NAME

gcloud alpha dataplex tasks create - create a Dataplex task resource

SYNOPSIS

gcloud alpha dataplex tasks create (TASK : --lake=LAKE --location=LOCATION) (--execution-service-account=EXECUTION_SERVICE_ACCOUNT : --execution-args=EXECUTION_ARGS --execution-project=EXECUTION_PROJECT --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=NOTEBOOK_CONTAINER_IMAGE_PROPERTIES --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-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) : --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=CONTAINER_IMAGE_PROPERTIES --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]) (--trigger-type=TRIGGER_TYPE : --trigger-disabled --trigger-max-retires=TRIGGER_MAX_RETIRES --trigger-schedule=TRIGGER_SCHEDULE --trigger-start-time=TRIGGER_START_TIME) [--async] [--description=DESCRIPTION] [--display-name=DISPLAY_NAME] [--labels=[KEY=VALUE,...]] [GCLOUD_WIDE_FLAG ...]

DESCRIPTION

(ALPHA) Create a Dataplex task resource.

A task represents a user visible job that you want Dataplex to perform on a schedule. It encapsulates your code, your parameters and the schedule.

This task ID must follow these rules: o Must contain only lowercase letters, numbers, and hyphens. o Must start with a letter. o Must end with a number or a letter. o Must be between 1-63 characters. o Must be unique within the customer project / location.

EXAMPLES

To create a Dataplex task test-task with ON_DEMAND trigger type, dataplex-demo-test@test-project.iam.gserviceaccount.com as execution service account and gs://test-bucket/test-file.py as spark python script file within lake test-lake in location us-central1.

$ gcloud alpha dataplex tasks create test-task \ --location=us-central1 --lake=test-lake \ --execution-service-account=dataplex-demo-test@test-project.iam.\ gserviceaccount.com \ --spark-python-script-file=gs://test-bucket/test-file.py \ --trigger-type=ON_DEMAND

To create a Dataplex task test-task with RECURRING trigger type starting every hour at minute 0, dataplex-demo-test@test-project.iam.gserviceaccount.com as execution service account and gs://test-bucket/test-file.py as spark python script file within lake test-lake in location us-central1.

$ gcloud alpha dataplex tasks create test-task \ --location=us-central1 --lake=test-lake \ --execution-service-account=dataplex-demo-test@test-project.iam.\ gserviceaccount.com \ --spark-python-script-file=gs://test-bucket/test-file.py \ --trigger-type=RECURRING --trigger-schedule="0 * * * *"

POSITIONAL ARGUMENTS

Task resource - Arguments and flags that specify the Dataplex Task you want to

create. 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;

—

set the property core/project;

—

provide the argument --project on the command line.

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.

REQUIRED FLAGS

Spec related to how a task is executed.

This must be specified.

--execution-service-account=EXECUTION_SERVICE_ACCOUNT

Service account to use to execute a task.

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

--execution-args=EXECUTION_ARGS

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. See https://cloud.google.com/sdk/gcloud/reference/topic/escaping for details on using a delimiter other than a comma. 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.

--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 for

the task. The 2 types of tasks supported are:-

—

spark tasks

—

notebook tasks

Exactly one of these must be specified:

Config related to running custom notebook tasks.

--notebook=NOTEBOOK

Path to input notebook. This can be the Google Cloud Storage URI of the notebook file or the path to a Notebook Content. The execution args are accessible as environment variables (TASK_key=value).

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

--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=NOTEBOOK_CONTAINER_IMAGE_PROPERTIES

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.

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.

Exactly one of these must 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 jar_file_uris. The execution args are passed in as a sequence of named process arguments (--key=value).

--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.

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=CONTAINER_IMAGE_PROPERTIES

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.

At most one of these can be specified:

--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.

Spec related to Dataplex task scheduling and frequency settings.

This must be specified.

--trigger-type=TRIGGER_TYPE

Trigger type of the user-specified Dataplex Task. TRIGGER_TYPE must be one of:

on-demand

The ON_DEMAND trigger type runs the Dataplex task one time shortly after task creation.

recurring

The RECURRING trigger type makes the task scheduled to run periodically.

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

--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 begins after this time. If not specified, an ON_DEMAND task runs when it is submitted and a RECURRING task runs based on the trigger schedule.

OPTIONAL FLAGS

--async

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

--description=DESCRIPTION

Description of the Dataplex task.

--display-name=DISPLAY_NAME

Display name of the Dataplex task.

--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.

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 create