#spark-etl

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frommedium.com
4 weeks ago
Scala

Spark Scala Exercise 24: Error Handling and Logging in SparkBuild Safe, Auditable ETL Pipelines

Build a defensive Spark ETL pipeline to ensure robust data processing.
Handle data issues like schema mismatches and corrupt records effectively.
Implement custom logging and audit trails for better failure management.
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