如何在没有任何连接的情况下优化大型MySQL表中的查询?

时间：2022-05-14 20:45:12

How can I optimize this single query from a single large-ish table (~75M rows)?

如何从一个大的表(~75M行)优化这个查询?

SELECT
    log_id
FROM
    score
WHERE
    class_id IN (17,395)
ORDER BY date_reverse
LIMIT 10000;

I pull the most recent 10k records for a particular set of classes so that I can quickly know if they already exist or not during a larger import script.

我为一组特定的类提取最近的10k记录，以便在较大的导入脚本中快速知道它们是否已经存在。

I think I've indexed appropriately but this query lasts anywhere from 5-50 seconds!

我认为我已经适当地建立了索引，但是这个查询可以持续5-50秒!

Let me know if you need anything else.

如果你还需要什么，请告诉我。

EXPLAIN
    SELECT
        log_id
    FROM
        score
    WHERE
        class_id IN (17,395)
    ORDER BY date_reverse
    LIMIT 10000;

*** row 1 ***
          table:  score
           type:  range
  possible_keys:  class_id,score_multi_2,class_id_date_reverse,score_multi_5
            key:  class_id_date_reverse
        key_len:  4
            ref:  NULL
           rows:  1287726
          Extra:  Using where; Using index; Using filesort

CREATE TABLE `score` (
  `log_id` bigint(20) NOT NULL,
  `profile_id` bigint(20) DEFAULT NULL,
  `date` datetime DEFAULT NULL,
  `class_id` int(11) NOT NULL,
  `score` float(10,6) DEFAULT NULL,
  `score_date` datetime DEFAULT NULL,
  `process_date` datetime DEFAULT NULL,
  `status_type_id` int(3) NOT NULL DEFAULT '0',
  `date_reverse` int(11) DEFAULT NULL,
  UNIQUE KEY `unique_key` (`log_id`,`class_id`),
  KEY `class_id` (`class_id`),
  KEY `profile_id` (`profile_id`),
  KEY `date` (`date`),
  KEY `score` (`score`),
  KEY `status_type_id` (`status_type_id `),
  KEY `status_type_id_date` (`status_type_id`,`date`),
  KEY `class_status_type_id_date_log_id` (`class_id`,`status_type_id`,`date`,`log_id`),
  KEY `date_reverse` (`date_reverse`),
  KEY `class_id_date_reverse` (`class_id`,`date_reverse`),
  KEY `date` (`date`),
  KEY `class_id_date_reverse_log_id` (`class_id`,`date_reverse`,`log_id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8 COLLATE=utf8_unicode_ci;

1 个解决方案

#1

3  

My guess is that the fastest way to run this query is to bite the bullet and allow a sort on 20,000 rows. The query I have in mind is:

我的猜测是，运行这个查询的最快方式是咬紧牙关，允许对20,000行进行排序。我想到的问题是:

SELECT *
FROM ((SELECT log_id
       FROM score
       WHERE class_id = 17
       ORDER BY date_reverse
       LIMIT 10000
      ) UNION ALL
      (SELECT log_id
       FROM score
       WHERE class_id = 395
       ORDER BY date_reverse
       LIMIT 10000
      )
     ) s
ORDER BY date_reverse
LIMIT 10000;

For this query, you want the composite index on score(class_id, date_reverse, log_id). Each subquery should use this index quite effectively. However, the final sort will need to use file sort.

对于这个查询，需要在score(class_id、date_reverse、log_id)上建立复合索引。每个子查询都应该非常有效地使用这个索引。但是，最终的排序将需要使用文件排序。

#1

3  

My guess is that the fastest way to run this query is to bite the bullet and allow a sort on 20,000 rows. The query I have in mind is:

我的猜测是，运行这个查询的最快方式是咬紧牙关，允许对20,000行进行排序。我想到的问题是:

SELECT *
FROM ((SELECT log_id
       FROM score
       WHERE class_id = 17
       ORDER BY date_reverse
       LIMIT 10000
      ) UNION ALL
      (SELECT log_id
       FROM score
       WHERE class_id = 395
       ORDER BY date_reverse
       LIMIT 10000
      )
     ) s
ORDER BY date_reverse
LIMIT 10000;

For this query, you want the composite index on score(class_id, date_reverse, log_id). Each subquery should use this index quite effectively. However, the final sort will need to use file sort.

对于这个查询，需要在score(class_id、date_reverse、log_id)上建立复合索引。每个子查询都应该非常有效地使用这个索引。但是，最终的排序将需要使用文件排序。

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