Exemple #1
0
    def offline_to_online_ingestion(
        self, ingestion_job_params: BatchIngestionJobParameters
    ) -> BatchIngestionJob:
        """
        Submits a batch ingestion job to a Spark cluster.

        Raises:
            SparkJobFailure: The spark job submission failed, encountered error
                during execution, or timeout.

        Returns:
            BatchIngestionJob: wrapper around remote job that can be used to check when job completed.
        """

        main_file = self._datalake.upload_file(
            ingestion_job_params.get_main_file_path())

        job_info = _submit_job(
            self._api,
            ingestion_job_params.get_project() +
            "_offline_to_online_ingestion",
            main_file,
            main_class=ingestion_job_params.get_class_name(),
            arguments=ingestion_job_params.get_arguments(),
            reference_files=[main_file],
            tags=_prepare_job_tags(ingestion_job_params,
                                   OFFLINE_TO_ONLINE_JOB_TYPE),
            configuration=None)

        return cast(BatchIngestionJob, self._job_from_job_info(job_info))
Exemple #2
0
    def offline_to_online_ingestion(
        self, ingestion_job_params: BatchIngestionJobParameters
    ) -> BatchIngestionJob:
        """
        Submits a batch ingestion job to a Spark cluster.

        Raises:
            SparkJobFailure: The spark job submission failed, encountered error
                during execution, or timeout.

        Returns:
            BatchIngestionJob: wrapper around remote job that can be used to check when job completed.
        """

        jar_s3_path = self._upload_jar(
            ingestion_job_params.get_main_file_path())

        job_id = _generate_job_id()

        resource = _prepare_job_resource(
            job_template=self._batch_ingestion_template,
            job_id=job_id,
            job_type=OFFLINE_TO_ONLINE_JOB_TYPE,
            main_application_file=jar_s3_path,
            main_class=ingestion_job_params.get_class_name(),
            packages=[],
            jars=[],
            extra_metadata={},
            azure_credentials=self._get_azure_credentials(),
            arguments=ingestion_job_params.get_arguments(),
            namespace=self._namespace,
            extra_labels={
                LABEL_FEATURE_TABLE:
                _truncate_label(ingestion_job_params.get_feature_table_name()),
                LABEL_FEATURE_TABLE_HASH:
                _generate_project_table_hash(
                    ingestion_job_params.get_project(),
                    ingestion_job_params.get_feature_table_name(),
                ),
                LABEL_PROJECT:
                ingestion_job_params.get_project(),
            },
        )

        job_info = _submit_job(
            api=self._api,
            resource=resource,
            namespace=self._namespace,
        )

        return cast(BatchIngestionJob, self._job_from_job_info(job_info))