What is the difference in idea, design and code, between Apache Spark and Apache Hadoop?

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Meenu Sharma

Apache Spark is designed as an interface for large-scale processing, while Apache Hadoop provides a broader software framework for the distributed storage and processing of big data
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Hadoop's MapReduce model reads and writes from a disk, thus slowing down the processing speed. Spark reduces the number of read/write cycles to disk and stores intermediate data in memory, hence faster-processing speed. Hadoop is designed to handle batch processing efficiently.
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