gcloud-help/gcloud/alpha/dataplex/tasks/update

NAME
    gcloud alpha dataplex tasks update - update a Dataplex task resource

SYNOPSIS
    gcloud alpha dataplex tasks update (TASK : --lake=LAKE --location=LOCATION)
        [--async] [--description=DESCRIPTION] [--display-name=DISPLAY_NAME]
        [--update-labels=[KEY=VALUE,...]]
        [--clear-labels | --remove-labels=[KEY,...]]
        [--execution-args=[KEY=VALUE,...] --execution-project=EXECUTION_PROJECT
          --execution-service-account=EXECUTION_SERVICE_ACCOUNT
          --kms-key=KMS_KEY
          --max-job-execution-lifetime=MAX_JOB_EXECUTION_LIFETIME]
        [--notebook=NOTEBOOK
          --notebook-archive-uris=[NOTEBOOK_ARCHIVE_URIS,...]
          --notebook-file-uris=[NOTEBOOK_FILE_URIS,...]
          --notebook-batch-executors-count=NOTEBOOK_BATCH_EXECUTORS_COUNT
          --notebook-batch-max-executors-count=NOTEBOOK_BATCH_MAX_EXECUTORS_COUNT --notebook-container-image=NOTEBOOK_CONTAINER_IMAGE --notebook-container-image-java-jars=[NOTEBOOK_CONTAINER_IMAGE_JAVA_JARS,
          ...] --notebook-container-image-properties=[KEY=VALUE,...]
          --notebook-vpc-network-tags=[NOTEBOOK_VPC_NETWORK_TAGS,...]
          --notebook-vpc-network-name=NOTEBOOK_VPC_NETWORK_NAME
          | --notebook-vpc-sub-network-name=NOTEBOOK_VPC_SUB_NETWORK_NAME
          | --spark-archive-uris=[SPARK_ARCHIVE_URIS,...]
          --spark-file-uris=[SPARK_FILE_URIS,...]
          --batch-executors-count=BATCH_EXECUTORS_COUNT
          --batch-max-executors-count=BATCH_MAX_EXECUTORS_COUNT
          --container-image=CONTAINER_IMAGE
          --container-image-java-jars=[CONTAINER_IMAGE_JAVA_JARS,...]
          --container-image-properties=[KEY=VALUE,...]
          --container-image-python-packages=[CONTAINER_IMAGE_PYTHON_PACKAGES,
          ...] --vpc-network-tags=[VPC_NETWORK_TAGS,...]
          --vpc-network-name=VPC_NETWORK_NAME
          --vpc-sub-network-name=VPC_SUB_NETWORK_NAME
          --spark-main-class=SPARK_MAIN_CLASS
          | --spark-main-jar-file-uri=SPARK_MAIN_JAR_FILE_URI
          | --spark-python-script-file=SPARK_PYTHON_SCRIPT_FILE
          | --spark-sql-script=SPARK_SQL_SCRIPT
          | --spark-sql-script-file=SPARK_SQL_SCRIPT_FILE]
        [--trigger-disabled --trigger-max-retires=TRIGGER_MAX_RETIRES
          --trigger-schedule=TRIGGER_SCHEDULE
          --trigger-start-time=TRIGGER_START_TIME] [GCLOUD_WIDE_FLAG ...]

DESCRIPTION
    (ALPHA) Update a Dataplex task resource with the given configurations.

EXAMPLES
    To update a Dataplex task test-task within lake test-lake in location
    us-central1 and change the description to Updated Description, run:

        $ gcloud alpha dataplex tasks update \
            projects/test-project/locations/us-central1/lakes/test-lake/\
        tasks/test-task --description='Updated Description'

POSITIONAL ARGUMENTS
     Task resource - Arguments and flags that specify the Dataplex Task you
     want to update. The arguments in this group can be used to specify the
     attributes of this 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 task on the command line with a fully specified
        name;
      ◆ provide the argument --project on the command line;
      ◆ set the property core/project.

     This must be specified.

       TASK
          ID of the task or fully qualified identifier for the task.

          To set the task attribute:
          ▸ provide the argument task on the command line.

          This positional argument must be specified if any of the other
          arguments in this group are specified.

       --lake=LAKE
          Identifier of the Dataplex lake resource.

          To set the lake attribute:
          ▸ provide the argument task on the command line with a fully
            specified name;
          ▸ provide the argument --lake on the command line.

       --location=LOCATION
          Location of the Dataplex resource.

          To set the location attribute:
          ▸ provide the argument task on the command line with a fully
            specified name;
          ▸ provide the argument --location on the command line;
          ▸ set the property dataplex/location.

