MRGIS: A MapReduce-enabled high performance workflow system for GIS

Proceedings - 4th IEEE International Conference on eScience, eScience 2008

Volumn , Issue , 2008, Pages 646-651

  Chen, Qichang ^a   Wang, Liqiang ^a   Shang, Zongbo ^b  

^a UNIVERSITY OF WYOMING   (United States)

^b UNIVERSITY OF WYOMING   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CURRENT STATUS; DATA DEPENDENCIES; DATA-INTENSIVE APPLICATIONS; DATA-INTENSIVE COMPUTATIONS; DESIGN INTERFACES; DISTRIBUTED COMPUTING; GEOGRAPHICAL INFORMATION SYSTEMS; GIS APPLICATIONS; PARALLEL AND DISTRIBUTED COMPUTING; RUNTIME SUPPORT SYSTEMS; SINGLE PROCESSORS; WORK-FLOW SYSTEMS; WORKFLOW EXECUTIONS;

APPLICATION PROGRAMMING INTERFACES (API); GEOGRAPHIC INFORMATION SYSTEMS; MANAGEMENT; SCHEDULING;

DISTRIBUTED COMPUTER SYSTEMS;

EID: 62749175782     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/eScience.2008.169     Document Type: Conference Paper

References (12)

1. ESRI. http://www.esri.com/.
2. GRASS. http://grass.ibiblio.org/.
3. Hadoop. http://lucene.apache.org/hadoop/.
4. pyDev. http://pydev.sourceforge.net/.
5. J. Dean and S. Ghemawat. Mapreduce: Simplified data processing on large clusters. In Proceedings of the 6th symposium on Operating systems design and implementation (OSDI), pages 137-150. USENIX Association, 2004.
6. E. Deelman, G. Singh, M.-H. Su, J. Blythe, Y. Gil, C. Kesselman, G. Mehta, K. Vahi, G. B. Berriman, J. Good, A. Laity, J. C. Jacob, and D. S. Katz. Pegasus: A framework for mapping complex scientific workflows onto distributed systems. Scientific Programming, 13(3):219-237, 2005.
7. M. Isard, M. Budiu, Y. Yu, A. Birrell, and D. Fetterly. Dryad: Distributed data-parallel programs from sequential building blocks. In European Conference on Computer Systems (EuroSys). ACM, 2007.
8. H. Liu and D. Orban. Gridbatch: Cloud computing for large-scale data-intensive batch applications. In Proceedings of the 8th IEEE International Symposium on Cluster Computing and the Grid (CCGrid), pages 295-305. IEEE Computer Society, 2008.
9. C. Olston, B. Reed, U. Srivastava, R. Kumar, and A. Tomkins. Pig latin: a not-so-foreign language for data processing. In Proceedings of the 2008 ACM SIGMOD international conference on Management of data (SIGMOD), pages 1099-1110. ACM, 2008.
10. R. Pike, S. Dorward, R. Griesemer, and S. Quinlan. Interpreting the data: Parallel analysis with Sawzall. Scientific Programming, 13(4):277-298, 2005.
11. H.-C. Yang, A. Dasdan, R.-L. Hsiao, and D. S. Parker. Map-reduce-merge: simplified relational data processing on large clusters. In Proceedings of the 2007 ACM SIGMOD international conference on Management of data (SIGMOD), pages 1029-1040. ACM, 2007.
12. Y. Zhao, M. Hategan, B. Clifford, I. Foster, G. von Laszewski, I. Raicu, T. Stef-Praun, and M. Wilde. Swift: Fast, reliable, loosely coupled parallel computation. In Proceedings of the IEEE International Workshop on Scientific Workflows (SWF), pages 199-206. IEEE, 2007.