### Description

#27647 has introduced filtering for invalid schemas in Hive hook based on the characters `;` and `!`. I'm wondering if a more generic filtering could be introduced, e.g. one that adheres to the regex `[^a-z0-9_]`, since Hive schemas (and table names) can only contain alphanumeric characters and the character `_`.

Note: since the Hive metastore [stores schemas and tables in lowercase](https://stackoverflow.com/questions/57181316/how-to-keep-column-names-in-camel-case-in-hive/57183048#57183048), checking against `[^a-z0-9_]` is probably better than `[^a-zA-Z0-9_]`.

### Use case/motivation

Ensure that Hive schemas used in `apache-airflow-providers-apache-hive` hooks contain no invalid characters.

### Related issues

_No response_

### Are you willing to submit a PR?

- [X] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

field_dict = _infer_field_types_from_df(df)
                df.to_csv(
                    path_or_buf=f,
                    sep=delimiter,
                    header=False,
                    index=False,
                    encoding=encoding,
                    date_format="%Y-%m-%d %H:%M:%S",
                    **pandas_kwargs,
                )
                f.flush()
                return self.load_file(
                    filepath=f.name, table=table, delimiter=delimiter, field_dict=field_dict, **kwargs
                )
    def load_file(
        self,
        filepath: str,
        table: str,
        delimiter: str = ",",
        field_dict: dict[Any, Any] | None = None,
        create: bool = True,
        overwrite: bool = True,
        partition: dict[str, Any] | None = None,
        recreate: bool = False,
        tblproperties: dict[str, Any] | None = None,
    ) -> None:
        """
        Loads a local file into Hive
        Note that the table generated in Hive uses ``STORED AS textfile``
        which isn't the most efficient serialization format. If a