`<http://www.elastic.co/guide/en/elasticsearch/reference/current/ml-flush-job.html>`_

        :arg job_id: The name of the job to flush
        :arg body: Flush parameters
        :arg advance_time: Advances time to the given value generating results
            and updating the model for the advanced interval
        :arg calc_interim: Calculates interim results for the most recent bucket
            or all buckets within the latency period
        :arg end: When used in conjunction with calc_interim, specifies the
            range of buckets on which to calculate interim results
        :arg skip_time: Skips time to the given value without generating results
            or updating the model for the skipped interval
        :arg start: When used in conjunction with calc_interim, specifies the
            range of buckets on which to calculate interim results

def flush_job(self, job_id, body=None, params=None):
        """
        `<http://www.elastic.co/guide/en/elasticsearch/reference/current/ml-flush-job.html>`_

        :arg job_id: The name of the job to flush
        :arg body: Flush parameters
        :arg advance_time: Advances time to the given value generating results
            and updating the model for the advanced interval
        :arg calc_interim: Calculates interim results for the most recent bucket
            or all buckets within the latency period
        :arg end: When used in conjunction with calc_interim, specifies the
            range of buckets on which to calculate interim results
        :arg skip_time: Skips time to the given value without generating results
            or updating the model for the skipped interval
        :arg start: When used in conjunction with calc_interim, specifies the
            range of buckets on which to calculate interim results
        """
        if job_id in SKIP_IN_PATH:
            raise ValueError("Empty value passed for a required argument 'job_id'.")
        return self.transport.perform_request(
            "POST",
            _make_path("_ml", "anomaly_detectors", job_id, "_flush"),
            params=params,
            body=body,
        )