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Posted to commits@airflow.apache.org by GitBox <gi...@apache.org> on 2019/10/19 17:28:05 UTC
[GitHub] [airflow] nuclearpinguin commented on a change in pull request
#6371: [AIRFLOW-5691] Rewrite Dataproc operators to use python library
nuclearpinguin commented on a change in pull request #6371: [AIRFLOW-5691] Rewrite Dataproc operators to use python library
URL: https://github.com/apache/airflow/pull/6371#discussion_r336746250
##########
File path: airflow/gcp/example_dags/example_dataproc.py
##########
@@ -41,69 +40,130 @@
PYSPARK_MAIN = os.environ.get("PYSPARK_MAIN", "hello_world.py")
PYSPARK_URI = "gs://{}/{}".format(BUCKET, PYSPARK_MAIN)
+
+# Cluster definition
+CLUSTER = {
+ "project_id": PROJECT_ID,
+ "cluster_name": CLUSTER_NAME,
+ "config": {
+ "master_config": {
+ "num_instances": 1,
+ "machine_type_uri": "n1-standard-4",
+ "disk_config": {"boot_disk_type": "pd-standard", "boot_disk_size_gb": 1024},
+ },
+ "worker_config": {
+ "num_instances": 2,
+ "machine_type_uri": "n1-standard-4",
+ "disk_config": {"boot_disk_type": "pd-standard", "boot_disk_size_gb": 1024},
+ },
+ },
+}
+
+
+# Update options
+CLUSTER_UPDATE = {
+ "config": {
+ "worker_config": {"num_instances": 3},
+ "secondary_worker_config": {"num_instances": 3},
+ }
+}
+UPDATE_MASK = {
+ "paths": [
+ "config.worker_config.num_instances",
+ "config.secondary_worker_config.num_instances",
+ ]
+}
+
+TIMEOUT = {"seconds": 1 * 24 * 60 * 60}
+
+
+# Jobs definitions
+PIG_JOB = {
+ "reference": {"project_id": PROJECT_ID},
+ "placement": {"cluster_name": CLUSTER_NAME},
+ "pig_job": {"query_list": {"queries": ["define sin HiveUDF('sin');"]}},
+}
+
+SPARK_SQL_JOB = {
+ "reference": {"project_id": PROJECT_ID},
+ "placement": {"cluster_name": CLUSTER_NAME},
+ "spark_sql_job": {"query_list": {"queries": ["SHOW DATABASES;"]}},
+}
+
+SPARK_JOB = {
+ "reference": {"project_id": PROJECT_ID},
+ "placement": {"cluster_name": CLUSTER_NAME},
+ "spark_job": {
+ "jar_file_uris": ["file:///usr/lib/spark/examples/jars/spark-examples.jar"],
+ "main_class": "org.apache.spark.examples.SparkPi",
+ },
+}
+
+PYSPARK_JOB = {
+ "reference": {"project_id": PROJECT_ID},
+ "placement": {"cluster_name": CLUSTER_NAME},
+ "pyspark_job": {"main_python_file_uri": PYSPARK_URI},
+}
+
+HIVE_JOB = {
+ "reference": {"project_id": PROJECT_ID},
+ "placement": {"cluster_name": CLUSTER_NAME},
+ "hive_job": {"query_list": {"queries": ["SHOW DATABASES;"]}},
+}
+
+HADOOP_JOB = {
+ "reference": {"project_id": PROJECT_ID},
+ "placement": {"cluster_name": CLUSTER_NAME},
+ "hadoop_job": {
+ "main_jar_file_uri": "file:///usr/lib/hadoop-mapreduce/hadoop-mapreduce-examples.jar",
+ "args": ["wordcount", "gs://pub/shakespeare/rose.txt", OUTPUT_PATH],
+ },
+}
+
with models.DAG(
"example_gcp_dataproc",
default_args={"start_date": airflow.utils.dates.days_ago(1)},
schedule_interval=None,
) as dag:
create_cluster = DataprocClusterCreateOperator(
- task_id="create_cluster",
- cluster_name=CLUSTER_NAME,
- project_id=PROJECT_ID,
- num_workers=2,
- region=REGION,
+ task_id="create_cluster", project_id=PROJECT_ID, cluster=CLUSTER, region=REGION
Review comment:
Yes, that was how I checked backwards compatibility. Channing example DAG was last thing I did. If you wish I can change the DAG in separate PR.
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