窗口函数 LAG 可以引用正在计算哪个值的列吗？

Question

我需要根据当前记录的其他一些列和前一条记录的 X 值来计算某些列 X 的值（使用一些分区和顺序）。基本上我需要在表单中实现查询

SELECT <some fields>, 
  <some expression using LAG(X) OVER(PARTITION BY ... ORDER BY ...) AS X
FROM <table>

这是不可能的，因为只有现有的列可以在窗口函数中使用，所以我正在寻找解决这个问题的方法。

这是一个例子。我有一张有活动的桌子。每个事件都有type 和time_stamp。

create table event (id serial, type integer, time_stamp integer);

我不想找到“重复”事件（跳过它们）。重复是指以下内容。让我们按time_stamp 升序排列给定type 的所有事件。那么

1. 第一个事件不是重复的
2. 所有不重复且在其后某个时间范围内的事件（即它们的time_stamp 不大于前一个不重复的time_stamp 加上一些常量TIMEFRAME）都是重复的
3. 下一个time_stamp 比上一个不重复的事件大于TIMEFRAME 的下一个事件不重复
4. 等等

对于这个数据

insert into event (type, time_stamp) 
 values 
  (1, 1), (1, 2), (2, 2), (1,3), (1, 10), (2,10), 
  (1,15), (1, 21), (2,13), 
  (1, 40);

TIMEFRAME=10 结果应该是

time_stamp | type | duplicate
-----------------------------
        1  |    1 | false
        2  |    1 | true     
        3  |    1 | true 
       10  |    1 | true 
       15  |    1 | false 
       21  |    1 | true
       40  |    1 | false
        2  |    2 | false
       10  |    2 | true
       13  |    2 | false

我可以根据上一个非重复事件的当前time_stamp 和time_stamp 计算duplicate 字段的值，如下所示：

WITH evt AS (
  SELECT 
    time_stamp, 
    CASE WHEN 
      time_stamp - LAG(current_non_dupl_time_stamp) OVER w >= TIMEFRAME
    THEN 
      time_stamp
    ELSE
      LAG(current_non_dupl_time_stamp) OVER w
    END AS current_non_dupl_time_stamp
  FROM event
  WINDOW w AS (PARTITION BY type ORDER BY time_stamp ASC)
)
SELECT time_stamp, time_stamp != current_non_dupl_time_stamp AS duplicate

但这不起作用，因为LAG中无法引用计算的字段：

ERROR:  column "current_non_dupl_time_stamp" does not exist.

那么问题来了：我可以重写这个查询来达到我需要的效果吗？

Answer 1

朴素的递归链编织器：

---

        -- temp view to avoid nested CTE
CREATE TEMP VIEW drag AS
        SELECT e.type,e.time_stamp
        , ROW_NUMBER() OVER www as rn                   -- number the records
        , FIRST_VALUE(e.time_stamp) OVER www as fst     -- the "group leader"
        , EXISTS (SELECT * FROM event x
                WHERE x.type = e.type
                AND x.time_stamp < e.time_stamp) AS is_dup
        FROM event e
        WINDOW www AS (PARTITION BY type ORDER BY time_stamp)
        ;

WITH RECURSIVE ttt AS (
        SELECT d0.*
        FROM drag d0 WHERE d0.is_dup = False -- only the "group leaders"
    UNION ALL
        SELECT d1.type, d1.time_stamp, d1.rn
          , CASE WHEN d1.time_stamp - ttt.fst > 20 THEN d1.time_stamp
                 ELSE ttt.fst END AS fst   -- new "group leader"
          , CASE WHEN d1.time_stamp - ttt.fst > 20 THEN False
                 ELSE True END AS is_dup
        FROM drag d1
        JOIN ttt ON d1.type = ttt.type AND d1.rn = ttt.rn+1
        )
SELECT * FROM ttt
ORDER BY type, time_stamp
        ;

