cj-zhukov opened a new pull request, #25299:
URL: https://github.com/apache/datafusion/pull/25299

   ## Which issue does this PR close?
   
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   - Closes #https://github.com/apache/datafusion/issues/25298.
   
   ## Rationale for this change
   
   `DataFrame::with_column` only adds an `Expr`. Appending an `ArrayRef` today 
means collecting the frame, concatenating columns, and calling `read_batch`. 
That executes the plan just to change the schema. Related 
https://github.com/apache/datafusion/issues/9672
   
   This PR adds a lazy API for that case: the array is stored on the plan and 
attached when the new `DataFrame` runs. No collect at the call site.
   ```rust
   let df = DataFrame::from_columns([("id", id), ("data", data)])?;
   let df = df.with_array_columns([("new_col", new_col)])?;
   let df = df.filter(col("id").gt(lit(1)))?;
   df.collect().await?;
   ```
   
   ## What changes are included in this PR?
   
   - `DataFrame::with_array_columns` - same shape as `from_columns` (name + 
`ArrayRef`).
   - `AddColumnProvider` (`TableProvider`) wraps the current `LogicalPlan` and 
the new columns.
   - `AddColumnExec` (`ExecutionPlan`) zips each input batch with 
`array.slice(offset, n)` at execution time.
   
   ## What is the testing strategy for this PR?
   
   Yes. Tests cover:
   
   - appending a column and collecting
   - filter / select after append (still lazy)
   - length mismatch at execution
   - duplicate column name
   
   ## Are there any user-facing changes?
   
   Yes - new `DataFrame::with_array_columns` method. Not a breaking change. 
Docs and an example are included.
   


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