核心论文2
[1] Zhou AY. Data intensive computing-challenges of data management techniques. Communications of CCF, 2009,5(7):50.53 (in Chinese with English abstract).
[2] Cohen J, Dolan B, Dunlap M, Hellerstein JM, Welton C. MAD skills: New analysis practices for big data. PVLDB, 2009,2(2): 1481.1492.
[3] Schroeder B, Gibson GA. Understanding failures in petascale computers. Journal of Physics: Conf. Series, 2007,78(1):1.11.
[4] Dean J, Ghemawat S. MapReduce: Simplified data processing on large clusters. In: Brewer E, Chen P, eds. Proc. of the OSDI. California: USENIX Association, 2004. 137.150.
[5] Pavlo A, Paulson E, Rasin A, Abadi DJ, Dewitt DJ, Madden S, Stonebraker M. A comparison of approaches to large-scale data analysis. In: Cetintemel U, Zdonik SB, Kossmann D, Tatbul N, eds. Proc. of the SIGMOD. Rhode Island: ACM Press, 2009. 165.178.
[6] Chu CT, Kim SK, Lin YA, Yu YY, Bradski G, Ng AY, Olukotun K. Map-Reduce for machine learning on multicore. In: Scholkopf B, Platt JC, Hoffman T, eds. Proc. of the NIPS. Vancouver: MIT Press, 2006. 281.288.
[7] Wang CK, Wang JM, Lin XM, Wang W, Wang HX, Li HS, Tian WP, Xu J, Li R. MapDupReducer: Detecting near duplicates over massive datasets. In: Elmagarmid AK, Agrawal D, eds. Proc. of the SIGMOD. Indiana: ACM Press, 2010. 1119.1122.
[8] Liu C, Guo F, Faloutsos C. BBM: Bayesian browsing model from petabyte-scale data. In: Elder JF IV, Fogelman-Soulié F, Flach PA, Zaki MJ, eds. Proc. of the KDD. Paris: ACM Press, 2009. 537.546.
[9] Panda B, Herbach JS, Basu S, Bayardo RJ. PLANET: Massively parallel learning of tree ensembles with MapReduce. PVLDB, 2009,2(2):1426.1437.
[10] Lin J, Schatz M. Design patterns for efficient graph algorithms in MapReduce. In: Rao B, Krishnapuram B, Tomkins A, Yang Q, eds. Proc. of the KDD. Washington: ACM Press, 2010. 78.85.
[11] Zhang CJ, Ma Q, Wang XL, Zhou AY. Distributed SLCA-based XML keyword search by Map-Reduce. In: Yoshikawa M, Meng XF, Yumoto T, Ma Q, Sun LF, Watanabe C, eds. Proc. of the DASFAA. Tsukuba: Springer-Verlag, 2010. 386.397.
[12] Stupar A, Michel S, Schenkel R. RankReduce—Processing K-nearest neighbor queries on top of MapReduce. In: Crestani F, Marchand-Maillet S, Chen HH, Efthimiadis EN, Savoy J, eds. Proc. of the SIGIR. Geneva: ACM Press, 2010. 13.18.
[13] Wang GZ, Salles MV, Sowell B, Wang X, Cao T, Demers A, Gehrke J, White W. Behavioral simulations in MapReduce. PVLDB, 2010,3(1-2):952.963.
[14] Gunarathne T, Wu TL, Qiu J, Fox G. Cloud computing paradigms for pleasingly parallel biomedical applications. In: Hariri S, Keahey K, eds. Proc. of the HPDC. Chicago: ACM Press, 2010. 460−469.
[15] Delmerico JA, Byrnesy NA, Brunoz AE, Jonesz MD, Galloz SM, Chaudhary V. Comparing the performance of clusters, hadoop, and active disks on microarray correlation computations. In: Yang YY, Parashar M, Muralidhar R, Prasanna VK, eds. Proc. of the HiPC. Kochi: IEEE Press, 2009. 378−387.
[16] Das S, Sismanis Y, Beyer KS, Gemulla R, Haas PJ, McPherson J. Ricardo: Integrating R and hadoop. In: Elmagarmid AK, Agrawal D, eds. Proc. of the SIGMOD. Indiana: ACM Press, 2010. 987−998.
