MySQL再深入执行计划之trace工具

素颜马尾好姑娘i 2023-09-29 13:47 5阅读 0赞

MySQL 执行查询语句时需要进行的查询成本分析了，而 MySQL 提供的 trace 工具就可以让我们看到 MySQL 计算的查询成本，以及选择索引的大致分析过程。

## \#一、示例表 ##

-- 示例表
    CREATE TABLE `employees` (
      `id` int(11) NOT NULL AUTO_INCREMENT,
      `name` varchar(24) NOT NULL DEFAULT '' COMMENT '姓名',
      `age` int(11) NOT NULL DEFAULT '0' COMMENT '年龄',
      `position` varchar(20) NOT NULL DEFAULT '' COMMENT '职位',
      `hire_time` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP COMMENT '入职时间',
      PRIMARY KEY (`id`),
      KEY `idx_name_age_position` (`name`,`age`,`position`) USING BTREE
    ) ENGINE=InnoDB AUTO_INCREMENT=1 DEFAULT CHARSET=utf8 COMMENT='员工记录表';
    
    INSERT INTO employees(name,age,position,hire_time) VALUES('itwxe',22,'manager',NOW());
    INSERT INTO employees(name,age,position,hire_time) VALUES('weiwei', 23,'test',NOW());
    INSERT INTO employees(name,age,position,hire_time) VALUES('leilei',23,'dev',NOW());
    
    -- 插入10w条测试数据
    drop procedure if exists insert_employees; 
    delimiter $$
    create procedure insert_employees()        
    begin
      declare i int;                    
      set i = 1;                          
      while(i <= 100000)do                 
        insert into employees(name, age, position) values(CONCAT('itwxe', i), rand() * 42 + 18, 'dev');  
        set i = i + 1;                       
      end while;
    end$$
    delimiter ;
    call insert_employees();

## \#二、trace使用步骤 ##

**首先需要说明的是开启 trace 工具会影响 MySQL 性能，所以只能临时分析 SQL 使用，用完之后立即关闭。**

使用 trace 工具步骤：

-- 首先开启trace
    mysql> set session optimizer_trace="enabled=on", end_markers_in_json=on;
    -- 执行查询SQL
    mysql> select * from employees where name > 'wei' order by position;
    -- 查询trace字段
    mysql> SELECT * FROM information_schema.OPTIMIZER_TRACE;

使用完成后关闭 trace 工具：

-- 当分析完SQL，关闭trace
    mysql> set session optimizer_trace="enabled=off";

## \#三、trace字段解析 ##

例如这条语句：

explain select * from employees where name > 'itwxe' order by position;
    
    explain select * from employees where name > 'wei' order by position;

![3d85aba8fed34dfca9a33c05977c5501.png][]

可以看到第一条 SQL 中 possible\_keys 有可以使用的索引 idx\_name\_age\_position ，但是最后实际上 MySQL 没有使用 idx\_name\_age\_position ，而是使用了全表扫描；而第二条 SQL 中使用到了 idx\_name\_age\_position 中的 name 列，这是为什么呢？

如果非常了解 MySQL 索引底层数据结构的小伙伴应该就知道因为第二条 SQL name > 'itwxe' 扫描的联合索引 idx\_name\_age\_position 的结果太多，回表成本太大，所以 MySQL 选择了全表扫描。要想看到 MySQL 计算的全表扫描成本和使用 idx\_name\_age\_position 成本就得使用咱们这篇的主角 trace 工具了，以第二条SQL为例。

