MySql中执行计划如何来的——Optimizer Trace | 京东云技术团队

作者：京东物流 籍磊

1.前言

当谈到MySQL的执行计划时，会有很多同学想：“我就觉得使用其他的执行方案比EXPLAIN语句输出的方案强，凭什么优化器做的决定与我得不一样？”。这个问题在MySQL 5.6之前或许自己很难解决，但是现在MySQL5.6及更高的版本中引入了Optimizer Trace。

2.optimizer_trace开启方式及表结构

当下面这行代码执行的时候会将会使用户能够方便地查看优化器生成执行计划的整个过程。

SET SESSION optimizer_trace=”enabled=on”;

optimizer_trace的开关默认是关闭的，我们可以使用下行代码查看optimizer_trace状态。

SHOW variables LIKE'optimizer_trace';

其中one_line值是用来控制输出格式的，如果值为on，那所有的信息会在同一行中展示（这样并不便于我们阅读），默认为off。当我们的optimizer_trace的enabled为on时，输入想要查看优化过程的查询语句，在该语句执行完之后，就可以到information_schema数据库下的optimizer_trace表中查看详细的执行计划生成过程，当然也可以直接对想要的查询语句使用EXPLAIN。

optimizer_trace表有四列，每列注释我补充在下方create语句中：

CREATE TEMPORARY TABLE `OPTIMIZER_TRACE` (
  `QUERY` longtext NOT NULL COMMENT '我们输入的查询语句',
  `TRACE` longtext NOT NULL COMMENT '优化过程的json文本',
  `MISSING_BYTES_BEYOND_MAX_MEM_SIZE` int(20) NOT NULL DEFAULT '0' COMMENT '执行计划生成
的过程中产生的超出字数限制的文本数',
  `INSUFFICIENT_PRIVILEGES` tinyint(1) NOT NULL DEFAULT '0' COMMENT '是否有权限查看执行
计划的生成过程，0有权限，1无权限'
) ENGINE=InnoDB DEFAULT CHARSET=utf8

3.optimizer_trace实践

我们现在根据一个例子来看看optimizer_trace的实践。

explain select * from ship_data.check_table 
where 
outbound_no ='ESL48400163536608' and 
yn=0 and 
update_user ='jilei18';
SELECT * FROM information_schema.OPTIMIZER_TRACE;

上述sql的执行计划如下：

OPTIMIZER_TRACE表中的信息，这里可以注意到MISSING_BYTES_BEYOND_MAX_MEM_SIZE的值为1023，说明TRACE中并没有显示出全部的优化过程：

Query列中的文本是我们执行的Sql语句：

/* ApplicationName=DBeaver 21.1.3 - SQLEditor <Script-2.sql> */ explain select * from ship_data.check_table 
where 
outbound_no ='ESL48400163536608' and 
yn=0 and 
update_user ='jilei18'

