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feat(dataproc): create pyspark nodegroup cluster sample #13513

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2 changes: 1 addition & 1 deletion dataproc/snippets/noxfile_config.py
Original file line number Diff line number Diff line change
Expand Up @@ -22,7 +22,7 @@

TEST_CONFIG_OVERRIDE = {
# You can opt out from the test for specific Python versions.
"ignored_versions": ["2.7", "3.7", "3.9", "3.10", "3.11"],
"ignored_versions": ["2.7", "3.7", "3.8", "3.10", "3.11", "3.12", "3.13"],
# Old samples are opted out of enforcing Python type hints
# All new samples should feature them
# "enforce_type_hints": True,
Expand Down
107 changes: 107 additions & 0 deletions dataproc/snippets/submit_pyspark_job_to_driver_node_group_cluster.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,107 @@
#!/usr/bin/env python

# Copyright 2025 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

# This sample walks a user through submitting a Spark job to a
# Dataproc driver node group cluster using the Dataproc
# client library.

# Usage:
# python submit_pyspark_job_to_driver_node_group_cluster.py \
# --project_id <PROJECT_ID> --region <REGION> \
# --cluster_name <CLUSTER_NAME>

# [START dataproc_submit_pyspark_job_to_driver_node_group_cluster]

import re

from google.cloud import dataproc_v1 as dataproc
from google.cloud import storage


def submit_job(project_id, region, cluster_name):
"""Submits a PySpark job to a Dataproc cluster with a driver node group.

Args:
project_id (str): The ID of the Google Cloud project.
region (str): The region where the Dataproc cluster is located.
cluster_name (str): The name of the Dataproc cluster.
"""
# Create the job client.
job_client = dataproc.JobControllerClient(
client_options={"api_endpoint": f"{region}-dataproc.googleapis.com:443"}
)

driver_scheduling_config = dataproc.DriverSchedulingConfig(
memory_mb=2048, # Example memory in MB
vcores=2, # Example number of vcores
)

# Create the job config. The main Python file URI points to the script in
# a Google Cloud Storage bucket.
job = {
"placement": {"cluster_name": cluster_name},
"pyspark_job": {
"main_python_file_uri": "gs://dataproc-examples/pyspark/hello-world/hello-world.py"
},
"driver_scheduling_config": driver_scheduling_config,
}

operation = job_client.submit_job_as_operation(
request={"project_id": project_id, "region": region, "job": job}
)
response = operation.result()

# Dataproc job output gets saved to the Google Cloud Storage bucket
# allocated to the job. Use a regex to obtain the bucket and blob info.
matches = re.match("gs://(.*?)/(.*)", response.driver_output_resource_uri)
if not matches:
raise ValueError(
f"Unexpected driver output URI: {response.driver_output_resource_uri}"
)

output = (
storage.Client()
.get_bucket(matches.group(1))
.blob(f"{matches.group(2)}.000000000")
.download_as_bytes()
.decode("utf-8")
)

print(f"Job finished successfully: {output}")


# [END dataproc_submit_pyspark_job_to_driver_node_group_cluster]

if __name__ == "__main__":
import argparse

parser = argparse.ArgumentParser(
description="Submits a Spark job to a Dataproc driver node group cluster."
)
parser.add_argument(
"--project_id", help="The Google Cloud project ID.", required=True
)
parser.add_argument(
"--region",
help="The Dataproc region where the cluster is located.",
required=True,
)
parser.add_argument(
"--cluster_name", help="The name of the Dataproc cluster.", required=True
)

args = parser.parse_args()
submit_job(args.project_id, args.region, args.cluster_name)
Original file line number Diff line number Diff line change
@@ -0,0 +1,88 @@
# Copyright 2020 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import os
import subprocess
import uuid

import backoff
from google.api_core.exceptions import (
Aborted,
InternalServerError,
NotFound,
ServiceUnavailable,
)
from google.cloud import dataproc_v1 as dataproc

import submit_pyspark_job_to_driver_node_group_cluster

PROJECT_ID = os.environ["GOOGLE_CLOUD_PROJECT"]
REGION = "us-central1"
CLUSTER_NAME = f"py-ps-test-{str(uuid.uuid4())}"

cluster_client = dataproc.ClusterControllerClient(
client_options={"api_endpoint": f"{REGION}-dataproc.googleapis.com:443"}
)


@backoff.on_exception(backoff.expo, (Exception), max_tries=5)
def teardown():
try:
operation = cluster_client.delete_cluster(
request={
"project_id": PROJECT_ID,
"region": REGION,
"cluster_name": CLUSTER_NAME,
}
)
# Wait for cluster to delete
operation.result()
except NotFound:
print("Cluster already deleted")


@backoff.on_exception(
backoff.expo,
(
InternalServerError,
ServiceUnavailable,
Aborted,
),
max_tries=5,
)
def test_workflows(capsys):
# Setup driver node group cluster. TODO: cleanup b/424371877
command = f"""gcloud dataproc clusters create {CLUSTER_NAME} \
--region {REGION} \
--project {PROJECT_ID} \
--driver-pool-size=1 \
--driver-pool-id=pytest"""

output = subprocess.run(
command,
capture_output=True,
shell=True,
check=True,
)
print(output)

# Wrapper function for client library function
submit_pyspark_job_to_driver_node_group_cluster.submit_job(
PROJECT_ID, REGION, CLUSTER_NAME
)

out, _ = capsys.readouterr()
assert "Job finished successfully" in out

# cluster deleted in teardown()