[17] Wegener D, Mock M, Adranale D, Wrobel S. Toolkit-Based high-performance data mining of large data on MapReduce clusters. In: Saygin Y, Yu JX, Kargupta H, Wang W, Ranka S, Yu PS, Wu XD, eds. Proc. of the ICDM Workshop. Washington: IEEE Computer Society, 2009. 296−301.
[18] Kovoor G, Singer J, Lujan M. Building a Java Map-Reduce framework for multi-core architectures. In: Ayguade E, Gioiosa R, Stenstrom P, Unsal O, eds. Proc. of the HiPEAC. Pisa: HiPEAC Endowment, 2010. 87−98.
[19] De Kruijf M, Sankaralingam K. MapReduce for the cell broadband engine architecture. IBM Journal of Research and Development, 2009,53(5):1−12.
[20] Becerra Y, Beltran V, Carrera D, Gonzalez M, Torres J, Ayguade E. Speeding up distributed MapReduce applications using hardware accelerators. In: Barolli L, Feng WC, eds. Proc. of the ICPP. Vienna: IEEE Computer Society, 2009. 42−49.
[21] Ranger C, Raghuraman R, Penmetsa A, Bradski G, Kozyrakis C. Evaluating MapReduce for multi-core and multiprocessor systems. In: Dally WJ, ed. Proc. of the HPCA. Phoenix: IEEE Computer Society, 2007. 13−24.
[22] Ma WJ, Agrawal G. A translation system for enabling data mining applications on GPUs. In: Zhou P, ed. Proc. of the Supercomputing (SC). New York: ACM Press, 2009. 400−409.
[23] He BS, Fang WB, Govindaraju NK, Luo Q, Wang TY. Mars: A MapReduce framework on graphics processors. In: Moshovos A, Tarditi D, Olukotun K, eds. Proc. of the PACT. Ontario: ACM Press, 2008. 260−269.
[24] Stuart JA, Chen CK, Ma KL, Owens JD. Multi-GPU volume rendering using MapReduce. In: Hariri S, Keahey K, eds. Proc. of the MapReduce Workshop (HPDC 2010). New York: ACM Press, 2010. 841−848.
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[26] Jiang W, Ravi VT, Agrawal G. A Map-Reduce system with an alternate API for multi-core environments. In: Chiba T, ed. Proc. of the CCGRID. Melbourne: IEEE Press, 2010. 84−93.
[27] Liao HJ, Han JZ, Fang JY. Multi-Dimensional index on hadoop distributed file system. In: Xu ZW, ed. Proc. of the Networking, Architecture, and Storage (NAS). Macau: IEEE Computer Society, 2010. 240−249.
[28] Zou YQ, Liu J, Wang SC, Zha L, Xu ZW. CCIndex: A complemental clustering index on distributed ordered tables for multi- dimensional range queries. In: Ding C, Shao ZY, Zheng R, eds. Proc. of the NPC. Zhengzhou: Springer-Verlag, 2010. 247−261.
[29] Zhang SB, Han JZ, Liu ZY, Wang K, Feng SZ. Accelerating MapReduce with distributed memory cache. In: Huang XX, ed. Proc. of the ICPADS. Shenzhen: IEEE Press, 2009. 472−478.
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[31] Chen ST. Cheetah: A high performance, custom data warehouse on top of MapReduce. PVLDB, 2010,3(1-2):1459−1468.
[32] Iu MY, Zwaenepoel W. HadoopToSQL: A MapReduce query optimizer. In: Morin C, Muller G, eds. Proc. of the EuroSys. Paris: ACM Press, 2010. 251−264.
[33] Blanas S, Patel JM, Ercegovac V, Rao J, Shekita EJ, Tian YY. A comparison of join algorithms for log processing in MapReduce. In: Elmagarmid AK, Agrawal D, eds. Proc. of the SIGMOD. Indiana: ACM Press, 2010. 975−986.
[34] Zhou MQ, Zhang R, Zeng DD, Qian WN, Zhou AY. Join optimization in the MapReduce environment for column-wise data store. In: Fang YF, Huang ZX, eds. Proc. of the SKG. Ningbo: EEE Computer Society, 2010. 97−104.
