如何从相邻 table 中动态数量的相关行获取聚合数据

Question

我打了 table 场比赛，大致是这样的：

player_id | match_id | result | opponent_rank
----------------------------------------------
82        | 2847     |   w    |   42
82        | 3733     |   w    |  185
82        | 4348     |   l    |   10
82        | 5237     |   w    |  732
82        | 5363     |   w    |   83
82        | 7274     |   w    |    6
51        | 2347     |   w    |   39
51        | 3746     |   w    |  394
51        | 5037     |   l    |   90
...       | ...      |  ...   |  ...

要获得所有连胜记录（不仅仅是任何玩家的最高连胜记录），我使用此查询：

SELECT player.tag, s.streak, match.date, s.player_id, s.match_id FROM (
    SELECT streaks.streak, streaks.player_id, streaks.match_id FROM (
        SELECT w1.player_id, max(w1.match_id) AS match_id, count(*) AS streak FROM (
            SELECT w2.player_id, w2.match_id, w2.win, w2.date, sum(w2.grp) OVER w AS grp FROM (
                SELECT m.player_id, m.match_id, m.win, m.date, (m.win = false AND LAG(m.win, 1, true) OVER w = true)::integer AS grp FROM matches_m AS m
                WHERE matches_m.opponent_position<'100'
                    WINDOW w AS (PARTITION BY m.player_id ORDER BY m.date, m.match_id)
                    ) AS w2
                    WINDOW w AS (PARTITION BY w2.player_id ORDER BY w2.date, w2.match_id)
                ) AS w1
            WHERE w1.win = true
            GROUP BY w1.player_id, w1.grp
            ORDER BY w1.player_id DESC, count(*) DESC
        ) AS streaks
    ORDER BY streaks.streak DESC
    LIMIT 100
    ) AS s
LEFT JOIN player ON player.id = s.player_id
LEFT JOIN match ON match.id = s.match_id

结果如下所示（请注意，这不是固定的 table/view，因为上面的查询可以通过某些参数进行扩展，例如国籍、日期范围、玩家排名等）：

player_id | match_id | streak
-------------------------------
82        | 3733     |  2
82        | 7274     |  3
51        | 3746     |  2
...       | ...      |  ...

我现在要添加的是一堆汇总数据，以提供有关连胜的详细信息。对于初学者，我想知道在每一次连胜中对手的平均排名。其他数据包括连胜的持续时间、第一个和最后一个日期、结束连胜的对手姓名或是否仍在进行中，等等。我尝试过各种方法——CTE、一些精心设计的连接、联合，或将它们作为滞后函数添加到现有代码中。但我完全不知道如何解决这个问题。

从代码中可以看出，我的SQL技能很基础，所以如果有错误或低效的陈述，请原谅。对于完整的上下文，我在 Debian 上使用 Postgres 9.4，matches_m table 是一个具有 550k 行的物化视图（查询现在需要 2.5 秒）。数据来自http://aligulac.com/about/db/，我只是镜像它来创建上述视图。

Answer 1

您需要获取所有行以获得最高连胜，而不是聚合行。

这 return 包含详细信息的前 100 条连胜（将 return 所有连胜改为 n 会更容易）。

SELECT ....
FROM
 (
   SELECT streaks.*,
      -- used to filter the top 100 streaks
      -- (would be more efficient without by filtering streaks only in Where)
      Dense_Rank()
      Over (ORDER BY streak DESC, grp, player_id) AS topStreak
   FROM
    (
      SELECT w1.*,
         Count(*) 
         Over (PARTITION BY player_id, grp) AS streak -- count wins per streak
      FROM
       ( --  simplified assigning the group numbers to a single Cumulative Sum
         SELECT m.player_id, m.match_id, m.win, m.DATE, --additional columns needed
            -- cumulative sum over 0/1, doesn't increase for wins, i.e. a streak of wins gets the same number
            Sum(CASE WHEN win = False THEN 1 ELSE 0 end)  
            Over(PARTITION BY m.player_id
                 ORDER BY DATE, match_id
                 ROWS Unbounded Preceding) AS grp
         FROM matches_m AS m
         WHERE matches_m.opponent_position<'100' -- should be <100 if it's an INT 
       ) AS w1
      WHERE w1.win = True  -- remove the losses
    ) AS streaks
   -- restrict the number of rows processed by the DENSE_RANK
   -- (could be used instead of DENSE_RANK + WHERE topStreak <= 100)
   WHERE streak > 20 
 ) AS s
WHERE topStreak <= 100

现在您可以对这些条纹应用任何类型的分析。由于 PG 不是我的主要 DBMS，我不知道使用数组或 Window 函数（如 last_value(opponent_player_id) over ...

是否更容易

Answer 2

我想这就是你想要的。

关键思想是为每个连胜分配一个 "streak group"，这样您就可以将它们汇总起来。你可以通过观察来做到这一点：

连胜的比赛显然是"win"。
可以通过计算之前的失败次数来识别连胜 -- 这对于连胜是不变的。

Postgres 在 9.4 中引入了 filter 子句，这使得语法更简单一些：

select player_id, count(*) as streak_length,
       avg(opponent_rank) as avg_opponent_rank
from (select m.*,
             count(*) filter (where result = 'l') over (partition by player_id order by date) as streak_grp
      from matches_m m
     ) m
where result = 'w'
group by player_id, streak_grp;

如何从相邻 table 中动态数量的相关行获取聚合数据

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