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State some use cases where Hadoop MapReduce works well and where it does not.
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Answer Posted / Ravi Soni
Hadoop MapReduce works well in processing large volumes of data, performing batch processing tasks, handling unstructured data, and in distributed computing where parallelism is required. However, it struggles with real-time data processing due to its batch nature, complex setup, and overhead for small data sets. It may also not be suitable for interactive queries or operations that require low latency.
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