Orchestrating workflows and pipelines with Apache Airflow in
Cloudera Data Engineering
Apache Airflow in Cloudera Data Engineering
Creating and managing Airflow jobs using Cloudera Data Engineering
Creating Airflow jobs using Cloudera Data Engineering
Creating an Airflow DAG using the Pipeline UI
Running Airflow jobs using Cloudera Data Engineering
Deleting Airflow jobs using Cloudera Data Engineering
Creating an Airflow DAG using the Pipeline UI
Managing an Airflow Pipeline using the CDE CLI
Creating a pipeline using the CDE CLI
Creating a basic Airflow pipeline using CDE CLI
Creating a pipeline with additional Airflow configurations using CDE CLI
Creating an Airflow pipeline with custom files using CDE CLI [Technical Preview]
Updating a pipeline using the CDE CLI
Updating a DAG file using the CDE CLI
Updating the Airflow job configurations using the CDE CLI
Updating the Airflow file mounts using the CDE CLI [Technical Preview]
Deleting an Airflow pipeline using the CDE CLI
Creating and managing Airflow connections
Creating a connection to Cloudera Data Warehouse Virtual Warehouse
Creating a connection to Cloudera Base on premises
Creating a connection for Sqoop Operator
Running Airflow jobs on other Cloudera Data Engineering Virtual Clusters
Using Cloudera Data Engineering with an external Apache Airflow deployment
Supported Airflow operators and hooks
Using custom operators and libraries for Apache Airflow
Adding custom operators and libraries
Updating custom operators and libraries
Deleting custom operators and libraries
Troubleshooting custom operators and libraries
Conducting error handling for custom operators and libraries for Apache Airflow
Viewing logs for custom operators and libraries
Retrying builds