Answer / Manu Devi

"Apache Spark is generally faster than Apache Hadoop MapReduce due to several reasons:-n1. In-memory processing: Spark keeps intermediate results in memory, reducing the number of disk operations compared to Hadoop.n2. Faster task execution: Spark can execute tasks much more quickly due to its support for parallel computation and in-built optimizations such as lazy evaluation and lineage storage.n3. Better fault tolerance: Spark provides faster recovery from failures because it stores enough information about each task to recalculate intermediate results, reducing the need for data retransmission.n4. Simpler API: Spark has a simpler and more flexible API compared to Hadoop, making it easier to write and optimize distributed applications."

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