执行后可以得到如下的示例结果，重要字段注释如下：

| select * from employees where name > 'wei' order by position | {
      "steps": [
        {
          "join_preparation": {  -- 第一阶段：SQL准备阶段，格式化SQL
            "select#": 1,
            "steps": [
              {
                "expanded_query": "/* select#1 */ select `employees`.`id` AS `id`,`employees`.`name` AS `name`,`employees`.`age` AS `age`,`employees`.`position` AS `position`,`employees`.`hire_time` AS `hire_time` from `employees` where (`employees`.`name` > 'wei') order by `employees`.`position`"
              }
            ] /* steps */
          } /* join_preparation */
        },
        {
          "join_optimization": {  -- 第二阶段：SQL优化阶段
            "select#": 1,
            "steps": [
              {
                "condition_processing": {  -- 条件处理，where，1=1之类的SQL优化
                  "condition": "WHERE",
                  "original_condition": "(`employees`.`name` > 'wei')",
                  "steps": [
                    {
                      "transformation": "equality_propagation",
                      "resulting_condition": "(`employees`.`name` > 'wei')"
                    },
                    {
                      "transformation": "constant_propagation",
                      "resulting_condition": "(`employees`.`name` > 'wei')"
                    },
                    {
                      "transformation": "trivial_condition_removal",
                      "resulting_condition": "(`employees`.`name` > 'wei')"
                    }
                  ] /* steps */
                } /* condition_processing */
              },
              {
                "substitute_generated_columns": {
                } /* substitute_generated_columns */
              },
              {
                "table_dependencies": [  -- 表依赖详情
                  {
                    "table": "`employees`",
                    "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": [  -- 预估表的访问成本
                  {
                    "table": "`employees`",
                    "range_analysis": {
                      "table_scan": {  -- 全表扫描情况
                        "rows": 100075,  -- 扫描行数，innodb中这个是预估值,MyISAM中时准确值
                        "cost": 20306  -- 查询成本
                      } /* table_scan */,
                      "potential_range_indexes": [  -- 查询可能使用的索引
                        {
                          "index": "PRIMARY",  -- 主键索引
                          "usable": false,
                          "cause": "not_applicable"
                        },
                        {
                          "index": "idx_name_age_position",  -- 联合索引
                          "usable": true,
                          "key_parts": [
                            "name",
                            "age",
                            "position",
                            "id"
                          ] /* key_parts */
                        }
                      ] /* potential_range_indexes */,
                      "setup_range_conditions": [
                      ] /* setup_range_conditions */,
                      "group_index_range": {
                        "chosen": false,
                        "cause": "not_group_by_or_distinct"
                      } /* group_index_range */,
                      "analyzing_range_alternatives": {  -- 分析各个索引使用成本
                        "range_scan_alternatives": [
                          {
                            "index": "idx_name_age_position",
                            "ranges": [
                              "wei < name"  -- 索引使用范围
                            ] /* ranges */,
                            "index_dives_for_eq_ranges": true,
                            "rowid_ordered": false, -- 使用该索引获取的记录是否按照主键排序
                            "using_mrr": false,  -- 是否使用mrr
                            "index_only": false,  -- 是否使用覆盖索引
                            "rows": 1,  -- 索引扫描行数，也是个预估值
                            "cost": 2.21,  -- 索引使用成本
                            "chosen": true  -- 是否选择该索引
                          }
                        ] /* range_scan_alternatives */,
                        "analyzing_roworder_intersect": {
                          "usable": false,
                          "cause": "too_few_roworder_scans"
                        } /* analyzing_roworder_intersect */
                      } /* analyzing_range_alternatives */,
                      "chosen_range_access_summary": {
                        "range_access_plan": {
                          "type": "range_scan",
                          "index": "idx_name_age_position",
                          "rows": 1,
                          "ranges": [
                            "wei < name"
                          ] /* ranges */
                        } /* range_access_plan */,
                        "rows_for_plan": 1,
                        "cost_for_plan": 2.21,
                        "chosen": true
                      } /* chosen_range_access_summary */
                    } /* range_analysis */
                  }
                ] /* rows_estimation */
