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sql - 在 Teradata 中一次获取多个百分位数(percentile_cont 等效项)

转载 作者:行者123 更新时间:2023-12-03 01:01:22 25 4
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据我了解,我们可以在 Teradata 中将 percentile_cont 重写为:

SELECT
part_col
,data_col
+ ((MIN(data_col) OVER (PARTITION BY part_col ORDER BY data_col ROWS BETWEEN 1 FOLLOWING AND 1 FOLLOWING) - data_col)
* (((COUNT(*) OVER (PARTITION BY part_col) - 1) * x) MOD 1)) AS percentile_cont
FROM tab
QUALIFY ROW_NUMBER() OVER (PARTITION BY part_col ORDER BY data_col)
= CAST((COUNT(*) OVER (PARTITION BY part_col) - 1) * x AS INT) + 1;

参见this very helpful discussion了解更多信息。

理解用 0.90 替换 x 将返回第 90 个百分位数,是否有一种优雅的方法来扩展它并一次返回多个百分位数?

例如,假设我想扩展此示例并一次返回第 25 个、第 50 个和第 75 个百分位数?这可能吗?似乎我需要多个 QUALIFY 语句?同样,如果我需要多个 GROUP BY 等价物,这是否类似于在 PARTITION BY 中传递更多列?

<小时/>
-- SQL:2008 Equivalent pseudo-code
SELECT
part_col_a
,part_col_b
,PERCENTILE_CONT(0.25) WITHIN GROUP (ORDER BY order_col) AS p25
,PERCENTILE_CONT(0.50) WITHIN GROUP (ORDER BY order_col) AS p50
,PERCENTILE_CONT(0.75) WITHIN GROUP (ORDER BY order_col) AS p75
FROM tab
GROUP BY
part_col_a
,part_col_b

最佳答案

你应该充分阅读我的博客,最终的查询正是你想要的:-)

SELECT part_col
,MIN(pc25) OVER (PARTITION BY part_col) AS quartile_1
,MIN(pc50) OVER (PARTITION BY part_col) AS quartile_2
,MIN(pc75) OVER (PARTITION BY part_col) AS quartile_3
FROM
(
SELECT
part_col
,COUNT(*) OVER (PARTITION BY part_col) - 1 AS N
,ROW_NUMBER() OVER (PARTITION BY part_col ORDER BY data_col) - 1 AS rowno
,MIN(data_col) OVER (PARTITION BY part_col ORDER BY data_col ROWS BETWEEN 1 FOLLOWING AND 1 FOLLOWING) - data_col AS diff

,CASE
WHEN rowno = CAST(N * 0.25 AS INT)
THEN data_col +(((N * 0.25) MOD 1) * diff)
END AS pc25

,CASE
WHEN rowno = CAST(N * 0.50 AS INT)
THEN data_col +(((N * 0.50) MOD 1) * diff)
END AS pc50

,CASE
WHEN rowno = CAST(N * 0.75 AS INT)
THEN data_col +(((N * 0.75) MOD 1) * diff)
END AS pc75
FROM tab
QUALIFY rowno = CAST(N * 0.25 AS INT)
OR rowno = CAST(N * 0.50 AS INT)
OR rowno = CAST(N * 0.75 AS INT)
) AS dt
QUALIFY ROW_NUMBER() OVER (PARTITION BY part_col ORDER BY part_col) = 1

关于sql - 在 Teradata 中一次获取多个百分位数(percentile_cont 等效项),我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/35733463/

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