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
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" alt="" />
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

aaarticlea/png;base64,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" alt="" />

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