Real questions from top companies in Spark/Big Data
What is the difference between MapReduce and Spark?
What is the difference between Pandas DataFrame and Spark DataFrame? When would you prefer using each?
What is the difference between external and internal tables in Hive?
What is the difference between head() and take() in PySpark?
What is the difference between managed and external tables in Hive or Spark SQL?
What is the difference between map and flatMap in Spark transformations?
What is the difference between partitions and repartitions in Spark, and when do you use each?
What is the importance of the checkpoint location in Databricks?
What is the most common performance bottleneck in Spark jobs, and how would you resolve it?
What is the purpose of the VACUUM command in Delta Lake?
What is the role of Zookeeper in Kafka?
What is the salting technique, and when would you use it?
What is the usage of Optimize and REORG commands in Databricks?
What limitations do you face when using Delta Tables in a multi-cloud environment?
What metrics do you use to determine whether a Spark job is going well or not?
What performance optimization techniques have you applied in Spark, Sqoop, or Databricks?
What performance tuning techniques do you apply in both Sqoop and Spark to optimize their execution?
What role does Kafka play in real-time data streaming pipelines?
What role does executor memory and CPU configuration play in maximizing parallelism?
What role would Kafka or similar event-driven platforms play in your architecture?
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