Question

编辑我案例的详细信息。

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');

根据以上数据，我使用下面的sql获得每周高分。

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。每次用户玩游戏时，它将节省时间作为得分1到得分4（4分的得分，得分4是最终得分）。

tbl_userscores用（fbuid，score4，updated_date，create_date）编制索引。它有45K的记录，并且还在不断增长。

我希望每周获得前30名的高分。这个查询让我平均完成了45秒。

所以我想就如何让它变得更好寻求专家的建议。

提前致谢。

Answer 1

我相信大部分时间花在相关子查询上，每个用户提取max（score4）。它可能会被重组，一次获得前30个分数，并用作主表的过滤器。不幸的是，由于您可能会获得重复项并且需要使用最早的updated_date来避免它们，因此需要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，您可以删除minUpdated派生表，包含完整查询并使用not exists来选择仅具有每个score4最小updated_date的记录。这应该更快，因为你会略微超过30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

我已将日期比较替换为更有前景的模式＆gt; =和＆lt;。此更改可避免日期时间解决问题（如果在一天的最后999毫秒内进行更新，则可能会丢失记录）。这也是很好的防御工具 - 即使某人设法输入您的业务逻辑不期望的日期的时间部分，您的查询也会起作用。

寻求有助于加快我的mysql查询

1 个答案: