跟踪MYSQL 的查询优化过程方法

 http://dev.mysql.com/doc/internals/en/tracing-example.html

http://blog.chinaunix.net/uid-20785090-id-5597524.html

handle_select()
   mysql_select()
     JOIN::prepare()
       setup_fields()
     JOIN::optimize()            /* optimizer is from here ... */
       optimize_cond()
       opt_sum_query()
       make_join_statistics()
         get_quick_record_count()
         choose_plan()
           /* Find the best way to access tables */
           /* as specified by the user.          */
           optimize_straight_join()
             best_access_path()
           /* Find a (sub-)optimal plan among all or subset */
           /* of all possible query plans where the user    */
           /* controls the exhaustiveness of the search.   */
           greedy_search()
             best_extension_by_limited_search()
               best_access_path()
           /* Perform an exhaustive search for an optimal plan */
           find_best()
       make_join_select()        /* ... to here */
     JOIN::exec()

 

CREATE TABLE `t` (
`a` int(11) NOT NULL,
`b` int(11) DEFAULT NULL,
`c` int(11) NOT NULL,
PRIMARY KEY (`a`),
KEY `b` (`b`),
KEY `ix` (`b`,`c`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8 

json格式:

mysql> explain format=json  select b from t\G
*************************** 1. row **********************
EXPLAIN: {
  "query_block": {
    "select_id": 1,
    "cost_info": {
      "query_cost": "1.20"
    },
    "table": {
      "table_name": "t",
      "access_type": "index",
      "key": "b",
      "used_key_parts": [
        "b"
      ],
      "key_length": "5",
      "rows_examined_per_scan": 1,
      "rows_produced_per_join": 1,
      "filtered": "100.00",
      "using_index": true,
      "cost_info": {
        "read_cost": "1.00",
        "eval_cost": "0.20",
        "prefix_cost": "1.20",
        "data_read_per_join": "16"
      },
      "used_columns": [
        "b"
      ]
    }
  }
}
1 row in set, 1 warning (0.00 sec)

更加详细的过程生成:

1.set optimizer_trace_max_mem_size=300000;
2.set end_markers_in_json=true;
3.set optimizer_trace="enabled=on";

4.sql语句

5.select trace from information_schema.optimizer_trace\G;
6.set optimizer_trace="enabled=off";

主要分为三个部分 

join_preparation：SQL的准备阶段，sql被格式化

对应函数 JOIN::prepare

  

join_optimization：SQL优化阶段

对应函数JOIN::optimize

 

 join_execution：SQL执行阶段

对应函数：JOIN::exec

 

join_optimization是核心。
下面详细介绍join_optimization的过程：
1）condition_processing阶段，进行where条件处理，分别是相等处理，常量处理，删除冗余条件
2）ref_optimizer_key_uses阶段，查找可进行ref type访问的索引（索引的等值访问）。
3）records_estimation阶段，进行访问开销预估。这个阶段是最复杂的。先处理访问类型（explain select_type字段的值），候选项分别为全表扫描和所有的索引，开销最小的那个胜出。如果你的语句有Group By,那么在group_index_range子阶段确定是否有适用于range 访问的索引。
4）considered_execution_plans节显示了选定的执行计划
5）attaching_conditions_to_tables分析where条件是否可以执行pushdown，应该是再扫描该表时过滤掉。
6）clause_processing阶段分别处理group by, order by从句。

eg：

set optimizer_trace_max_mem_size=300000;
set end_markers_in_json=true;
set optimizer_trace="enabled=on";

mysql> select b from t;

mysql> select trace from  information_schema.optimizer_trace\G

*************************** 1. row ***************************
trace: {
  "steps": [
    {
      "join_preparation": {
        "select#": 1,
        "steps": [
          {
            "expanded_query": "/* select#1 */ select `t`.`b` AS `b` from `t`"
          }
        ]
      }
    },
    {
      "join_optimization": {
        "select#": 1,
        "steps": [
          {
            "table_dependencies": [
              {
                "table": "`t`",
                "row_may_be_null": false,
                "map_bit": 0,
                "depends_on_map_bits": [
                ]
              }
            ]
          },
          {
            "rows_estimation": [
              {
                "table": "`t`",
                "table_scan": {
                  "rows": 1,
                  "cost": 1
                }
              }
            ]
          },
          {
            "considered_execution_plans": [
              {
                "plan_prefix": [
                ],
                "table": "`t`",
                "best_access_path": {
                  "considered_access_paths": [
                    {
                      "rows_to_scan": 1,
                      "access_type": "scan",
                      "resulting_rows": 1,
                      "cost": 1.2,
                      "chosen": true
                    }
                  ]
                },
                "condition_filtering_pct": 100,
                "rows_for_plan": 1,
                "cost_for_plan": 1.2,
                "chosen": true
              }
            ]
          },
          {
            "attaching_conditions_to_tables": {
              "original_condition": null,
              "attached_conditions_computation": [
              ],
              "attached_conditions_summary": [
                {
                  "table": "`t`",
                  "attached": null
                }
              ]
            }
          },
          {
            "refine_plan": [
              {
                "table": "`t`"
              }
            ]
          }
        ]
      }
    },
    {
      "join_explain": {
        "select#": 1,
        "steps": [
        ]
      }
    }
  ]
}
1 row in set (0.00 sec)

set optimizer_trace="enabled=off";

 

select trace into dumpfile "json.txt" from information_schema.optimizer_trace;