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What are the cases where Apache Spark surpasses Hadoop?
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Answer / Parvez Khan
{"Cases": "1. Real-time data processing: Spark can process and analyze real-time data faster than Hadoop MapReduce due to its in-memory caching capabilities. 2. Iterative computations: Spark is more efficient for iterative tasks like machine learning algorithms as it avoids the overhead of disk read/write operations. 3. Graph processing: With GraphX, Spark can perform graph processing much faster than Hadoop."}
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