Hi - I've been looking through the Arrow specification format to look for ways to allow zero-copy creation of Pandas DataFrames (beyond `split_blocks`). Am I right in thinking that if you created an Arrow file (let's say of `m` rows and `n` columns of `float64`s for now) as a single RecordBatch then your arrow file would have all the `float64` buffers end-to-end, effectively forming a long `m` x `n` 1D `float64` array (equivalently, a `m` x `n` 2D array in C-order)? If so, then it seems like you could pass the 2D grid of values to the Pandas BlockManager when exposing the Arrow file as a DataFrame, and so no consolidations would be triggered regardless of what operations you did on the DataFrame (unlike `split_blocks`).
Do you think this is a useful optimisation to do (I'm happy to work on the implementation)? Or would it be too fragile or rarely-triggered to be a useful addition to the codebase? Thanks - Nick
