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Build DAGs Using the Taskflow API in Apache Airflow
Enhance your Airflow workflows using the Taskflow API. This course will teach you how to use the Taskflow API to construct DAGs and pass data between tasks.
Managing and optimizing workflows in Airflow can be challenging without a clear understanding of how to use operators and the Taskflow API effectively. In this course, Build DAGs Using the Taskflow API in Apache Airflow, you'll gain the ability to create directed acyclic graphs (DAGs) for streamlined data validation, filtering, and passing. First, you'll set up a simple DAG, with no conditional operations, using Airflow operators for data processing and validation and pass data using XComs. Next, you'll convert the same DAG to use the Taskflow API using the @task and @dag decorators. You'll learn how to perform data passing using the "return" keyword, and collect and access the data passed using input arguments. Finally you'll build a more complex DAG which includes conditional branching workflows first using operators and then using the Taskflow API. When you're finished with this course, you'll have the skills and knowledge needed to use the Taskflow API to enhance and optimize your workflows efficiently.
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Published 7/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 48 KHz
Language: English | Size: 75.53 MB | Duration: 24m 53s
MP4 | Video: h264, 1920x1080 | Audio: AAC, 48 KHz
Language: English | Size: 75.53 MB | Duration: 24m 53s
Enhance your Airflow workflows using the Taskflow API. This course will teach you how to use the Taskflow API to construct DAGs and pass data between tasks.
Managing and optimizing workflows in Airflow can be challenging without a clear understanding of how to use operators and the Taskflow API effectively. In this course, Build DAGs Using the Taskflow API in Apache Airflow, you'll gain the ability to create directed acyclic graphs (DAGs) for streamlined data validation, filtering, and passing. First, you'll set up a simple DAG, with no conditional operations, using Airflow operators for data processing and validation and pass data using XComs. Next, you'll convert the same DAG to use the Taskflow API using the @task and @dag decorators. You'll learn how to perform data passing using the "return" keyword, and collect and access the data passed using input arguments. Finally you'll build a more complex DAG which includes conditional branching workflows first using operators and then using the Taskflow API. When you're finished with this course, you'll have the skills and knowledge needed to use the Taskflow API to enhance and optimize your workflows efficiently.
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