2

编辑我的案例的详细信息。

CREATE TABLE IF NOT EXISTS `tbl_user` (
  `id` int(50) NOT NULL auto_increment,
  `fbuid` bigint(20) unsigned NOT NULL,
  `fullname` varchar(255) NOT NULL,
  PRIMARY KEY  (`id`),
  UNIQUE KEY `fbuid` (`fbuid`)
) ENGINE=MyISAM  DEFAULT CHARSET=utf8 AUTO_INCREMENT=7 ;

INSERT INTO `tbl_user` (`id`, `fbuid`, `fullname`) VALUES
(1, 1002, 'User B'),
(2, 1001, 'User A'),
(3, 1003, 'User C'),
(4, 1004, 'User D'),
(5, 1005, 'User E'),
(6, 1006, 'User F');


CREATE TABLE IF NOT EXISTS `tbl_userscores` (
  `fbuid` bigint(20) NOT NULL,
  `game_id` varchar(255) NOT NULL,
  `score1` bigint(20) NOT NULL default '0',
  `score2` bigint(20) NOT NULL default '0',
  `score3` bigint(20) NOT NULL default '0',
  `score4` bigint(20) NOT NULL default '0',
  `created_date` datetime NOT NULL,
  `updated_date` datetime NOT NULL,
  PRIMARY KEY  (`game_id`),
  UNIQUE KEY `fbuid` (`fbuid`,`game_id`),
  KEY `fbuid_2` (`fbuid`,`game_id`,`score4`),
  KEY `fbuid_3` (`fbuid`,`game_id`,`score4`,`updated_date`),
  KEY `fbuid_4` (`fbuid`,`game_id`,`score1`,`score2`,`score3`,`score4`,`created_date`,`updated_date`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;

INSERT INTO `tbl_userscores` (`fbuid`, `game_id`, `score1`, `score2`, `score3`, `score4`, `created_date`, `updated_date`) VALUES
(1001, '13361975565253060', 650, 3300, 7675, 14500, '2012-05-05 13:59:55', '2012-05-05 14:01:50'),
(1001, '1336278398787510', 3100, 87725, 326675, 573625, '2012-05-06 12:28:20', '2012-05-06 12:33:27'),
(1001, '13368015862343980', 12875, 82550, 158625, 299550, '2012-05-12 13:48:08', '2012-05-12 13:53:15'),
(1001, '13369691453105020', 7925, 58525, 283100, 368225, '2012-05-14 12:20:47', '2012-05-14 12:25:54'),
(1002, '1336328839124400', 1275, 11475, 31450, 50475, '2012-05-07 02:27:34', '2012-05-07 02:28:20'),
(1002, '13363686059958120', 11025, 48900, 72725, 115150, '2012-05-07 13:30:21', '2012-05-07 13:31:07'),
(1002, '13364088902032830', 6650, 6700, 10200, 17625, '2012-05-08 00:41:46', '2012-05-08 00:42:32'),
(1002, '13364910479425300', 3600, 17050, 60450, 114800, '2012-05-08 23:31:03', '2012-05-08 23:31:49'),
(1002, '13364949763272710', 17250, 168125, 479475, 596925, '2012-05-07 00:37:33', '2012-05-07 00:41:21'),
(1003, '13363240964199380', 84150, 84150, 84150, 84150, '2012-05-07 01:11:37', '2012-05-07 01:12:22'),
(1003, '1336465518338010', 297275, 351300, 437150, 468350, '2012-05-08 16:31:52', '2012-05-08 16:32:38'),
(1003, '13368122913207860', 0, 82350, 94150, 102750, '2012-05-12 16:45:20', '2012-05-12 16:48:09'),
(1003, '13368125091164060', 423925, 428125, 521875, 589750, '2012-05-12 16:54:00', '2012-05-12 16:54:47'),
(1004, '13363118226930570', 3275, 10975, 16250, 22900, '2012-05-06 21:43:58', '2012-05-06 21:44:43'),
(1004, '13366228756934380', 23275, 149100, 380600, 382075, '2012-05-10 12:08:46', '2012-05-10 12:10:49'),
(1004, '13366232802957960', 3650, 23525, 49975, 49975, '2012-05-10 12:14:55', '2012-05-10 12:15:42'),
(1005, '13361215491096720', 1200, 16250, 39125, 55800, '2012-05-04 16:52:59', '2012-05-04 16:54:29'),
(1005, '13361216729657120', 11000, 29800, 82575, 188550, '2012-05-04 16:55:03', '2012-05-04 16:56:33'),
(1005, '13361364491988250', 6925, 50925, 89100, 180425, '2012-05-04 21:01:12', '2012-05-04 21:02:43'),
(1005, '13362204979150640', 11300, 39800, 63675, 78725, '2012-05-05 20:22:08', '2012-05-05 20:23:36'),
(1005, '13362311869003160', 11575, 61500, 134200, 233600, '2012-05-05 23:20:17', '2012-05-05 23:21:48'),
(1005, '133628163373910', 3500, 40175, 131375, 251725, '2012-05-06 13:21:03', '2012-05-06 13:22:35'),
(1006, '13361224889844730', 6700, 30575, 49650, 50475, '2012-05-04 17:08:24', '2012-05-04 17:09:10'),
(1006, '13366294182421110', 16800, 87675, 119150, 206500, '2012-05-10 13:57:42', '2012-05-10 14:00:15'),
(1006, '13366296357158010', 23050, 99025, 229075, 381925, '2012-05-10 14:01:27', '2012-05-10 14:03:58'),
(1006, '13368319289949330', 22975, 130375, 350600, 355150, '2012-05-12 22:13:00', '2012-05-12 22:15:08');

有了上面的数据，我使用下面的 sql 来获得每周的高分。

SELECT U1.fbuid, U1.fullname, U2.score4 AS weeklyhighscore, U2.created_date, U2.updated_date, TIMEDIFF( U2.updated_date, U2.created_date ) AS Duration
    FROM tbl_user AS U1, (  
                SELECT fbuid, score4, MIN( updated_date ) AS updated_date, created_date
                FROM tbl_userscores AS A
                WHERE A.score4
                IN (
                    SELECT MAX(  `score4` ) AS best
                    FROM tbl_userscores AS B
                    WHERE A.fbuid = B.fbuid
                    AND B.score1 >0
                    AND B.score2 >0
                    AND B.score3 >0
                    AND B.score4 >0
                    AND `updated_date` >= '2012-05-06 00:00:00' AND `updated_date` <= '2012-05-12 23:59:59'
                    GROUP BY fbuid
                )
                GROUP BY A.fbuid
                ORDER BY  `A`.`score4` DESC , updated_date ASC
            ) AS U2
WHERE U1.fbuid = U2.fbuid
ORDER BY weeklyhighscore DESC 
LIMIT 0 , 30

预期结果 ：

+-------+----------+-----------------+---------------------+---------------------+----------+
| fbuid | fullname | weeklyhighscore | created_date        | updated_date        | Duration |
| 1002  | User B   | 596925          | 2012-05-07 00:37:33 | 2012-05-07 00:41:21 | 00:03:48 |
| 1003  | User C   | 589750          | 2012-05-12 16:54:00 | 2012-05-12 16:54:47 | 00:00:47 |
| 1001  | User A   | 573625          | 2012-05-06 12:28:20 | 2012-05-06 12:33:27 | 00:05:07 |
| 1004  | User D   | 382075          | 2012-05-10 12:08:46 | 2012-05-10 12:10:49 | 00:02:03 |
| 1006  | User F   | 381925          | 2012-05-10 14:01:27 | 2012-05-10 14:03:58 | 00:02:31 |
| 1005  | User E   | 251725          | 2012-05-06 13:21:03 | 2012-05-06 13:22:35 | 00:01:32 |
+-------+----------+-----------------+---------------------+---------------------+----------+

我有两个表，tbl_user 和 tbl_userscores。用户每次玩游戏时，它会将次数保存为 score1 到 score4（4 次得分，其中 score4 为最终得分）。

tbl_userscores 使用 (fbuid,score4,updated_date,create_date) 编制索引。它拥有 45K 条记录，并且还在不断增长。

我想获得前 30 名的每周高分。这个查询平均需要 45 秒才能完成。

因此，我想就如何使它变得更好寻求专家的建议。

提前致谢。

4

1 回答 1

0

我相信大部分时间都花在为每个用户提取 max(score4) 的相关子查询上。可能会对其进行重组以一次获得前 30 名并用作主表的过滤器。不幸的是，由于您可能会得到重复项并且需要采用最早的 updated_date 来避免它们，因此还有额外的派生表来获取此过滤器。如果这被证明是最慢的部分，您可能会删除minUpdated派生表，封装完整的查询并使用not exists仅选择每个 score4 具有最小更新日期的记录。这应该更快，因为您通常只有 30 多条记录。

SELECT U1.fbuid, 
       U1.fullname, 
       U2.score4 AS weeklyhighscore, 
       U2.created_date, 
       U2.updated_date, 
       TIMEDIFF( U2.updated_date, U2.created_date ) AS Duration
FROM tbl_user AS U1
INNER JOIN tbl_userscores U2
   ON U1.FbUid = U2.FbUid
/* Top 30 scores by user */
INNER JOIN
(
  SELECT B.fbuid, 
         MAX(`score4`) AS best
    FROM tbl_userscores AS B
   WHERE B.score1 > 0
     AND B.score2 > 0
     AND B.score3 > 0
     AND B.score4 > 0
     AND `updated_date` >= '2012-05-06 00:00:00'
     AND `updated_date` < '2012-05-13 00:00:00'
   GROUP BY fbuid
   ORDER BY best DESC
   LIMIT 30
) A
   ON U2.FbUid = A.FbUid
  AND U2.Score4 = best
/* Filter by min(updated_date) in case of several same scores per user */
INNER JOIN
(
  SELECT FbUid, Score4, MIN(updated_date) updated_date
    FROM tbl_userscores
   GROUP BY FbUid, Score4
) minUpdated
   ON U2.FbUid = minUpdated.FbUid
  AND U2.Score4 = minUpdated.Score4
  AND U2.Updated_date = minUpdated.Updated_date
ORDER BY weeklyhighscore DESC

我已经用更有希望的模式 >= 和 < 替换了日期比较。此更改避免了日期时间解析问题（如果在一天的最后 999 毫秒内进行更新，您可能会丢失记录）。这也是一个很好的防御工具——即使有人以某种方式设法输入了您的业务逻辑不期望的日期的时间部分，您的查询也将起作用。

于 2012-05-14T09:13:36.567 回答