我的表 posts 有超过 650 万条记录。每个帖子都使用固定长度的 name 表示。我使用 MySQL Community 5.7，具有大约 10K-20K IOPS 和 1GB 内存的 SSD 磁盘，key-buffer-size 设置为 512M(顺便说一句，大多数时候我使用默认的 MySQL 配置驱动)。我的资源有限，因此我选择了 MyISAM 作为我的存储引擎。我的基准测试表明，在我的情况下，MyISAM 更快。我也不太关心数据，因为它可以更新。
所以，这是我的方案信息:
+------------+--------+------------+
| TABLE_NAME | ENGINE | row_format |
+------------+--------+------------+
| posts | MyISAM | Fixed |
+------------+--------+------------+
+---------------------+---------------------+------+-----+---------+----------------+
| Field | Type | Null | Key | Default | Extra |
+---------------------+---------------------+------+-----+---------+----------------+
| id | int(11) unsigned | NO | PRI | NULL | auto_increment |
| name | char(30) | NO | UNI | NULL | |
| worker_id | tinyint(4) unsigned | NO | MUL | NULL | |
| processing_priority | tinyint(4) unsigned | NO | MUL | 0 | |
| last_processed_at | datetime | YES | MUL | NULL | |
| scraped_at | datetime | NO | MUL | NULL | |
+---------------------+---------------------+------+-----+---------+----------------+
+-------+------------+---------------------+--------------+---------------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | Index_comment |
+-------+------------+---------------------+--------------+---------------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| posts | 0 | PRIMARY | 1 | id | A | 6579588 | NULL | NULL | | BTREE | | |
| posts | 0 | name | 1 | name | A | 6579588 | NULL | NULL | | BTREE | | |
| posts | 1 | last_processed_at | 1 | last_processed_at | A | 6579588 | NULL | NULL | YES | BTREE | | |
| posts | 1 | processing_priority | 1 | processing_priority | A | 3 | NULL | NULL | | BTREE | | |
| posts | 1 | worker_id | 1 | worker_id | A | 50 | NULL | NULL | | BTREE | | |
| posts | 1 | scraped_at | 1 | scraped_at | A | 234985 | NULL | NULL | | BTREE | | |
+-------+------------+---------------------+--------------+---------------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
我运行的查询:
SELECT COUNT(*) FROM `posts` WHERE `posts`.`worker_id` = 1 AND (last_processed_at >= '2017-11-04 22:20:27.203761')
MySQL 需要 3676.4ms 来执行这个查询。
查询解释:
+----+-------------+-------+------------+------+-----------------------------+-----------+---------+-------+--------+----------+-------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-------+------------+------+-----------------------------+-----------+---------+-------+--------+----------+-------------+
| 1 | SIMPLE | posts | NULL | ref | last_processed_at,worker_id | worker_id | 1 | const | 232621 | 37.45 | Using where |
+----+-------------+-------+------------+------+-----------------------------+-----------+---------+-------+--------+----------+-------------+
您对如何优化它有任何想法吗？
最佳答案
您可以使用 worker_id 和 last_processed_at 创建组合键，替换 worker_id 键。
关于mysql - 在 MySQL 中按日期时间范围选择非常慢，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/47120493/