[1] Lynch C. Big data: how do your data grow? [J]. Nature, 2008, 455(4): 28-29.
[2] Goldston D. Big data: data wrangling [J]. Nature, 2008, 455(4): 15.
[3] Wang S, Wang H J, Qin X P, et al. Architecting big data: challenges, studies and forecasts [J]. Chinese Journal of Computers, 2011, 34(10): 1741-1752.
[4] Qin X P, Wang H J, Li F R, et al. New landscape of data management technologies [J]. Journal of Software, 2013, 24(2): 175-197.
[5] Zhang Y S, Jiao M, Wang Z W, et al. One-size-fits-all OLAP technique for big data analysis [J]. Chinese Journal of Computers, 2011, 34(10): 1936-1946.
[6] Gong X Q, Jin C Q, Wang X L, et al. Data-intensive science and engineering: requirements and challenges [J]. Chinese Journal of Computers, 2012, 35(8): 1563-1578.
[7] Ma K, Yang B. Log-based change data capture from schema-free document stores using Map-Reduce [C]//2015 International Conference on Cloud Technologies and Applications (CloudTech). 2015: 1-6.
[8] Jung G, Gnanasambandam N, Mukherjee T. Synchronous parallel processing of bigdata [C]//2012 IEEE fifth International Conference on Cloud Computing. 2012: 811-818.
[9] Liu X, Gao W, Hu Z Y. Hybrid parallel bundle adjustment for 3D scene reconstruction with massive points [J]. Journal of Computer Science and Technology, 2012, 27(6): 1269-1280.
[10] Feinbube F, Sobania J A, Tr¨oger P, et al. Light-weight programming of hybrid systems [J]. Parallel & Cloud Computing, 2012, 1(2): 34-44.
[11] Wang P, Meng D, Han J Z, et al. Transformer: a new paradigm for building data-parallel programming models [J]. Micro IEEE, 2010, 30(4): 55-64.
[12] Pace M F. BSP vs. MapReduce [J]. Procedia Computer Science, 2012, 9: 246-255.
[13] 潘巍, 李战怀, 伍赛, 等. 基于消息传递机制的MapReduce 图算法研究[J]. 计算机学报, 2011, 34(10): 1768-1784.
[14] Fegaras L. Supporting bulk synchronous parallelism in Map-Reduce queries [C]//High Performance Computing, Networking, Storage and Analysis (SCC). 2012: 1068-1077.
[15] Qin X P, Wang H J, Du X Y, et al. Big data analysis-competition and symbiosis of RDBMS and MapReduce [J]. Journal of Software, 2012, 23(1): 32-45.
[16] Ding L L, Xin J C, Wang G R, et al. Efficient skyline query processing of massive data based on MapReduce [J]. Chinese Journal of Computers, 2011, 34(10): 1785-1796.
[17] Valiant L G. A bridging model for parallel computation [J]. Communication of the ACM, 1990, 33(8): 103-111.
[18] Malewicz G, Austern M H, Bik A J C, et al. Pregel: a system for large-scale graph processing [C]//Proceedings of the 2010 International Conference on Management of Data. 2010:
135-145.
[19] HAMA-a general BSP framework on top of Hadoop [EB/OL]. [2015-10-20]. http://hama.apache.org.
[20] Avery C. Giraph: large-scale graph processing infrastructure on Hadoop [C]//Proceedings of the Hadoop Summit. 2011: 1-8.
[21] Liu X D, Tong W Q, Fu Z R, et al. BSPCloud: a hybrid distributed-memory and sharedmemory programming model [J]. International Journal of Grid and Distributed Computing, 2013, 6(1): 87-98. |