1、AI让数据库的路走的“更快更远”阿里云数据库高级技术专家 戴健AI的使用将会越来越普及83%CEOs 相信AI 是一个战略重点MIT Sloan Management Review$2.9 trillion 商业价值由AI创造6.2 billion hours 人力花在了AI上Gartner1、特征、模型管理难AI的困境AI的困境业务数据算法AI一直迭代、演进中CRM MLOpsDataOpsCRM ModelOpsCRM DevOpsAI？DB？AIDB流程简单化、低代码量、更低的开发成本&运维成本DB+AI数据、特征、模型一起存DataOps、ModelOps统一做一起存一起算为什么我们选

2、择扩展DataOps到ModelOps事务 ACID查询加速索引缓存一写多读（多写多读）数据新鲜度数据易用性SQLUDF联邦查询ServerlessHTAP扩展DatOps到ModelOps，保持了数据新鲜度，维持了数据的易用性和可用性，避免了模型单独的数据管理系统，数据延迟和复杂的硬编码数据pipeline，方便了AI的在线决策。DataOps+ModelOps：核心功能数据特征模型AI模型创建AI模型评估AI模型调参AI模型组合AI模型部署数据管理+特征管理+模型管理SQL+SQL for MLOpsCREATE MODEL airlines_gbm_copy1 WITH(model_cl

3、ass=lightgbm,x_cols=Airline,Flight,AirportFrom,AirportTo,DayOfWeek,Time,Length,y_cols=Delay,model_parameter=(boosting_type=gbdt,n_estimators=100,max_depth=8,num_leaves=256)AS(SELECT*FROM airlines_train)SELECT TripID,Delay FROM PREDICT(MODEL airlines_gbm_copy1,SELECT*FROM airlines_train_1000_copy1)WI

4、TH(s_cols=TripID,Delay,x_cols=Airline,Flight,AirportFrom,AirportTo,DayOfWeek,Time,Length,y_cols=Delay,primary_key=TripID,CREATE MODEL airlines_gbm WITH(model_class=lightgbm,x_cols=Airline,Flight,AirportFrom,AirportTo,DayOfWeek,Time,Length,y_cols=Delay,model_parameter=(boosting_type=gbdt,n_estimators

5、=100,max_depth=8,num_leaves=256)AS(SELECT*FROM airlines_train)模型创建模型评估SELECT Delay FROM evaluate(MODEL airlines_gbm,SELECT*FROM airlines_test)WITH(x_cols=Airline,Flight,AirportFrom,AirportTo,DayOfWeek,Time,Length,y_cols=Delay,metrics=acc);模型推理（离线）SELECT TripID,Delay FROM PREDICT(MODEL airlines_gbm_c

6、opy1,SELECT*FROM airlines_train_1000_copy1)WITH(s_cols=TripID,Delay,x_cols=Airline,Flight,AirportFrom,AirportTo,DayOfWeek,Time,Length,y_cols=Delay,primary_key=TripID,mode=async)INTO lightgbm_v2_predict82201;特征创建模型上传模型部署PolarDB for AIUPLOAD MODEL model_name WITH(model_location=,req_location=)DEPLOY M