Apache Spark: Handle Corrupt/Bad Records
Reading Time: 3 minutes Most of the time writing ETL jobs becomes very expensive when it comes to handling corrupt records. And in such cases, ETL pipelines need a good solution to handle corrupted records. Because, larger the ETL pipeline is, the more complex it becomes to handle such bad records in between. Corrupt data includes: Missing information Incomplete information Schema mismatch Differing formats or data types Apache Spark: Continue Reading