sql – 填充时间轴空白的窗口函数

2023年6月5日 233次阅读

数据

session                             time_interval       activity
c889ddb532e76c961c2944dd90b10142    2017-05-25 20:16:40 walking
c889ddb532e76c961c2944dd90b10142    2017-05-25 20:16:41 (null)
c889ddb532e76c961c2944dd90b10142    2017-05-25 20:16:42 (null)
c889ddb532e76c961c2944dd90b10142    2017-05-25 20:16:43 (null)
c889ddb532e76c961c2944dd90b10142    2017-05-25 20:16:44 walking
c889ddb532e76c961c2944dd90b10142    2017-05-25 20:16:45 (null)
c889ddb532e76c961c2944dd90b10142    2017-05-25 20:16:46 running
c889ddb532e76c961c2944dd90b10142    2017-05-25 20:16:47 (null)
c889ddb532e76c961c2944dd90b10142    2017-05-25 20:16:48 (null)
c889ddb532e76c961c2944dd90b10142    2017-05-25 20:16:49 (null)
dddjg894hlog8sdlf2090288fmma201c    2017-05-25 20:16:50 walking
dddjg894hlog8sdlf2090288fmma201c    2017-05-25 20:16:51 (null)
dddjg894hlog8sdlf2090288fmma201c    2017-05-25 20:16:52 (null)
dddjg894hlog8sdlf2090288fmma201c    2017-05-25 20:16:53 (null)
dddjg894hlog8sdlf2090288fmma201c    2017-05-25 20:16:54 running
dddjg894hlog8sdlf2090288fmma201c    2017-05-25 20:16:55 (null)
dddjg894hlog8sdlf2090288fmma201c    2017-05-25 20:16:56 (null)
dddjg894hlog8sdlf2090288fmma201c    2017-05-25 20:16:57 (null)
dddjg894hlog8sdlf2090288fmma201c    2017-05-25 20:16:58 resting
dddjg894hlog8sdlf2090288fmma201c    2017-05-25 20:16:59 (null)
dddjg894hlog8sdlf2090288fmma201c    2017-05-25 20:17:00 (null)
dddjg894hlog8sdlf2090288fmma201c    2017-05-25 20:17:01 (null)
dddjg894hlog8sdlf2090288fmma201c    2017-05-25 20:17:02 walking

SQL

SELECT session, 
       time_interval, 
       activity, 
       FIRST_VALUE(activity) 
         OVER ( 
           PARTITION BY session 
           ORDER BY time_interval 
               RANGE BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING) AS activity_b
FROM   my_table;

但这只取得会话的第一个值.如何获得每秒的前一个值？

期望的结果

session                             time_interval       activity
c889ddb532e76c961c2944dd90b10142    2017-05-25 20:16:40 walking
c889ddb532e76c961c2944dd90b10142    2017-05-25 20:16:41 walking
c889ddb532e76c961c2944dd90b10142    2017-05-25 20:16:42 walking
c889ddb532e76c961c2944dd90b10142    2017-05-25 20:16:43 walking
c889ddb532e76c961c2944dd90b10142    2017-05-25 20:16:44 walking
c889ddb532e76c961c2944dd90b10142    2017-05-25 20:16:45 walking
c889ddb532e76c961c2944dd90b10142    2017-05-25 20:16:46 running
c889ddb532e76c961c2944dd90b10142    2017-05-25 20:16:47 running
c889ddb532e76c961c2944dd90b10142    2017-05-25 20:16:48 running
c889ddb532e76c961c2944dd90b10142    2017-05-25 20:16:49 running
dddjg894hlog8sdlf2090288fmma201c    2017-05-25 20:16:50 walking
dddjg894hlog8sdlf2090288fmma201c    2017-05-25 20:16:51 walking
dddjg894hlog8sdlf2090288fmma201c    2017-05-25 20:16:52 walking
dddjg894hlog8sdlf2090288fmma201c    2017-05-25 20:16:53 walking
dddjg894hlog8sdlf2090288fmma201c    2017-05-25 20:16:54 running
dddjg894hlog8sdlf2090288fmma201c    2017-05-25 20:16:55 running
dddjg894hlog8sdlf2090288fmma201c    2017-05-25 20:16:56 running
dddjg894hlog8sdlf2090288fmma201c    2017-05-25 20:16:57 running
dddjg894hlog8sdlf2090288fmma201c    2017-05-25 20:16:58 resting
dddjg894hlog8sdlf2090288fmma201c    2017-05-25 20:16:59 resting
dddjg894hlog8sdlf2090288fmma201c    2017-05-25 20:17:00 resting
dddjg894hlog8sdlf2090288fmma201c    2017-05-25 20:17:01 resting
dddjg894hlog8sdlf2090288fmma201c    2017-05-25 20:17:02 walking

