使用其他(不同的)过滤器聚合列 [英] Aggregate columns with additional (distinct) filters

问题描述

此代码按预期工作，但我很长而且令人毛骨悚然.

This code works as expected, but I it's long and creepy.

select p.name, p.played, w.won, l.lost from

(select users.name, count(games.name) as played
from users
inner join games on games.player_1_id = users.id
where games.winner_id > 0
group by users.name
union
select users.name, count(games.name) as played
from users
inner join games on games.player_2_id = users.id
where games.winner_id > 0
group by users.name) as p

inner join

(select users.name, count(games.name) as won
from users
inner join games on games.player_1_id = users.id
where games.winner_id = users.id
group by users.name
union
select users.name, count(games.name) as won
from users
inner join games on games.player_2_id = users.id
where games.winner_id = users.id
group by users.name) as w on p.name = w.name

inner join

(select users.name, count(games.name) as lost
from users
inner join games on games.player_1_id = users.id
where games.winner_id != users.id
group by users.name
union
select users.name, count(games.name) as lost
from users
inner join games on games.player_2_id = users.id
where games.winner_id != users.id
group by users.name) as l on l.name = p.name

如您所见，它由 3 个用于检索的重复部分组成:

As you can see, it consists of 3 repetitive parts for retrieving:

• 玩家姓名和他们玩过的游戏数量
• 玩家姓名和他们赢得的游戏数量
• 玩家姓名和他们输掉的游戏数量

每一个也由两部分组成:

And each of those also consists of 2 parts:

• 玩家姓名和他们作为 player_1 参与的游戏数量
• 玩家姓名和他们作为 player_2 参与的游戏数量

如何简化?

结果如下:

           name            | played | won | lost 
---------------------------+--------+-----+------
 player_a                  |      5 |   2 |    3
 player_b                  |      3 |   2 |    1
 player_c                  |      2 |   1 |    1

推荐答案

Postgres 9.4 或更新版本中的 aggregate FILTER 子句 更短且更快:

The aggregate FILTER clause in Postgres 9.4 or newer is shorter and faster:

SELECT u.name
     , count(*) FILTER (WHERE g.winner_id  > 0)    AS played
     , count(*) FILTER (WHERE g.winner_id  = u.id) AS won
     , count(*) FILTER (WHERE g.winner_id <> u.id) AS lost
FROM   games g
JOIN   users u ON u.id IN (g.player_1_id, g.player_2_id)
GROUP  BY u.name;

• 手册
• Postgres Wiki
• Depesz 博文

在 Postgres 9.3(或 any 版本)中，这仍然比嵌套子选择或 CASE 表达式更短且更快:

In Postgres 9.3 (or any version) this is still shorter and faster than nested sub-selects or CASE expressions:

SELECT u.name
     , count(g.winner_id  > 0 OR NULL)    AS played
     , count(g.winner_id  = u.id OR NULL) AS won
     , count(g.winner_id <> u.id OR NULL) AS lost
FROM   games g
JOIN   users u ON u.id IN (g.player_1_id, g.player_2_id)
GROUP  BY u.name;

详情:

• 对于绝对性能，SUM 更快还是 COUNT 更快?

这篇关于使用其他(不同的)过滤器聚合列的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！