针对该问题,可以使用Airflow DAG来实现。具体实现方式为:首先使用Google Cloud Storage Hook连接到Google Cloud Storage,并使用BashOperator执行Shell脚本,将非空的CSV文件插入到BigQuery中;同时使用PythonOperator,结合GCS存储桶监听器,在发现空的CSV文件时将其移动到归档桶中。以下是对应的代码示例:
from airflow import DAG
from datetime import datetime, timedelta
from airflow.contrib.hooks.gcs_hook import GoogleCloudStorageHook
from airflow.operators.bash_operator import BashOperator
from airflow.operators.python_operator import PythonOperator
default_args = {
'owner': 'airflow',
'depends_on_past': False,
'start_date': datetime(2021, 7, 1),
'email_on_failure': False,
'email_on_retry': False,
'retries': 1,
'retry_delay': timedelta(minutes=5),
}
dag = DAG(
'move_csv_to_gcs_and_bigquery',
default_args=default_args,
description='Moving empty CSV files to archive bucket and inserting non-empty files into BigQuery',
schedule_interval=timedelta(hours=1),
)
gcs_hook = GoogleCloudStorageHook()
def move_empty_csv_to_archive_bucket(file_path: str, **kwargs):
if gcs_hook.exists(file_path):
file_size = gcs_hook.get_size(file_path)
if file_size == 0:
archive_bucket = kwargs['bucket_name']
archive_file_path = file_path.replace(kwargs['gcs_prefix'], '')
gcs_hook.copy(kwargs['bucket_name'], file_path, archive_bucket, archive_file_path)
gcs_hook.delete(file_path)
move_csv_to_gcs = BashOperator(
task_id='move_csv_to_gcs',
bash_command='gsutil mv /path/to/local/files/*.csv gs://{}/{}'.format(your_bucket_name, your_gcs_prefix),
dag=dag,
)
insert_csv_into_bigquery = BashOperator(
task_id='insert_csv_into_bigquery',
bash_command='bq load --autodetect --source_format=CSV your_dataset.your_table gs://{}/{}'.format(your_bucket_name, your_gcs_prefix),
dag=dag,
)
watch_for_empty_files = PythonOperator(
task_id='watch_for_empty_files',
python_callable=move_empty_csv_to_archive_bucket,
op_kwargs={
'file_path': 'gs://{}/{}'.format(your_bucket_name, your_gcs_prefix),
'bucket_name': your_archive_bucket_name,
'gcs_prefix': your_gcs_prefix,
},
dag=dag,
)
move_csv_to_gcs >> insert_csv_into_bigquery >> watch_for_empty_files