关于mysql:MySql中执行计划如何来的Optimizer-Trace-京东云技术团队

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作者：京东物流籍磊

当谈到 MySQL 的执行打算时，会有很多同学想：“我就感觉应用其余的执行计划比 EXPLAIN 语句输入的计划强，凭什么优化器做的决定与我得不一样？”。这个问题在 MySQL 5.6 之前或者本人很难解决，然而当初 MySQL5.6 及更高的版本中引入了 Optimizer Trace。

当上面这行代码执行的时候会将会使用户可能不便地查看优化器生成执行打算的整个过程。

SET SESSION optimizer_trace=”enabled=on”;

optimizer\_trace 的开关默认是敞开的，咱们能够应用上行代码查看 optimizer\_trace 状态。

SHOW variables LIKE'optimizer_trace';

其中 one\_line 值是用来管制输入格局的，如果值为 on，那所有的信息会在同一行中展现（这样并不便于咱们浏览），默认为 off。当咱们的 optimizer\_trace 的 enabled 为 on 时，输出想要查看优化过程的查问语句，在该语句执行完之后，就能够到 information\_schema 数据库下的 optimizer\_trace 表中查看具体的执行打算生成过程，当然也能够间接对想要的查问语句应用 EXPLAIN。

optimizer_trace 表有四列，每列正文我补充在下方 create 语句中：

CREATE TEMPORARY TABLE `OPTIMIZER_TRACE` (
  `QUERY` longtext NOT NULL COMMENT '咱们输出的查问语句',
  `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 ' 执行打算生成
的过程中产生的超出字数限度的文本数 ',
  `INSUFFICIENT_PRIVILEGES` tinyint(1) NOT NULL DEFAULT '0' COMMENT ' 是否有权限查看执行
打算的生成过程，0 有权限，1 无权限 '
) ENGINE=InnoDB DEFAULT CHARSET=utf8

咱们当初依据一个例子来看看 optimizer_trace 的实际。

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 的执行打算如下：

OPTIMIZER\_TRACE 表中的信息，这里能够留神到 MISSING\_BYTES\_BEYOND\_MAX\_MEM\_SIZE 的值为 1023，阐明 TRACE 中并没有显示出全副的优化过程：

Query 列中的文本是咱们执行的 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，其中剖析过程须要留神的点在上面代码框中应用 #正文的模式给出：

{
  "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": {# 解决搜寻条件
              "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",# 解决等值转换
                  "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": {# 去除虚构生成的列}
          },
          {
            "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": [# 预估不同单表拜访办法的拜访老本
              {
                "table": "`ship_data`.`check_table`",
                "range_analysis": {
                  "table_scan": {# 全表扫描的行数及老本
                    "rows": 79745,
                    "cost": 19127
                  },
                  "potential_range_indexes": [# 剖析可能应用的索引，此处就是执行打算中的 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": {# 剖析可能应用的索引的老本
                    "range_scan_alternatives": [
                      {
                        "index": "idx_outboundno",# 应用 idx_outboundno 索引的老本
                        "ranges": ["ESL48400163536608 <= outbound_no <= ESL48400163536608"],
                        "index_dives_for_eq_ranges": true,# 是否应用 index_dives
                        "rowid_ordered": true,# 应用该索引获取的记录是否依照主键排序
                        "using_mrr": false,# 是否应用 mrr
                        "index_only": false,# 是否是笼罩索引
                        "rows": 1,# 应用该索引获取的记录条数
                        "cost": 2.21,# 应用该索引破费的老本
                        "chosen": true# 是否抉择该索引
                        "cause": "cost"# 该字段为作者增加，当有索引未被应用时会标记未被应用的起因，cost 为老本不合理未被选用
                      }
                    ],
                    "analyzing_roworder_intersect": {# 剖析应用索引合并的老本
                      "usable": false,
                      "cause": "too_few_roworder_scans"
                    }
                  },
                  "chosen_range_access_summary": {# 对于上述单表查问 check_table 最优的办法
                    "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": [# 剖析各种可能的执行打算
              {"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,# 上面的数据来自官网示例，作者示例中超出长度的文本无奈获取到
                "rows_for_plan": 0.05,
                                        "cost_for_plan": 8.55,
                                        "chosen": true
                                    }
                                ] /* rest_of_plan */
                            }
                        ] /* considered_execution_plans */
                    },
                    {
                        "attaching_conditions_to_tables": {# 尝试给查问增加一些其余的查问条件
                            "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": [# 再稍加改良执行打算
                            {"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 */
}

上述内容大抵分为三个阶段：prepare 阶段、optimize 阶段、execute 阶段，MySQL 中基于老本的优化次要在 optimize 阶段，在单表查问时会次要关注 optimize 阶段的 rows_estimation 过程，这个 rows_estimation 过程剖析了多种执行计划的老本消耗，在多表连贯查问的时候，咱们更多关注 considered\_execution\_plans 过程，不过总而言之查问优化器最终会抉择老本最低的计划来作为最终的执行打算，即咱们应用 EXPLAIN 语句时显示出的计划。

正文完