Real questions from top companies in Spark/Big Data · hard
Discuss how you integrated Azure services into your Spark application.
Discuss stages and tasks in a Spark execution plan.
Explain Apache Spark fundamentals, OOM scenarios and their resolutions, optimization techniques, strategies for optimized joins, and handling data skewness with Key Salting techniques.
Explain Azure Databricks architecture and its integration with other Azure services.
Explain Delta Live Tables and their features, such as declarative pipeline definition and automatic data validation.
Explain Delta Table features – Z-ordering and Time Travel.
Explain Delta Time Travel and the purpose of the vacuum command.
Explain Hive, its purpose, and its default metadata storage.
Explain MapReduce Architecture.
Explain PySpark's Catalyst Optimizer.
Explain SCD1 and SCD2 in Databricks PySpark with examples.
Explain Spark Architecture – Driver, Executors, and Tasks.
Explain Spark transformations (lazy evaluation, wide vs narrow).
Explain Spark's execution process – Job/Stage/Task creation.
Explain Spark's narrow vs. wide transformations and when to use each
Explain a scenario-based question on Spark optimization and how you would troubleshoot performance issues.
Explain aggregation functions in PySpark with examples and use cases.
Explain caching techniques in Databricks.
Explain data encryption in Databricks, both at rest and in transit.
Explain database drivers/connectors and their use cases.
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