#Airflow dag decorator how to
#Airflow dag decorator code

#Airflow dag decorator code

The code in Image 2 is very simple, but illustrates the point of where to put circuit breakers in your pipeline. Image 2: Example Airflow circuit breaker code using the Airflow ShortCircuitOperator. When the data trips the always_false_circuit, example_elt_job_2 will be skipped. In Image 1, above, we have a simple DAG with two circuit breakers always_false and always_true between example_elt_job_1 and example_elt_job_2. Image 1: Example Airflow ShortCircuitOperator circuit breaker DAG. This means that while they can prevent data issues from occurring, the AirflowShortCircuitOperator can also wreak havoc on your pipeline with delayed jobs creating chain reactions of data failures downstream. This is also happening in your pipeline completely automatically – it’s not like you’re comparing results in a console or looking at a spreadsheet.

The reason for this is the Airflow ShortCircuitOperator, by design, introduces data downtime when the circuit breaker is tripped and needs to be reset. You should also only leverage circuit breakers when you completely understand the history and what types of incidents and thresholds constitute a trigger.įor example, a data model requiring absolutely no null columns could be an ideal circuit breaker, but if some small range of null columns were acceptable, that’s likely a poor circuit breaker. Airflow circuit breaker challengesĬircuit breakers leveraging the Airflow ShortCircuitOperator should be the most critical of your tests from the underlying query operation and only consist of the most well-defined logic that mandates your pipeline should stop running. This task in the DAG is green, but nothing updated in the underlying table because of the bogus query in example_job_2. While data circuit breakers are most frequently used to prevent bad data from entering the storage layer, they can be deployed at multiple stages prior to the BI dashboards being updated– between transformation steps or after an ETL or ELT job executes, for example. When the data does not meet your defined quality or integrity thresholds in your Airflow DAG the pipeline is stopped, preventing a worse outcome, like a CEO getting bad information, from occurring.

When the breaker encounters those electrical incidents it breaks the current to prevent an even worse issue, like a fire, from occurring.ĭata circuit breakers are essentially data tests on steroids and the philosophy is the same. In electrical engineering, a circuit breaker is a safety device that protects your home from damage caused by an overcurrent or a short.

What is an Airflow circuit breaker and how do they help with data reliability? How data observability platforms helps with Airflow circuit breaker implementation.

#Airflow dag decorator how to

How to build a circuit breaker using the ShortCircuitOperator within Airflow DAGs.What is an Airflow circuit breaker and how do they help with data reliability?.Otherwise, you can make a bad problem worse. One helpful but underutilized solution is to leverage the Airflow ShortCircuitOperator to create data circuit breakers to prevent bad data from flowing across your data pipelines.ĭata circuit breakers are powerful, but as with most data quality tactics, the nuances of how they are implemented are critical. I’m a huge fan of Apache Airflow and how the open source tool enables data engineers to scale data pipelines by more precisely orchestrating workloads.īut what happens when Airflow testing doesn’t catch all of your bad data? What if “unknown unknown” data quality issues fall through the cracks and affect your Airflow jobs?