Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

feat: added dataproc workflows samples #3056

Merged
merged 20 commits into from
Mar 24, 2020
Merged
Show file tree
Hide file tree
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
98 changes: 98 additions & 0 deletions dataproc/instantiate_inline_workflow_template.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,98 @@
# 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.

# This sample walks a user through instantiating an inline
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Totally possible I haven't noticed, but do we tend to repeat the comment in the method and at the file level?

Copy link
Collaborator Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

I haven't found anything concrete for or against, but for a single-snippet file like this, it's probably not needed at the file level.

# workflow for Cloud Dataproc using the Python client library.
#
# This script can be run on its own:
# python workflows.py ${PROJECT_ID} ${REGION}

import sys
# [START dataproc_instantiate_inline_workflow_template]
from google.cloud import dataproc_v1 as dataproc


def instantiate_inline_workflow_template(project_id, region):
"""This sample walks a user through submitting a workflow
for a Cloud Dataproc using the Python client library.

Args:
project_id (string): Project to use for running the workflow.
region (string): Region where the workflow resources should live.
"""

# Create a client with the endpoint set to the desired region.
workflow_template_client = dataproc.WorkflowTemplateServiceClient(
client_options={
'api_endpoint': '{}-dataproc.googleapis.com:443'.format(region)}
)

parent = workflow_template_client.region_path(project_id, region)

template = {
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

where do I get this template?

Copy link
Collaborator Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

(optional) Comment with link to template?

'jobs': [
{
'hadoop_job': {
'main_jar_file_uri': 'file:///usr/lib/hadoop-mapreduce/'
'hadoop-mapreduce-examples.jar',
'args': [
'teragen',
'1000',
'hdfs:///gen/'
]
},
'step_id': 'teragen'
},
{
'hadoop_job': {
'main_jar_file_uri': 'file:///usr/lib/hadoop-mapreduce/'
'hadoop-mapreduce-examples.jar',
'args': [
'terasort',
'hdfs:///gen/',
'hdfs:///sort/'
]
},
'step_id': 'terasort',
'prerequisite_step_ids': [
'teragen'
]
}],
'placement': {
'managed_cluster': {
'cluster_name': 'my-managed-cluster',
'config': {
'gce_cluster_config': {
# Leave 'zone_uri' empty for 'Auto Zone Placement'
# 'zone_uri': ''
'zone_uri': 'us-central1-a'
}
}
}
}
}

# Submit the request to instantiate the workflow from an inline template.
operation = workflow_template_client.instantiate_inline_workflow_template(
parent, template
)
operation.result()

# Output a success message.
print('Workflow ran successfully.')
# [END dataproc_instantiate_inline_workflow_template]


if __name__ == "__main__":
instantiate_inline_workflow_template(sys.argv[1], sys.argv[2])
31 changes: 31 additions & 0 deletions dataproc/instantiate_inline_workflow_template_test.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,31 @@
# 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 instantiate_inline_workflow_template


PROJECT_ID = os.environ['GCLOUD_PROJECT']
REGION = 'us-central1'


def test_workflows(capsys):
# Wrapper function for client library function
instantiate_inline_workflow_template.instantiate_inline_workflow_template(
PROJECT_ID, REGION
)

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