### Description

Google Cloud Dataproc cluster creation should eagerly delete ERROR state clusters.

It is possible for Google Cloud Dataproc clusters to create in the ERROR state.  The current operator (DataprocCreateClusterOperator) will require three total task attempts (original + two retries) in order to create the cluster, assuming underlying GCE infrastructure resolves itself between task attempts.  This can be reduced to two total attempts by eagerly deleting a cluster in ERROR state before failing the current task attempt. 

Clusters in the ERROR state are not useable to submit Dataproc based jobs via the Dataproc API. 



### Use case/motivation

Reducing the number of task attempts can reduce GCP based cost as delays between retry attempts could be minutes.  There's no reason to keep a running, costly cluster in the ERROR state if it can be detected in the initial create task. 

### 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)

"""Start a Hive query Job on a Cloud DataProc cluster.
    .. seealso::
        This operator is deprecated, please use
        :class:`~airflow.providers.google.cloud.operators.dataproc.DataprocSubmitJobOperator`:
    :param query: The query or reference to the query file (q extension).
    :param query_uri: The HCFS URI of the script that contains the Hive queries.
    :param variables: Map of named parameters for the query.
    """
    template_fields: Sequence[str] = (
        "query",
        "variables",
        "job_name",
        "cluster_name",
        "region",
        "dataproc_jars",
        "dataproc_properties",
        "impersonation_chain",
    )
    template_ext = (".q", ".hql")
    ui_color = "#0273d4"
    job_type = "hive_job"
    def __init__(