在 PostgreSQL 中查找具有多个用户的时间戳中的间隙和重叠的时间范围

Finding Gaps in Timestamps with Multiple Users and Overlapping Timeranges in PostgreSQL

这是本网站上一个 post 的延续:

我正在处理一个数据集,其中包含过去 5 年多个办公室的入住和退房时间。我被要求从事的项目之一是计算每个房间在不同时间范围内(每天、每周、每月等)忙碌和空闲的时间,假设设定的营业时间(早上 7:30 到下午 5 点)。 与我的上一个 post、 不同,存在时间范围重叠的实例。一天的数据集示例如下所示:

room_id     check_in                check_out
"Room D"    "2014-07-18 12:23:00"   "2014-07-18 12:54:00"
"Room D"    "2014-07-19 09:16:00"   "2014-07-19 10:30:00"
"Room D"    "2014-07-19 09:10:00"   "2014-07-19 10:30:00"
"Room D"    "2014-07-18 08:45:00"   "2014-07-18 22:40:00"
"Room 5"    "2014-07-19 10:20:00"   "2014-07-19 12:20:00"
"Room 5"    "2014-07-18 07:59:00"   "2014-07-18 09:00:00"
"Room 5"    "2014-07-18 09:04:00"   "2014-07-18 14:00:00"
"Room 5"    "2014-07-18 07:59:00"   "2014-07-18 10:00:00"

从我之前的 post 中,我得到了这段代码,它 完美地适用于没有重叠的所有实例 ,正如作者:

select date_trunc('day', start_dt), room_id,
       sum( least(extract(epoch from end_dt), v.epoch2) - 
            greatest(extract(epoch from start_dt), epoch1)
          ) as busy_seconds,
       (epoch2 - epoch1 -
        sum( least(extract(epoch from end_dt), v.epoch2) - 
             greatest(extract(epoch from start_dt), epoch1)
           )
       ) as free_seconds
from rooms r cross join
     (values (extract(epoch from date_trunc('day', start_dt) + interval '7 hours 30 minutes'),
              extract(epoch from date_trunc('day', start_dt) + interval '17 hour')
             )
     ) v(epoch1, epoch2)                  
group by date_trunc('day', start_dt), room_id

但是,在深入研究我们的数据后,时间范围重叠的实例比我预期的要多。这是我想从上面的示例数据中检索的目标输出:

target_day      room_id         busy_time         Free Time
2014-07-18      Room D          8.25              1.25
2014-07-19      Room 4          1.33              8.17
2014-07-18      Room 5          8                 1.5
2014-07-19      Room 5          2                 7.5

我现在正在学习 PostgreSQL,所以这个问题有点让我头疼。任何帮助或指导将不胜感激!

为了解决差距,我建议首先将它们结合起来——比如使用 CTE。逻辑如下:

  • 查看给定行之前的最大结束日期(对于同一房间和同一时间。
  • 在上一个最大结束日期和开始日期之间存在差距的地方进行累计。
  • 使用此聚合 room_id 来计算新的开始和结束时间。

这应该可行,但您可以在将逻辑应用到其他查询之前验证 CTE(唯一的变化是引用 CTE 而不是基础 table)。

作为查询:

with r as (
      select room_id, min(start_dt) as start_dt, max(end_dt) as end_ddt
      from (select r.*,
                   count(*) over (filter where prev_end_dt < start_dt) over (partition by room_id date_trunc('day', start_dt) order by start_dt) as grp
            from (select r.*,
                         max(end_dt) over (partition by room_id, date_trunc('day', start_dt) rows between unbounded preceding and 1 preceding) as prev_end_dt
                  from rooms r
                 ) r
           ) r
      group by room_id, grp
     )
select date_trunc('day', start_dt), room_id,
       sum( least(extract(epoch from end_dt), v.epoch2) - 
            greatest(extract(epoch from start_dt), epoch1)
          ) as busy_seconds,
       (epoch2 - epoch1 -
        sum( least(extract(epoch from end_dt), v.epoch2) - 
             greatest(extract(epoch from start_dt), epoch1)
           )
       ) as free_seconds
from r cross join
     (values (extract(epoch from date_trunc('day', start_dt) + interval '7 hours 30 minutes'),
              extract(epoch from date_trunc('day', start_dt) + interval '17 hour')
             )
     ) v(epoch1, epoch2)                  
group by date_trunc('day', start_dt), room_id