12/9/2023 0 Comments Airflow github examplesfrom _rule import TriggerRuleįrom _operator import BranchPythonOperatorĬonditional_t_upstream(task_start) a Considered a failure in the ETL, conditional would be helpful, in order to run the scale in regardless of the success or failure of the ETL. say you want to scale out BEFORE the ETL, and scale in AFTER the ETL. When should you use this case? for example you a dataproc cluster or EMR cluster, and you have an ETL. I wrote an as simple example, you can check it out in github: You need to use trigger rules , as each task has a trigger by default to success. #create_dataproc_cluster > run_dataproc_hadoop > delete_dataproc_cluster Write_disposition='WRITE_TRUNCATE', #overwrite?ĭestination_project_dataset_table='DATA.Replica_android_review' Load_to_bq_from_gcs = gcs_to_bq.GoogleCloudStorageToBigQueryOperator( #load from local bucket o GCS table of android # and then encoding the files to UTF8 to load to BQ (UTF8 is not supported yet. using bash to copy the files to DST_BUCKET # source bucekt is not in out project, and there permission issues with IT. no need to add gs://ĭST_BUCKET = ('pubsite_prod_rev/reviews')ĭST_BUCKET_UTF8 = ('pubsite_prod_rev_ingestion/reviews_utf8') #from airflow.operators import BashOperatorįrom import gcs_to_gcs Schedule_interval=datetime.timedelta(days=1),įrom import bigquery_to_gcsįrom import gcs_to_bqįrom airflow.operators import dummy_operator 'retry_delay': datetime.timedelta(minutes=5), # If a task fails, retry it once after waiting at least 5 minutes # To email on failure or retry set 'email' arg to your email and enable # Setting start date as yesterday starts the DAG immediately when it is Table_name = 'DATA_LAKE_INGESTION_US.Daily_Stats'ĭ() - datetime.timedelta(1), #table_name = 'omid.test_results' + '$' + today_date From _operator import BigQueryOperatorįrom _operator import DummyOperator
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |