Discuss techniques such as partitioning, broadcast joins, and caching to enhance Spark job performance.
Spark/Big Datamedium
2
Explain Apache Spark fundamentals, OOM scenarios and their resolutions, optimization techniques, strategies for optimized joins, and handling data skewness with Key Salting techniques.
Spark/Big Datahard
3
Explain PySpark's Catalyst Optimizer.
Spark/Big Datahard
4
Explain SCD1 and SCD2 in Databricks PySpark with examples.
Spark/Big Datahard
5
Explain Spark transformations (lazy evaluation, wide vs narrow).
Spark/Big Datahard
6
Explain Spark's execution process – Job/Stage/Task creation.
Spark/Big Datahard
7
Explain Spark's narrow vs. wide transformations and when to use each
Spark/Big Datahard
8
Explain a scenario-based question on Spark optimization and how you would troubleshoot performance issues.
Spark/Big Datahard
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