Cloud-aware processing of MapReduce-based OLAP applications

Conferences in Research and Practice in Information Technology Series

Volumn 140, Issue , 2013, Pages 31-38

  Han, Hyuck ^a   Lee, Young Choon ^b   Choi, Seungmi ^a   Yeom, Heon Y ^a   Zomaya, Albert Y ^b  

^a Seoul National University   (South Korea)

^b UNIVERSITY OF SYDNEY   (Australia)

Author keywords

Cloud computing; Cost efficiency; Hybrid cloud; Mapreduce; On line analytical processing (OLAP)

Indexed keywords

CLOUD COMPUTING; COST BENEFIT ANALYSIS; COST EFFECTIVENESS; COSTS; DATA WAREHOUSES; DIGITAL STORAGE; EFFICIENCY;

ANALYTICAL QUERIES; COST EFFICIENCY; DATA-INTENSIVE APPLICATION; HYBRID CLOUDS; LARGE-SCALE DATA ANALYSIS; MAP-REDUCE; ON-LINE ANALYTICAL PROCESSING; TRANSMISSION OVERHEADS;

BIG DATA;

EID: 84907003243     PISSN: 14451336     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (29)

1. Amazon Web Services (2012), Customer Success, http://aws.amazon.com/solutions/case-studies/.
2. Apache (2012a), Hadoop, http://hadoop.apache.org.
3. Apache (2012b), Hive, http://hive.apache.org.
4. Apache (2012c), Pig, http://pig.apache.org.
5. Armbrust, M., Fox, A., Griffth, R., Joseph, A. D., Katz, R., Konwinski, A., Lee, G., Patterson, D., Rabkin, A., Stoica, I. & Zaharia, M. (2010), 'A view of cloud computing', Commun. ACM 53, 50-58.
6. Bloom, B. H. (1970), 'Space/time trade-offs in hash coding with allowable errors', Commun. ACM 13, 422-426.
7. Boyd-Wickizer, S., Clements, A. T., Mao, Y., Pesterev, A., Kaashoek, M. F., Morris, R. & Zeldovich, N. (2010), An analysis of linux scalability to many cores, in 'Proceedings of the 9th USENIX conference on Operating systems design and implementation', OSDI'10, pp. 1-8.
8. Business.com (2012), CloudBase, http://cloudbase.sourceforge.net.
9. Buyya, R., Ranjan, R. & Calheiros, R. (2010), Intercloud: Utility oriented federation of cloud computing environments for scaling of application services, in 'Algorithms and Architectures for Parallel Processing', Vol. 6081 of Lecture Notes in Computer Science, pp. 13-31.
10. Celesti, A., Tusa, F., Villari, M. & Puliafito, A. (2010), 'How to Enhance Cloud Architectures to Enable Cross-Federation', Cloud Computing, IEEE International Conference on pp. 337-345.
11. CycleComputing (2012), CycleCloud Achieves Ludicrous Speed! (Utility Supercomputing with 50,000-cores), http://blog.cyclecomputing.com/2012/04/cyclecloud-50000core-utility-supercomputing.html.
12. Dean, J. & Ghemawat, S. (2008), 'MapReduce: simplified data processing on large clusters', Commun. ACM 51(1), 107-113.
13. Ghemawat, S., Gobioff, H. & Leung, S.-T. (2003), The google file system, in 'SOSP '03: Proceedings of the nineteenth ACM symposium on Operating systems principles'.
14. Han, H., Jung, H., Eom, H. & Yeom, H. (2011), 'Scatter-gathermerge: An efficient star-join query processing algorithm for data-parallel frameworks', Cluster Computing 14, 183-197.
15. Hey, T., Tansley, S. & Tolle, K., eds (2009), The Fourth Paradigm: Data-Intensive Scientific Discovery, Microsoft.
16. Humphrey, M. (2011), Cloud, hpc, or hybrid: A case study involving satellite image processing, in 'Cloud Futures 2011'.
17. Johnston, S. (2009), 'Intercloud is a global cloud of clouds'.
18. Monash, C. (2009), Cloudera presents the MapReduce bull case, http://www.dbms2.com/2009/04/15/cloudera-presentsthe-mapreduce-bull-case.
19. O'Neil, P., O'Neil, E. & Chen, X. (2007), The Star Schema Benchmark.
20. Paul, M. (2008), 'The cloud is the computer', IEEE Spectrum Online.
21. Pike, R., Dorward, S., Griesemer, R. & Quinlan, S. (2005), 'Interpreting the data: Parallel analysis with sawzall', Scientific Programming Journal.
22. Song, X., Chen, H., Chen, R., Wang, Y. & Zang, B. (2011), A case for scaling applications to many-core with os clustering, in 'Proceedings of the sixth conference on Computer systems', EuroSys '11, pp. 61-76.
23. Stonebraker, M., Abadi, D., DeWitt, D. J., Madden, S., Paulson, E., Pavlo, A. & Rasin, A. (2010), 'MapReduce and parallel DBMSs: friends or foes?', Commun. ACM.
24. Transaction Processing Performance Council (2012), TPC-H, http://www.tpc.org/tpch.
25. Vaquero, L. M., Rodero-Merino, L. & Buyya, R. (2011), 'Dynamically scaling applications in the cloud', ACM SIGCOMM Computer Communication Review 41(1), 45-52.
26. Vaquero, L. M., Rodero-Merino, L., Caceres, J. & Lindner, M. (2008), 'A break in the clouds: towards a cloud definition', SIGCOMM Comput. Commun. Rev. 39, 50-55.
27. W.H. Inmon (1996), Building the Data Warehouse, J. Wiley & Sons, Inc.
28. Yang, H.-c., Dasdan, A., Hsiao, R.-L. & Parker, D. S. (2007), Mapreduce-merge: simplified relational data processing on large clusters, in 'SIGMOD '07: Proceedings of the 2007 ACM SIGMOD international conference on Management of data'.
29. Zhai, Y., Liu, M., Zhai, J., Ma, X. & Chen, W. (2011), Cloud versus in-house cluster: evaluating amazon cluster compute instances for running mpi applications, in 'State of the Practice Reports', SC '11.