6/21/2023 0 Comments Data pipelines with apache airflow![]() sequential scripts 1.1.4 Running pipeline using workflow managers 1.2 Introducing Airflow 1.2.1 Defining pipelines flexibly in (Python) code 1.2.2 Scheduling and executing pipelines 1.2.3 Monitoring and handling failures 1.2.4 Incremental loading and backfilling 1.3 When to use Airflow 1.3.1 Reasons to choose Airflow 1.3.2 Reasons not to choose Airflow 1.4 The rest of this book Summary 2 Anatomy of an Airflow DAG 2.1 Collecting data from numerous sources 2.1.1 Exploring the data 2.2 Writing your first Airflow DAG 2.2.1 Tasks vs. ![]() Table of contents : Data Pipelines with Apache Airflow brief contents contents preface acknowledgments Bas Harenslak Julian de Ruiter about this book Who should read this book How this book is organized: A road map About the code LiveBook discussion forum about the authors about the cover illustration Part 1-Getting started 1 Meet Apache Airflow 1.1 Introducing data pipelines 1.1.1 Data pipelines as graphs 1.1.2 Executing a pipeline graph 1.1.3 Pipeline graphs vs. ![]()
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