TRACE列是优化的具体过程，其中分析过程需要注意的点在下面代码框中使用#注释的形式给出：

{
  "steps": [
    {
      "join_preparation": { #prepare阶段
        "select#": 1,
        "steps": [
          {
            "expanded_query": "/* select#1 */ select `ship_data`.`check_table`.`m_id` AS `m_id`,`ship_data`.`check_table`.`wave_no` AS `wave_no`,`ship_data`.`check_table`.`wave_type` AS `wave_type`,`ship_data`.`check_table`.`outbound_no` AS `outbound_no`,`ship_data`.`check_table`.`outbound_type` AS `outbound_type`,`ship_data`.`check_table`.`check_type` AS `check_type`,`ship_data`.`check_table`.`production_mode` AS `production_mode`,`ship_data`.`check_table`.`sku_qty` AS `sku_qty`,`ship_data`.`check_table`.`total_qty` AS `total_qty`,`ship_data`.`check_table`.`uncheck_qty` AS `uncheck_qty`,`ship_data`.`check_table`.`container_no` AS `container_no`,`ship_data`.`check_table`.`production_wave_no` AS `production_wave_no`,`ship_data`.`check_table`.`carriage_no` AS `carriage_no`,`ship_data`.`check_table`.`realcarriage_no` AS `realcarriage_no`,`ship_data`.`check_table`.`case_no` AS `case_no`,`ship_data`.`check_table`.`rebinwall_no` AS `rebinwall_no`,`ship_data`.`check_table`.`locate_sum_qty` AS `locate_sum_qty`,`ship_data`.`check_table`.`check_differ_qty_small` AS `check_differ_qty_small`,`ship_data`.`check_table`.`supplier_code` AS `supplier_code`,`ship_data`.`check_table`.`supplier_name` AS `supplier_name`,`ship_data`.`check_table`.`broke_type` AS `broke_type`,`ship_data`.`check_table`.`outbound_level` AS `outbound_level`,`ship_data`.`check_table`.`outbound_time` AS `outbound_time`,`ship_data`.`check_table`.`sort_entry` AS `sort_entry`,`ship_data`.`check_table`.`end_time` AS `end_time`,`ship_data`.`check_table`.`end_time_attr` AS `end_time_attr`,`ship_data`.`check_table`.`send_address` AS `send_address`,`ship_data`.`check_table`.`site_no` AS `site_no`,`ship_data`.`check_table`.`site_name` AS `site_name`,`ship_data`.`check_table`.`sort_slot_no` AS `sort_slot_no`,`ship_data`.`check_table`.`valueadd_flag` AS `valueadd_flag`,`ship_data`.`check_table`.`package_qty` AS `package_qty`,`ship_data`.`check_table`.`send_type` AS `send_type`,`ship_data`.`check_table`.`resource` AS `resource`,`ship_data`.`check_table`.`platform_no` AS `platform_no`,`ship_data`.`check_table`.`pack_table_no` AS `pack_table_no`,`ship_data`.`check_table`.`total_weight` AS `total_weight`,`ship_data`.`check_table`.`total_volume` AS `total_volume`,`ship_data`.`check_table`.`status` AS `status`,`ship_data`.`check_table`.`status_lock` AS `status_lock`,`ship_data`.`check_table`.`cancel_order_status` AS `cancel_order_status`,`ship_data`.`check_table`.`is_shortage` AS `is_shortage`,`ship_data`.`check_table`.`check_num` AS `check_num`,`ship_data`.`check_table`.`multiple_check` AS `multiple_check`,`ship_data`.`check_table`.`org_no` AS `org_no`,`ship_data`.`check_table`.`distribute_no` AS `distribute_no`,`ship_data`.`check_table`.`warehouse_no` AS `warehouse_no`,`ship_data`.`check_table`.`create_user` AS `create_user`,`ship_data`.`check_table`.`create_time` AS `create_time`,`ship_data`.`check_table`.`update_user` AS `update_user`,`ship_data`.`check_table`.`update_time` AS `update_time`,`ship_data`.`check_table`.`yn` AS `yn`,`ship_data`.`check_table`.`OWNER_NO` AS `OWNER_NO`,`ship_data`.`check_table`.`OWNER_NAME` AS `OWNER_NAME`,`ship_data`.`check_table`.`batch_no` AS `batch_no`,`ship_data`.`check_table`.`check_business_tag` AS `check_business_tag`,`ship_data`.`check_table`.`group_no` AS `group_no`,`ship_data`.`check_table`.`TRIAL_PRODUCT_FLAG` AS `TRIAL_PRODUCT_FLAG`,`ship_data`.`check_table`.`CHECK_MODE` AS `CHECK_MODE`,`ship_data`.`check_table`.`check_differ_qty_total` AS `check_differ_qty_total`,`ship_data`.`check_table`.`check_differ_qty_medium` AS `check_differ_qty_medium`,`ship_data`.`check_table`.`picking_finished` AS `picking_finished`,`ship_data`.`check_table`.`cell_no` AS `cell_no`,`ship_data`.`check_table`.`rebin_no` AS `rebin_no`,`ship_data`.`check_table`.`status_picking` AS `status_picking`,`ship_data`.`check_table`.`status_picking_small` AS `status_picking_small`,`ship_data`.`check_table`.`status_picking_medium` AS `status_picking_medium`,`ship_data`.`check_table`.`status_small` AS `status_small`,`ship_data`.`check_table`.`status_medium` AS `status_medium`,`ship_data`.`check_table`.`picking_time` AS `picking_time`,`ship_data`.`check_table`.`isv_outstore_no` AS `isv_outstore_no`,`ship_data`.`check_table`.`pick_type` AS `pick_type`,`ship_data`.`check_table`.`sf_ship_no` AS `sf_ship_no`,`ship_data`.`check_table`.`isCollectDeliveryInfo` AS `isCollectDeliveryInfo`,`ship_data`.`check_table`.`expect_package_qty` AS `expect_package_qty`,`ship_data`.`check_table`.`print_shopping_flag` AS `print_shopping_flag`,`ship_data`.`check_table`.`product_mode_flag` AS `product_mode_flag`,`ship_data`.`check_table`.`schedulebill_code` AS `schedulebill_code`,`ship_data`.`check_table`.`uppershelf_time` AS `uppershelf_time`,`ship_data`.`check_table`.`mixedorder_type` AS `mixedorder_type`,`ship_data`.`check_table`.`child_order_flag` AS `child_order_flag`,`ship_data`.`check_table`.`inbound_no` AS `inbound_no`,`ship_data`.`check_table`.`production_order_no` AS `production_order_no`,`ship_data`.`check_table`.`check_user` AS `check_user`,`ship_data`.`check_table`.`check_finish_time` AS `check_finish_time`,`ship_data`.`check_table`.`check_style` AS `check_style` from `ship_data`.`check_table` where ((`ship_data`.`check_table`.`outbound_no` = 'ESL48400163536608') and (`ship_data`.`check_table`.`yn` = 0) and (`ship_data`.`check_table`.`update_user` = 'jilei18'))"
