并發(fā)丟數(shù)據深度剖析：MySQL鎖機制與事務實戰(zhàn)踩坑及解決方案
1、理論來源于實踐
現(xiàn)象：于2025-08-13 21:45:35，事實邏輯表將自身的指標與維度同步到原子服務的實現(xiàn)時，出現(xiàn)同步過來的指標與維度丟失。
核心原因：兩次重復的事實邏輯表同步時間非常相近，導致同步過來的指標與維度丟失。
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2、倒帶進事故現(xiàn)場
邏輯表向原子服務同步的核心邏輯是 “先刪后增”：刪除舊數(shù)據→對比新老數(shù)據→插入新增數(shù)據，具體流程如下：
整體業(yè)務代碼精簡邏輯如下：
@Transactional(rollbackFor = Exception.class) public Map driveToAtomService(Map logicTableData, String erp) { //獲得環(huán)境信息 String env = driveLogicTable.getString(DRIVE_LOGIC_TABLE_ENV); //獲取/更新實現(xiàn)id Long logicTableId = getOrAddLogicTableId(atomicServiceId, driveLogicTable, erp, EnvType.of(env)); //刪除關聯(lián)指標 metricImplMapper.deleteByLogicTableIds(Collections.singletonList(logicId)); //獲取請求中的所有的指標信息 List metricList = getMetricImpls(logicTableData, logicTableId); //獲取需要新增的指標實現(xiàn)(包含了查詢庫里現(xiàn)有的指標實現(xiàn)) List metricImpls = metricImplMapper.getMetricImpls(logicTableId); Set metricDefIdSet = metricImpls.stream() .map(MetricImplRelBO::getMetricDefId).collect(Collectors.toSet()); List addList = metricList.stream() .filter(s -> !metricDefIdSet.contains(s.getMetricDefId())).collect(Collectors.toList()); //將需要新增的指標實現(xiàn)插入數(shù)據庫 addMetricImpl(addList); }
用一個請求進行舉例：
{"header":{"appKey":null,"uuid":"ce7cef2d-c417-464a-a519-311599fddfca","serviceName":"driveToAtomService","context":{"PIN":"wanyue3"}},"body":{"dimList":[{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":72,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":2501,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":2484,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":2502,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":4591,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":3822,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":4523,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":4524,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":76,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":1767,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":1907,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":1598,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":4620,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":4621,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":4622,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":2504,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":2485,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":2486,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":2487,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":2488,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":3077,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":3080,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":3081,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":2483,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":2482,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":3082,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":3083,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":4851,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":2503,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":5070,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":5044,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":5087,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":5144,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":5145,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":3089,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":3680,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":2223,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":5428,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":5101,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":1315,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":5247,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":3318,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":5262,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":4646,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":2252,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":2254,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":2959,