Jinshuang Yan

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As a widely-used parallel computing framework for big data processing today, the Hadoop MapReduce framework puts more emphasis on high-throughput of data than on low-latency of job execution. However, today more and more big data applications developed with MapReduce require quick response time. As a result, improving the performance of MapReduce jobs,(More)
Hadoop MapReduce is a widely used parallel computing framework for solving data-intensive problems. To be able to process large-scale datasets, the fundamental design of the standard Hadoop places more emphasis on high-throughput of data than on job execution performance. This causes performance limitation when we use Hadoop MapReduce to execute short jobs(More)
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