NAME
    gcloud dataproc batches submit spark-sql - submit a Spark SQL batch job

SYNOPSIS
    gcloud dataproc batches submit spark-sql SQL_SCRIPT [--async]
        [--batch=BATCH] [--container-image=CONTAINER_IMAGE]
        [--deps-bucket=DEPS_BUCKET]
        [--history-server-cluster=HISTORY_SERVER_CLUSTER] [--jars=[JAR,...]]
        [--kms-key=KMS_KEY] [--labels=[KEY=VALUE,...]]
        [--metastore-service=METASTORE_SERVICE]
        [--properties=[PROPERTY=VALUE,...]] [--region=REGION]
        [--request-id=REQUEST_ID] [--service-account=SERVICE_ACCOUNT]
        [--tags=[TAGS,...]] [--vars=[NAME=VALUE,...]] [--version=VERSION]
        [--network=NETWORK | --subnet=SUBNET] [GCLOUD_WIDE_FLAG ...]

DESCRIPTION
    Submit a Spark SQL batch job.

EXAMPLES
    To submit a Spark SQL job running "my-sql-script.sql" and upload it to
    "gs://my-bucket", run:

        $ gcloud dataproc batches submit spark-sql my-sql-script.sql \
            --deps-bucket=gs://my-bucket --region=us-central1 \
            --vars="NAME=VALUE,NAME2=VALUE2"

POSITIONAL ARGUMENTS
     SQL_SCRIPT
        URI of the script that contains Spark SQL queries to execute.

FLAGS
     --async
        Return immediately without waiting for the operation in progress to
        complete.

     --batch=BATCH
        The ID of the batch job to submit. The ID must contain only lowercase
        letters (a-z), numbers (0-9) and hyphens (-). The length of the name
        must be between 4 and 63 characters. If this argument is not provided,
        a random generated UUID will be used.

     --container-image=CONTAINER_IMAGE
        Optional custom container image to use for the batch/session runtime
        environment. If not specified, a default container image will be used.
        The value should follow the container image naming format:
        {registry}/{repository}/{name}:{tag}, for example,
        gcr.io/my-project/my-image:1.2.3

     --deps-bucket=DEPS_BUCKET
        A Cloud Storage bucket to upload workload dependencies.

     --history-server-cluster=HISTORY_SERVER_CLUSTER
        Spark History Server configuration for the batch/session job. Resource
        name of an existing Dataproc cluster to act as a Spark History Server
        for the workload in the format:
        "projects/{project_id}/regions/{region}/clusters/{cluster_name}".

     --jars=[JAR,...]
        Comma-separated list of jar files to be provided to the classpaths.

     --kms-key=KMS_KEY
        Cloud KMS key to use for encryption.

     --labels=[KEY=VALUE,...]
        List of label KEY=VALUE pairs to add.

        Keys must start with a lowercase character and contain only hyphens
        (-), underscores (_), lowercase characters, and numbers. Values must
        contain only hyphens (-), underscores (_), lowercase characters, and
        numbers.

     --metastore-service=METASTORE_SERVICE
        Name of a Dataproc Metastore service to be used as an external
        metastore in the format:
        "projects/{project-id}/locations/{region}/services/{service-name}".

     --properties=[PROPERTY=VALUE,...]
        Specifies configuration properties for the workload. See Dataproc
        Serverless for Spark documentation
        (https://cloud.google.com/dataproc-serverless/docs/concepts/properties)
        for the list of supported properties.

     Region resource - Dataproc region to use. Each Dataproc region constitutes
     an independent resource namespace constrained to deploying instances into
     Compute Engine zones inside the region. This represents a Cloud resource.
     (NOTE) Some attributes are not given arguments in this group but can be
     set in other ways. To set the project attribute:
      ◆ provide the argument --region on the command line with a fully
        specified name;
      ◆ set the property dataproc/region with a fully specified name;
      ◆ provide the argument --project on the command line;
      ◆ set the property core/project.

       --region=REGION
          ID of the region or fully qualified identifier for the region. To set
          the region attribute:
          ▸ provide the argument --region on the command line;
          ▸ set the property dataproc/region.

     --request-id=REQUEST_ID
        A unique ID that identifies the request. If the service receives two
        batch create requests with the same request_id, the second request is
        ignored and the operation that corresponds to the first Batch created
        and stored in the backend is returned. Recommendation: Always set this
        value to a UUID. The value must contain only letters (a-z, A-Z),
        numbers (0-9), underscores (), and hyphens (-). The maximum length is
        40 characters.

     --service-account=SERVICE_ACCOUNT
        The IAM service account to be used for a batch/session job.

     --tags=[TAGS,...]
        Network tags for traffic control.

     --vars=[NAME=VALUE,...]
        Mapping of query variable names to values (equivalent to the Spark SQL
        command: SET name="value";).

     --version=VERSION
        Optional runtime version. If not specified, a default version will be
        used.

     At most one of these can be specified:

       --network=NETWORK
          Network URI to connect network to.

       --subnet=SUBNET
          Subnetwork URI to connect network to. Subnet must have Private Google
          Access enabled.

GCLOUD WIDE FLAGS
    These flags are available to all commands: --access-token-file, --account,
    --billing-project, --configuration, --flags-file, --flatten, --format,
    --help, --impersonate-service-account, --log-http, --project, --quiet,
    --trace-token, --user-output-enabled, --verbosity.

    Run $ gcloud help for details.

NOTES
    This variant is also available:

        $ gcloud beta dataproc batches submit spark-sql