从SQL表中查找前5个MAX（）值，然后在没有它们的情况下对该表执行AVG（）

I want to be able to perform an avg() on a column after removing the 5 highest values in it and see that the stddev is not above a certain number. This has to be done entirely as a PL/SQL query.

我希望能够在删除其中的5个最高值后对列执行avg（）并查看stddev不高于某个数字。这必须完全作为PL / SQL查询完成。

EDIT: To clarify, I have a data set that contains values in a certain range and tracks latency. I want to know whether the AVG() of those values is due to a general rise in latency, or due to a few values with a very high stddev. I.e - (1, 2, 1, 3, 12311) as opposed to (122, 124, 111, 212). I also need to achieve this via an SQL query due to our monitoring software's limitations.

编辑：为了澄清，我有一个包含特定范围内的值并跟踪延迟的数据集。我想知道这些值的AVG（）是否是由于延迟的普遍增加，或者是由于stddev非常高的一些值。 I.e - （1,2,1,3,12311）而不是（122,124,111,212）。由于我们的监控软件的限制，我还需要通过SQL查询来实现这一点。

4 个解决方案

#1

You can use row_number to find the top 5 values, and filter them out in a where clause:

您可以使用row_number查找前5个值，并在where子句中过滤掉它们：

select  avg(col1)
from    (
        select  row_number() over (order by col1 desc) as rn
        ,       *
        from    YourTable
        ) as SubQueryAlias
where   rn > 5

#2

select column_name1 from 
(
  select column_name1 from table_name order by nvl(column_name,0) desc
)a 
where rownum<6

(the nvl is done to omit the null value if there is/are any in the column column_name)

（如果column_name列中有/，则完成nvl以省略空值）

#3

Well, the most efficient way to do it would be to calculate (sum(all values) - sum(top 5 values)) / (row_count - 5)

那么，最有效的方法是计算（总和（所有值） - 总和（前5个值））/（row_count - 5）

SELECT SUM(val) AS top5sum FROM table ORDER BY val DESC LIMIT 5

SELECT SUM(val) AS allsum FROM table

SELECT (COUNT(*) - 5) AS bottomCount FROM table

The average is then (allsum - top5sum) / bottomCount

那么平均值是（allsum - top5sum）/ bottomCount

#4

-1

First, get the MAX 5 values:

首先，获取MAX 5值：

SELECT TOP 5 RowId FROM Table ORDER BY Column

Now use this in your main statement:

现在在主要声明中使用它：

SELECT AVG(Column) FROM Table WHERE RowId NOT IN (SELECT TOP 5 RowId FROM Table ORDER BY Column)

#1