Menu
In the airflow tutorial, the BashOperators have output (via echo). If the task runs in the scheduler, where do you view the output? Is there a console or something? I'm sure I'm just not looking in the right place.
307
If you run Airflow locally, logging information will be accessible in the following locations: Scheduler logs are printed to the console and accessible in $AIRFLOW_HOME/logs/scheduler . Webserver and Triggerer logs are printed to the console. Task logs can be viewed either in the Airflow UI or at $AIRFLOW_HOME/logs/ .
Users can specify the directory to place log files in airflow. cfg using base_log_folder . By default, logs are placed in the AIRFLOW_HOME directory.
Create a subdirectory called dags in your main project directory and move your DAG there. Then refresh the Airflow UI and you should be able to see it.
Start by grabbing the task_ids and state of the task you're interested in with a db call. That should give you the state (and name, for reference) of the task you're trying to monitor. State is stored as a simple lowercase string.
See Modules Management for details on how Python and Airflow manage modules. Most task handlers send logs upon completion of a task. In order to view logs in real time, airflow automatically starts an http server to serve the logs in the following cases: If SchedulerExecutor or LocalExecutor is used, then when airflow scheduler is running.
Airflow writes logs for tasks in a way that allows to see the logs for each task separately via Airflow UI. The Core Airflow implements writing and serving logs locally. However you can also write logs to remote services - via community providers, but you can also write your own loggers.
To start the airflow job scheduler, simply run the command: The DAG runs represent the instantiation of DAG in form of an object that is used for Airflow Job Scheduling. since DAG may or may not have a schedule, which informs how DAG RUNS are created.
The Airflow UI makes it easy to monitor and troubleshoot your data pipelines. Here’s a quick overview of some of the features and visualizations you can find in the Airflow UI. List of the DAGs in your environment, and a set of shortcuts to useful pages. You can see exactly how many tasks succeeded, failed, or are currently running at a glance.
Like @tobi6 said, you can view the output from your DAG runs in your webserver or in your console depending on the environment.
To do so in your webserver:
Graph View.View Log.If you want to view the logs from your run, you do so in your airflow_home directory.
Users can specify a logs folder in airflow.cfg. By default, it is in the AIRFLOW_HOME directory.
In addition, users can supply a remote location for storing logs and log backups in cloud storage. At this time, Amazon S3 and Google Cloud Storage are supported. To enable this feature, airflow.cfg must be configured as in this example:
[core] # Airflow can store logs remotely in AWS S3 or Google Cloud Storage. Users # must supply a remote location URL (starting with either 's3://...' or # 'gs://...') and an Airflow connection id that provides access to the storage # location. remote_base_log_folder = s3://my-bucket/path/to/logs remote_log_conn_id = MyS3Conn # Use server-side encryption for logs stored in S3 encrypt_s3_logs = False Remote logging uses an existing Airflow connection to read/write logs. If you don’t have a connection properly setup, this will fail.In the above example, Airflow will try to use S3Hook('MyS3Conn').
In the Airflow Web UI, local logs take precedance over remote logs. If local logs can not be found or accessed, the remote logs will be displayed. Note that logs are only sent to remote storage once a task completes (including failure). In other words, remote logs for running tasks are unavailable. Logs are stored in the log folder as {dag_id}/{task_id}/{execution_date}/{try_number}.log.
105
If a task is in Airflow, here is how to find its logs in the web UI:
Click on the task run
Click on "View Log" button in the pop-up that opens
42
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With
