ITAIPU DATA STREAM MANAGEMENT SYSTEM - A Stream Processing System with Business Users in Mind

Azza Abouzied, Jacob Slonim, Michael McAllister

2008

Abstract

Business Intelligence (BI) provides enterprise decision makers with reliable and holistic business information. Data Warehousing systems typically provide accurate and summarized reports of the enterprise’s operation. While this information is valuable to decision makers, it remains an after-the-fact analysis. Just-in-time, finer-grained information is necessary to enable decision makers to detect opportunities or problems as they occur. Business Activity Monitoring is the technology that provides right-time analysis of business data. The purpose of this paper is to describe the requirements of a BAM system, establish the relation of BAM to a Data Stream Management System (DSMS) and describe the architecture and design challenges we faced building the Itaipu system: a DSMS developed for BAM end-users.

References

  1. Abadi, D. J., Ahmad, Y., Balazinska, M., C¸ etintemel, U., Cherniack, M., Hwang, J.-H., Lindner, W., Maskey, A. S., Rasin, A., Ryvkina, E., Tatbul, N., Xing, Y., and Zdonik, S. (2005). The design of the borealis stream processing engine. In CIDR 7805: Second Biennial Conference on Innovative Data Systems Research, Online Proceedings.
  2. Abadi, D. J., Carney, D., C¸etintemel, U., Cherniack, M., Convey, C., Lee, S., Stonebraker, M., Tatbul, N., and Zdonik, S. (2003). Aurora: a new model and architecture for data stream management. The Very Large Data Bases (VLDB) Journal, 12(2):120 - 139.
  3. Arasu, A., Babu, S., and Widom, J. (2006). The cql continuous query language: Semantic foundations and query execution. The Very Large Data Bases (VLDB) Journal, 15(2):121-142.
  4. Arasu, A., Cherniack, M., Galvez, E., Maier, D., Maskey, A. S., Ryvkina, E., Stonebraker, M., and Tibbetts, R. (2004). Linear road: a stream data management benchmark. In VLDB 7804: Proceedings of the Thirtieth international conference on Very large data bases, pages 480-491. VLDB Endowment.
  5. Babcock, B., Babu, S., Datar, M., Motwani, R., and Widom, J. (2002). Models and issues in data stream systems. In PODS 7802: Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems, pages 1-16, New York, NY, USA. ACM.
  6. Cisco (2008). Petroleum company improves real-time information sharing with rigs. Retrieved March 31, 2008, from Cisco Customer Case Study on First Mile Wireless: http://www.cisco.com/web/strategy/ docs/energy/ Caseworks 31530 Petrobel CS.pdf.
  7. Demers, A. J., Gehrke, J., Panda, B., Riedewald, M., Sharma, V., and White, W. M. (2007). Cayuga: A general purpose event monitoring system. In CIDR, pages 412-422.
  8. Han, J., Chen, Y., Dong, G., Pei, J., Wah, B. W., Wang, J., and Cai, Y. D. (2005). Stream cube: An architecture for multi-dimensional analysis of data streams. Distrib. Parallel Databases, 18(2):173-197.
  9. Han, J. and Kamber, M. (2000). Data Mining: Concepts and Techniques. Morgan Kaufmann.
  10. Hwang, J.-H., C¸ etintemel, U., and Zdonik, S. (17-20 April 2007). Fast and reliable stream processing over wide area networks. Data Engineering Workshop, 2007 IEEE 23rd International Conference on, pages 604- 613.
  11. IBM (2007). Smarter oilfields make dollars and sense. Retrieved March 31, 2008, from IDEAS from IBM: http://www.ibm.com/ibm/ideasfromibm/us/ oilfields/042307/ images/SmartOF 042307.pdf.
  12. Krishnamurthy, S., Chandrasekaran, S., Cooper, O., Deshpande, A., Franklin, M. J., Hellerstein, J. M., Hong, W., Madden, S., Reiss, F., and Shah, M. A. (2003). Telegraphcq: An architectural status report. IEEE Data Engineering Bulletin, 26(1):11-18.
  13. Shah, M. A., Franklin, M. J., Madden, S., and Hellerstein, J. M. (2001). Java support for data-intensive systems: experiences building the telegraph dataflow system. SIGMOD Rec., 30(4):103-114.
  14. Stonebraker, M., C¸ etintemel, U., and Zdonik, S. (2005). The 8 requirements of real-time stream processing. SIGMOD Rec., 34(4):42-47.
  15. Wu, E., Diao, Y., and Rizvi, S. (2006). High-performance complex event processing over streams. In SIGMOD 7806: Proceedings of the 2006 ACM SIGMOD international conference on Management of data.
Download


Paper Citation


in Harvard Style

Abouzied A., Slonim J. and McAllister M. (2008). ITAIPU DATA STREAM MANAGEMENT SYSTEM - A Stream Processing System with Business Users in Mind . In Proceedings of the Third International Conference on Software and Data Technologies - Volume 3: ICSOFT, ISBN 978-989-8111-53-1, pages 54-64. DOI: 10.5220/0001882000540064


in Bibtex Style

@conference{icsoft08,
author={Azza Abouzied and Jacob Slonim and Michael McAllister},
title={ITAIPU DATA STREAM MANAGEMENT SYSTEM - A Stream Processing System with Business Users in Mind},
booktitle={Proceedings of the Third International Conference on Software and Data Technologies - Volume 3: ICSOFT,},
year={2008},
pages={54-64},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001882000540064},
isbn={978-989-8111-53-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Third International Conference on Software and Data Technologies - Volume 3: ICSOFT,
TI - ITAIPU DATA STREAM MANAGEMENT SYSTEM - A Stream Processing System with Business Users in Mind
SN - 978-989-8111-53-1
AU - Abouzied A.
AU - Slonim J.
AU - McAllister M.
PY - 2008
SP - 54
EP - 64
DO - 10.5220/0001882000540064