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：

conda activate mlflow-1.11.0

参考mlflow db upgrade ，执行

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

其中

如果执行成功则会看到如下输出信息:

2020/11/02 10:24:50 INFO mlflow.store.db.utils: Updating database tablesINFO  [alembic.runtime.migration] Context impl MySQLImpl.INFO  [alembic.runtime.migration] Will assume non-transactional DDL.INFO  [alembic.runtime.migration] Running upgrade 2b4d017a5e9b -> cfd24bdc0731, Update run status constraint with killedINFO  [alembic.runtime.migration] Running upgrade cfd24bdc0731 -> 0a8213491aaa, drop_duplicate_killed_constraintWARNI [0a8213491aaa_drop_duplicate_killed_constraint_py] Failed to drop check constraint. Dropping check constraints may not be supported by your SQL database. Exception content: (MySQLdb._exceptions.ProgrammingError) (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near 'CHECK status' at line 1")[SQL: ALTER TABLE runs DROP CHECK status](Background on this error at: http://sqlalche.me/e/f405)INFO  [alembic.runtime.migration] Running upgrade 0a8213491aaa -> 728d730b5ebd, add registered model tags tableINFO  [alembic.runtime.migration] Running upgrade 728d730b5ebd -> 27a6a02d2cf1, add model version tags tableINFO  [alembic.runtime.migration] Running upgrade 27a6a02d2cf1 -> 84291f40a231, add run_link to model_version

如果此时再在mlflow 1.4.0的环境下 再执行：

mlflow server \      --backend-store-uri mysql://root:root@localhost/mlflow \      --host 0.0.0.0 -p 5002 \      --default-artifact-root s3://mlflow

就会报错：

2020/11/02 10:25:41 ERROR mlflow.cli: Error initializing backend store2020/11/02 10:25:41 ERROR mlflow.cli: Detected out-of-date database schema (found version 84291f40a231, but expected 2b4d017a5e9b). Take a backup of your database, then run 'mlflow db upgrade ' to migrate your database to the latest schema. NOTE: schema migration may result in database downtime - please consult your database's documentation for more detail.Traceback (most recent call last):  File "/Users/ljh/opt/miniconda3/envs/mlflow-1.4.0-dev/lib/python3.6/site-packages/mlflow/cli.py", line 263, in server    initialize_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", line 97, in initialize_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", line 83, 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", line 37, in get_store    return builder(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", line 54, in _get_sqlalchemy_store    return SqlAlchemyStore(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", line 99, 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", line 52, in _verify_schema    "more detail." % (current_rev, head_revision))mlflow.exceptions.MlflowException: Detected out-of-date database schema (found version 84291f40a231, but expected 2b4d017a5e9b). Take a backup of your database, then run 'mlflow db upgrade ' to migrate your database to the latest schema. NOTE: schema migration may result in database downtime - please consult your database's documentation for more detail.

这说明升级成功

此时再在mlflow 1.11.0的conda环境下执行：

 mlflow server \      --backend-store-uri mysql://root:root@localhost/mlflow \      --host 0.0.0.0 -p 5003 \      --default-artifact-root s3://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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