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What are the common faults of the developer while using Apache Spark?
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Answer / Nikhilesh Kumar
"Some common mistakes developers make when working with Apache Spark include:
1. Not optimizing RDD operations for performance (using multiple transformations unnecessarily or not caching and reusing RDDs).
2. Misusing Spark’s built-in APIs (e.g., using map() instead of flatMap(), or parallelizing too much data at once).
3. Ignoring serialization overhead during data transfer between nodes in the cluster.
4. Failing to handle failures effectively, causing the entire application to crash."
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