          }
        ]
      }
    },
    {
      "join_optimization": { #optimize阶段
        "select#": 1,
        "steps": [
          {
            "condition_processing": {#处理搜索条件
              "condition": "WHERE",
              "original_condition": "((`ship_data`.`check_table`.`outbound_no` = 'ESL48400163536608') and (`ship_data`.`check_table`.`yn` = 0) and (`ship_data`.`check_table`.`update_user` = 'jilei18'))",
              "steps": [
                {
                  "transformation": "equality_propagation",#处理等值转换
                  "resulting_condition": "((`ship_data`.`check_table`.`outbound_no` = 'ESL48400163536608') and (`ship_data`.`check_table`.`update_user` = 'jilei18') and multiple equal(0, `ship_data`.`check_table`.`yn`))"
                },
                {
                  "transformation": "constant_propagation",#常量传递转换
                  "resulting_condition": "((`ship_data`.`check_table`.`outbound_no` = 'ESL48400163536608') and (`ship_data`.`check_table`.`update_user` = 'jilei18') and multiple equal(0, `ship_data`.`check_table`.`yn`))"
                },
                {
                  "transformation": "trivial_condition_removal",#去除没用的条件
                  "resulting_condition": "((`ship_data`.`check_table`.`outbound_no` = 'ESL48400163536608') and (`ship_data`.`check_table`.`update_user` = 'jilei18') and multiple equal(0, `ship_data`.`check_table`.`yn`))"
                }
              ]
            }
          },
          {
            "substitute_generated_columns": {#去除虚拟生成的列
            }
          },
          {
            "table_dependencies": [#表的依赖信息
              {
                "table": "`ship_data`.`check_table`",
                "row_may_be_null": false,
                "map_bit": 0,
                "depends_on_map_bits": [
                ]
              }
            ]
          },
          {
            "ref_optimizer_key_uses": [#列出所有可用的ref类型的索引
              {
                "table": "`ship_data`.`check_table`",
                "field": "outbound_no",
                "equals": "'ESL48400163536608'",
                "null_rejecting": false
              }
            ]
          },
          {
            "rows_estimation": [#预估不同单表访问方法的访问成本
              {
                "table": "`ship_data`.`check_table`",
                "range_analysis": {
                  "table_scan": {#全表扫描的行数及成本
                    "rows": 79745,
                    "cost": 19127
                  },
                  "potential_range_indexes": [#分析可能使用的索引，此处就是执行计划中的possiable_keys
                    {
                      "index": "PRIMARY",#主键不可用
                      "usable": false,
                      "cause": "not_applicable"
                    },
                    {
                      "index": "UK_batch_production",#UK_batch_production索引不可用
                      "usable": false,
                      "cause": "not_applicable"
                    },
                    {
                      "index": "idx_update_time",#idx_update_time索引不可用
                      "usable": false,
                      "cause": "not_applicable"
                    },
                    {
                      "index": "IDX_status",#IDX_status索引不可用
                      "usable": false,
                      "cause": "not_applicable"
                    },
                    {
                      "index": "idx_case_no",#idx_case_no索引不可用
                      "usable": false,
                      "cause": "not_applicable"
                    },
                    {
                      "index": "idx_outbound_time",#idx_outbound_time索引不可用
                      "usable": false,
                      "cause": "not_applicable"
                    },
                    {
                      "index": "idx_outboundno",#idx_outboundno索引可用
                      "usable": true,
                      "key_parts": [
                        "outbound_no",
                        "m_id"
                      ]
                    },
                    {
                      "index": "idx_wave_no",#idx_wave_no索引不可用
                      "usable": false,
                      "cause": "not_applicable"
                    },
                    {
                      "index": "idx_cancel_order_status",#idx_cancel_order_status索引不可用
                      "usable": false,
                      "cause": "not_applicable"
                    },
                    {
                      "index": "idx_production_wave_no",#idx_production_wave_no索引不可用
                      "usable": false,
                      "cause": "not_applicable"
                    },
                    {
                      "index": "idx_schedulebillcode_uppershelftime",#idx_schedulebillcode_uppershelftime索引不可用
                      "usable": false,
                      "cause": "not_applicable"
                    },
                    {
                      "index": "idx_production_orderno",#idx_production_orderno索引不可用
                      "usable": false,
                      "cause": "not_applicable"
                    },
                    {
                      "index": "idx_end_time_attr",#idx_end_time_attr索引不可用
