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。