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

     --description=DESCRIPTION
        Description of the task.

     --display-name=DISPLAY_NAME
        Display name of the task.

     --update-labels=[KEY=VALUE,...]
        List of label KEY=VALUE pairs to update. If a label exists, its value
        is modified. Otherwise, a new label is created.

        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.

     At most one of these can be specified:

       --clear-labels
          Remove all labels. If --update-labels is also specified then
          --clear-labels is applied first.

          For example, to remove all labels:

              $ gcloud alpha dataplex tasks update --clear-labels

          To remove all existing labels and create two new labels, foo and baz:

              $ gcloud alpha dataplex tasks update --clear-labels \
                --update-labels foo=bar,baz=qux

       --remove-labels=[KEY,...]
          List of label keys to remove. If a label does not exist it is
          silently ignored. If --update-labels is also specified then
          --update-labels is applied first.

     Spec related to how a task is executed.

       --execution-args=[KEY=VALUE,...]
          The arguments to pass to the task. The args can use placeholders of
          the format ${placeholder} as part of key/value string. These will be
          interpolated before passing the args to the driver. Currently
          supported placeholders:
          ▸ ${task_id}
          ▸ ${job_time} To pass positional args, set the key as TASK_ARGS.
            The value should be a comma-separated string of all the positional
            arguments. To use a delimiter other than comma, refer to
            https://cloud.google.com/sdk/gcloud/reference/topic/escaping. In
            case of other keys being present in the args, then TASK_ARGS will
            be passed as the last argument.

       --execution-project=EXECUTION_PROJECT
          The project in which jobs are run. By default, the project containing
          the Lake is used. If a project is provided, the
          --execution-service-account must belong to this same project.

       --execution-service-account=EXECUTION_SERVICE_ACCOUNT
          Service account to use to execute a task. If not provided, the
          default Compute service account for the project is used.

       --kms-key=KMS_KEY
          The Cloud KMS key to use for encryption, of the form:
          projects/{project_number}/locations/{location_id}/keyRings/{key-ring-name}/cryptoKeys/{key-name}

       --max-job-execution-lifetime=MAX_JOB_EXECUTION_LIFETIME
          The maximum duration before the job execution expires.

     Select which task you want to schedule and provide the required
     arguments:-
      ◆ spark tasks
      ◆ notebook tasks

     At most one of these can be specified:

       Config related to running custom Notebook tasks.

         --notebook=NOTEBOOK
            Google Cloud Storage URIs of the notebook file or the path to a
            Notebook Content. Path to input notebook.

         --notebook-archive-uris=[NOTEBOOK_ARCHIVE_URIS,...]
            Google Cloud Storage URIs of archives to be extracted into the
            working directory of each executor. Supported file types: .jar,
            .tar, .tar.gz, .tgz, and .zip.

         --notebook-file-uris=[NOTEBOOK_FILE_URIS,...]
            Google Cloud Storage URIs of files to be placed in the working
            directory of each executor.

         Compute resources needed for a Task when using Dataproc Serverless.

           --notebook-batch-executors-count=NOTEBOOK_BATCH_EXECUTORS_COUNT
              Total number of job executors.

           --notebook-batch-max-executors-count=NOTEBOOK_BATCH_MAX_EXECUTORS_COUNT
              Max configurable executors. If max_executors_count >
              executors_count, then auto-scaling is enabled.

         Container Image Runtime Configuration.

           --notebook-container-image=NOTEBOOK_CONTAINER_IMAGE
              Optional custom container image for the job.

           --notebook-container-image-java-jars=[NOTEBOOK_CONTAINER_IMAGE_JAVA_JARS,...]
              A list of Java JARS to add to the classpath. Valid input includes
              Cloud Storage URIs to Jar binaries. For example,
              gs://bucket-name/my/path/to/file.jar

           --notebook-container-image-properties=[KEY=VALUE,...]
              Override to common configuration of open source components
              installed on the Dataproc cluster. The properties to set on
              daemon config files. Property keys are specified in
              prefix:property format, for example core:hadoop.tmp.dir. For more
              information, see Cluster properties
              (https://cloud.google.com/dataproc/docs/concepts/cluster-properties).

         Cloud VPC Network used to run the infrastructure.

           --notebook-vpc-network-tags=[NOTEBOOK_VPC_NETWORK_TAGS,...]
              List of network tags to apply to the job.

           The Cloud VPC network identifier.

           At most one of these can be specified:

             --notebook-vpc-network-name=NOTEBOOK_VPC_NETWORK_NAME
                The Cloud VPC network in which the job is run. By default, the
                Cloud VPC network named Default within the project is used.

