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What are the common mistakes developers make when running Spark applications?
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Answer / Rohit Singh
Common mistakes include not configuring Spark properly for the specific use case, such as setting insufficient memory or not optimizing data storage formats. Another mistake is poor job design, like using too many partitions, which can lead to increased shuffle operations. Lastly, developers may not pay attention to the ordering of data and operations, leading to incorrect results.
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