MySql中執行計劃如何來的——Optimizer Trace
2023-04-26 15:00:54
作者：京東物流 籍磊
1.前言
當談到MySQL的執行計劃時，會有很多同學想：「我就覺得使用其他的執行方案比EXPLAIN語句輸出的方案強，憑什麼優化器做的決定與我得不一樣？」。這個問題在MySQL 5.6之前或許自己很難解決，但是現在MySQL5.6及更高的版本中引入了Optimizer Trace。
2.optimizer_trace開啟方式及表結構
當下面這行程式碼執行的時候會將會使使用者能夠方便地檢視優化器生成執行計劃的整個過程。
SET SESSION optimizer_trace=」enabled=on」;
optimizer_trace的開關預設是關閉的，我們可以使用下行程式碼檢視optimizer_trace狀態。
SHOW variables LIKE'optimizer_trace';
其中one_line值是用來控制輸出格式的，如果值為on，那所有的資訊會在同一行中展示（這樣並不便於我們閱讀），預設為off。當我們的optimizer_trace的enabled為on時，輸入想要檢視優化過程的查詢語句，在該語句執行完之後，就可以到information_schema資料庫下的optimizer_trace表中檢視詳細的執行計劃生成過程，當然也可以直接對想要的查詢語句使用EXPLAIN。
optimizer_trace表有四列，每列註釋我補充在下方create語句中：
CREATE TEMPORARY TABLE `OPTIMIZER_TRACE` (
`QUERY` longtext NOT NULL COMMENT '我們輸入的查詢語句',
`TRACE` longtext NOT NULL COMMENT '優化過程的json文字',
`MISSING_BYTES_BEYOND_MAX_MEM_SIZE` int(20) NOT NULL DEFAULT '0' COMMENT '執行計劃生成
的過程中產生的超出字數限制的文字數',
`INSUFFICIENT_PRIVILEGES` tinyint(1) NOT NULL DEFAULT '0' COMMENT '是否有許可權檢視執行
計劃的生成過程，0有許可權，1無許可權'
) ENGINE=InnoDB DEFAULT CHARSET=utf8
3.optimizer_trace實踐
我們現在根據一個例子來看看optimizer_trace的實踐。
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的執行計劃如下：
OPTIMIZER_TRACE表中的資訊，這裡可以注意到MISSING_BYTES_BEYOND_MAX_MEM_SIZE的值為1023，說明TRACE中並沒有顯示出全部的優化過程：
Query列中的文字是我們執行的Sql語句：
/* 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列是優化的具體過程，其中分析過程需要注意的點在下面程式碼框中使用#註釋的形式給出：
{
"steps": [
{
"join_preparation": { #prepare階段
"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階段
"select#": 1,
"steps": [
{
"condition_processing": {#處理搜尋條件
"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",#處理等值轉換
"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",#常數傳遞轉換
"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",#去除沒用的條件
"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": {#去除虛擬生成的列
}
},
{
"table_dependencies": [#表的依賴資訊
{
"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型別的索引
{
"table": "`ship_data`.`check_table`",
"field": "outbound_no",
"equals": "'ESL48400163536608'",
"null_rejecting": false
}
]
},
{
"rows_estimation": [#預估不同單表存取方法的存取成本
{
"table": "`ship_data`.`check_table`",
"range_analysis": {
"table_scan": {#全表掃描的行數及成本
"rows": 79745,
"cost": 19127
},
"potential_range_indexes": [#分析可能使用的索引，此處就是執行計劃中的possiable_keys
{
"index": "PRIMARY",#主鍵不可用
"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,#使用該索引獲取的記錄是否按照主鍵排序
"using_mrr": false,#是否使用mrr
"index_only": false,#是否是覆蓋索引
"rows": 1,#使用該索引獲取的記錄條數
"cost": 2.21,#使用該索引花費的成本
"chosen": true#是否選擇該索引
"cause": "cost"#該欄位為作者新增，當有索引未被使用時會標記未被使用的原因，cost為成本不合理未被選用
}
],
"analyzing_roworder_intersect": {#分析使用索引合併的成本
"usable": false,
"cause": "too_few_roworder_scans"
}
},
"chosen_range_access_summary": {#對於上述單表查詢check_table最優的方法
"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": [#分析各種可能的執行計劃
{
"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,#下面的資料來自官網範例，作者範例中超出長度的文字無法獲取到
"rows_for_plan": 0.05,
"cost_for_plan": 8.55,
"chosen": true
}
] /* rest_of_plan */
}
] /* considered_execution_plans */
},
{
"attaching_conditions_to_tables": {#嘗試給查詢新增一些其他的查詢條件
"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": [#再稍加改進執行計劃
{
"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階段
"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.總結
上述內容大致分為三個階段：prepare階段、optimize階段、execute階段，MySQL中基於成本的優化主要在optimize階段，在單表查詢時會主要關注optimize階段的rows_estimation過程，這個rows_estimation過程分析了多種執行方案的成本耗費，在多表連線查詢的時候，我們更多關注considered_execution_plans過程，不過總而言之查詢優化器最終會選擇成本最低的方案來作為最終的執行計劃，即我們使用EXPLAIN語句時顯示出的方案。