[BUG] sqlite for backend store

Willingness to contribute

Yes. I would be willing to contribute a fix for this bug with guidance from the MLflow community.

MLflow version

1.26

System information

• OS Platform and Distribution (e.g., Linux Ubuntu 16.04): 20.04
• Python version: 3.8
• yarn version, if running the dev UI:

Describe the problem

Upgraded from 1.23, setting sqlite as backend store an sqlalchemy.future library error is produced.

A similar issue with this one https://stackoverflow.com/questions/72341647/mlflow-modulenotfounderror-no-module-named-sqlalchemy-future/72432684#72432684

Tracking information

mlflow server --backend-store-uri sqlite:///mlflow.sqlite --default-artifact-root ./mlruns

Code to reproduce issue

mlflow server --backend-store-uri sqlite:///mlflow.sqlite  --default-artifact-root ./mlruns

Other info / logs

2022/05/30 13:18:36 ERROR mlflow.cli: Error initializing backend store
2022/05/30 13:18:36 ERROR mlflow.cli: No module named 'sqlalchemy.future'
Traceback (most recent call last):
lib/python3.8/site-packages/mlflow/store/tracking/sqlalchemy_store.py", line 11, in <module>
    from sqlalchemy.future import select
ModuleNotFoundError: No module named 'sqlalchemy.future'

What component(s) does this bug affect?

• area/artifacts: Artifact stores and artifact logging
• area/build: Build and test infrastructure for MLflow
• area/docs: MLflow documentation pages
• area/examples: Example code
• area/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registry
• area/models: MLmodel format, model serialization/deserialization, flavors
• area/projects: MLproject format, project running backends
• area/scoring: MLflow Model server, model deployment tools, Spark UDFs
• area/server-infra: MLflow Tracking server backend
• area/tracking: Tracking Service, tracking client APIs, autologging

What interface(s) does this bug affect?

• area/uiux: Front-end, user experience, plotting, JavaScript, JavaScript dev server
• area/docker: Docker use across MLflow’s components, such as MLflow Projects and MLflow Models
• area/sqlalchemy: Use of SQLAlchemy in the Tracking Service or Model Registry
• area/windows: Windows support

What language(s) does this bug affect?

• language/r: R APIs and clients
• language/java: Java APIs and clients
• language/new: Proposals for new client languages

What integration(s) does this bug affect?

• integrations/azure: Azure and Azure ML integrations
• integrations/sagemaker: SageMaker integrations
• integrations/databricks: Databricks integrations

[harupy]

@sniafas We can just make the following change:

diff --git a/setup.py b/setup.py
index adf20d1e6..8d73781b0 100644
--- a/setup.py
+++ b/setup.py
@@ -79,7 +79,7 @@ CORE_REQUIREMENTS = SKINNY_REQUIREMENTS + [
     # Pin sqlparse for: https://github.com/mlflow/mlflow/issues/3433
     "sqlparse>=0.3.1",
     # Required to run the MLflow server against SQL-backed storage
-    "sqlalchemy",
+    "sqlalchemy>=1.4.0",
     "waitress; platform_system == 'Windows'",
 ]

[harupy]

Hi @sniafas, we discussed this issue in the team and decided to drop support for SQLAlchemy 1.3. Would you be interested in filing a PR to update a SQLAlchemy requirement in setup.py?