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":2958,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":2728,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":2618,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":5061,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":6032,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":6375,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":6388,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":6389,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":1316,"type":"ALL"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":1081,"type":"FILTER"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":1351,"type":"FILTER"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":1082,"type":"FILTER"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":1499,"type":"COMBINE"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":1596,"type":"FILTER"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":1606,"type":"FILTER"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":1083,"type":"FILTER"},{"isRequiredForFilter":0,"supportCrossTopic":0,"dimDefId":1108,"type":"FILTER"}],"dimCombineList":[],"metricList":[{"lightDecorateIdList":"","aggregationType":"toSql","middleAggregationType":"DEFAULT","extendDecorateIdList":"4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867","staticDecorateIdListCombination":"","metricDefId":19872,"nameEnAtomic":null,"extendFunctionIdList":"25,6,5,7,23,22,20,21,19,18,4,1,2,3,24"},{"lightDecorateIdList":"","aggregationType":"toSql","middleAggregationType":"DEFAULT","extendDecorateIdList":"4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867","staticDecorateIdListCombination":"","metricDefId":19873,"nameEnAtomic":null,"extendFunctionIdList":"25,6,5,7,23,22,20,21,19,18,4,1,2,3,24"},{"lightDecorateIdList":"","aggregationType":"toSql","middleAggregationType":"DEFAULT","extendDecorateIdList":"4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867","staticDecorateIdListCombination":"","metricDefId":19875,"nameEnAtomic":null,"extendFunctionIdList":"25,6,5,7,23,22,20,21,19,18,4,1,2,3,24"},{"lightDecorateIdList":"","aggregationType":"toSql","middleAggregationType":"DEFAULT","extendDecorateIdList":"4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867","staticDecorateIdListCombination":"","metricDefId":19945,"nameEnAtomic":null,"extendFunctionIdList":"25,6,5,7,23,22,20,21,19,18,4,1,2,3,24"},{"lightDecorateIdList":"","aggregationType":"toSql","middleAggregationType":"DEFAULT","extendDecorateIdList":"4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867","staticDecorateIdListCombination":"","metricDefId":17263,"nameEnAtomic":null,"extendFunctionIdList":"25,6,5,7,23,22,20,21,19,18,4,1,2,3,24"},{"lightDecorateIdList":"","aggregationType":"COUNT_DISTINCT","middleAggregationType":"DEFAULT","extendDecorateIdList":"4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867","staticDecorateIdListCombination":"","metricDefId":28017,"nameEnAtomic":null,"extendFunctionIdList":"25,6,5,7,23,22,20,21,19,18,4,1,2,3,24"},{"lightDecorateIdList":"","aggregationType":"toSql","middleAggregationType":"DEFAULT","extendDecorateIdList":"4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867","staticDecorateIdListCombination":"","metricDefId":20242,"nameEnAtomic":null,"extendFunctionIdList":"25,6,5,7,23,22,20,21,19,18,4,1,2,3,24"},{"lightDecorateIdList":"","aggregationType":"toSql","middleAggregationType":"DEFAULT","extendDecorateIdList":"4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867","staticDecorateIdListCombination":"","metricDefId":18450,"nameEnAtomic":null,"extendFunctionIdList":"25,6,5,7,23,22,20,21,19,18,4,1,2,3,24"},{"lightDecorateIdList":"","aggregationType":"toSql","middleAggregationType":"DEFAULT","extendDecorateIdList":"4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867","staticDecorateIdListCombination":"","metricDefId":20276,"nameEnAtomic":null,"extendFunctionIdList":"25,6,5,7,23,22,20,21,19,18,4,1,2,3,24"},{"lightDecorateIdList":"","aggregationType":"toSql","middleAggregationType":"DEFAULT","extendDecorateIdList":"4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867","staticDecorateIdListCombination":"","metricDefId":18452,"nameEnAtomic":null,"extendFunctionIdList":"25,6,5,7,23,22,20,21,19,18,4,1,2,3,24"},{"lightDecorateIdList":"","aggregationType":"toSql","middleAggregationType":"DEFAULT","extendDecorateIdList":"4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867","staticDecorateIdListCombination":"","metricDefId":18453,"nameEnAtomic":null,"extendFunctionIdList":"25,6,5,7,23,22,20,21,19,18,4,1,2,3,24"},{"lightDecorateIdList":"","aggregationType":"toSql","middleAggregationType":"DEFAULT","extendDecorateIdList":"4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867","staticDecorateIdListCombination":"","metricDefId":18456,"nameEnAtomic":null,"extendFunctionIdList":"25,6,5,7,23,22,20,21,19,18,4,1,2,3,24"},{"lightDecorateIdList":"","aggregationType":"toSql","middleAggregationType":"DEFAULT","extendDecorateIdList":"4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867","staticDecorateIdListCombination":"","metricDefId":19866,"nameEnAtomic":null,"extendFunctionIdList":"25,6,5,7,23,22,20,21,19,18,4,1,2,3,24"},{"lightDecorateIdList":"","aggregationType":"toSql","middleAggregationType":"DEFAULT","extendDecorateIdList":"4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867","staticDecorateIdListCombination":"","metricDefId":21691,"nameEnAtomic":null,"extendFunctionIdList":"25,6,5,7,23,22,20,21,19,18,4,1,2,3,24"},{"lightDecorateIdList":"","aggregationType":"toSql","middleAggregationType":"DEFAULT","extendDecorateIdList":"4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867","staticDecorateIdListCombination":"","metricDefId":19871,"nameEnAtomic":null,"extendFunctionIdList":"25,6,5,7,23,22,20,21,19,18,4,1,2,3,24"}],"driveLogicTable":"{"dimensionType":"DETAIL","oldNameCn":"七鮮實時交易_for地推中間態(tài)新老標志","atomicAliasProd":"prod","implServiceTypeKey":"realtime","originPhysicDataSourceId":0,"nameCn":"七鮮實時交易_for地推中間態(tài)新老標志","description":"七鮮實時交易_for地推中間態(tài)新老標志","driveLogicTableId":9881,"driveLogicTableEnv":"DEV","commonDecorateIdList":"9665,3269,3270,3271,4556,8012,8270,6030,7247,6031,7248,6032,7249,6033,7250,6034,6035,2134,7254,7255,2085,619,620,5997,1586,7867,6845","atomicAliasPre":"pre","committer":"panjingrong","physicDataSourceId":9494,"storageType":"ONLINE","atomicAliasDev":"pre"}","atomicServiceId":1088},"pin":"wanyue3"}
共計15個指標，64個維度
| 請求1(事務) | 請求2(事務) |
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| 21:06:17.262 | 進入同步方法 | 21:06:17.263 | 進入同步方法 |
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| 21:06:17.063 | select unify_metric_impl where logic_id = 3245 查詢出15條數(shù)據(快照讀，readview1) | 21:06:17.363 | select unify_metric_impl where logic_id = 3245 查詢出15條數(shù)據(快照讀，readview2) |
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| 21:06:17.363 | delete from unify_metric_impl where logic_id = 3245 | 21:06:17.372 | delete from unify_metric_impl where logic_id = 3245 |
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| 21:06:17.459 | select unify_metric_impl where logic_id = 3245 查詢出0條數(shù)據 |
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delete 由于logic_id不是索引，會表鎖阻塞 |
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| 21:06:18.459 | insert into unify_metric_impl 插入的logic_id = 3245的數(shù)據，15條 |
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| 21:06:19.408 | 方法結束 |
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21:06:19.529 | 刪除成功 |
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21:06:20.362 | select unify_metric_impl where logic_id = 3245 得到 15條數(shù)據 |
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21:06:20.435 | 讀出15條數(shù)據，比較本次是否有新增指標， 得出沒有新增指標，因此不進行新增。addAtomicMetricNameForDrive addList empty |
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21:06:21.435 | 方法結束 |
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核心結論點：
1.請求2的刪除操作被阻塞了，直到請求1執(zhí)行完整個方法。
2.請求2中去查看當前實現(xiàn)的指標的時候，發(fā)現(xiàn)庫里已經存在所有指標不會進行新增，與上一步刪除的邏輯相悖。
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3、結論點深度剖析
3.1 分析結論一
請求2的刪除操作被阻塞了，直到請求1執(zhí)行完整個方法。
3.1.1 復習mysql的InnoDB鎖機制
3.1.1.1 不是“一把鎖”，而是 “鎖矩陣”
| 鎖粒度 | 共享鎖（S 鎖） （讀鎖，允許多讀） | 排他鎖（X 鎖） （寫鎖，獨占） | 意向鎖（表級，輔助判斷） |
| 表級 | 表 S 鎖（極少用，如LOCK TABLES ... READ） | 表 X 鎖（極少用，如LOCK TABLES ... WRITE） | 意向 S 鎖（IS）、意向 X 鎖（IX） |
| 行級 | 行 S 鎖（SELECT ... FOR SHARE） | 行 X 鎖（UPDATE/DELETE/INSERT默認加） | （行鎖無需意向鎖） |
