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Questions tagged spark · hard
Describe handling schema evolution in AWS Redshift without downtime.
Describe how Kafka ensures data durability and fault tolerance.
Describe how data is ingested, transformed, and served in a data pipeline.
Describe how to monitor and log errors effectively in a real-time data pipeline.
Describe how you would architect a pipeline to process real-time logs with schema evolution
Describe how you would debug a failing ETL pipeline in production.
Describe how you would design a data catalog for managing metadata
Describe how you'd design a system to track inventory and sales in real-time.
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