[BUG] Incorrect read_parquet on spark distributed parquet files.

When I read in a parquet dataset saved with Spark on a databricks catalog I get lots of .
I tried

```
import glob

cudf_dfs = [cudf.read_parquet(file) for file in glob.glob("/Volumes/path/*.parquet")]
cudf_df = cudf.concat(cudf_dfs,ignore_index=True)
```

and

```
import dask_cudf
dask_df = dask_cudf.read_parquet("/Volumes/path/*.parquet",chunksize='50MB')
cudf_df = dask_df.compute()

```

and I also tried using the pyarrow engine on the load which overflows.

Let me know if you need some code to replicate but it should be easy. Any spark based parquet would do.