                      "usable": false,
                      "cause": "not_applicable"
                    }
                  ],
                  "setup_range_conditions": [
                  ],
                  "group_index_range": {
                    "chosen": false,
                    "cause": "not_group_by_or_distinct"
                  },
                  "analyzing_range_alternatives": {#分析可能使用的索引的成本
                    "range_scan_alternatives": [
                      {
                        "index": "idx_outboundno",#使用idx_outboundno索引的成本
                        "ranges": [
                          "ESL48400163536608 <= outbound_no <= ESL48400163536608"
                        ],
                        "index_dives_for_eq_ranges": true,#是否使用index_dives
                        "rowid_ordered": true,#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,#是否是覆盖索引
                        "rows": 1,#使用该索引获取的记录条数
                        "cost": 2.21,#使用该索引花费的成本
                        "chosen": true#是否选择该索引
                        "cause": "cost"#该字段为作者添加，当有索引未被使用时会标记未被使用的原因，cost为成本不合理未被选用
                      }
                    ],
                    "analyzing_roworder_intersect": {#分析使用索引合并的成本
                      "usable": false,
                      "cause": "too_few_roworder_scans"
                    }
                  },
                  "chosen_range_access_summary": {#对于上述单表查询check_table最优的方法
                    "range_access_plan": {
                      "type": "range_scan",
                      "index": "idx_outboundno",
                      "rows": 1,
                      "ranges": [
                        "ESL48400163536608 <= outbound_no <= ESL48400163536608"
                      ]
                    },
                    "rows_for_plan": 1,
                    "cost_for_plan": 2.21,
                    "chosen": true
                  }
                }
              }
            ]
          },
          {
            "considered_execution_plans": [#分析各种可能的执行计划
              {
                "plan_prefix": [
                ],
                "table": "`ship_data`.`check_table`",
                "best_access_path": {
                  "considered_access_paths": [
                    {
                      "access_type": "ref",
                      "index": "idx_outboundno",
                      "rows": 1,
                      "cost": 1.2,
                      "chosen": true
                    },
                    {
                      "access_type": "range",
                      "range_details": {
                        "used_index": "idx_outboundno"
                      },
                      "chosen": false,
                      "cause": "heuristic_index_cheaper"
                    }
                  ]
                },
                "condition_filtering_pct": 5,#下面的数据来自官网示例，作者示例中超出长度的文本无法获取到
                "rows_for_plan": 0.05,
                                        "cost_for_plan": 8.55,
                                        "chosen": true
                                    }
                                ] /* rest_of_plan */
                            }
                        ] /* considered_execution_plans */
                    },
                    {
                        "attaching_conditions_to_tables": {#尝试给查询添加一些其他的查询条件
                            "original_condition": "((`alias2`.`pk` = `alias1`.`col_int_key`) and (0 <> `alias1`.`pk`))",
                            "attached_conditions_computation": [] /* attached_conditions_computation */,
                            "attached_conditions_summary": [
                                {
                                    "table": "`t1` `alias1`",
                                    "attached": "((0 <> `alias1`.`pk`) and (`alias1`.`col_int_key` is not null))"
                                },
                                {
                                    "table": "`t2` `alias2`",
                                    "attached": "(`alias2`.`pk` = `alias1`.`col_int_key`)"
                                }
                            ] /* attached_conditions_summary */
                        } /* attaching_conditions_to_tables */
                    },
                    {
                        "optimizing_distinct_group_by_order_by": {
                            "simplifying_order_by": {
                                "original_clause": "`alias1`.`col_int_key`,`alias2`.`pk`",
                                "items": [
                                    {
                                        "item": "`alias1`.`col_int_key`"
                                    },
                                    {
                                        "item": "`alias2`.`pk`",
                                        "eq_ref_to_preceding_items": true
                                    }
                                ] /* items */,
                                "resulting_clause_is_simple": true,
                                "resulting_clause": "`alias1`.`col_int_key`"
                            } /* simplifying_order_by */,
                            "simplifying_group_by": {
                                "original_clause": "`field2`",
                                "items": [
                                    {