| 間隙級 | 間隙 S 鎖（無，間隙只防插入） | 間隙 X 鎖（防其他事務插入相同間隙） | 無 |
| Next-Key | 無 | Next-Key 鎖（行鎖 + 間隙鎖，默認行鎖算法） | 無 |
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3.1.1.2 一張圖總結：InnoDB 鎖的 “決策邏輯”
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3.1.2 理論應用實踐
3.1.2.1 本次事故的物料：
mysql表：
CREATE TABLE `unify_metric_impl` ( `id` bigint(50) unsigned NOT NULL AUTO_INCREMENT COMMENT '自增ID', `metric_def_id` bigint(11) unsigned NOT NULL DEFAULT '0' COMMENT '指標定義id', `logic_table_id` bigint(11) unsigned NOT NULL DEFAULT '0' COMMENT '邏輯表id', `name_en_atomic` varchar(256) NOT NULL DEFAULT '' COMMENT '真實指標名', `committer` varchar(64) NOT NULL DEFAULT '' COMMENT '負責人', `create_time` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP COMMENT '開始時間', `update_time` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP COMMENT '修改時間', `metric_atomic_name_temp` varchar(32) NOT NULL DEFAULT '' COMMENT '原子指標id', `decorate_id_list_temp` varchar(32) NOT NULL DEFAULT '' COMMENT '修飾列表', `name_cn_alias_temp` varchar(32) NOT NULL DEFAULT '' COMMENT '中文別名', `metric_type_temp` varchar(32) NOT NULL DEFAULT '' COMMENT '指標類型：DERIVE 衍生指標，F(xiàn)ORMULA 復合指標', `description_temp` varchar(64) NOT NULL DEFAULT '' COMMENT '指標說明', `data_type_temp` varchar(16) NOT NULL DEFAULT '' COMMENT '數(shù)據類型：STRING，DOUBLE, LONG, INT', `data_accuracy_temp` tinyint(4) NOT NULL DEFAULT '2' COMMENT '數(shù)據精度-小數(shù)點后幾位', `security_level_temp` varchar(16) DEFAULT '-1' COMMENT '安全等級', `logic_table_id_excel_temp` varchar(16) DEFAULT '-1' COMMENT '模型excelId', `implement_type` varchar(32) NOT NULL DEFAULT '' COMMENT '指標實現(xiàn)類型：APP、ATOMIC 原子服務', `app_ori_metric_name_temp` varchar(16) DEFAULT '' COMMENT '所依賴的app層原始名字（適用于導數(shù)任務改變字段的情況）', `name_en_depend_atomic` varchar(256) NOT NULL DEFAULT '' COMMENT '指標依賴字段', `name_en_depend_app` varchar(16) DEFAULT '' COMMENT '所依賴的app層原始名字（適用于導數(shù)任務改變字段的情況）', `update_status` tinyint(4) NOT NULL DEFAULT '0' COMMENT '信息更新狀態(tài) 0-未完成更新，1-完成更新', `status` tinyint(4) NOT NULL DEFAULT '0' COMMENT '信息更新狀態(tài) 0-未完成更新，1-完成更新', `light_decorate_id_list` varchar(1024) NOT NULL DEFAULT '' COMMENT '點燈修飾id列表', `extend_decorate_id_list` varchar(1024) NOT NULL DEFAULT '' COMMENT '支持的動態(tài)修飾id列表', `extend_function_id_list` varchar(1024) NOT NULL DEFAULT '' COMMENT '支持的原子服務函數(shù)id列表', `aggregation_type` varchar(64) NOT NULL DEFAULT '' COMMENT '聚合類型:ORIGINAL 原值 COUNT 計數(shù) DISTINCT 指定字段去重 SUM 求和 AVG 均值 MIN 求最大值 MAX 求最小值 QUANTITLE 求分位數(shù)', `middle_aggregation_type` varchar(30) NOT NULL DEFAULT '' COMMENT '中間層類型,UNKNOWN:未知,AGG_BY_FIELD:按聚合字段分組后聚合,AGG_BY_DAY:按天去重后累加', `static_decorate_id_list_combination` varchar(1024) NOT NULL DEFAULT '' COMMENT '支持的固化修飾id列表組合,[[d1,d2],[d2]]', PRIMARY KEY (`id`), KEY `idx_metric_def_id` (`metric_def_id`,`logic_table_id`) ) ENGINE=InnoDB DEFAULT CHARSET=utf8 COMMENT='指標實現(xiàn)';
3.1.2.2 實踐分析
通過mysql的innoDB的鎖決策，可以得出
//刪除關聯(lián)指標 metricImplMapper.deleteByLogicTableIds(Collections.singletonList(logicId));
delete from unify_metric_impl where logic_table_id in (45631);
mysql的索引：KEY `idx_metric_def_id` (`metric_def_id`,`logic_table_id`)
刪除寫操作，不符合最左匹配原則，因此為表x鎖。
因此請求2的刪除操作需要等待請求1的事務釋放表鎖后才可繼續(xù)進行，符合當時場景。
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3.2 分析結論二
請求2中去查看當前實現(xiàn)的指標的時候，發(fā)現(xiàn)庫里已經存在所有指標不會進行新增，與上一步刪除的邏輯相悖。
3.2.1 復習Mysql的事務
3.2.1.1 ACID 不是 "四個獨立特性"，而是 "因果鏈"
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?一句話：ACID 的核心是一致性，其他三個特性都是為了實現(xiàn)它的手段。
?一致性（Consistency）：一致性確保事務將數(shù)據庫從一個一致的狀態(tài)轉變到另一個一致的狀態(tài)。即使在多個事務同時執(zhí)行的情況下，數(shù)據庫也能保持數(shù)據的一致性。
?原子性（Atomicity）：事務是 "不可分割的工作單元"（要么全成，要么全?。?，是一致性的前提（如果步驟能拆分，中間失敗就會破壞一致性）。
?隔離性（Isolation）：通過控制多事務并發(fā)規(guī)則，避免互相干擾，是一致性的保障（并發(fā)混亂會直接破壞一致性）。
?耐久性（Durability）：事務提交后結果永久保存，是一致性的最終落點（否則重啟后數(shù)據丟失，之前的一致性白搭）。
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3.2.1.2 隔離級別：不是 "越嚴越好"，而是 "成本與需求的平衡術"
InnoDB 的 4 種隔離級別，本質是用 "數(shù)據可見性" 換 "并發(fā)性能"的選擇：
| 隔離級別 | 解決的問題 | 無法解決的問題 | 性能消耗 | 典型場景 |
| 讀未提交（RU） | 無 | 臟讀、不可重復讀、幻讀 | 極低 | 實時監(jiān)控（允許臟數(shù)據） |
| 讀已提交（RC） | 臟讀 | 不可重復讀、幻讀 | 低 | 互聯(lián)網普通業(yè)務 |
| 可重復讀（RR，默認） | 臟讀、不可重復讀 | 幻讀（被 Next-Key 鎖解決） | 中 | 金融交易、庫存管理 |
| 串行化（Serializable） | 所有并發(fā)問題 | 無 | 極高 | 銀行對賬（無并發(fā)需求） |
?
