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Course Description
Short Course | 12 hours | 1.2 CEUs | $1,320
Apache Airflow is a configuration-as-code OSS solution for workflow automation that is positioned as a replacement of cron-like scheduling systems. Written in Python, Airflow enables developers to programmatically author, schedule for execution, and monitor highly configurable complex workflows.
Course Outline
- Chapter 1. Apache Airflow Introduction
- A Traditional ETL Approach
- Apache Airflow Defined
- Airflow Core Components
- The Component Collaboration Diagram
- Workflow Building Blocks and Concepts
- Airflow CLI
- Main Configuration File
- Extending Airflow
- Jinja Templates
- Variables and Macros
- Summary
- Chapter 2. Apache Airflow Web UI
- Web UI - the Landing (DAGs) Page
- Web UI - the DAG Graph View
- Run Status Legends
- The Pause Button (Trigger Latch)
- The DAG Triggering/Job Checking Sequence
- The Control Panel for a Task
- Sample Log File Messages (Abridged for Space)
- Summary
- Chapter 3. Anatomy of a DAG and Scheduling
- What is a DAG?
- Scheduled and Manually Triggered DAG Runs
- The DAG Object
- Tasks
- Task Lifecycle
- Operators
- Idempotent Operators
- Operator Types
- Airflow Common Operators
- Specifying Dependencies
- Associating Operators with a DAG
- Associating Operators Using the "With DAG" Statement Example
- Associating Operators with DAG Using the Operator's Constructor
- The default_args Parameter
- Passing DAG Parameters Through Web UI
- DAG Run Scheduling
- Examples of the schedule_interval Parameter
- DAG Scheduling Nuances
- Understanding The Backfill Process
- Killing/Stopping DAG Runs
- An XCom Messaging Example
- Summary
Prerequisites
Participants should be familiar with Python syntax (or have a background in programming).Duration
12 Hours | 2 Days or 4 NightsLoading...
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*Academic Unit eligibility to be determined by college/university in which you are enrolled in a degree seeking program.