gcloud dataplex tasks update - update a Dataplex task resource

gcloud 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 …]

Task resource - Arguments and flags that specify the Dataplex Task you want toupdate. The arguments in this group can be used to specify the attributes ofthis resource. (NOTE) Some attributes are not given arguments in this group butcan be set in other ways.

To set theproject attribute:

• provide the argumenttask on the command line with a fullyspecified name;
• provide the argument--project on the command line;
• set the propertycore/project.

This must be specified.

TASK

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

To set thetask attribute:

• provide the argumenttask on the command line.

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

--lake=LAKE

Identifier of the Dataplex lake resource.To set thelake attribute:

• provide the argumenttask on the command line with a fullyspecified name;
• provide the argument--lake on the command line.

--location=LOCATION

Location of the Dataplex resource.To set thelocation attribute:

• provide the argumenttask on the command line with a fullyspecified name;
• provide the argument--location on the command line;
• set the propertydataplex/location.

--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 ismodified. Otherwise, a new label is created.

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

gclouddataplextasksupdate--clear-labels

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

gclouddataplextasksupdate--clear-labels--update-labelsfoo=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 beforepassing the args to the driver. Currently supported placeholders:

• ${task_id}
• ${job_time} To pass positional args, set the key as TASK_ARGS. The value shouldbe a comma-separated string of all the positional arguments. To use a delimiterother than comma, refer tohttps://cloud.google.com/sdk/gcloud/reference/topic/escaping.In case of other keys being present in the args, then TASK_ARGS will be passedas the last argument.

--execution-project=EXECUTION_PROJECT

The project in which jobs are run. By default, the project containing the Lakeis used. If a project is provided, the --execution-service-account must belongto this same project.

--execution-service-account=EXECUTION_SERVICE_ACCOUNT

Service account to use to execute a task. If not provided, the default Computeservice 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 NotebookContent. Path to input notebook.

--notebook-archive-uris=[NOTEBOOK_ARCHIVE_URIS,…]

Google Cloud Storage URIs of archives to be extracted into the working directoryof 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 eachexecutor.

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, thenauto-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 StorageURIs 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 theDataproc cluster. The properties to set on daemon config files. Property keysare specified inprefix:property format, for examplecore:hadoop.tmp.dir. For more information, seeClusterproperties.

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 networknamed 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 directoryof 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 eachexecutor.

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, thenauto-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 StorageURIs 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 theDataproc cluster. The properties to set on daemon config files. Property keysare specified inprefix:property format, for examplecore:hadoop.tmp.dir. For more information, seeClusterproperties.

--container-image-python-packages=[CONTAINER_IMAGE_PYTHON_PACKAGES,…]

A list of python packages to be installed. Valid formats include Cloud StorageURI 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 networknamed 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 eitherthe 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 mustbe 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. Theexecution 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. Mustbe 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 thequery 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. Itis 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 retrya failed task.

--trigger-schedule=TRIGGER_SCHEDULE

Cron schedule (https://en.wikipedia.org/wiki/Cron) for running tasksperiodically.

--trigger-start-time=TRIGGER_START_TIME

The first run of the task will be after this time. If not specified, the taskwill run shortly after being submitted if ON_DEMAND and based on the schedule ifRECURRING.

Run$gcloud help for details.