PostgreSQL 在一次查询中获取事件发生的每日、每周和每月平均值

Question

目前我有一个相当大的查询，由

1. 通过获取按事件名称和日期分组的事件的

   count()

   ，将每日、每周、每月的计数汇总到中间表中。
2. 通过

   avg()

   按事件分组选择每个中间表的平均计数，对结果进行联合，因为我想为每日、每周、每月设置一个单独的列，将填充值 0 放入空专栏。
3. 然后我对所有列求和，0 基本上充当空操作，它只为每个事件提供一个值。

---

虽然查询量很大，但我觉得我在做很多重复性的工作。有什么办法可以更好地执行此查询或使其更小吗？我以前没有真正做过这样的查询，所以我不太确定。

WITH monthly_counts as (
  SELECT
    event,
    count(*) as count
  FROM tracking_stuff
  WHERE
    event = 'thing'
    OR event = 'thing2'
    OR event = 'thing3'
  GROUP BY event, date_trunc('month', created_at)
),
weekly_counts as (
  SELECT
    event,
    count(*) as count
  FROM tracking_stuff
  WHERE
    event = 'thing'
    OR event = 'thing2'
    OR event = 'thing3'
  GROUP BY event, date_trunc('week', created_at)
),
daily_counts as (
  SELECT
    event,
    count(*) as count
  FROM tracking_stuff
  WHERE
    event = 'thing'
    OR event = 'thing2'
    OR event = 'thing3'
  GROUP BY event, date_trunc('day', created_at)
),
query as (
  SELECT
    event,
    0 as daily_avg,
    0 as weekly_avg,
    avg(count) as monthly_avg
  FROM monthly_counts
  GROUP BY event
  UNION
  SELECT
    event,
    0 as daily_avg,
    avg(count) as weekly_avg,
    0 as monthly_avg
  FROM weekly_counts
  GROUP BY event
  UNION
  SELECT
    event,
    avg(count) as daily_avg,
    0 as weekly_avg,
    0 as monthly_avg
  FROM daily_counts
  GROUP BY event
)
SELECT
  event,
  sum(daily_avg) as daily_avg,
  sum(weekly_avg) as weekly_avg,
  sum(monthly_avg) as monthly_avg
FROM query
GROUP BY event;

Answer 1

我会这样写查询：

select event, daily_avg, weekly_avg, monthly_avg
from (
    select event, avg(count) monthly_avg
    from (
        select event, count(*)
        from tracking_stuff
        where event in ('thing1', 'thing2', 'thing3')
        group by event, date_trunc('month', created_at)
    ) s
    group by 1
) monthly
join (
    select event, avg(count) weekly_avg
    from (
        select event, count(*)
        from tracking_stuff
        where event in ('thing1', 'thing2', 'thing3')
        group by event, date_trunc('week', created_at)
    ) s
    group by 1
) weekly using(event)
join (
    select event, avg(count) daily_avg
    from (
        select event, count(*)
        from tracking_stuff
        where event in ('thing1', 'thing2', 'thing3')
        group by event, date_trunc('day', created_at)
    ) s
    group by 1
) daily using(event)
order by 1;

---

如果

where

条件消除了很大一部分数据（比如超过一半），使用

cte

可以稍微加快查询执行速度：

with the_data as (
    select event, created_at
    from tracking_stuff
    where event in ('thing1', 'thing2', 'thing3')
    )

select event, daily_avg, weekly_avg, monthly_avg
from (
    select event, avg(count) monthly_avg
    from (
        select event, count(*)
        from the_data
        group by event, date_trunc('month', created_at)
    ) s
    group by 1
) monthly
--  etc ... 

---

出于好奇，我对数据做了测试：

create table tracking_stuff (event text, created_at timestamp);
insert into tracking_stuff
    select 'thing' || random_int(9), '2016-01-01'::date+ random_int(365)
    from generate_series(1, 1000000);

在每个查询中，我用

thing

替换了

thing1

，因此查询消除了大约 2/3 的行。

10 次测试的平均执行时间：

    Original query          1106 ms
    My query without cte    1077 ms
    My query with cte        902 ms
    Clodoaldo's query       5187 ms

Answer 2

9.5+使用

grouping sets

FROM和WHERE子句选择的数据分别按照每个指定的分组集进行分组，就像简单的GROUP BY子句一样为每个组计算聚合，然后返回结果

select event,
    avg(total) filter (where day is not null) as avg_day,
    avg(total) filter (where week is not null) as avg_week,
    avg(total) filter (where month is not null) as avg_month    
from (
    select
        event,
        date_trunc('day', created_at) as day,
        date_trunc('week', created_at) as week,
        date_trunc('month', created_at) as month,
        count(*) as total
    from tracking_stuff
    where event in ('thing','thing2','thing3')
    group by grouping sets ((event, 2), (event, 3), (event, 4))
) s
group by event

要了解有关

grouping sets

的更多信息，请考虑以下教程：one、two