                                        "item": "`alias2`.`pk`"
                                    }
                                ] /* items */,
                                "resulting_clause_is_simple": false,
                                "resulting_clause": "`field2`"
                            } /* simplifying_group_by */
                        } /* optimizing_distinct_group_by_order_by */
                    },
                    {
                        "finalizing_table_conditions": [
                            {
                                "table": "`t1` `alias1`",
                                "original_table_condition": "((0 <> `alias1`.`pk`) and (`alias1`.`col_int_key` is not null))",
                                "final_table_condition   ": "((0 <> `alias1`.`pk`) and (`alias1`.`col_int_key` is not null))"
                            },
                            {
                                "table": "`t2` `alias2`",
                                "original_table_condition": "(`alias2`.`pk` = `alias1`.`col_int_key`)",
                                "final_table_condition   ": null
                            }
                        ] /* finalizing_table_conditions */
                    },
                    {
                        "refine_plan": [#再稍加改进执行计划
                            {
                                "table": "`t1` `alias1`"
                            },
                            {
                                "table": "`t2` `alias2`"
                            }
                        ] /* refine_plan */
                    },
                    {
                        "considering_tmp_tables": [
                            {
                                "adding_tmp_table_in_plan_at_position": 2,
                                "write_method": "continuously_update_group_row"
                            },
                            {
                                "adding_sort_to_table": ""
                            } /* filesort */
                        ] /* considering_tmp_tables */
                    }
                ] /* steps */
            } /* join_optimization */
        },
        {
            "join_execution": {#execute阶段
                "select#": 1,
                "steps": [
                    {
                        "temp_table_aggregate": {
                            "select#": 1,
                            "steps": [
                                {
                                    "creating_tmp_table": {
                                        "tmp_table_info": {
                                            "in_plan_at_position": 2,
                                            "columns": 3,
                                            "row_length": 18,
                                            "key_length": 4,
                                            "unique_constraint": false,
                                            "makes_grouped_rows": true,
                                            "cannot_insert_duplicates": false,
                                            "location": "TempTable"
                                        } /* tmp_table_info */
                                    } /* creating_tmp_table */
                                }
                            ] /* steps */
                        } /* temp_table_aggregate */
                    },
                    {
                        "sorting_table": "<temporary>",
                        "filesort_information": [
                            {
                                "direction": "asc",
                                "expression": "`alias1`.`col_int_key`"
                            }
                        ] /* filesort_information */,
                        "filesort_priority_queue_optimization": {
                            "usable": false,
                            "cause": "not applicable (no LIMIT)"
                        } /* filesort_priority_queue_optimization */,
                        "filesort_execution": [] /* filesort_execution */,
                        "filesort_summary": {
                            "memory_available": 262144,
                            "key_size": 9,
                            "row_size": 26,
                            "max_rows_per_buffer": 7710,
                            "num_rows_estimate": 18446744073709551615,
                            "num_rows_found": 8,
                            "num_initial_chunks_spilled_to_disk": 0,
                            "peak_memory_used": 32840,
                            "sort_algorithm": "std::sort",
                            "unpacked_addon_fields": "skip_heuristic",
                            "sort_mode": "<fixed_sort_key, additional_fields>"
                        } /* filesort_summary */
                    }
                ] /* steps */
            } /* join_execution */
        }
    ] /* steps */
}

4.总结

上述内容大致分为三个阶段：prepare阶段、optimize阶段、execute阶段，MySQL中基于成本的优化主要在optimize阶段，在单表查询时会主要关注optimize阶段的rows_estimation过程，这个rows_estimation过程分析了多种执行方案的成本耗费，在多表连接查询的时候，我们更多关注considered_execution_plans过程，不过总而言之查询优化器最终会选择成本最低的方案来作为最终的执行计划，即我们使用EXPLAIN语句时显示出的方案。文章来源地址https://www.toymoban.com/news/detail-429431.html

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