Add ability to create Flink Jobs in dataproc cluster

airflow/providers/google/provider.yaml

@@ -125,7 +125,7 @@ dependencies:
   - google-cloud-dataflow-client>=0.8.6
   - google-cloud-dataform>=0.5.0
   - google-cloud-dataplex>=1.10.0
-  - google-cloud-dataproc>=5.8.0
+  - google-cloud-dataproc>=5.12.0
   - google-cloud-dataproc-metastore>=1.12.0
   - google-cloud-dlp>=3.12.0
   - google-cloud-kms>=2.15.0

docs/apache-airflow-providers-google/operators/cloud/dataproc.rst

@@ -249,7 +249,7 @@ Submit a job to a cluster
 -------------------------
 
 Dataproc supports submitting jobs of different big data components.
-The list currently includes Spark, Hadoop, Pig and Hive.
+The list currently includes Spark, PySpark, Hadoop, Trino, Pig, Flink and Hive.
 For more information on versions and images take a look at `Cloud Dataproc Image version list <https://cloud.google.com/dataproc/docs/concepts/versioning/dataproc-versions>`__
 
 To submit a job to the cluster you need to provide a job source file. The job source file can be on GCS, the cluster or on your local
@@ -351,6 +351,14 @@ Example of the configuration for a Trino Job:
     :start-after: [START how_to_cloud_dataproc_trino_config]
     :end-before: [END how_to_cloud_dataproc_trino_config]
 
+Example of the configuration for a Flink Job:
+
+.. exampleinclude:: /../../tests/system/providers/google/cloud/dataproc/example_dataproc_flink.py
+    :language: python
+    :dedent: 0
+    :start-after: [START how_to_cloud_dataproc_flink_config]
+    :end-before: [END how_to_cloud_dataproc_flink_config]
+
 Working with workflows templates
 --------------------------------
 

generated/provider_dependencies.json

@@ -645,7 +645,7 @@
       "google-cloud-dataform>=0.5.0",
       "google-cloud-dataplex>=1.10.0",
       "google-cloud-dataproc-metastore>=1.12.0",
-      "google-cloud-dataproc>=5.8.0",
+      "google-cloud-dataproc>=5.12.0",
       "google-cloud-dlp>=3.12.0",
       "google-cloud-kms>=2.15.0",
       "google-cloud-language>=2.9.0",

tests/system/providers/google/cloud/dataproc/example_dataproc_flink.py

@@ -0,0 +1,135 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you 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.
+"""
+Example Airflow DAG for DataprocSubmitJobOperator with hadoop job.
+"""
+
+from __future__ import annotations
+
+import os
+from datetime import datetime
+
+from google.api_core.retry import Retry
+
+from airflow.models.dag import DAG
+from airflow.providers.google.cloud.operators.dataproc import (
+    DataprocCreateClusterOperator,
+    DataprocDeleteClusterOperator,
+    DataprocSubmitJobOperator,
+)
+from airflow.providers.google.cloud.operators.gcs import GCSCreateBucketOperator, GCSDeleteBucketOperator
+from airflow.utils.trigger_rule import TriggerRule
+from tests.system.providers.google import DEFAULT_GCP_SYSTEM_TEST_PROJECT_ID
+
+ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID", "default")
+DAG_ID = "dataproc_flink"
+PROJECT_ID = os.environ.get("SYSTEM_TESTS_GCP_PROJECT") or DEFAULT_GCP_SYSTEM_TEST_PROJECT_ID
+
+BUCKET_NAME = f"bucket_{DAG_ID}_{ENV_ID}"
+CLUSTER_NAME_BASE = f"cluster-{DAG_ID}".replace("_", "-")
+CLUSTER_NAME_FULL = CLUSTER_NAME_BASE + f"-{ENV_ID}".replace("_", "-")
+CLUSTER_NAME = CLUSTER_NAME_BASE if len(CLUSTER_NAME_FULL) >= 33 else CLUSTER_NAME_FULL
+REGION = "europe-west1"
+
+OUTPUT_FOLDER = "wordcount"
+OUTPUT_PATH = f"gs://{BUCKET_NAME}/{OUTPUT_FOLDER}/"
+
+# Cluster definition
+CLUSTER_CONFIG = {
+    "master_config": {
+        "num_instances": 1,
+        "machine_type_uri": "n1-standard-4",
+        "disk_config": {"boot_disk_type": "pd-standard", "boot_disk_size_gb": 32},
+    },
+    "software_config": {"image_version": "2.2-debian12", "properties": {}, "optional_components": ["FLINK"]},
+    "worker_config": {
+        "num_instances": 3,
+        "machine_type_uri": "n1-standard-4",
+        "disk_config": {"boot_disk_type": "pd-standard", "boot_disk_size_gb": 32},
+    },
+}
+
+# Jobs definitions
+# [START how_to_cloud_dataproc_flink_config]
+FLINK_JOB = {
+    "reference": {"project_id": PROJECT_ID},
+    "placement": {"cluster_name": CLUSTER_NAME},
+    "flink_job": {
+        "main_class": "org.apache.flink.examples.java.wordcount.WordCount",
+        "jar_file_uris": ["file:///usr/lib/flink/examples/batch/WordCount.jar"],
+    },
+}
+# [END how_to_cloud_dataproc_flink_config]
+
+
+with DAG(
+    DAG_ID,
+    schedule="@once",
+    start_date=datetime(2021, 1, 1),
+    catchup=False,
+    tags=["example", "dataproc", "hadoop"],
+) as dag:
+    create_bucket = GCSCreateBucketOperator(
+        task_id="create_bucket", bucket_name=BUCKET_NAME, project_id=PROJECT_ID
+    )
+
+    create_cluster = DataprocCreateClusterOperator(
+        task_id="create_cluster",
+        project_id=PROJECT_ID,
+        cluster_config=CLUSTER_CONFIG,
+        region=REGION,
+        cluster_name=CLUSTER_NAME,
+        retry=Retry(maximum=100.0, initial=10.0, multiplier=1.0),
+    )
+
+    flink_task = DataprocSubmitJobOperator(
+        task_id="hadoop_task", job=FLINK_JOB, region=REGION, project_id=PROJECT_ID
+    )
+
+    delete_cluster = DataprocDeleteClusterOperator(
+        task_id="delete_cluster",
+        project_id=PROJECT_ID,
+        cluster_name=CLUSTER_NAME,
+        region=REGION,
+        trigger_rule=TriggerRule.ALL_DONE,
+    )
+
+    delete_bucket = GCSDeleteBucketOperator(
+        task_id="delete_bucket", bucket_name=BUCKET_NAME, trigger_rule=TriggerRule.ALL_DONE
+    )
+
+    (
+        # TEST SETUP
+        [create_bucket, create_cluster]
+        # TEST BODY
+        >> flink_task
+        # TEST TEARDOWN
+        >> [delete_cluster, delete_bucket]
+    )
+
+    from tests.system.utils.watcher import watcher
+
+    # This test needs watcher in order to properly mark success/failure
+    # when "teardown" task with trigger rule is part of the DAG
+    list(dag.tasks) >> watcher()
+
+
+from tests.system.utils import get_test_run  # noqa: E402
+
+# Needed to run the example DAG with pytest (see: tests/system/README.md#run_via_pytest)
+test_run = get_test_run(dag)