mikezucc
diff --git a/‎dataproc/README.md
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+8-3Lines changed: 8 additions & 3 deletions b/‎dataproc/README.md
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+8-3Lines changed: 8 additions & 3 deletions
diff --git a/‎dataproc/dataproc_e2e_test.py
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+2-2Lines changed: 2 additions & 2 deletions b/‎dataproc/dataproc_e2e_test.py
Copy file name to clipboardExpand all lines: dataproc/dataproc_e2e_test.py
+2-2Lines changed: 2 additions & 2 deletions
diff --git a/‎dataproc/create_cluster_and_submit_job.py renamed to ‎dataproc/submit_job_to_cluster.py
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+51-30Lines changed: 51 additions & 30 deletions b/‎dataproc/create_cluster_and_submit_job.py renamed to ‎dataproc/submit_job_to_cluster.py
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+51-30Lines changed: 51 additions & 30 deletions
@@ -35,14 +35,19 @@ To run list_clusters.py:
     python list_clusters.py <YOUR-PROJECT-ID> --region=us-central1
 
 
-To run create_cluster_and_submit_job, first create a GCS bucket, from the Cloud Console or with
+To run submit_job_to_cluster.py, first create a GCS bucket, from the Cloud Console or with
 gsutil:
 
     gsutil mb gs://<your-input-bucket-name>
 
-Then run:
+Then, if you want to rely on an existing cluster, run:
 
-    python create_cluster_and_submit_job.py --project_id=<your-project-id> --zone=us-central1-b --cluster_name=testcluster --gcs_bucket=<your-input-bucket-name>
+    python submit_job_to_cluster.py --project_id=<your-project-id> --zone=us-central1-b --cluster_name=testcluster --gcs_bucket=<your-input-bucket-name>
+    
+Otherwise, if you want the script to create a new cluster for you:
+
+    python submit_job_to_cluster.py --project_id=<your-project-id> --zone=us-central1-b --cluster_name=testcluster --gcs_bucket=<your-input-bucket-name> --create_new_cluster
+
 
 This will setup a cluster, upload the PySpark file, submit the job, print the result, then
 delete the cluster.
 
@@ -20,7 +20,7 @@
 
 from gcp_devrel.testing.flaky import flaky
 
-import create_cluster_and_submit_job
+import submit_job_to_cluster
 
 PROJECT = os.environ['GCLOUD_PROJECT']
 BUCKET = os.environ['CLOUD_STORAGE_BUCKET']
@@ -30,6 +30,6 @@
 
 @flaky
 def test_e2e():
-    output = create_cluster_and_submit_job.main(
+    output = submit_job_to_cluster.main(
         PROJECT, ZONE, CLUSTER_NAME, BUCKET)
     assert b"['Hello,', 'dog', 'elephant', 'panther', 'world!']" in output
@@ -19,8 +19,6 @@
 from google.cloud import storage
 import googleapiclient.discovery
 
-# Currently only the "global" region is supported
-REGION = 'global'
 DEFAULT_FILENAME = 'pyspark_sort.py'
 
 
@@ -36,6 +34,14 @@ def get_pyspark_file(filename):
     return f, os.path.basename(filename)
 
 
+def get_region_from_zone(zone):
+    try:
+        region_as_list = zone.split('-')[:-1]
+        return '-'.join(region_as_list)
+    except (AttributeError, IndexError, ValueError):
+        raise ValueError('Invalid zone provided, please check your input.')
+
+
 def upload_pyspark_file(project_id, bucket_name, filename, file):
     """Uploads the PySpark file in this directory to the configured
     input bucket."""
@@ -59,8 +65,8 @@ def download_output(project_id, cluster_id, output_bucket, job_id):
 
 
 # [START create_cluster]
-def create_cluster(dataproc, project, cluster_name, zone):
-    print('Creating cluster.')
+def create_cluster(dataproc, project, zone, region, cluster_name):
+    print('Creating cluster...')
     zone_uri = \
         'https://www.googleapis.com/compute/v1/projects/{}/zones/{}'.format(
             project, zone)
@@ -75,19 +81,19 @@ def create_cluster(dataproc, project, cluster_name, zone):
     }
     result = dataproc.projects().regions().clusters().create(
         projectId=project,
-        region=REGION,
+        region=region,
         body=cluster_data).execute()
     return result
 # [END create_cluster]
 
 
-def wait_for_cluster_creation(dataproc, project_id, cluster_name, zone):
-    print('Waiting for cluster creation')
+def wait_for_cluster_creation(dataproc, project_id, region, cluster_name):
+    print('Waiting for cluster creation...')
 
     while True:
         result = dataproc.projects().regions().clusters().list(
             projectId=project_id,
-            region=REGION).execute()
+            region=region).execute()
         cluster_list = result['clusters']
         cluster = [c
                    for c in cluster_list
@@ -100,10 +106,10 @@ def wait_for_cluster_creation(dataproc, project_id, cluster_name, zone):
 
 
 # [START list_clusters_with_detail]
-def list_clusters_with_details(dataproc, project):
+def list_clusters_with_details(dataproc, project, region):
     result = dataproc.projects().regions().clusters().list(
         projectId=project,
-        region=REGION).execute()
+        region=region).execute()
     cluster_list = result['clusters']
     for cluster in cluster_list:
         print("{} - {}"
@@ -120,7 +126,8 @@ def get_cluster_id_by_name(cluster_list, cluster_name):
 