3.2.1.3 MVCC：事務的 "平行宇宙" 機制（為什么讀寫不沖突？）
InnoDB 的多版本并發(fā)控制是 "無鎖讀" 的核心，它讓讀和寫像在平行宇宙中運行：
底層邏輯（用 "時間戳" 理解）：
?每個事務啟動時，會拿到一個全局遞增的事務 ID（trx_id）。
?每行數(shù)據隱藏 3 個字段：
?DB_TRX_ID：最后修改該行的事務 ID；
?DB_ROLL_PTR：指向 undo 日志的指針（存儲歷史版本）；
?DB_DELETED：標記是否刪除（邏輯刪除）。
讀操作的 "幻術"：
?快照讀（普通 SELECT）：只看 "事務 ID ≤ 自己 ID" 且 "未被刪除" 的版本，完全不加鎖。 例：事務 A（ID=100）查詢時，會忽略所有被 ID>100 的事務修改的數(shù)據。
包含 4 個核心字段：
?m_ids：生成 Read View 時，當前活躍的事務 ID 列表（未提交的事務）。
?min_trx_id：m_ids中最小的事務 ID。
?max_trx_id：下一個將要分配的事務 ID（非活躍事務 ID，僅用于判斷 “未來事務”）。
?creator_trx_id：生成該 Read View 的事務自身 ID。
可見性判斷規(guī)則（一條記錄是否對當前事務可見，取決于其 “最后修改事務 ID”，記為db_trx_id）：
1.若db_trx_id == creator_trx_id：可見（自己修改的自己可見）。
2.若db_trx_id < min_trx_id：可見（修改記錄的事務在當前快照生成前已提交）。
3.若db_trx_id >= max_trx_id：不可見（修改記錄的事務在當前快照生成后才啟動）。
4.若min_trx_id ≤ db_trx_id < max_trx_id：
?若db_trx_id在m_ids中：不可見（該事務仍活躍，未提交）。
?若db_trx_id不在m_ids中：可見（該事務已提交）。
5.當前讀（加鎖讀 / 寫操作）：讀取最新版本，并加鎖防止其他事務修改。
3.2.1.4 事務日志：InnoDB 的 "安全與性能" 平衡術
事務能既保證 durability 又不慢，全靠兩大日志：
1.redo log（重做日志）：
?作用：崩潰后恢復未寫入磁盤的數(shù)據（保證 durability）。
?反直覺：事務提交時，數(shù)據先寫 redo log（內存 + 磁盤），再異步刷到數(shù)據文件（這叫 WAL 技術）。
?為什么快？redo log 是順序寫（磁盤順序寫比隨機寫快 100 倍 +）。
2.undo log（回滾日志）：
?作用：保存數(shù)據修改前的版本，用于事務回滾（保證 atomicity）和 MVCC 快照讀。
?注意：undo log 會被 purge 線程定期清理（當沒有事務需要舊版本時）。
3.2.1.5 終極心法：事務設計的 "3 個凡是"
1.凡是不需要事務的操作，堅決不用（如日志插入可關閉自動提交，批量提交）。
2.凡是能在 RC 解決的，絕不升 RR（互聯(lián)網業(yè)務優(yōu)先選 RC，用業(yè)務邏輯防不可重復讀）。
3.凡是大事務，必拆分成 "讀 - 算 - 寫" 三步（讀階段不加鎖，算階段在應用層，寫階段用最短事務加鎖）。
記住：事務的本質不是 "約束"，而是 "工具"—— 能解決問題的最簡單事務，才是最好的事務。
?
3.2.2 理論應用實踐
3.2.2.1 本次事故的物料：
表的事務等級：
SELECT @@transaction_isolation;
?
需要刪除的指標實現(xiàn)(根據實現(xiàn)id):
delete from unify_metric_impl where logic_table_id in (45631);
需要插入的指標實現(xiàn)：
INSERT INTO `unify_metric_impl` (`id`, `metric_def_id`, `logic_table_id`, `name_en_atomic`, `committer`, `create_time`, `update_time`, `metric_atomic_name_temp`, `decorate_id_list_temp`, `name_cn_alias_temp`, `metric_type_temp`, `description_temp`, `data_type_temp`, `data_accuracy_temp`, `security_level_temp`, `logic_table_id_excel_temp`, `implement_type`, `app_ori_metric_name_temp`, `name_en_depend_atomic`, `name_en_depend_app`, `update_status`, `status`, `light_decorate_id_list`, `extend_decorate_id_list`, `extend_function_id_list`, `aggregation_type`, `middle_aggregation_type`, `static_decorate_id_list_combination`) VALUES (1358195, 19872, 45631, 'jdr_7fresh_trade_complete_ord_user_qtty_deal_7fresh', '', '2025-09-02 09:23:41', '2025-09-02 09:23:41', '', '', '', '', '', '', 2, '-1', '-1', '', '', '', '', 0, 0, '', '4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867', '25,6,5,7,23,22,20,21,19,18,4,1,2,3,24', 'toSql', 'DEFAULT', ''), (1358196, 19873, 45631, 'jdr_7fresh_trade_complete_ord_sku_dis_qtty_deal_7fresh', '', '2025-09-02 09:23:41', '2025-09-02 09:23:41', '', '', '', '', '', '', 2, '-1', '-1', '', '', '', '', 0, 0, '', '4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867', '25,6,5,7,23,22,20,21,19,18,4,1,2,3,24', 'toSql', 'DEFAULT', ''), (1358197, 19875, 45631, 'jdr_7fresh_trade_complete_ord_ord_dis_qtty_deal_7fresh', '', '2025-09-02 09:23:41', '2025-09-02 09:23:41', '', '', '', '', '', '', 2, '-1', '-1', '', '', '', '', 0, 0, '', '4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867', '25,6,5,7,23,22,20,21,19,18,4,1,2,3,24', 'toSql', 'DEFAULT', ''), (1358198, 19945, 45631, 'jdr_7fresh_sku_deal_ord_sku_dis_qtty_main_img_video_num', '', '2025-09-02 09:23:41', '2025-09-02 09:23:41', '', '', '', '', '', '', 2, '-1', '-1', '', '', '', '', 0, 0, '', '4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867', '25,6,5,7,23,22,20,21,19,18,4,1,2,3,24', 