feat: dataproc quickstart sample added and create_cluster updated [(#…

…2629)](GoogleCloudPlatform/python-docs-samples#2629)

* Adding quickstart sample

* Added new quickstart sample and updated create_cluster sample

* Fix to create_cluster.py

* deleted dataproc quickstart files not under dataproc/quickstart/

* Added quickstart test

* Linting and formatting fixes

* Revert "Linting and formatting fixes"

This reverts commit c5afcbcdf9deccbb7a21ddd82ae0fc305e79c008.

* Added bucket cleanup to quickstart test

* Changes to samples and tests

* Linting fixes

* Removed todos in favor of clearer docstring

* Fixed lint error

Co-authored-by: Leah E. Cole <6719667+leahecole@users.noreply.github.com>

samples/snippets/create_cluster.py

@@ -14,22 +14,29 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+# This sample walks a user through creating a Cloud Dataproc cluster using
+# the Python client library.
+
+# [START dataproc_create_cluster]
+from google.cloud import dataproc_v1 as dataproc
+
 
 def create_cluster(project_id, region, cluster_name):
-    # [START dataproc_create_cluster]
-    from google.cloud import dataproc_v1 as dataproc
+    """This sample walks a user through creating a Cloud Dataproc cluster
+       using the Python client library.
 
-    # TODO(developer): Uncomment and set the following variables
-    # project_id = 'YOUR_PROJECT_ID'
-    # region = 'YOUR_CLUSTER_REGION'
-    # cluster_name = 'YOUR_CLUSTER_NAME'
+       Args:
+           project_id (string): Project to use for creating resources.
+           region (string): Region where the resources should live.
+           cluster_name (string): Name to use for creating a cluster.
+    """
 
-    # Create a client with the endpoint set to the desired cluster region
-    client = dataproc.ClusterControllerClient(client_options={
+    # Create a client with the endpoint set to the desired cluster region.
+    cluster_client = dataproc.ClusterControllerClient(client_options={
         'api_endpoint': '{}-dataproc.googleapis.com:443'.format(region)
     })
 
-    # Create the cluster config
+    # Create the cluster config.
     cluster = {
         'project_id': project_id,
         'cluster_name': cluster_name,
@@ -45,10 +52,10 @@ def create_cluster(project_id, region, cluster_name):
         }
     }
 
-    # Create the cluster
-    operation = client.create_cluster(project_id, region, cluster)
+    # Create the cluster.
+    operation = cluster_client.create_cluster(project_id, region, cluster)
     result = operation.result()
 
-    # Output a success message
+    # Output a success message.
     print('Cluster created successfully: {}'.format(result.cluster_name))
     # [END dataproc_create_cluster]

samples/snippets/create_cluster_test.py

@@ -20,20 +20,23 @@
 
 import create_cluster
 
+
 PROJECT_ID = os.environ['GCLOUD_PROJECT']
 REGION = 'us-central1'
-CLUSTER_NAME = 'test-cluster-{}'.format(str(uuid.uuid4()))
+CLUSTER_NAME = 'py-cc-test-{}'.format(str(uuid.uuid4()))
 
 
 @pytest.fixture(autouse=True)
 def teardown():
     yield
 
-    client = dataproc.ClusterControllerClient(client_options={
+    cluster_client = dataproc.ClusterControllerClient(client_options={
         'api_endpoint': '{}-dataproc.googleapis.com:443'.format(REGION)
     })
     # Client library function
-    client.delete_cluster(PROJECT_ID, REGION, CLUSTER_NAME)
+    operation = cluster_client.delete_cluster(PROJECT_ID, REGION, CLUSTER_NAME)
+    # Wait for cluster to delete
+    operation.result()
 
 
 def test_cluster_create(capsys):

