sql - PostgreSQL 中的条件累积平均

Question

我有一个简单的表，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“num1”列为负值，则“num2”列应更新为上一行的累积平均值。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:

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，我想不出获取前一行的累积平均值的方法。而不是上面的，预期的输出应该是:

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  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。我非常喜欢 Gordon Linoff 的方法的回答。但遗憾的是，根据脚本更改，它会产生不正确的结果:

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 Multisync 的答案，它也会产生错误的结果:

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

我已经接受了 Multisync 的更新答案，因为它会产生正确的结果。我还想知道如何在我们有很多聚合函数和窗口函数的情况下改进这样的查询。有关此主题的任何引用资料都会有所帮助。

Answer 1

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 必须包含连续的数字(您可以使用 row_number() 代替，我没有使用它来简化)

num2 在计算过程中发生变化，这就是为什么我除了递归查询之外想不出任何其他东西(上一步的输出是下一步的输入)