将每N个值分组

本文介绍了将每N个值分组的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！

问题描述

我在PostgreSQL中有一个这样的表。我想基于ID（这是主键）对每16条记录执行诸如均值和最大值的聚合函数。例如，我必须计算前16个记录和后16个记录的平均值，依此类推。

I have a table like this in PostgreSQL. I want to perform aggregation functions like mean and max for every 16 records based on ID (which is primary key). For example I have to calculate mean value for first 16 records and second 16 records and so on.

+-----+-------------
| ID  |  rainfall  |
+-----+----------- |
|  1  |  110.2     |
|  2  |  56.6      |
|  3  |  65.6      |
|  4  |  75.9      |
+-----+------------

推荐答案

想到的第一种方法是使用 row_number（）注释表，然后按16行的块进行分组。

The 1st approach that comes to mind is to use row_number() to annotate the table, then group by blocks of 16 rows.

SELECT min(id) as first_id, max(id) AS last_id, avg(rainfall) AS avg_this_16
FROM (
  SELECT id, rainfall, row_number() OVER (order by id) AS n
  FROM the_table
) x(id,rainfall,n)
GROUP BY n/16
ORDER BY n/16;

请注意，这不一定包括最后一组的16个样本。

Note that this won't necessarily include 16 samples for the last group.

或者，您可以使用 avg（）作为窗口函数来计算运行平均值：

Alternately you can calculate a running average by using avg() as a window function:

SELECT id, avg(rainfall) OVER (ORDER BY id ROWS 15 PRECEDING)
FROM the_table;

...可能用行号注释并选择所需的行号：

... possibly annotating that with the row number and selecting the ones you want:

SELECT id AS greatest_id_in_group, avg_last_16_inclusive FROM (
  SELECT
    id,
    avg(rainfall) OVER (ORDER BY id ROWS 15 PRECEDING) AS avg_last_16_inclusive,
    row_number() OVER (ORDER BY id) AS n
  FROM the_table
) x WHERE n % 16 = 0;

这将忽略最后n个

This will disregard the last n<16 samples, not returning a row for them.

请注意，我假设ID不能保证是连续的。如果它们之间没有间隙，则可以按id / 16 分组并避免使用窗口功能。

Note that I'm assuming the IDs aren't guaranteed to be contiguous. If they are gap-less, you can just group by id/16 and avoid the window function.

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