samples/snippets/quickstart/quickstart.py

@@ -0,0 +1,128 @@
+#!/usr/bin/env python
+
+# Copyright 2019 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.
+
+# [START dataproc_quickstart]
+import time
+
+from google.cloud import dataproc_v1 as dataproc
+from google.cloud import storage
+
+
+def quickstart(project_id, region, cluster_name, job_file_path):
+    """This quickstart sample walks a user through creating a Cloud Dataproc
+       cluster, submitting a PySpark job from Google Cloud Storage to the
+       cluster, reading the output of the job and deleting the cluster, all
+       using the Python client library.
+
+       Args:
+           project_id (string): Project to use for creating resources.
+           region (string): Region where the resources should live.
+           cluster_name (string): Name to use for creating a cluster.
+           job_file_path (string): Job in GCS to execute against the cluster.
+    """
+
+    # Create the cluster client.
+    cluster_client = dataproc.ClusterControllerClient(client_options={
+        'api_endpoint': '{}-dataproc.googleapis.com:443'.format(region)
+    })
+
+    # Create the cluster config.
+    cluster = {
+        'project_id': project_id,
+        'cluster_name': cluster_name,
+        'config': {
+            'master_config': {
+                'num_instances': 1,
+                'machine_type_uri': 'n1-standard-1'
+            },
+            'worker_config': {
+                'num_instances': 2,
+                'machine_type_uri': 'n1-standard-1'
+            }
+        }
+    }
+
+    # Create the cluster.
+    operation = cluster_client.create_cluster(project_id, region, cluster)
+    result = operation.result()
+
+    print('Cluster created successfully: {}'.format(result.cluster_name))
+
+    # Create the job client.
+    job_client = dataproc.JobControllerClient(client_options={
+        'api_endpoint': '{}-dataproc.googleapis.com:443'.format(region)
+    })
+
+    # Create the job config.
+    job = {
+        'placement': {
+            'cluster_name': cluster_name
+        },
+        'pyspark_job': {
+            'main_python_file_uri': job_file_path
+        }
+    }
+
+    job_response = job_client.submit_job(project_id, region, job)
+    job_id = job_response.reference.job_id
+
+    print('Submitted job \"{}\".'.format(job_id))
+
+    # Termimal states for a job.
+    terminal_states = {
+        dataproc.types.JobStatus.ERROR,
+        dataproc.types.JobStatus.CANCELLED,
+        dataproc.types.JobStatus.DONE
+    }
+
+    # Create a timeout such that the job gets cancelled if not in a
+    # terminal state after a fixed period of time.
+    timeout_seconds = 600
+    time_start = time.time()
+
+    # Wait for the job to complete.
+    while job_response.status.state not in terminal_states:
+        if time.time() > time_start + timeout_seconds:
+            job_client.cancel_job(project_id, region, job_id)
+            print('Job {} timed out after threshold of {} seconds.'.format(
+                job_id, timeout_seconds))
+
+        # Poll for job termination once a second.
+        time.sleep(1)
+        job_response = job_client.get_job(project_id, region, job_id)
+
+    # Cloud Dataproc job output gets saved to a GCS bucket allocated to it.
+    cluster_info = cluster_client.get_cluster(
+        project_id, region, cluster_name)
+
+    storage_client = storage.Client()
+    bucket = storage_client.get_bucket(cluster_info.config.config_bucket)
+    output_blob = (
+        'google-cloud-dataproc-metainfo/{}/jobs/{}/driveroutput.000000000'
+        .format(cluster_info.cluster_uuid, job_id))
+    output = bucket.blob(output_blob).download_as_string()
+
+    print('Job {} finished with state {}:\n{}'.format(
+        job_id,
+        job_response.status.State.Name(job_response.status.state),
+        output))
+
+    # Delete the cluster once the job has terminated.
+    operation = cluster_client.delete_cluster(project_id, region, cluster_name)
+    operation.result()
+
+    print('Cluster {} successfully deleted.'.format(cluster_name))
+    # [END dataproc_quickstart]

samples/snippets/quickstart/quickstart_test.py

@@ -0,0 +1,70 @@
+# Copyright 2019 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 uuid
+import pytest
+
+from google.cloud import dataproc_v1 as dataproc
+from google.cloud import storage
+
+import quickstart
+
+
+PROJECT_ID = os.environ['GCLOUD_PROJECT']
+REGION = 'us-central1'
+CLUSTER_NAME = 'py-qs-test-{}'.format(str(uuid.uuid4()))
+STAGING_BUCKET = 'py-dataproc-qs-bucket-{}'.format(str(uuid.uuid4()))
+JOB_FILE_NAME = 'sum.py'
+JOB_FILE_PATH = 'gs://{}/{}'.format(STAGING_BUCKET, JOB_FILE_NAME)
+SORT_CODE = (
+  "import pyspark\n"
+  "sc = pyspark.SparkContext()\n"
+  "rdd = sc.parallelize((1,2,3,4,5))\n"
+  "sum = rdd.reduce(lambda x, y: x + y)\n"
+)
+
+
+@pytest.fixture(autouse=True)
+def setup_teardown():
+    storage_client = storage.Client()
+    bucket = storage_client.create_bucket(STAGING_BUCKET)
+    blob = bucket.blob(JOB_FILE_NAME)
+    blob.upload_from_string(SORT_CODE)
+
+    yield
+
+    cluster_client = dataproc.ClusterControllerClient(client_options={
+      'api_endpoint': '{}-dataproc.googleapis.com:443'.format(REGION)
+    })
+
+    # The quickstart sample deletes the cluster, but if the test fails
+    # before cluster deletion occurs, it can be manually deleted here.
+    clusters = cluster_client.list_clusters(PROJECT_ID, REGION)
+
+    for cluster in clusters:
+        if cluster.cluster_name == CLUSTER_NAME:
+            cluster_client.delete_cluster(PROJECT_ID, REGION, CLUSTER_NAME)
+
+    blob.delete()
+
+
+def test_quickstart(capsys):
+    quickstart.quickstart(PROJECT_ID, REGION, CLUSTER_NAME, JOB_FILE_PATH)
+
+    out, _ = capsys.readouterr()
+    assert 'Cluster created successfully' in out
+    assert 'Submitted job' in out
+    assert 'finished with state DONE:' in out
+    assert 'successfully deleted' in out