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Real questions from top companies in Spark/Big Data
What strategies would you use to optimize Spark jobs for both performance and cost on AWS?
What strategies would you use to reduce latency in a streaming data pipeline?
What techniques ensure deduplication in large datasets?
What trade-offs would you consider when choosing between batch processing and real-time streaming?
What's the difference between narrow and wide transformations?
When submitting Spark jobs, how does the process work in the backend? Explain.
When would you choose a broadcast join over a shuffle join? Any memory risks?
Which Spark property controls the number of shuffle partitions?
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