gcloud dataproc batches submit

NAME
gcloud dataproc batches submit - submit a Dataproc batch job
SYNOPSIS
gcloud dataproc batches submit COMMAND [--async] [--batch=BATCH] [--container-image=CONTAINER_IMAGE] [--history-server-cluster=HISTORY_SERVER_CLUSTER] [--kms-key=KMS_KEY] [--labels=[KEY=VALUE,…]] [--metastore-service=METASTORE_SERVICE] [--properties=[PROPERTY=VALUE,…]] [--region=REGION] [--request-id=REQUEST_ID] [--service-account=SERVICE_ACCOUNT] [--staging-bucket=STAGING_BUCKET] [--tags=[TAGS,…]] [--ttl=TTL] [--version=VERSION] [--network=NETWORK     | --subnet=SUBNET] [GCLOUD_WIDE_FLAG …]
DESCRIPTION
Submit a Dataproc batch job.
EXAMPLES
To submit a PySpark job, run: 
gcloud dataproc batches submit pyspark my-pyspark.py --region='us-central1' --deps-bucket=gs://my-bucket --py-files='path/to/my/python/scripts'

To submit a Spark job, run: 

gcloud dataproc batches submit spark --region='us-central1' --deps-bucket=gs://my-bucket --jar='my_jar.jar' -- ARG1 ARG2

To submit a Spark-R job, run: 

gcloud dataproc batches submit spark-r my-main-r.r --region='us-central1' --deps-bucket=gs://my-bucket -- ARG1 ARG2

To submit a Spark-Sql job, run: 

gcloud dataproc batches submit spark-sql 'my-sql-script.sql' --region='us-central1' --deps-bucket=gs://my-bucket --vars='variable=value'

To submit a Ray job, run: 

gcloud dataproc batches submit ray my-ray.py --location='us-central1' --deps-bucket=gs://my-bucket -- ARG1 ARG2
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
--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}".
--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 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.
--staging-bucket=STAGING_BUCKET
The Cloud Storage bucket to use to store job dependencies, config files, and job driver console output. If not specified, the default [staging bucket] (https://cloud.google.com/dataproc-serverless/docs/concepts/buckets) is used.
--tags=[TAGS,…]
Network tags for traffic control.
--ttl=TTL
The duration after the workload will be unconditionally terminated, for example, '20m' or '1h'. Run gcloud topic datetimes for information on duration formats.
--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: --help.

Run $ gcloud help for details.

COMMANDS
COMMAND is one of the following:
pyspark
Submit a PySpark batch job.
spark
Submit a Spark batch job.
spark-r
Submit a Spark R batch job.
spark-sql
Submit a Spark SQL batch job.
NOTES
This variant is also available: 
gcloud beta dataproc batches submit