 
 # [START submit_pyspark_job]
-def submit_pyspark_job(dataproc, project, cluster_name, bucket_name, filename):
+def submit_pyspark_job(dataproc, project, region,
+                       cluster_name, bucket_name, filename):
     """Submits the Pyspark job to the cluster, assuming `filename` has
     already been uploaded to `bucket_name`"""
     job_details = {
@@ -136,7 +143,7 @@ def submit_pyspark_job(dataproc, project, cluster_name, bucket_name, filename):
     }
     result = dataproc.projects().regions().jobs().submit(
         projectId=project,
-        region=REGION,
+        region=region,
         body=job_details).execute()
     job_id = result['reference']['jobId']
     print('Submitted job ID {}'.format(job_id))
@@ -145,29 +152,29 @@ def submit_pyspark_job(dataproc, project, cluster_name, bucket_name, filename):
 
 
 # [START delete]
-def delete_cluster(dataproc, project, cluster):
+def delete_cluster(dataproc, project, region, cluster):
     print('Tearing down cluster')
     result = dataproc.projects().regions().clusters().delete(
         projectId=project,
-        region=REGION,
+        region=region,
         clusterName=cluster).execute()
     return result
 # [END delete]
 
 
 # [START wait]
-def wait_for_job(dataproc, project, job_id):
+def wait_for_job(dataproc, project, region, job_id):
     print('Waiting for job to finish...')
     while True:
         result = dataproc.projects().regions().jobs().get(
             projectId=project,
-            region=REGION,
+            region=region,
             jobId=job_id).execute()
         # Handle exceptions
         if result['status']['state'] == 'ERROR':
             raise Exception(result['status']['details'])
         elif result['status']['state'] == 'DONE':
-            print('Job finished')
+            print('Job finished.')
             return result
 # [END wait]
 
@@ -181,34 +188,44 @@ def get_client():
 # [END get_client]
 
 
-def main(project_id, zone, cluster_name, bucket_name, pyspark_file=None):
+def main(project_id, zone, cluster_name, bucket_name,
+         pyspark_file=None, create_new_cluster=True):
     dataproc = get_client()
+    region = get_region_from_zone(zone)
     try:
         if pyspark_file:
             spark_file, spark_filename = get_pyspark_file(pyspark_file)
         else:
             spark_file, spark_filename = get_default_pyspark_file()
 
-        create_cluster(dataproc, project_id, cluster_name, zone)
-        wait_for_cluster_creation(dataproc, project_id, cluster_name, zone)
-        upload_pyspark_file(project_id, bucket_name,
-                            spark_filename, spark_file)
+        if create_new_cluster:
+            create_cluster(
+                dataproc, project_id, zone, region, cluster_name)
+            wait_for_cluster_creation(
+                dataproc, project_id, region, cluster_name)
+
+        upload_pyspark_file(
+            project_id, bucket_name, spark_filename, spark_file)
+
         cluster_list = list_clusters_with_details(
-            dataproc, project_id)['clusters']
+            dataproc, project_id, region)['clusters']
 
         (cluster_id, output_bucket) = (
             get_cluster_id_by_name(cluster_list, cluster_name))
+
         # [START call_submit_pyspark_job]
         job_id = submit_pyspark_job(
-            dataproc, project_id, cluster_name, bucket_name, spark_filename)
+            dataproc, project_id, region,
+            cluster_name, bucket_name, spark_filename)
         # [END call_submit_pyspark_job]
-        wait_for_job(dataproc, project_id, job_id)
+        wait_for_job(dataproc, project_id, region, job_id)
 
         output = download_output(project_id, cluster_id, output_bucket, job_id)
         print('Received job output {}'.format(output))
         return output
     finally:
-        delete_cluster(dataproc, project_id, cluster_name)
+        if create_new_cluster:
+            delete_cluster(dataproc, project_id, region, cluster_name)
         spark_file.close()
 
 
@@ -220,15 +237,19 @@ def main(project_id, zone, cluster_name, bucket_name, pyspark_file=None):
     parser.add_argument(
         '--project_id', help='Project ID you want to access.', required=True),
     parser.add_argument(
-        '--zone', help='Region to create clusters in', required=True)
+        '--zone', help='Zone to create clusters in/connect to', required=True)
     parser.add_argument(
-        '--cluster_name', help='Name of the cluster to create', required=True)
+        '--cluster_name',
+        help='Name of the cluster to create/connect to', required=True)
     parser.add_argument(
         '--gcs_bucket', help='Bucket to upload Pyspark file to', required=True)
     parser.add_argument(
         '--pyspark_file', help='Pyspark filename. Defaults to pyspark_sort.py')
+    parser.add_argument(
+        '--create_new_cluster',
+        action='store_true', help='States if the cluster should be created')
 
     args = parser.parse_args()
     main(
-        args.project_id, args.zone,
-        args.cluster_name, args.gcs_bucket, args.pyspark_file)
+        args.project_id, args.zone, args.cluster_name,
+        args.gcs_bucket, args.pyspark_file, args.create_new_cluster)