MAPREDUCE SYSTEM MODEL BASED ON CLOUD COMPUTING INFRASTRUCTURE
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Abstract
This paper proposes a fault-tolerant and scalable MapReduce system model based on modern cloud computing infrastructures. By leveraging cloud services such as table storage and message queues, the model eliminates single points of failure and improves data handling. The system enhances reliability, simplifies distributed programming, and efficiently processes large datasets using cloud-native parallel computing capabilities.
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References
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DOI: 10.1016/j.jpdc.2018.05.010
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