Core Concepts

Airflow Concepts Everyone Should Know

1. DAG (Directed Acyclic Graph)

  • What it is: A DAG is a way to organize tasks and define the order in which they should run. The tasks flow from one to another, but there are no loops (hence “acyclic”).
  • Why it matters: DAGs help you arrange tasks in the right order, so they run smoothly and automatically.

2. Tasks

  • What it is: A task is a single piece of work that you want to do, like running a script, moving data, or checking the system.
  • Why it matters: Tasks are the steps of your workflow, and Airflow helps you execute them in the correct sequence.

3. Operators

  • What it is: Operators are pre-built actions you can use in tasks. For example, there are operators to run Python code, execute shell commands, or interact with cloud services.
  • Why it matters: Operators make it easy to do common tasks without needing to write everything from scratch.

4. Scheduler

  • What it is: The scheduler is in charge of triggering tasks when they are supposed to run. It checks your DAG and starts tasks based on the schedule or conditions you set.
  • Why it matters: The scheduler automates when and how tasks run, so you don’t have to do it manually.

5. Executor

  • What it is: The executor decides how and where tasks should run. For example, it can run tasks on your local machine or distribute them across multiple machines.
  • Why it matters: The executor helps Airflow scale, so it can handle small to large workloads efficiently.

6. Airflow UI (Web Interface)

  • What it is: The Airflow web interface is a dashboard where you can see the status of your tasks, logs, and errors. You can also start or stop tasks manually from here.
  • Why it matters: The UI makes it easy to monitor and manage your workflows, all in one place.

7. Sensors

  • What it is: Sensors are special tasks that wait for something to happen before they proceed. For example, they might wait for a file to appear in a folder before continuing.
  • Why it matters: Sensors add flexibility to your workflows, allowing tasks to wait for specific conditions to be met.

8. Dependencies

  • What it is: Dependencies define which tasks must be completed before others can start. For example, Task B can only run after Task A finishes.
  • Why it matters: Dependencies ensure tasks run in the correct order, preventing errors in your workflow.

9. Hooks

  • What it is: Hooks are tools that help Airflow connect with other systems, like databases or cloud services. They let Airflow fetch data or trigger actions in those systems.
  • Why it matters: Hooks make it easy to work with external services, so your workflows can do more without extra code.

10. Task Instances

  • What it is: A task instance is a specific run of a task in a DAG. It includes details like whether the task was successful, its logs, and how long it took to run.
  • Why it matters: Task instances help you track the history of tasks, so you can see if there were any issues and fix them.

These are the main concepts that make Airflow work. Understanding these will help you automate tasks and manage complex workflows more easily.