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[2] Cohen J, Dolan B, Dunlap M, Hellerstein JM, Welton C. MAD skills: New analysis practices for big data. PVLDB, 2009,2(2): 1481.1492.
[3] Schroeder B, Gibson GA. Understanding failures in petascale computers. Journal of Physics: Conf. Series, 2007,78(1):1.11.
[4] Dean J, Ghemawat S. MapReduce: Simplified data processing on large clusters. In: Brewer E, Chen P, eds. Proc. of the OSDI. California: USENIX Association, 2004. 137.150.
[5] Pavlo A, Paulson E, Rasin A, Abadi DJ, Dewitt DJ, Madden S, Stonebraker M. A comparison of approaches to large-scale data analysis. In: Cetintemel U, Zdonik SB, Kossmann D, Tatbul N, eds. Proc. of the SIGMOD. Rhode Island: ACM Press, 2009. 165.178.
[6] Chu CT, Kim SK, Lin YA, Yu YY, Bradski G, Ng AY, Olukotun K. Map-Reduce for machine learning on multicore. In: Scholkopf B, Platt JC, Hoffman T, eds. Proc. of the NIPS. Vancouver: MIT Press, 2006. 281.288.
[7] Wang CK, Wang JM, Lin XM, Wang W, Wang HX, Li HS, Tian WP, Xu J, Li R. MapDupReducer: Detecting near duplicates over massive datasets. In: Elmagarmid AK, Agrawal D, eds. Proc. of the SIGMOD. Indiana: ACM Press, 2010. 1119.1122.
[8] Liu C, Guo F, Faloutsos C. BBM: Bayesian browsing model from petabyte-scale data. In: Elder JF IV, Fogelman-Soulié F, Flach PA, Zaki MJ, eds. Proc. of the KDD. Paris: ACM Press, 2009. 537.546.
[9] Panda B, Herbach JS, Basu S, Bayardo RJ. PLANET: Massively parallel learning of tree ensembles with MapReduce. PVLDB, 2009,2(2):1426.1437.
[10] Lin J, Schatz M. Design patterns for efficient graph algorithms in MapReduce. In: Rao B, Krishnapuram B, Tomkins A, Yang Q, eds. Proc. of the KDD. Washington: ACM Press, 2010. 78.85.
[11] Zhang CJ, Ma Q, Wang XL, Zhou AY. Distributed SLCA-based XML keyword search by Map-Reduce. In: Yoshikawa M, Meng XF, Yumoto T, Ma Q, Sun LF, Watanabe C, eds. Proc. of the DASFAA. Tsukuba: Springer-Verlag, 2010. 386.397.
[12] Stupar A, Michel S, Schenkel R. RankReduce—Processing K-nearest neighbor queries on top of MapReduce. In: Crestani F, Marchand-Maillet S, Chen HH, Efthimiadis EN, Savoy J, eds. Proc. of the SIGIR. Geneva: ACM Press, 2010. 13.18.
[13] Wang GZ, Salles MV, Sowell B, Wang X, Cao T, Demers A, Gehrke J, White W. Behavioral simulations in MapReduce. PVLDB, 2010,3(1-2):952.963.
[14] Gunarathne T, Wu TL, Qiu J, Fox G. Cloud computing paradigms for pleasingly parallel biomedical applications. In: Hariri S, Keahey K, eds. Proc. of the HPDC. Chicago: ACM Press, 2010. 460−469.
[15] Delmerico JA, Byrnesy NA, Brunoz AE, Jonesz MD, Galloz SM, Chaudhary V. Comparing the performance of clusters, hadoop, and active disks on microarray correlation computations. In: Yang YY, Parashar M, Muralidhar R, Prasanna VK, eds. Proc. of the HiPC. Kochi: IEEE Press, 2009. 378−387.
[16] Das S, Sismanis Y, Beyer KS, Gemulla R, Haas PJ, McPherson J. Ricardo: Integrating R and hadoop. In: Elmagarmid AK, Agrawal D, eds. Proc. of the SIGMOD. Indiana: ACM Press, 2010. 987−998.
[17] Wegener D, Mock M, Adranale D, Wrobel S. Toolkit-Based high-performance data mining of large data on MapReduce clusters. In: Saygin Y, Yu JX, Kargupta H, Wang W, Ranka S, Yu PS, Wu XD, eds. Proc. of the ICDM Workshop. Washington: IEEE Computer Society, 2009. 296−301.