             --notebook-vpc-sub-network-name=NOTEBOOK_VPC_SUB_NETWORK_NAME
                The Cloud VPC sub-network in which the job is run.

       Config related to running custom Spark tasks.

         --spark-archive-uris=[SPARK_ARCHIVE_URIS,...]
            Google Cloud Storage URIs of archives to be extracted into the
            working directory of each executor. Supported file types: .jar,
            .tar, .tar.gz, .tgz, and .zip.

         --spark-file-uris=[SPARK_FILE_URIS,...]
            Google Cloud Storage URIs of files to be placed in the working
            directory of each executor.

         Compute resources needed for a Task when using Dataproc Serverless.

           --batch-executors-count=BATCH_EXECUTORS_COUNT
              Total number of job executors.

           --batch-max-executors-count=BATCH_MAX_EXECUTORS_COUNT
              Max configurable executors. If max_executors_count >
              executors_count, then auto-scaling is enabled.

         Container Image Runtime Configuration.

           --container-image=CONTAINER_IMAGE
              Optional custom container image for the job.

           --container-image-java-jars=[CONTAINER_IMAGE_JAVA_JARS,...]
              A list of Java JARS to add to the classpath. Valid input includes
              Cloud Storage URIs to Jar binaries. For example,
              gs://bucket-name/my/path/to/file.jar

           --container-image-properties=[KEY=VALUE,...]
              Override to common configuration of open source components
              installed on the Dataproc cluster. The properties to set on
              daemon config files. Property keys are specified in
              prefix:property format, for example core:hadoop.tmp.dir. For more
              information, see Cluster properties
              (https://cloud.google.com/dataproc/docs/concepts/cluster-properties).

           --container-image-python-packages=[CONTAINER_IMAGE_PYTHON_PACKAGES,...]
              A list of python packages to be installed. Valid formats include
              Cloud Storage URI to a PIP installable library. For example,
              gs://bucket-name/my/path/to/lib.tar.gz

         Cloud VPC Network used to run the infrastructure.

           --vpc-network-tags=[VPC_NETWORK_TAGS,...]
              List of network tags to apply to the job.

           The Cloud VPC network identifier.

             --vpc-network-name=VPC_NETWORK_NAME
                The Cloud VPC network in which the job is run. By default, the
                Cloud VPC network named Default within the project is used.

             --vpc-sub-network-name=VPC_SUB_NETWORK_NAME
                The Cloud VPC sub-network in which the job is run.

         The specification of the main method to call to drive the job. Specify
         either the jar file that contains the main class or the main class
         name.

         At most one of these can be specified:

           --spark-main-class=SPARK_MAIN_CLASS
              The name of the driver's main class. The jar file that contains
              the class must be in the default CLASSPATH or specified in

           --spark-main-jar-file-uri=SPARK_MAIN_JAR_FILE_URI
              The Google Cloud Storage URI of the jar file that contains the
              main class. The execution args are passed in as a sequence of
              named process arguments (--key=value).

           --spark-python-script-file=SPARK_PYTHON_SCRIPT_FILE
              The Google Cloud Storage URI of the main Python file to use as
              the driver. Must be a .py file.

           --spark-sql-script=SPARK_SQL_SCRIPT
              The SQL query text.

           --spark-sql-script-file=SPARK_SQL_SCRIPT_FILE
              A reference to a query file. This can be the Google Cloud Storage
              URI of the query file or it can the path to a SqlScript Content.

     Spec related to how often and when a task should be triggered.

       --trigger-disabled
          Prevent the task from executing. This does not cancel already running
          tasks. It is intended to temporarily disable RECURRING tasks.

       --trigger-max-retires=TRIGGER_MAX_RETIRES
          Number of retry attempts before aborting. Set to zero to never
          attempt to retry a failed task.

       --trigger-schedule=TRIGGER_SCHEDULE
          Cron schedule (https://en.wikipedia.org/wiki/Cron) for running tasks
          periodically.

       --trigger-start-time=TRIGGER_START_TIME
          The first run of the task will be after this time. If not specified,
          the task will run shortly after being submitted if ON_DEMAND and
          based on the schedule if RECURRING.

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.

API REFERENCE
    This command uses the dataplex/v1 API. The full documentation for this API
    can be found at: https://cloud.google.com/dataplex/docs

NOTES
    This command is currently in alpha and might change without notice. If this
    command fails with API permission errors despite specifying the correct
    project, you might be trying to access an API with an invitation-only early
    access allowlist. This variant is also available:

        $ gcloud dataplex tasks update