'toSql', 'DEFAULT', ''), (1358199, 17263, 45631, 'jdr_7fresh_trade_deal_ord_ord_dis_qtty_deal_7fresh', '', '2025-09-02 09:23:41', '2025-09-02 09:23:41', '', '', '', '', '', '', 2, '-1', '-1', '', '', '', '', 0, 0, '', '4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867', '25,6,5,7,23,22,20,21,19,18,4,1,2,3,24', 'toSql', 'DEFAULT', ''), (1358200, 28017, 45631, 'jdr_7fresh_bd_bd_attendance_offline__store_cnt_bd_attendance_cnt', '', '2025-09-02 09:23:41', '2025-09-02 09:23:41', '', '', '', '', '', '', 2, '-1', '-1', '', '', '', '', 0, 0, '', '4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867', '25,6,5,7,23,22,20,21,19,18,4,1,2,3,24', 'COUNT_DISTINCT', 'DEFAULT', ''), (1358201, 20242, 45631, 'jdr_7fresh_trade_deal_ord_app__ord_qtty_deal_7fresh', '', '2025-09-02 09:23:41', '2025-09-02 09:23:41', '', '', '', '', '', '', 2, '-1', '-1', '', '', '', '', 0, 0, '', '4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867', '25,6,5,7,23,22,20,21,19,18,4,1,2,3,24', 'toSql', 'DEFAULT', ''), (1358202, 18450, 45631, 'jdr_7fresh_trade_deal_ord_ord_amt_deal_7fresh', '', '2025-09-02 09:23:41', '2025-09-02 09:23:41', '', '', '', '', '', '', 2, '-1', '-1', '', '', '', '', 0, 0, '', '4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867', '25,6,5,7,23,22,20,21,19,18,4,1,2,3,24', 'toSql', 'DEFAULT', ''), (1358203, 20276, 45631, 'jdr_7fresh_trade_deal_ord_app__ord_cnt_deal_7fresh', '', '2025-09-02 09:23:41', '2025-09-02 09:23:41', '', '', '', '', '', '', 2, '-1', '-1', '', '', '', '', 0, 0, '', '4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867', '25,6,5,7,23,22,20,21,19,18,4,1,2,3,24', 'toSql', 'DEFAULT', ''), (1358204, 18452, 45631, 'jdr_7fresh_trade_deal_ord_sku_qtty_deal_7fresh', '', '2025-09-02 09:23:41', '2025-09-02 09:23:41', '', '', '', '', '', '', 2, '-1', '-1', '', '', '', '', 0, 0, '', '4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867', '25,6,5,7,23,22,20,21,19,18,4,1,2,3,24', 'toSql', 'DEFAULT', ''), (1358205, 18453, 45631, 'jdr_7fresh_trade_deal_ord_user_qtty_deal_7fresh', '', '2025-09-02 09:23:41', '2025-09-02 09:23:41', '', '', '', '', '', '', 2, '-1', '-1', '', '', '', '', 0, 0, '', '4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867', '25,6,5,7,23,22,20,21,19,18,4,1,2,3,24', 'toSql', 'DEFAULT', ''), (1358206, 18456, 45631, 'jdr_7fresh_trade_deal_ord_sku_dis_qtty_deal_7fresh', '', '2025-09-02 09:23:41', '2025-09-02 09:23:41', '', '', '', '', '', '', 2, '-1', '-1', '', '', '', '', 0, 0, '', '4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867', '25,6,5,7,23,22,20,21,19,18,4,1,2,3,24', 'toSql', 'DEFAULT', ''), (1358207, 19866, 45631, 'jdr_7fresh_trade_complete_ord_ord_amt_deal_7fresh', '', '2025-09-02 09:23:41', '2025-09-02 09:23:41', '', '', '', '', '', '', 2, '-1', '-1', '', '', '', '', 0, 0, '', '4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867', '25,6,5,7,23,22,20,21,19,18,4,1,2,3,24', 'toSql', 'DEFAULT', ''), (1358208, 21691, 45631, 'jdr_7fresh_trade_deal_ord_ord_amt_include_moutai', '', '2025-09-02 09:23:41', '2025-09-02 09:23:41', '', '', '', '', '', '', 2, '-1', '-1', '', '', '', '', 0, 0, '', '4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867', '25,6,5,7,23,22,20,21,19,18,4,1,2,3,24', 'toSql', 'DEFAULT', ''), (1358209, 19871, 45631, 'jdr_7fresh_trade_complete_ord_sku_qtty_deal_7fresh', '', '2025-09-02 09:23:41', '2025-09-02 09:23:41', '', '', '', '', '', '', 2, '-1', '-1', '', '', '', '', 0, 0, '', '4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867', '25,6,5,7,23,22,20,21,19,18,4,1,2,3,24', 'toSql', 'DEFAULT', '');
