我有一张简单的桌子,它是:

    DROP TABLE IF EXISTS running_averages;

    CREATE TABLE running_averages
    (
            avg_id          SERIAL NOT NULL PRIMARY KEY,
            num1             integer,
            num2             integer   DEFAULT 0

    );

    INSERT INTO running_averages(num1, num2)
    SELECT 100, 100 UNION ALL
    SELECT 200, 175 UNION ALL
    SELECT -400, NULL UNION ALL
    SELECT 300, 200 UNION ALL
    SELECT -100, NULL;

在上表中,如果列“num1”是负值,则应使用前一行的累积平均值更新“num2”列。我当前的查询是:
    SELECT *,
            num1 * num2 AS current_total,
            SUM(num1 * num2) OVER(order by avg_id) AS cumulative_sum,
            SUM(num1)  OVER(order by avg_id) AS culmulative_num1,

            CASE WHEN num1 > 0 THEN
            SUM(num1 * num2) OVER(order by avg_id)
            /
            SUM(num1)  OVER(order by avg_id)
            ELSE
            0
            END AS cumulative_average
    FROM running_averages;

结果是:
avg_id  num1  num2    current_total cumulative_sum   cumulative_num1 cumulative_average
1       100   100     10,000        10,000           100             100
2       200   175     35,000        45,000           300             150
3       -400          NULL          45,00            -100            0
4       300   200     60,000        105,000          200             525
5       -100          NULL          105,000          100               0

如果当前行的num1列是负数,我就无法计算出将前一行的累积平均值带过来的方法。预期产出应为:
avg_id  num1  num2    current_total cumulative_sum   cumulative_num1 cumulative_average
1       100   100     10,000        10,000           100             100
2       200   175     35,000        45,000           300             150
3       -400  150     -60,000       -15,00           -100            150
4       300   200     60,000        45,000           200             225
5       -100  225     -22,500       22,500           100             225

在这种情况下,如何获取最后一行的列的值?
编辑:
我编辑了上面的SQL脚本。我很喜欢这个答案。但遗憾的是,根据脚本的更改,它会产生错误的结果:
avg_id  num1  num2    new_num2
1       100   100     100
2       200   175     175
3       -400  150     150 (Correct)
4       300   200     200
5       -100  225     50  (Incorrect)

编辑2
我还测试了Gordon Linoff的答案,它也产生了错误的结果:
avg_id  num1  num2              current_total cumulative_sum   cumulative_num1 cumulative_average
1       100   100               10,000        10,000           100             100
2       200   175               35,000        45,000           300             150
3       -400  150 (Correct)     -60,000       -15,00           -100            150
4       300   200               60,000        45,000           200             225
5       -100  175 (Incorrect)   -17,500       27,500           100             275

编辑3
我接受了Multisync的更新答案,因为它产生了正确的结果。我还想知道如何改进这样的查询,我们有很多聚合函数和窗口函数。关于这个话题的任何参考都会有帮助。

最佳答案

我只能想到一个递归查询:

with recursive tmp (avg_id, num1, num2, sum_m, sum_num1, last_id) as (
  select avg_id, num1, num2, num1 * num2, num1, avg_id
  from running_averages where avg_id = 1
  union all
  select r.avg_id, r.num1,
         case when r.num1 < 0 then t.sum_m / t.sum_num1 else r.num2 end,
         t.sum_m + case when r.num1 < 0 then t.sum_m / t.sum_num1 else r.num2 end * r.num1,
         t.sum_num1 + r.num1,
         r.avg_id
  from running_averages r join tmp t on r.avg_id = t.last_id + 1
)
select avg_id, num1, num2,
       num1 * num2 AS current_total,
       SUM(num1 * num2) OVER(order by avg_id) AS cumulative_sum,
       SUM(num1) OVER(order by avg_id) AS culmulative_num1,
       SUM(num1 * num2) OVER(order by avg_id)
       / SUM(num1) OVER(order by avg_id) AS cumulative_average
from tmp;

avg_id必须包含consequentive数字(您可以使用row_number()代替,我没有使用它来简化)
num2在计算过程中发生了变化,这就是为什么除了递归查询之外,我不能考虑其他任何查询(上一步的输出是下一步的输入)

09-30 13:44