Q: Can you explain how you would optimize a Hive query that is running slower than expected? A: I mentioned techniques like using partitioning and bucketing, avoiding SELECT *, preferring ORC/Parquet file formats, and checking query execution with EXPLAIN to tune performance. Q: What is the difference between Spark and Hadoop MapReduce in terms of performance and execution model? A: I explained that Spark uses in-memory computation, which makes it much faster than MapReduce, which writes intermediate results to disk. Spark also supports iterative and real-time processing, unlike MapReduce. Q: Can you describe an ETL pipeline you worked on and how you handled data quality issues? A: I discussed a project where data was ingested from raw files into Hive, cleaned using Spark, and validated with automated checks. I explained how I implemented null checks, schema validation, and exception handling to ensure reliability.