mlflow升级的方法是什么

mlflow升级的方法是什么

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升级以及准备

参照之前mlflow的搭建使用 ，我们先建立mlflow 1.4.0和mlflow 1.11.0的conda环境
假设你已经建立好了对应的conda环境，且分别为mlflow-1.4.0 和mlflow-1.11.0 则执行：

condaactivatemlflow-1.11.0

参考mlflow db upgrade ，执行

mlflowdbupgrademysql://user:passwd@host:port/db如：mlflowdbupgrademysql://root:root@localhost/mlflow

其中

如果执行成功则会看到如下输出信息:

2020/11/0210:24:50INFOmlflow.store.db.utils:UpdatingdatabasetablesINFO[alembic.runtime.migration]ContextimplMySQLImpl.INFO[alembic.runtime.migration]Willassumenon-transactionalDDL.INFO[alembic.runtime.migration]Runningupgrade2b4d017a5e9b->cfd24bdc0731,UpdaterunstatusconstraintwithkilledINFO[alembic.runtime.migration]Runningupgradecfd24bdc0731->0a8213491aaa,drop_duplicate_killed_constraintWARNI[0a8213491aaa_drop_duplicate_killed_constraint_py]Failedtodropcheckconstraint.DroppingcheckconstraintsmaynotbesupportedbyyourSQLdatabase.Exceptioncontent:(MySQLdb._exceptions.ProgrammingError)(1064,"YouhaveanerrorinyourSQLsyntax;checkthemanualthatcorrespondstoyourMySQLserverversionfortherightsyntaxtousenear'CHECKstatus'atline1")[SQL:ALTERTABLErunsDROPCHECKstatus](Backgroundonthiserrorat:http://sqlalche.me/e/f405)INFO[alembic.runtime.migration]Runningupgrade0a8213491aaa->728d730b5ebd,addregisteredmodeltagstableINFO[alembic.runtime.migration]Runningupgrade728d730b5ebd->27a6a02d2cf1,addmodelversiontagstableINFO[alembic.runtime.migration]Runningupgrade27a6a02d2cf1->84291f40a231,addrun_linktomodel_version

如果此时再在mlflow 1.4.0的环境下 再执行：

mlflowserver\--backend-store-urimysql://root:root@localhost/mlflow\--host0.0.0.0-p5002\--default-artifact-roots3://mlflow

就会报错：

2020/11/0210:25:41ERRORmlflow.cli:Errorinitializingbackendstore2020/11/0210:25:41ERRORmlflow.cli:Detectedout-of-datedatabaseschema(foundversion84291f40a231,butexpected2b4d017a5e9b).Takeabackupofyourdatabase,thenrun'mlflowdbupgrade<database_uri>'tomigrateyourdatabasetothelatestschema.NOTE:schemamigrationmayresultindatabasedowntime-pleaseconsultyourdatabase'sdocumentationformoredetail.Traceback(mostrecentcalllast):File"/Users/ljh/opt/miniconda3/envs/mlflow-1.4.0-dev/lib/python3.6/site-packages/mlflow/cli.py",line263,inserverinitialize_backend_stores(backend_store_uri,default_artifact_root)File"/Users/ljh/opt/miniconda3/envs/mlflow-1.4.0-dev/lib/python3.6/site-packages/mlflow/server/handlers.py",line97,ininitialize_backend_stores_get_tracking_store(backend_store_uri,default_artifact_root)File"/Users/ljh/opt/miniconda3/envs/mlflow-1.4.0-dev/lib/python3.6/site-packages/mlflow/server/handlers.py",line83,in_get_tracking_store_tracking_store=_tracking_store_registry.get_store(store_uri,artifact_root)File"/Users/ljh/opt/miniconda3/envs/mlflow-1.4.0-dev/lib/python3.6/site-packages/mlflow/tracking/_tracking_service/registry.py",line37,inget_storereturnbuilder(store_uri=store_uri,artifact_uri=artifact_uri)File"/Users/ljh/opt/miniconda3/envs/mlflow-1.4.0-dev/lib/python3.6/site-packages/mlflow/server/handlers.py",line54,in_get_sqlalchemy_storereturnSqlAlchemyStore(store_uri,artifact_uri)File"/Users/ljh/opt/miniconda3/envs/mlflow-1.4.0-dev/lib/python3.6/site-packages/mlflow/store/tracking/sqlalchemy_store.py",line99,in__init__mlflow.store.db.utils._verify_schema(self.engine)File"/Users/ljh/opt/miniconda3/envs/mlflow-1.4.0-dev/lib/python3.6/site-packages/mlflow/store/db/utils.py",line52,in_verify_schema"moredetail."%(current_rev,head_revision))mlflow.exceptions.MlflowException:Detectedout-of-datedatabaseschema(foundversion84291f40a231,butexpected2b4d017a5e9b).Takeabackupofyourdatabase,thenrun'mlflowdbupgrade<database_uri>'tomigrateyourdatabasetothelatestschema.NOTE:schemamigrationmayresultindatabasedowntime-pleaseconsultyourdatabase'sdocumentationformoredetail.

这说明升级成功

此时再在mlflow 1.11.0的conda环境下执行：

mlflowserver\--backend-store-urimysql://root:root@localhost/mlflow\--host0.0.0.0-p5003\--default-artifact-roots3://mlflow

就能正常的看到页面,这样mlflow 从1.4.0到1.11.0的升级就完成了

注意事项

如果是线上操作，则先备份数据库，因为该升级不一定能保证升级成功，如升级失败,直接从备份数据库恢复或者参照失败处理进行处理

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