Chapter: Workflow Orchestration with Apache Airflow

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Home > Modern Data Engineering with Apache Spark: A Hands-On Guide for Building Mission-Critical Streaming Applications > Workflow Orchestration with Apache Airflow

Modern Data Engineering with Apache Spark: A Hands-On Guide for Building Mission-Critical Streaming Applications |

Scott Haines

Apress

Modern Data Engineering with Apache Spark: A Hands-On Guide for Building Mission-Critical Streaming Applications

Workflow Orchestration with Apache Airflow

Chapter Info

Authors

Scott Haines

ARI Id

1665373056827_6148074

Access

Not Available Free

Pages

255-295

DOI

10.1007/978-1-4842-7452-1_8

Chapter URL

https://rd.springer.com/chapter/10.1007/978-1-4842-7452-1_8

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Chapters/Headings	Author(s)	Pages	Info
Front Matter		i-xxv
Front Matter		1-1
Introduction to Modern Data Engineering	Scott Haines	3-29
Getting Started with Apache Spark	Scott Haines	31-57
Working with Data	Scott Haines	59-91
Transforming Data with Spark SQL and the DataFrame API	Scott Haines	93-115
Bridging Spark SQL with JDBC	Scott Haines	117-151
Data Discovery and the Spark SQL Catalog	Scott Haines	153-202
Data Pipelines and Structured Spark Applications	Scott Haines	203-252
Front Matter		253-253
Workflow Orchestration with Apache Airflow	Scott Haines	255-295
A Gentle Introduction to Stream Processing	Scott Haines	297-322
Patterns for Writing Structured Streaming Applications	Scott Haines	323-363
Apache Kafka and Spark Structured Streaming	Scott Haines	365-404
Analytical Processing and Insights	Scott Haines	405-450
Front Matter		451-451
Advanced Analytics with Spark Stateful Structured Streaming	Scott Haines	453-488
Deploying Mission-Critical Spark Applications on Spark Standalone	Scott Haines	489-521
Deploying Mission-Critical Spark Applications on Kubernetes	Scott Haines	523-571
Back Matter		573-585
Chapters/Headings	Author(s)	Pages	Info

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