A data pipeline processes files for different clients stored in separate directories. Explain how you would use dynamic DAG creation to handle client-specific workflows in Airflow.
Spark/Big Datahard
2
Describe how you would monitor ETL job performance and handle long-running tasks.
Spark/Big Datahard
3
Explain how I handle performance optimizations, scheduling tasks, and monitoring DAGs in Airflow.
Spark/Big Datahard
4
Explain how to schedule an automated task using Apache Airflow.
Spark/Big Datahard
5
Explain the difference between TriggerDagRunOperator and ExternalTaskSensor in Airflow.
Spark/Big Datahard
6
How do you initiate a DAG in Airflow?
Spark/Big Datahard
7
Limiting Parallel Tasks
Spark/Big Datahard
8
List all the technologies you have worked on in your project (e.g., Spark, Hadoop, Hive, Databricks).
Spark/Big Datahard
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