[Feature][DataLoader] Add DataFusion SQL transformation support

[ShreyeshArangath]

Summary

• Replace the LogicalPlan/Substrait-based TableTransformer with a simpler SQL-string interface — transformers return a SQL string (or None) that is executed per-batch via DataFusion
• Each split creates one DataFusion SessionContext and rebinds the batch table for each record batch, avoiding per-batch session overhead

High-Level Design

The TableTransformer.transform() method is called once during planning to produce a SQL string. That SQL is then attached to every DataLoaderSplit and executed per-batch at iteration time. This keeps the transformer interface simple (no DataFusion dependency for implementors) and the SQL string is trivially picklable for distributed execution.

OpenHouseDataLoader.__iter__()
      ├── transformer.transform(table_id, context) → SQL string (once)
      ├── to_datafusion_sql(sql, dialect) → transpile if needed
      └── for each file scan task:
            yield DataLoaderSplit(scan_context, transform_sql)


  DataLoaderSplit.__iter__()
    ├── SessionContext created (once per split)
    └── for each batch from ArrowScan:
          ├── bind batch as table_id.sql_name
          ├── execute transform SQL
          └── yield result batches

Changes

• Client-facing API Changes
• Internal API Changes
• Bug Fixes
• New Features
• Performance Improvements
• Code Style
• Refactoring
• Documentation
• Tests

For all the boxes checked, please include additional details of the changes made in this pull request.

Testing Done

• Manually Tested on local docker setup. Please include commands ran, and their output.
• Added new tests for the changes made.
• Updated existing tests to reflect the changes made.
• No tests added or updated. Please explain why. If unsure, please feel free to ask for help.
• Some other form of testing like staging or soak time in production. Please explain.

For all the boxes checked, include a detailed description of the testing done for the changes made in this pull request.

Additional Information

• Breaking Changes
• Deprecations
• Large PR broken into smaller PRs, and PR plan linked in the description.

For all the boxes checked, include additional details of the changes made in this pull request.