![]() The use case/S3 example for the continuous timetable is a pipeline which waits for a file to drop in S3 using the S3KeySensorAsync. No connections need to be created in order to use this DAG. The continuous_toy DAG contains one task which sleeps for a random number of seconds, after completion of the task the DAG will reschedule itself automatically, irrespective of whether it was successful or not. You can filter DAGs in the UI by their tags. The following sections list the DAGs shown sorted by the feature that they showcase. Run astro dev start in your cloned repository. ![]() Docker Desktop/Docker Engine is a prerequisite, but you don't need in-depth Docker knowledge to run Airflow with the Astro CLI. Install the Astro CLI by following the steps in the Astro CLI documentation.Run git clone on your computer to create a local clone of this repository.astro is the only package you will need to install. Once the Airflow project has started, access the Airflow UI by clicking on the Ports tab and opening the forward URL for port 8080.ĭownload the Astro CLI to run Airflow locally in Docker.After creating the codespaces project the Astro CLI will automatically start up all necessary Airflow components.Create a new GitHub codespaces project on your fork.Run this Airflow project without installing anything locally. DAGs with the tag toy work without any additional connections or tools. ![]() See the Manage Connections in Apache Airflow guide for instructions. Note that for some DAGs you will need to define extra connections (AWS and/or Slack). This section explains how to run this repository with Airflow. This repository contains example DAGs showing features released in Apache Airflow 2.6.Īside from Apache Airflow this project uses DuckDB (via the Airflow DuckDB provider), the Airflow Slack provider and the Astro Python SDK.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |