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Real questions from top companies in Spark/Big Data
How do you handle out-of-memory errors in Spark jobs?
How do you handle schema evolution in Spark, especially when reading data from sources like Parquet or Avro?
How do you handle very large datasets in Spark to ensure scalability and efficiency?
How do you help stakeholders query Delta Lake tables? What tools and approaches?
How do you identify skewed partitions in a dataset?
How do you implement incremental updates in a data lake using AWS services and Spark?
How do you implement row and column-level security in Databricks?
How do you initiate a DAG in Airflow?
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