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- W2891888092 abstract "With the development of big data, big data processing systems, such as Hadoop and Spark, are widely used to handle large-scale data. To avoid the complexity and expensiveness of building a self-owned big data processing system, cloud providers tend to deploy big data processing tools as cloud services. Typical examples include Amazon EMR, Azure HDInsight and AliCloud E-MapReduce. However, how to build a cost-efficient system and scale the system is still challenging. In this paper, we have conducted a case study on AliCloud E-MapReduce, and analyzed the system performance upon local and remote file systems. We compared the scalability of Hadoop and Spark by using scaleout and scale-up strategies respectively. Based on the analysis results, we derive several observations and implications, which will contribute to guide the performance optimization." @default.
- W2891888092 created "2018-09-27" @default.
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- W2891888092 date "2018-07-01" @default.
- W2891888092 modified "2023-09-26" @default.
- W2891888092 title "Towards Building a Scalable Data Analytics System on Clouds: An Early Experience on AliCloud" @default.
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- W2891888092 doi "https://doi.org/10.1109/cloud.2018.00129" @default.
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