              },
              {
                "considered_execution_plans": [
                  {
                    "plan_prefix": [
                    ] /* plan_prefix */,
                    "table": "`employees`",
                    "best_access_path": {  -- 最优访问路径
                      "considered_access_paths": [  -- 最终访问路径
                        {
                          "rows_to_scan": 1,
                          "access_type": "range",  -- 访问类型 range：访问扫描；scan：全表扫描
                          "range_details": {
                            "used_index": "idx_name_age_position"
                          } /* range_details */,
                          "resulting_rows": 1,
                          "cost": 2.41,
                          "chosen": true,  -- 确定选择
                          "use_tmp_table": true
                        }
                      ] /* considered_access_paths */
                    } /* best_access_path */,
                    "condition_filtering_pct": 100,
                    "rows_for_plan": 1,
                    "cost_for_plan": 2.41,
                    "sort_cost": 1,
                    "new_cost_for_plan": 3.41,
                    "chosen": true
                  }
                ] /* considered_execution_plans */
              },
              {
                "attaching_conditions_to_tables": {
                  "original_condition": "(`employees`.`name` > 'wei')",
                  "attached_conditions_computation": [
                  ] /* attached_conditions_computation */,
                  "attached_conditions_summary": [
                    {
                      "table": "`employees`",
                      "attached": "(`employees`.`name` > 'wei')"
                    }
                  ] /* attached_conditions_summary */
                } /* attaching_conditions_to_tables */
              },
              {
                "clause_processing": {
                  "clause": "ORDER BY",
                  "original_clause": "`employees`.`position`",
                  "items": [
                    {
                      "item": "`employees`.`position`"
                    }
                  ] /* items */,
                  "resulting_clause_is_simple": true,
                  "resulting_clause": "`employees`.`position`"
                } /* clause_processing */
              },
              {
                "reconsidering_access_paths_for_index_ordering": {
                  "clause": "ORDER BY",
                  "steps": [
                  ] /* steps */,
                  "index_order_summary": {
                    "table": "`employees`",
                    "index_provides_order": false,
                    "order_direction": "undefined",
                    "index": "idx_name_age_position",
                    "plan_changed": false
                  } /* index_order_summary */
                } /* reconsidering_access_paths_for_index_ordering */
              },
              {
                "refine_plan": [
                  {
                    "table": "`employees`",
                    "pushed_index_condition": "(`employees`.`name` > 'wei')",
                    "table_condition_attached": null
                  }
                ] /* refine_plan */
              }
            ] /* steps */
          } /* join_optimization */
        },
        {
          "join_execution": {  -- 第三阶段：SQL执行阶段
            "select#": 1,
            "steps": [
              {
                "filesort_information": [
                  {
                    "direction": "asc",
                    "table": "`employees`",
                    "field": "position"
                  }
                ] /* filesort_information */,
                "filesort_priority_queue_optimization": {
                  "usable": false,
                  "cause": "not applicable (no LIMIT)"
                } /* filesort_priority_queue_optimization */,
                "filesort_execution": [
                ] /* filesort_execution */,
                "filesort_summary": {
                  "rows": 1,
                  "examined_rows": 1,
                  "number_of_tmp_files": 0,
                  "sort_buffer_size": 262056,
                  "sort_mode": "<sort_key, packed_additional_fields>"
                } /* filesort_summary */
              }
            ] /* steps */
          } /* join_execution */
        }
      ] /* steps */
    } |                                 0 |                       0 |

可以看到预估表的访问成本计算过程中，MySQL 会计算全表扫描和可以使用的索引成本，比较各个可以使用的索引和全表扫描的查询成本，最终选择最优的一种方式去查询。例如这个例子中全表扫描成本为20306，使用 idx\_name\_age\_position 联合索引成本为2.21，所以最终 MySQL 选择使用 idx\_name\_age\_position 索引去执行查询。

当然 trace 工具主要看的是 MySQL 大致的优化和计算成本过程，那么 MySQL 是通过什么去计算出的这个成本呢？哈哈哈~~~

![1327cba274cb3bf8f56c83865c6b7ca7.png][]

感谢大家阅读，本人见识有限，写的博客难免有错误或者疏忽的地方，还望各位大佬指点，在此表示感激不尽。文章持续更新中…....

[3d85aba8fed34dfca9a33c05977c5501.png]: https://img-blog.csdnimg.cn/img_convert/3d85aba8fed34dfca9a33c05977c5501.png
[1327cba274cb3bf8f56c83865c6b7ca7.png]: https://img-blog.csdnimg.cn/img_convert/1327cba274cb3bf8f56c83865c6b7ca7.png