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Apache Airflow: The Operators Guide

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Apache Airflow: The Operators Guide, available at $84.99, has an average rating of 4.66, with 60 lectures, based on 357 reviews, and has 5451 subscribers.

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You will learn about Master Apache Airflow Operators How to version your DAGs How to create DAG dependencies efficiently How to trigger your DAGs on specific days Create Incredible Data Pipelines by truly understanding Airflow operators This course is ideal for individuals who are Data engineers or Data scientist or Business Analysts or Software Engineers It is particularly useful for Data engineers or Data scientist or Business Analysts or Software Engineers.

Enroll now: Apache Airflow: The Operators Guide

Summary

Title: Apache Airflow: The Operators Guide

Price: $84.99

Average Rating: 4.66

Number of Lectures: 60

Number of Published Lectures: 56

Number of Curriculum Items: 60

Number of Published Curriculum Objects: 56

Original Price: $89.99

Quality Status: approved

Status: Live

What You Will Learn

  • Master Apache Airflow Operators
  • How to version your DAGs
  • How to create DAG dependencies efficiently
  • How to trigger your DAGs on specific days
  • Create Incredible Data Pipelines by truly understanding Airflow operators

Who Should Attend

  • Data engineers
  • Data scientist
  • Business Analysts
  • Software Engineers

Target Audiences

  • Data engineers
  • Data scientist
  • Business Analysts
  • Software Engineers

Apache Airflow has more than 700 Operators and 70 tools it can interact with.

It’s huge! ?

Operators are tasks in your data pipeline. They are important as they correspond to the actions of your data pipeline, to the different steps to produce the output you want.

Now,

Do you know well the Airflow’s operators?

Do you want to create reliable data pipelines? 

Are you looking for best practices around Operators?

If yes, you’ve come to the right place!

With the course Apache Airflow: The Operators Guide,  will be able to

  • Version your DAGs

  • Retry your tasks properly

  • Create dependencies between your tasks and even your DAG Runs

  • Demystifies the owner parameter

  • Take actions if a task fails

  • Choose the right way to create DAG dependencies

  • Execute a task only in a specific interval of time

  • Group your tasks to make your DAG cleaner (not with SubDAG)

  • Trigger your DAG based on a Calendar

and much more!

Warning! You must already know Airflow! Think of this course as your Airflow Operators Reference.

The operator you are looking for is there?

NOT YET!

Vote for it, and I will make video in the month. You decide!

So,

If you already know Airflow and you’re ready to step up! Enroll now and truly take your data pipelines to another level. ?

Course Curriculum

Chapter 1: Introduction

Lecture 1: Important Prerequisites

Lecture 2: Install Docker

Lecture 3: Course Objectives

Lecture 4: Who am I?

Lecture 5: Development Environment

Chapter 2: The BaseOperator Exposed

Lecture 1: Introduction

Lecture 2: What you need to know

Lecture 3: Important details

Lecture 4: The task id exposed!

Lecture 5: Dag versioning

Lecture 6: Who owns the task?

Lecture 7: The start_date is more than you think

Lecture 8: Retry your task!

Lecture 9: Be PROPERLY notified by emails

Lecture 10: Make your tasks dependent between DAGRuns

Lecture 11: Wait for downstream tasks

Lecture 12: Pool party!

Lecture 13: Task priority

Lecture 14: Define the priority!

Lecture 15: Change task execution with trigger_rules

Lecture 16: Execute cleaning tasks with trigger_rules

Lecture 17: Set expectations to your tasks with SLAs

Lecture 18: Timeout

Lecture 19: Define a timeout

Lecture 20: A callback to react

Lecture 21: Catch a timeout with the failure callback

Lecture 22: Share data with the famous XCOMs

Lecture 23: Limit the concurrency

Lecture 24: Chain and Cross dependency helpers

Lecture 25: Let's play with chain and cross helpers

Lecture 26: Customize your task according to the executor

Chapter 3: The Most Common Operators

Lecture 1: Introduction to Providers

Lecture 2: The PythonOperator

Lecture 3: The PythonOperator with the TaskFlow API

Lecture 4: The BashOperator

Lecture 5: Quick note about templated fields

Lecture 6: The PostgresOperator

Lecture 7: Passing Dynamic Parameters to the PostgresOperator

Chapter 4: Choose your path

Lecture 1: Introduction

Lecture 2: The BranchPythonOperator

Lecture 3: DAG scheduling based on Calendar!

Lecture 4: The BranchSQLOperator

Lecture 5: The BranchDateTimeOperator

Lecture 6: The BranchDayOfWeekOperator

Chapter 5: DAG dependencies

Lecture 1: Introduction

Lecture 2: SubDagOperator

Lecture 3: Deep dive into the SubDagOperator

Lecture 4: Discover the TaskGroups

Lecture 5: TriggerDagRunOperator

Lecture 6: The famous ExternalTaskSensor

Lecture 7: DAG dependencies view

Chapter 6: The Exotic Ones

Lecture 1: One DAG different schedules with the ShortCircuitOperator

Lecture 2: Prevent from running past tasks with the LatestOnlyOperator

Lecture 3: Side Notes with the LatestOnlyOperator

Lecture 4: You think you know the DummyOperator?

Chapter 7: Last Words!

Lecture 1: Bonus Lecture

Instructors

Rating Distribution

  • 1 stars: 2 votes
  • 2 stars: 4 votes
  • 3 stars: 20 votes
  • 4 stars: 89 votes
  • 5 stars: 242 votes

Frequently Asked Questions


How long do I have access to the course materials?


You can view and review the lecture materials indefinitely, like an on-demand channel.


Can I take my courses with me wherever I go?


Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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