3.2.2.2 實踐分析：
用sql模擬兩個事務的執(zhí)行過程：
事務1：
begin; select * from unify_metric_impl umi where logic_table_id = 45631; delete from unify_metric_impl where logic_table_id in (45631); SELECT trx_id, trx_query FROM INFORMATION_SCHEMA.INNODB_TRX; select * from unify_metric_impl umi where logic_table_id = 45631; INSERT INTO `unify_metric_impl` ( `metric_def_id`, `logic_table_id`, `name_en_atomic`, `committer`, `create_time`, `update_time`, `metric_atomic_name_temp`, `decorate_id_list_temp`, `name_cn_alias_temp`, `metric_type_temp`, `description_temp`, `data_type_temp`, `data_accuracy_temp`, `security_level_temp`, `logic_table_id_excel_temp`, `implement_type`, `app_ori_metric_name_temp`, `name_en_depend_atomic`, `name_en_depend_app`, `update_status`, `status`, `light_decorate_id_list`, `extend_decorate_id_list`, `extend_function_id_list`, `aggregation_type`, `middle_aggregation_type`, `static_decorate_id_list_combination`) VALUES (19872, 45631, 'jdr_7fresh_trade_complete_ord_user_qtty_deal_7fresh', '', '2025-09-02 09:23:41', '2025-09-02 09:23:41', '', '', '', '', '', '', 2, '-1', '-1', '', '', '', '', 0, 0, '', '4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867', '25,6,5,7,23,22,20,21,19,18,4,1,2,3,24', 'toSql', 'DEFAULT', ''), (19873, 45631, 'jdr_7fresh_trade_complete_ord_sku_dis_qtty_deal_7fresh', '', '2025-09-02 09:23:41', '2025-09-02 09:23:41', '', '', '', '', '', '', 2, '-1', '-1', '', '', '', '', 0, 0, '', '4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867', '25,6,5,7,23,22,20,21,19,18,4,1,2,3,24', 'toSql', 'DEFAULT', ''), (19875, 45631, 'jdr_7fresh_trade_complete_ord_ord_dis_qtty_deal_7fresh', '', '2025-09-02 09:23:41', '2025-09-02 09:23:41', '', '', '', '', '', '', 2, '-1', '-1', '', '', '', '', 0, 0, '', '4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867', '25,6,5,7,23,22,20,21,19,18,4,1,2,3,24', 'toSql', 'DEFAULT', ''), (19945, 45631, 'jdr_7fresh_sku_deal_ord_sku_dis_qtty_main_img_video_num', '', '2025-09-02 09:23:41', '2025-09-02 09:23:41', '', '', '', '', '', '', 2, '-1', '-1', '', '', '', '', 0, 0, '', '4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867', '25,6,5,7,23,22,20,21,19,18,4,1,2,3,24', 'toSql', 'DEFAULT', ''), (17263, 45631, 'jdr_7fresh_trade_deal_ord_ord_dis_qtty_deal_7fresh', '', '2025-09-02 09:23:41', '2025-09-02 09:23:41', '', '', '', '', '', '', 2, '-1', '-1', '', '', '', '', 0, 0, '', '4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867', '25,6,5,7,23,22,20,21,19,18,4,1,2,3,24', 'toSql', 'DEFAULT', ''), (28017, 45631, 'jdr_7fresh_bd_bd_attendance_offline__store_cnt_bd_attendance_cnt', '', '2025-09-02 09:23:41', '2025-09-02 09:23:41', '', '', '', '', '', '', 2, '-1', '-1', '', '', '', '', 0, 0, '', '4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867', '25,6,5,7,23,22,20,21,19,18,4,1,2,3,24', 'COUNT_DISTINCT', 'DEFAULT', ''), (20242, 45631, 'jdr_7fresh_trade_deal_ord_app__ord_qtty_deal_7fresh', '', '2025-09-02 09:23:41', '2025-09-02 09:23:41', '', '', '', '', '', '', 2, '-1', '-1', '', '', '', '', 0, 0, '', '4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867', '25,6,5,7,23,22,20,21,19,18,4,1,2,3,24', 'toSql', 'DEFAULT', ''), (18450, 45631, 'jdr_7fresh_trade_deal_ord_ord_amt_deal_7fresh', '', '2025-09-02 09:23:41', '2025-09-02 09:23:41', '', '', '', '', '', '', 2, '-1', '-1', '', '', '', '', 0, 0, '', '4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867', '25,6,5,7,23,22,20,21,19,18,4,1,2,3,24', 'toSql', 'DEFAULT', ''), (20276, 45631, 