Dept. of Comput. Sci. & Eng. Shanghai Jiao Tong Univ. Shanghai China;
data handling; multiprocessing programs; parallel processing; public domain software; task analysis; Hadoop; MapReduce cluster resources; data-parallel frame; large-scale data-intensive processing; multicore system; open-source implementation; programming model; task execution; Computational modeling; Distributed databases; Fault tolerance; Fault tolerant systems; Instruction sets; Parallel processing; Scalability; MapReduce; Multi-core; Parallelism; Resources utilization; Subtask;
机译:SHadoop:通过优化Hadoop集群中的作业执行机制来提高MapReduce性能
机译:优化的推测执行以提高虚拟化计算环境中MapReduce作业的性能
机译:用于在MapReduce集群中优化数据局部性的预测性Map Task Scheduler
机译:改进任务执行的并行性,以优化MapReduce集群资源的利用率
机译:在肉牛经营中优化资源利用:减少干草浪费,提高粗饲料的价值,并保持口粮的完整性
机译:并行MapReduce:使用并行执行策略来最大程度地利用云资源并提高性能
机译:并行MapReduce:使用并行执行策略最大限度地提高云资源利用率和性能改进
机译:改进的曲线拟合,并行性测试,灵敏度和特异性的表征,验证和放射性配体分析的优化