[18] Kovoor G, Singer J, Lujan M. Building a Java Map-Reduce framework for multi-core architectures. In: Ayguade E, Gioiosa R, Stenstrom P, Unsal O, eds. Proc. of the HiPEAC. Pisa: HiPEAC Endowment, 2010. 87−98.
[19] De Kruijf M, Sankaralingam K. MapReduce for the cell broadband engine architecture. IBM Journal of Research and Development, 2009,53(5):1−12.
[20] Becerra Y, Beltran V, Carrera D, Gonzalez M, Torres J, Ayguade E. Speeding up distributed MapReduce applications using hardware accelerators. In: Barolli L, Feng WC, eds. Proc. of the ICPP. Vienna: IEEE Computer Society, 2009. 42−49.
[21] Ranger C, Raghuraman R, Penmetsa A, Bradski G, Kozyrakis C. Evaluating MapReduce for multi-core and multiprocessor systems. In: Dally WJ, ed. Proc. of the HPCA. Phoenix: IEEE Computer Society, 2007. 13−24.
[22] Ma WJ, Agrawal G. A translation system for enabling data mining applications on GPUs. In: Zhou P, ed. Proc. of the Supercomputing (SC). New York: ACM Press, 2009. 400−409.
[23] He BS, Fang WB, Govindaraju NK, Luo Q, Wang TY. Mars: A MapReduce framework on graphics processors. In: Moshovos A, Tarditi D, Olukotun K, eds. Proc. of the PACT. Ontario: ACM Press, 2008. 260−269.
[24] Stuart JA, Chen CK, Ma KL, Owens JD. Multi-GPU volume rendering using MapReduce. In: Hariri S, Keahey K, eds. Proc. of the MapReduce Workshop (HPDC 2010). New York: ACM Press, 2010. 841−848.
[25] Hong CT, Chen DH, Chen WG, Zheng WM, Lin HB. MapCG: Writing parallel program portable between CPU and GPU. In: Salapura V, Gschwind M, Knoop J, eds. Proc. of the PACT. Vienna: ACM Press, 2010. 217−226.
[26] Jiang W, Ravi VT, Agrawal G. A Map-Reduce system with an alternate API for multi-core environments. In: Chiba T, ed. Proc. of the CCGRID. Melbourne: IEEE Press, 2010. 84−93.
[27] Liao HJ, Han JZ, Fang JY. Multi-Dimensional index on hadoop distributed file system. In: Xu ZW, ed. Proc. of the Networking, Architecture, and Storage (NAS). Macau: IEEE Computer Society, 2010. 240−249.
[28] Zou YQ, Liu J, Wang SC, Zha L, Xu ZW. CCIndex: A complemental clustering index on distributed ordered tables for multi- dimensional range queries. In: Ding C, Shao ZY, Zheng R, eds. Proc. of the NPC. Zhengzhou: Springer-Verlag, 2010. 247−261.
[29] Zhang SB, Han JZ, Liu ZY, Wang K, Feng SZ. Accelerating MapReduce with distributed memory cache. In: Huang XX, ed. Proc. of the ICPADS. Shenzhen: IEEE Press, 2009. 472−478.
[30] Dittrich J, Quian′e-Ruiz JA, Jindal A, Kargin Y, Setty V, Schad J. Hadoop++: Making a yellow elephant run like a cheetah (without it even noticing). PVLDB, 2010,3(1-2):518−529.
[31] Chen ST. Cheetah: A high performance, custom data warehouse on top of MapReduce. PVLDB, 2010,3(1-2):1459−1468.
[32] Iu MY, Zwaenepoel W. HadoopToSQL: A MapReduce query optimizer. In: Morin C, Muller G, eds. Proc. of the EuroSys. Paris: ACM Press, 2010. 251−264.
[33] Blanas S, Patel JM, Ercegovac V, Rao J, Shekita EJ, Tian YY. A comparison of join algorithms for log processing in MapReduce. In: Elmagarmid AK, Agrawal D, eds. Proc. of the SIGMOD. Indiana: ACM Press, 2010. 975−986.
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