SQL Fiddle是容量,所以这里有一些DDL

CREATE TABLE public.my_table (
  session varchar(32),
  time_interval timestamp,
  activity varchar(10));

INSERT INTO public.my_table VALUES ('c889ddb532e76c961c2944dd90b10142','2017-05-25 20:16:40','walking');
INSERT INTO public.my_table VALUES ('c889ddb532e76c961c2944dd90b10142','2017-05-25 20:16:41','');
INSERT INTO public.my_table VALUES ('c889ddb532e76c961c2944dd90b10142','2017-05-25 20:16:42','');
INSERT INTO public.my_table VALUES ('c889ddb532e76c961c2944dd90b10142','2017-05-25 20:16:43','');
INSERT INTO public.my_table VALUES ('c889ddb532e76c961c2944dd90b10142','2017-05-25 20:16:44','walking');
INSERT INTO public.my_table VALUES ('c889ddb532e76c961c2944dd90b10142','2017-05-25 20:16:45','');
INSERT INTO public.my_table VALUES ('c889ddb532e76c961c2944dd90b10142','2017-05-25 20:16:46','running');
INSERT INTO public.my_table VALUES ('c889ddb532e76c961c2944dd90b10142','2017-05-25 20:16:47','');
INSERT INTO public.my_table VALUES ('c889ddb532e76c961c2944dd90b10142','2017-05-25 20:16:48','');
INSERT INTO public.my_table VALUES ('c889ddb532e76c961c2944dd90b10142','2017-05-25 20:16:49','');
INSERT INTO public.my_table VALUES ('dddjg894hlog8sdlf2090288fmma201c','2017-05-25 20:16:50','walking');
INSERT INTO public.my_table VALUES ('dddjg894hlog8sdlf2090288fmma201c','2017-05-25 20:16:51','');
INSERT INTO public.my_table VALUES ('dddjg894hlog8sdlf2090288fmma201c','2017-05-25 20:16:52','');
INSERT INTO public.my_table VALUES ('dddjg894hlog8sdlf2090288fmma201c','2017-05-25 20:16:53','');
INSERT INTO public.my_table VALUES ('dddjg894hlog8sdlf2090288fmma201c','2017-05-25 20:16:54','running');
INSERT INTO public.my_table VALUES ('dddjg894hlog8sdlf2090288fmma201c','2017-05-25 20:16:55','');
INSERT INTO public.my_table VALUES ('dddjg894hlog8sdlf2090288fmma201c','2017-05-25 20:16:56','');
INSERT INTO public.my_table VALUES ('dddjg894hlog8sdlf2090288fmma201c','2017-05-25 20:16:57','');
INSERT INTO public.my_table VALUES ('dddjg894hlog8sdlf2090288fmma201c','2017-05-25 20:16:58','resting');
INSERT INTO public.my_table VALUES ('dddjg894hlog8sdlf2090288fmma201c','2017-05-25 20:16:59','');
INSERT INTO public.my_table VALUES ('dddjg894hlog8sdlf2090288fmma201c','2017-05-25 20:17:00','');
INSERT INTO public.my_table VALUES ('dddjg894hlog8sdlf2090288fmma201c','2017-05-25 20:17:01','');
INSERT INTO public.my_table VALUES ('dddjg894hlog8sdlf2090288fmma201c','2017-05-25 20:17:02','resting');

最佳答案 这实际上是您想要ignore nulls选项的地方.但那是不可用的.因此,一种方法使用最大扫描和连接：

select t.session, t.time_interval, tt.activity
from (select t.*,
              max(case when t.activity is not null then t.time_interval end) over (partition by t.session order by t.time_interval) as value_ti
      from t
     ) t left join
     t tt
     on t.value_ti = tt.time_interval and t.session = tt.session;

当值不为NULL时,这将计算每行的最近时间间隔.然后它加入以获得当时的活动.

如果你知道一行中永远不会超过3个NULL,你也可以使用lag()：

select t.session, t.time_interval,
       coalesce(t.activity,
                lag(t.activity, 1) over (partition by t.session order by t.time_interval),
                lag(t.activity, 2) over (partition by t.session order by t.time_interval),
                lag(t.activity, 3) over (partition by t.session order by t.time_interval)
               ) as acctivity
from t;
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