'jdr_7fresh_trade_deal_ord_app__ord_cnt_deal_7fresh', '', '2025-09-02 09:23:41', '2025-09-02 09:23:41', '', '', '', '', '', '', 2, '-1', '-1', '', '', '', '', 0, 0, '', '4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867', '25,6,5,7,23,22,20,21,19,18,4,1,2,3,24', 'toSql', 'DEFAULT', ''), (18452, 45631, 'jdr_7fresh_trade_deal_ord_sku_qtty_deal_7fresh', '', '2025-09-02 09:23:41', '2025-09-02 09:23:41', '', '', '', '', '', '', 2, '-1', '-1', '', '', '', '', 0, 0, '', '4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867', '25,6,5,7,23,22,20,21,19,18,4,1,2,3,24', 'toSql', 'DEFAULT', ''), (18453, 45631, 'jdr_7fresh_trade_deal_ord_user_qtty_deal_7fresh', '', '2025-09-02 09:23:41', '2025-09-02 09:23:41', '', '', '', '', '', '', 2, '-1', '-1', '', '', '', '', 0, 0, '', '4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867', '25,6,5,7,23,22,20,21,19,18,4,1,2,3,24', 'toSql', 'DEFAULT', ''), (18456, 45631, 'jdr_7fresh_trade_deal_ord_sku_dis_qtty_deal_7fresh', '', '2025-09-02 09:23:41', '2025-09-02 09:23:41', '', '', '', '', '', '', 2, '-1', '-1', '', '', '', '', 0, 0, '', '4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867', '25,6,5,7,23,22,20,21,19,18,4,1,2,3,24', 'toSql', 'DEFAULT', ''), (19866, 45631, 'jdr_7fresh_trade_complete_ord_ord_amt_deal_7fresh', '', '2025-09-02 09:23:41', '2025-09-02 09:23:41', '', '', '', '', '', '', 2, '-1', '-1', '', '', '', '', 0, 0, '', '4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867', '25,6,5,7,23,22,20,21,19,18,4,1,2,3,24', 'toSql', 'DEFAULT', ''), (21691, 45631, 'jdr_7fresh_trade_deal_ord_ord_amt_include_moutai', '', '2025-09-02 09:23:41', '2025-09-02 09:23:41', '', '', '', '', '', '', 2, '-1', '-1', '', '', '', '', 0, 0, '', '4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867', '25,6,5,7,23,22,20,21,19,18,4,1,2,3,24', 'toSql', 'DEFAULT', ''), (19871, 45631, 'jdr_7fresh_trade_complete_ord_sku_qtty_deal_7fresh', '', '2025-09-02 09:23:41', '2025-09-02 09:23:41', '', '', '', '', '', '', 2, '-1', '-1', '', '', '', '', 0, 0, '', '4556,8012,8270,7247,7248,7249,7250,2134,7254,7255,5997,7867', '25,6,5,7,23,22,20,21,19,18,4,1,2,3,24', 'toSql', 'DEFAULT', ''); commit;
?
事務2：
begin; select * from unify_metric_impl umi where logic_table_id = 45631; delete from unify_metric_impl where logic_table_id in (45631); select * from unify_metric_impl umi where logic_table_id = 45631; commit;
?
流程圖(用一行數(shù)據進行演示版本控制)：
?
為何事務1的select查詢出“為空”，事務2的select查詢出“不為空”：
| 對比維度 | 事務 1 查詢（讀自己的刪除版本 V2） | 事務 2 查詢（讀readview前的V1版本） |
| 自己生成的版本 | V2（trx_id=17190，已刪除） | V4（trx_id=17191，已刪除） |
| 對自己版本的處理 | 可見，且事務內需反映自己的刪除操作，所以不追溯前驅 V1 | 不可見，但當前刪除的版本是由其他事務得到(V3)，并非在readview之前的數(shù)據。 |
| 追溯的終止條件 | 遇到自己生成的版本，即使已刪除，也終止追溯 | 遇到自己生成的已刪除版本，但不符合"有效刪除"，需繼續(xù)追溯 |
| 最終返回結果 | v2（已刪除版本，反映自己的刪除操作） | V1（readview之前有效的版本） |
?
4.解決辦法
為了解決事務2的查詢"不為空"的問題，分別列出以下方案：
|
? |
解決辦法 | 優(yōu)點 | 缺點 | 傾向 |
| 方式1 | 針對同一個邏輯表的同步添加分布式鎖 | 實現(xiàn)成本低，影響范圍小 | 存在長事務的問題 | 短期解法 |
| 方式2 | 將事務2的select改為當前讀(使用slecet...for update)，這樣就能查詢出最新的數(shù)據為空 | 實現(xiàn)成本低， | 存在長事務的問題，影響范圍大(長事務涉及邏輯多) | 不推薦 |
| 方式3 | 將長事務拆分， "讀 - 算 - 寫" 三步 1. 讀：無鎖讀取原子服務與實現(xiàn)數(shù)據； 2. 算：在應用層對比新增 / 刪除數(shù)據； 3. 寫：僅對差異數(shù)據執(zhí)行短事務操作 | 從根源解決問題 | 實現(xiàn)成本大，重構該方法 | 長期解法 |
當前落地情況：已通過 “分布式鎖控制同一邏輯表同步并發(fā)” 的短期方案解決事故，后續(xù)將在業(yè)務迭代中推進 “讀 - 算 - 寫” 拆分的長期優(yōu)化，進一步降低事務粒度與鎖沖突風險。
5.附錄
5.1名詞解釋
事實邏輯表：由物理數(shù)倉中的事實表和維度邏輯表關聯(lián)形成的語義表，可以描述業(yè)務過程的詳細信息，是指標的數(shù)據來源。
原子服務：指標的實現(xiàn)方式，一個指標可以有多個實現(xiàn)。
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審核編輯 黃宇
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