---

结果：

---

CREATE TABLE
INSERT 0 10
CREATE VIEW
 type | time_stamp | rn | fst | is_dup 
------+------------+----+-----+--------
    1 |          1 |  1 |   1 | f
    1 |          2 |  2 |   1 | t
    1 |          3 |  3 |   1 | t
    1 |         10 |  4 |   1 | t
    1 |         15 |  5 |   1 | t
    1 |         21 |  6 |   1 | t
    1 |         40 |  7 |  40 | f
    2 |          2 |  1 |   2 | f
    2 |         10 |  2 |   2 | t
    2 |         13 |  3 |   2 | t
(10 rows)

Answer 2

递归方法的替代方法是自定义聚合。一旦掌握了编写自己的聚合的技术，创建转换函数和最终函数就变得容易且合乎逻辑。

状态转换函数：

create or replace function is_duplicate(st int[], time_stamp int, timeframe int)
returns int[] language plpgsql as $$
begin
    if st is null or st[1] + timeframe <= time_stamp
    then 
        st[1] := time_stamp;
    end if;
    st[2] := time_stamp;
    return st;
end $$;

最终功能：

create or replace function is_duplicate_final(st int[])
returns boolean language sql as $$
    select st[1] <> st[2];
$$;

聚合：

create aggregate is_duplicate_agg(time_stamp int, timeframe int)
(
    sfunc = is_duplicate,
    stype = int[],
    finalfunc = is_duplicate_final
);

查询：

select *, is_duplicate_agg(time_stamp, 10) over w
from event
window w as (partition by type order by time_stamp asc)
order by type, time_stamp;

 id | type | time_stamp | is_duplicate_agg 
----+------+------------+------------------
  1 |    1 |          1 | f
  2 |    1 |          2 | t
  4 |    1 |          3 | t
  5 |    1 |         10 | t
  7 |    1 |         15 | f
  8 |    1 |         21 | t
 10 |    1 |         40 | f
  3 |    2 |          2 | f
  6 |    2 |         10 | t
  9 |    2 |         13 | f
(10 rows)   

阅读文档：37.10. User-defined Aggregates 和 CREATE AGGREGATE.

Answer 3

这感觉更像是一个递归问题，而不是窗口函数。以下查询获得了预期的结果：

WITH RECURSIVE base(type, time_stamp) AS (

  -- 3. base of recursive query
  SELECT x.type, x.time_stamp, y.next_time_stamp
    FROM 
         -- 1. start with the initial records of each type   
         ( SELECT type, min(time_stamp) AS time_stamp
             FROM event
             GROUP BY type
         ) x
         LEFT JOIN LATERAL
         -- 2. for each of the initial records, find the next TIMEFRAME (10) in the future
         ( SELECT MIN(time_stamp) next_time_stamp
             FROM event
             WHERE type = x.type
               AND time_stamp > (x.time_stamp + 10)
         ) y ON true

  UNION ALL

  -- 4. recursive join, same logic as base
  SELECT e.type, e.time_stamp, z.next_time_stamp
    FROM event e
    JOIN base b ON (e.type = b.type AND e.time_stamp = b.next_time_stamp)
    LEFT JOIN LATERAL
    ( SELECT MIN(time_stamp) next_time_stamp
       FROM event
       WHERE type = e.type
         AND time_stamp > (e.time_stamp + 10)
    ) z ON true

)

-- The actual query:

-- 5a. All records from base are not duplicates
SELECT time_stamp, type, false
  FROM base

UNION

-- 5b. All records from event that are not in base are duplicates
SELECT time_stamp, type, true
  FROM event
  WHERE (type, time_stamp) NOT IN (SELECT type, time_stamp FROM base) 

ORDER BY type, time_stamp

对此有很多警告。它假定给定的type 没有重复的time_stamp。实际上，连接应该基于唯一的 id 而不是 type 和 time_stamp。我没有测试这么多，但它至少可以建议一种方法。

这是我第一次尝试LATERAL 加入。所以可能有一种方法可以简化那个moe。我真正想做的是递归 CTE，其递归部分使用基于 time_stamp > (x.time_stamp + 10) 的 MIN(time_stamp)，但 CTE 中不允许以这种方式聚合函数。不过好像横向连接可以用在CTE中。