MySQL 的order by 涉及到三个参数:
A. sort_buffer_size 排序缓存。
B. read_rnd_buffer_size 第二次排序缓存。
C. max_length_for_sort_data 带普通列的最大排序约束。
我来简单说下MySQL的排序规则。
假设查询语句select * from tb1 where 1 order by a ; 字段a没有建立索引;以上三个参数都足够大。
MySQL内部有两种排序规则:
第一种,是普通的排序。这种排序的特点是节省内存,但是最终会对磁盘有一次随机扫描。 大概主要过程如下:
1. 由于没有WHERE条件,所以直接对磁盘进行全表扫描,把字段a以及每行的物理ID(假设为TID)拿出来。然后把所有拿到的记录全部放到sort_buffer_size中进行排序。
2. 根据排好序的TID,从磁盘随机扫描所需要的所有记录,排好序后再次把所有必须的记录放到read_rnd_buffer_size中。
第二种,是冗余排序。这种排序的特点是不需要二次对磁盘进行随机扫描,但是缺点很明显,太浪费内存空间。
跟第一种不同的是,在第一步里拿到的不仅仅是字段a以及TID,而是把所有请求的记录全部拿到后,放到sort_buffer_size中进行排序。这样可以直接从缓存中返回记录给客户端,不用再次从磁盘上获取一次。
从MySQL 5.7 后,对第二种排序进行了打包压缩处理,避免太浪费内存。比如对于varchar(255)来说,实际存储为varchar(3)。那么相比之前的方式节约了好多内存,避免缓存区域不够时,建立磁盘临时表。
以下为简单的演示
mysql> use t_girl;
Database changed
三个参数的具体值:
mysql> select truncate(@@sort_buffer_size/1024/1024,2)||‘MB‘ as ‘sort_buffer_size‘,truncate(@@read_rnd_buffer_size/1024/1024,2)||‘MB‘ as read_rnd_buffer_zie,@@max_length_for_sort_data as max_length_for_sort_data; +------------------+---------------------+--------------------------+ | sort_buffer_size | read_rnd_buffer_zie | max_length_for_sort_data | +------------------+---------------------+--------------------------+ | 2.00MB | 2.00MB | 1024 | +------------------+---------------------+--------------------------+ 1 row in set (0.00 sec)
演示表的相关数据:
mysql> select table_name,table_rows,concat(truncate(data_length/1024/1024,2),‘MB‘) as ‘table_size‘ from information_schema.tables where table_name = ‘t1‘ and table_schema = ‘t_girl‘; +------------+------------+------------+ | table_name | table_rows | table_size | +------------+------------+------------+ | t1 | 2092640 | 74.60MB | +------------+------------+------------+ 1 row in set (0.00 sec)
开启优化器跟踪:
mysql> SET OPTIMIZER_TRACE="enabled=on",END_MARKERS_IN_JSON=on; Query OK, 0 rows affected (0.00 sec)
从数据字典里面拿到跟踪结果:
mysql> select * from information_schema.optimizer_trace\G *************************** 1. row *************************** QUERY: select * from t1 where id < 10 order by id TRACE: { "steps": [ { "join_preparation": { "select#": 1, "steps": [ { "expanded_query": "/* select#1 */ select `t1`.`id` AS `id`,`t1`.`log_time` AS `log_time` from `t1` where (`t1`.`id` < 10) order by `t1`.`id`" } ] /* steps */ } /* join_preparation */ }, { "join_optimization": { "select#": 1, "steps": [ { "condition_processing": { "condition": "WHERE", "original_condition": "(`t1`.`id` < 10)", "steps": [ { "transformation": "equality_propagation", "resulting_condition": "(`t1`.`id` < 10)" }, { "transformation": "constant_propagation", "resulting_condition": "(`t1`.`id` < 10)" }, { "transformation": "trivial_condition_removal", "resulting_condition": "(`t1`.`id` < 10)" } ] /* steps */ } /* condition_processing */ }, { "table_dependencies": [ { "table": "`t1`", "row_may_be_null": false, "map_bit": 0, "depends_on_map_bits": [ ] /* depends_on_map_bits */ } ] /* table_dependencies */ }, { "ref_optimizer_key_uses": [ ] /* ref_optimizer_key_uses */ }, { "rows_estimation": [ { "table": "`t1`", "table_scan": { "rows": 2092640, "cost": 4775 } /* table_scan */ } ] /* rows_estimation */ }, { "considered_execution_plans": [ { "plan_prefix": [ ] /* plan_prefix */, "table": "`t1`", "best_access_path": { "considered_access_paths": [ { "access_type": "scan", "rows": 2.09e6, "cost": 423303, "chosen": true, "use_tmp_table": true } ] /* considered_access_paths */ } /* best_access_path */, "cost_for_plan": 423303, "rows_for_plan": 2.09e6, "sort_cost": 2.09e6, "new_cost_for_plan": 2.52e6, "chosen": true } ] /* considered_execution_plans */ }, { "attaching_conditions_to_tables": { "original_condition": "(`t1`.`id` < 10)", "attached_conditions_computation": [ ] /* attached_conditions_computation */, "attached_conditions_summary": [ { "table": "`t1`", "attached": "(`t1`.`id` < 10)" } ] /* attached_conditions_summary */ } /* attaching_conditions_to_tables */ }, { "clause_processing": { "clause": "ORDER BY", "original_clause": "`t1`.`id`", "items": [ { "item": "`t1`.`id`" } ] /* items */, "resulting_clause_is_simple": true, "resulting_clause": "`t1`.`id`" } /* clause_processing */ }, { "refine_plan": [ { "table": "`t1`", "access_type": "table_scan" } ] /* refine_plan */ } ] /* steps */ } /* join_optimization */ }, { "join_execution": { "select#": 1, "steps": [ { "filesort_information": [ { "direction": "asc", "table": "`t1`", "field": "id" } ] /* filesort_information */, "filesort_priority_queue_optimization": { "usable": false, "cause": "not applicable (no LIMIT)" } /* filesort_priority_queue_optimization */, "filesort_execution": [ ] /* filesort_execution */, "filesort_summary": { "rows": 62390, "examined_rows": 2097152, "number_of_tmp_files": 0, "sort_buffer_size": 2097152, "sort_mode": "<sort_key, additional_fields>" } /* filesort_summary */ } ] /* steps */ } /* join_execution */ } ] /* steps */ } MISSING_BYTES_BEYOND_MAX_MEM_SIZE: 0 INSUFFICIENT_PRIVILEGES: 0 1 row in set (0.00 sec) mysql>
其中以上红色部分<sort_key, additional_fields> 表示用了第二种排序规则。
其他的两种<sort_key, rowid> 以及<sort_key, packed_additional_fields>分别代表第一种和后续版本MySQL的提升, 自己体验去吧。
MySQL新旧版本ORDER BY 处理方法,布布扣,bubuko.com