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ShenZhen transportation system (SZTS): a novel big data benchmark suite

(2016) JOURNAL OF SUPERCOMPUTING. 72(11). p.4337-4364
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Abstract
Data analytics is at the core of the supply chain for both products and services in modern economies and societies. Big data workloads, however, are placing unprecedented demands on computing technologies, calling for a deep understanding and characterization of these emerging workloads. In this paper, we propose ShenZhen Transportation System (SZTS), a novel big data Hadoop benchmark suite comprised of real-life transportation analysis applications with real-life input data sets from Shenzhen in China. SZTS uniquely focuses on a specific and real-life application domain whereas other existing Hadoop benchmark suites, such as HiBench and CloudRank-D, consist of generic algorithms with synthetic inputs. We perform a cross-layer workload characterization at the microarchitecture level, the operating system (OS) level, and the job level, revealing unique characteristics of SZTS compared to existing Hadoop benchmarks as well as general-purpose multi-core PARSEC benchmarks. We also study the sensitivity of workload behavior with respect to input data size, and we propose a methodology for identifying representative input data sets.
Keywords
Benchmarking, ShenZhen transportation system (SZTS), Big data, MapReduce/hadoop, Performance measurement, RECONFIGURABLE MULTIRING NETWORK

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Citation

Please use this url to cite or link to this publication:

MLA
Xiong, Wen et al. “ShenZhen Transportation System (SZTS): a Novel Big Data Benchmark Suite.” JOURNAL OF SUPERCOMPUTING 72.11 (2016): 4337–4364. Print.
APA
Xiong, W., Yu, Z., Eeckhout, L., Bei, Z., Zhang, F., & Xu, C. (2016). ShenZhen transportation system (SZTS): a novel big data benchmark suite. JOURNAL OF SUPERCOMPUTING, 72(11), 4337–4364.
Chicago author-date
Xiong, Wen, Zhibin Yu, Lieven Eeckhout, Zhengdong Bei, Fan Zhang, and Chengzhong Xu. 2016. “ShenZhen Transportation System (SZTS): a Novel Big Data Benchmark Suite.” Journal of Supercomputing 72 (11): 4337–4364.
Chicago author-date (all authors)
Xiong, Wen, Zhibin Yu, Lieven Eeckhout, Zhengdong Bei, Fan Zhang, and Chengzhong Xu. 2016. “ShenZhen Transportation System (SZTS): a Novel Big Data Benchmark Suite.” Journal of Supercomputing 72 (11): 4337–4364.
Vancouver
1.
Xiong W, Yu Z, Eeckhout L, Bei Z, Zhang F, Xu C. ShenZhen transportation system (SZTS): a novel big data benchmark suite. JOURNAL OF SUPERCOMPUTING. Springer; 2016;72(11):4337–64.
IEEE
[1]
W. Xiong, Z. Yu, L. Eeckhout, Z. Bei, F. Zhang, and C. Xu, “ShenZhen transportation system (SZTS): a novel big data benchmark suite,” JOURNAL OF SUPERCOMPUTING, vol. 72, no. 11, pp. 4337–4364, 2016.
@article{8200340,
  abstract     = {Data analytics is at the core of the supply chain for both products and services in modern economies and societies. Big data workloads, however, are placing unprecedented demands on computing technologies, calling for a deep understanding and characterization of these emerging workloads. In this paper, we propose ShenZhen Transportation System (SZTS), a novel big data Hadoop benchmark suite comprised of real-life transportation analysis applications with real-life input data sets from Shenzhen in China. SZTS uniquely focuses on a specific and real-life application domain whereas other existing Hadoop benchmark suites, such as HiBench and CloudRank-D, consist of generic algorithms with synthetic inputs. We perform a cross-layer workload characterization at the microarchitecture level, the operating system (OS) level, and the job level, revealing unique characteristics of SZTS compared to existing Hadoop benchmarks as well as general-purpose multi-core PARSEC benchmarks. We also study the sensitivity of workload behavior with respect to input data size, and we propose a methodology for identifying representative input data sets.},
  author       = {Xiong, Wen and Yu, Zhibin and Eeckhout, Lieven and Bei, Zhengdong and Zhang, Fan and Xu, Chengzhong},
  issn         = {0920-8542},
  journal      = {JOURNAL OF SUPERCOMPUTING},
  keywords     = {Benchmarking,ShenZhen transportation system (SZTS),Big data,MapReduce/hadoop,Performance measurement,RECONFIGURABLE MULTIRING NETWORK},
  language     = {eng},
  number       = {11},
  pages        = {4337--4364},
  publisher    = {Springer},
  title        = {ShenZhen transportation system (SZTS): a novel big data benchmark suite},
  url          = {http://dx.doi.org/10.1007/s11227-016-1742-7},
  volume       = {72},
  year         = {2016},
}

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