P2P shuffling - ArrowInvalid: These dictionaries cannot be combined. The unified dictionary requires a larger index type.

**Describe the issue**:

During P2P shuffling, the error `ArrowInvalid: These dictionaries cannot be combined. The unified dictionary requires a larger index type.` occurs.

**Minimal Complete Verifiable Example**:

To reproduce the error, we created a [repository](https://github.com/hidemire/dask-bug) containing the dataset, code to reproduce the error, and a docker-compose file to start the dask cluster and dask-notebook.

***How to reproduce the bug***

To start containers, run the following command:
```bash
docker compose up
```

In the logs of the notebook container, there will be a link to the notebook of the next format:
```
http://127.0.0.1:8888/lab?token=c5ff9594e94ae9556be22c1c385152d8b30e0b11ae7b0689
```

Two notebooks will be available in JupyterLab, `distributed.ipynb` and `local-cluster.ipynb`.

An example of code that throws an error:
```python
import dask.dataframe as dd

df = dd.read_parquet('/data/test_dataset.parquet')

def _calculate_time(df):
df = df.sort_values('sd')
df['time_diff'] = (df['sd'].diff().dt.total_seconds())
return df

df = (
df.groupby(['date', 'fn', 'a', 'wa', 'wp'], observed=True)
.apply(_calculate_time, meta=_calculate_time(df._meta))
.reset_index(drop=True)
)

df.groupby(['a'], observed=True).count().compute()
```

**Anything else we need to know?**:

The dataset for which this error occurs:

```
# Column Non-Null Count Dtype
--- ------ -------------- -----
0 date 5 non-null datetime64[us]
1 fn 5 non-null category
2 a 5 non-null category
3 st 5 non-null datetime64[ns]
4 pc 5 non-null category
5 sd 5 non-null datetime64[ns]
6 it 0 non-null category
7 ps 5 non-null category
8 ss 5 non-null category
9 lb 5 non-null category
10 ri 5 non-null category
11 watc 5 non-null category
12 wat 5 non-null category
13 wa 5 non-null category
14 wp 5 non-null category
```
```
pyarrow.Table
date: timestamp[us]
fn: dictionary
a: dictionary
st: timestamp[ns]
pc: dictionary
sd: timestamp[ns]
it: dictionary
ps: dictionary
ss: dictionary
lb: dictionary
ri: dictionary
watc: dictionary
wat: dictionary
wa: dictionary
wp: dictionary
```

The error resolves when changing the type of some fields to str before groupby:
```python
df['ps'] = df['ps'].astype(str)
df['ss'] = df['ss'].astype(str)
df['lb'] = df['lb'].astype(str)
df['ri'] = df['ri'].astype(str)
```

We suspect that during P2P shuffling, the initial index size (int32 as seen in pyarrow.Table) for the dictionary is not used.
Therefore, it seems to us that the error occurs during combining a dictionary with int8 and int16 indexes.

Stacktrace can be viewed here [distributed.ipynb](https://github.com/hidemire/dask-bug/blob/main/distributed.ipynb) and here [local-cluster.ipynb](https://github.com/hidemire/dask-bug/blob/main/local-cluster.ipynb)

Feel free to ask any additional questions.

**Environment**:

- Dask version: 2024.1.0
- Python version: 3.10.12.final.0
- Operating System: macOS Sonoma 14.2.1
- Install method (conda, pip, source): docker