postgresql - 如何在 Postgres 中使用具有多个分位数的 percentile_conts

Question

我目前有一个查询是这样工作的:

select AVG(t2 - t1) as delay,
       percentile_cont(0.25) within group (order by (t2 - t1)) as q25,
       percentile_cont(0.5) within group (order by (t2 - t1)) as median,
       percentile_cont(0.75) within group (order by (t2 - t1)) as q75,
       p.bool1,
       p.cat1
from people p
group by p.bool1, p.cat1
order by p.cat1,p.bool1

但是，我在 postgres 函数聚合页面上看到: https://www.postgresql.org/docs/9.4/functions-aggregate.html

我应该能够指定多个分位数:

percentile_cont(fractions) WITHIN GROUP (ORDER BY sort_expression)  double precision[]  double precision or interval    array of sort expression's type     multiple continuous percentile: returns an array of results matching the shape of the fractions parameter, with each non-null element replaced by the value corresponding to that percentile

我想使用它，这样我就不会为每个分位数重新计算 t2 - t1。获得多个分位数的正确语法是什么？我需要子查询吗？

Answer 1

I'd like to use this so I don't recalculate the t2 - t1 for every quantile

在这种情况下，横向连接可能会有所帮助:

select AVG(t2 - t1) as delay,
       percentile_cont(0.25) within group (order by s.col) as q25,
       percentile_cont(0.5) within group (order by s.col) as median,
       percentile_cont(0.75) within group (order by s.col) as q75,
       p.bool1,
       p.cat1
from people p
,LATERAL(SELECT t2 - t1 AS col) s
group by p.bool1, p.cat1
order by p.cat1,p.bool1;

相关:PostgreSQL: using a calculated column in the same query

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数组定义为:ARRAY[0.25, 0.5, 0.75] 或 '{0.25, 0.5, 0.75}'::double precision[]

select AVG(t2 - t1) as delay,
   -- 1
   percentile_cont(ARRAY[0.25, 0.5, 0.75]) within group (order by (t2 - t1)) as q25,
   -- 2
   percentile_cont('{0.25, 0.5, 0.75}'::double precision[]) 
   within group (order by (t2 - t1)) as q
       p.bool1,
       p.cat1
from people p
group by p.bool1, p.cat1
order by p.cat1,p.bool1;

db<>fiddle demo

---

Is there an easy way to inline specify the names of each of the resulting percentile fields as they had been with q25, q50, q75, etc

WITH cte AS (
    select AVG(t2 - t1) as delay,
       percentile_cont(ARRAY[0.25, 0.5, 0.75]) within group (order by (t2 - t1)) as q,
           p.bool1,
           p.cat1
    from people p
    group by p.bool1, p.cat1
)
select cte.*, q[1] AS q25, q[2] AS q50, q[3] AS q75
from cte
order by cat1,bool1;

db<>fiddle demo2