Data Engine: Autolog to MLflow on datasource queries

[kbolashev]

Implemented in this PR:

• Added a link to open the query in the gallery view
• Added autologging only on ds.all() of queries to MLflow
• The logging happens in a parallel thread so as to not interfere with the querying
• Querying works with multiple datasources, correctly saving the query for each ds.
• A new run is created in the last modified experiment per datasource that's being queried, all the queries are then logged into that run.

Left to implement:

• RIght now the artifacts all get logged with the same name, so they are being overwritten every time. I need to add a tracker for how many logs has been saved.
• Probably would be a good idea to have the autologging togglable in some ways, because the runs created are not being closed and are going to pollute the environment, so I expect advanced users to be able to turn this off.

Caveats/bugs:

• Closing a run doesn't work if there's a logging session going on to another repo's MLflow. Possible solution - if the current datasource is not in the active run's repo, log in foreground instead of background.

[kbolashev]

Changes to be done:

• Log ONLY to the active run, no point in creating a run on the datasource's repo as it turns out
• Come up with a better naming in these cases (probably log the name of the repo+datasource+index), would be good if the index could be gotten from mlflow also.

[kbolashev]

Changed it so it logs to the current one.
The format is autolog_<datasource_name>_<#>.dagshub.json. Decided that adding the repo is a bit too verbose.

Example:

[guysmoilov]

Would be wise to pass along the active run as a parameter

[guysmoilov]

And, are you very sure that log_to_mlflow is safe to do async?
The datasource object won't be modified, or otherwise be made into garbage by the time log_to_mlflow gets executed?

[kbolashev]

The datasource object is deep copied on every modification, so log_to_mlflowis guaranteed to be working with the same object

[guysmoilov]

Might want to reuse the active_run() from line 753