Batched mapping does not raise an error if values for an existing column are empty
### Describe the bug

Using `Dataset.map(fn, batched=True)` allows resizing the dataset by returning a dict of lists, all of which must be the same size. If they are not the same size, an error like `pyarrow.lib.ArrowInvalid: Column 1 named x expected length 1 but got length 0` is raised.

This is not the case if the function returns an empty list for an existing column in the dataset. In that case, the dataset is silently resized to 0 rows.

### Steps to reproduce the bug

MWE:

```
import datasets
data = datasets.Dataset.from_dict({"test": [1]})

def mapping_fn(examples):
    return {"test": [], "y": [1]}

data = data.map(mapping_fn, batched=True)
print(len(data))
```

Note  that when returning `"x": []`, the error is raised correctly, also when returning `"test": [1,2]`.

### Expected behavior

Expected an exception: `pyarrow.lib.ArrowInvalid: Column 1 named test expected length 1 but got length 0` or `pyarrow.lib.ArrowInvalid: Column 2 named y expected length 0 but got length 1`.

Any exception would be acceptable.

### Environment info

- `datasets` version: 2.19.1
- Platform: Linux-5.4.0-153-generic-x86_64-with-glibc2.31
- Python version: 3.11.8
- `huggingface_hub` version: 0.22.2
- PyArrow version: 15.0.2
- Pandas version: 2.2.1
- `fsspec` version: 2024.2.0