gcloud beta dataproc batches submit spark - submit a Spark batch job
gcloud beta dataproc batches submit spark (--class=MAIN_CLASS | --jar=MAIN_JAR) [--archives=[ARCHIVE,...]] [--async] [--batch=BATCH] [--container-image=CONTAINER_IMAGE] [--deps-bucket=DEPS_BUCKET] [--files=[FILE,...]] [--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,...]] [--version=VERSION] [--network=NETWORK | --subnet=SUBNET] [GCLOUD_WIDE_FLAG ...] [-- JOB_ARG ...]
(BETA) Submit a Spark batch job.
To submit a Spark job, run:
$ gcloud beta dataproc batches submit spark --region=us-central1 \ --jar=my_jar.jar --deps-bucket=gs://my-bucket -- ARG1 ARG2
To submit a Spark job that runs a specific class of a jar, run:
$ gcloud beta dataproc batches submit spark --region=us-central1 \ --class=org.my.main.Class --jars=my_jar1.jar,my_jar2.jar \ --deps-bucket=gs://my-bucket -- ARG1 ARG2
To submit a Spark job that runs a jar installed on the cluster, run:
$ gcloud beta dataproc batches submit spark --region=us-central1 \ --class=org.apache.spark.examples.SparkPi \ --deps-bucket=gs://my-bucket \ --jars=file:///usr/lib/spark/examples/jars/spark-examples.jar \ -- 15
- [-- JOB_ARG ...]
Arguments to pass to the driver.
The '--' argument must be specified between gcloud specific args on the left and JOB_ARG on the right.
- Exactly one of these must be specified:
- --class=MAIN_CLASS
Class contains the main method of the job. The jar file that contains the class must be in the classpath or specified in jar_files.
- --jar=MAIN_JAR
URI of the main jar file.
- --archives=[ARCHIVE,...]
Archives to be extracted into the working directory. Supported file types: .jar,
- --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.
- --files=[FILE,...]
Files to be placed in the working directory.
- --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.
- --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.
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.
This command is currently in beta and might change without notice. This variant is also available:
$ gcloud dataproc batches submit spark