【原创】MySQL新旧版本ORDERBY处理方法

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 ;

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 表示用了第二种排序规则。

其他的两种 以及分别代表第一种和后续版本MySQL的提升， 自己体验去吧。