySQL数据库计有所帮助。

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