# MySQL再深入执行计划之trace工具

作者:IT王小二

博客:https://itwxe.com (opens new window)

不知不觉过年半个多月没更新啦,不得不说老家真冷啊,完全不想伸出小二滴爪子,回到深圳开始更新啦,还是深圳暖和!

上一篇 Explain执行计划详解 (opens new window) 中提到执行计划分析查询语句时 possible_keys 列中存在可以使用的索引,但是实际最后 key 列中却并没有使用索引,走的全表扫描,这是为啥捏?

这就涉及小二说的 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;

explain_two_sql

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。

-- 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;

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?小二先在这里挖个坑吧,看下啥时候填上,哈哈哈~~~