AWS Batch¶

AWS Batch enables you to run batch computing workloads on the AWS Cloud. Batch computing is a common way for developers, scientists, and engineers to access large amounts of compute resources. AWS Batch removes the undifferentiated heavy lifting of configuring and managing the required infrastructure.

Prerequisite Tasks¶

To use these operators, you must do a few things:

Create necessary resources using AWS Console or AWS CLI.
Install API libraries via pip.
pip install 'apache-airflow[amazon]'
Detailed information is available Installation
Setup Connection.

Operators¶

Submit a new AWS Batch job¶

To submit a new AWS Batch job and monitor it until it reaches a terminal state you can use BatchOperator.

airflow/providers/amazon/aws/example_dags/example_batch.py[source]

submit_batch_job = BatchOperator(
    task_id='submit_batch_job',
    job_name=JOB_NAME,
    job_queue=JOB_QUEUE,
    job_definition=JOB_DEFINITION,
    overrides=JOB_OVERRIDES,
)

Sensors¶

Wait on an AWS Batch job state¶

To wait on the state of an AWS Batch Job until it reaches a terminal state you can use BatchSensor.

airflow/providers/amazon/aws/example_dags/example_batch.py[source]

wait_for_batch_job = BatchSensor(
    task_id='wait_for_batch_job',
    job_id=JOB_ID,
)

Reference¶

AWS boto3 library documentation for Batch