Abstract
In current international context boundaries set for applications are being pushed by the emergence of bursty and time-varying data streams required to be processed in near real-time. Furthermore, traditional techniques for data mining cannot be applied to data streams. Thus, stream-based applications must exhibit to excel at a plurality of requirements. According to defined rules presented in previous promulgated researches on this subject we differ stream-based applications and evaluate their aptitude to stream sources management. By this work we intend to present features and drawbacks of existing software coming from both industry and academic world, along with outlining our contribution to this field.
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References
Apache Samza official website. http://samza.incubator.apache.org/
Apache Storm official website. http://storm.incubator.apache.org/
D.J. Abadi, Y. Ahmad, M. Balazinska, U. Çetintemel, M. Cherniack, J.-H. Hwang, W. Lindner, A. Maskey, A. Rasin, E. Ryvkina, N. Tatbul, Y. Xing, S.B. Zdonik. The design of the borealis stream processing engine. in: CIDR, pp. 277–289, 2005
D.J. Abadi, D. Carney, U. Çetintemel, M. Cherniack, C. Convey, S. Lee, M. Stonebraker, N. Tatbul, S. Zdonik, Aurora: a new model and architecture for data stream management. VLDB J. 12(2), 120–139 (2003)
M. Ali, B. Chandramouli, J. Goldstein, and R. Schindlauer. The extensibility framework in microsoft streaminsight. in: Proceedings of the 2011 IEEE 27th International Conference on Data Engineering, ICDE ’11, IEEE Computer Society, pp. 1242–1253. 2011
A. Arasu, B. Babcock, S. Babu, J. Cieslewicz, M. Datar, K. Ito, R. Motwani, U. Srivastava, J. Widom, Stream: the stanford stream data manager. Technical Report 2003–21, Stanford InfoLab, 2003
R.S. Barga, J. Goldstein, M.H. Ali, M. Hong. Consistent streaming through time: a vision for event stream processing. in: CIDR, pp. 363–374. www.cidrdb.org
M. Cammert, C. Heinz, J. Krmer, A. Markowetz, B. Seeger, Pipes: a multi-threaded publish-subscribe architecture for continuous queries over streaming data sources. Technical report, 2003
T.M. Ghanem, M.A. Hammad, M.F. Mokbel, W.G. Aref, A.K. Elmagarmid, Incremental evaluation of sliding-window queries over data streams. IEEE Trans. Knowl. Data Eng. 19(1), 57–72 (2007)
M. Gorawski, A. Chrószcz, Query processing using negative and temporal tuples in stream query engines. in: Advances in Software Engineering Techniques—4th IFIP TC 2 Central and East European Conference on Software Engineering Techniques, CEE-SET 2009, Revised Selected Papers, volume 7054 of Lecture Notes in Computer Science, (Springer, 2009) pp. 70–83
M. Gorawski, A. Chrószcz, StreamAPAS: query language and data model. in: 2009 International Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2009, IEEE Computer Society, pp. 75–82, 2009
M. Gorawski, A. Gorawska, Research on the Stream ETL Process. in: Beyond Databases, Architectures, and Structures, volume 424 of Communications in Computer and Information Science, (Springer, 2014) pp. 61–71
M. Gorawski, A. Gorawska, K. Pasterak, Evaluation and development perspectives of stream data processing systems, in: Computer Networks, vol. 370 (Springer, Berlin, 2013), pp. 300–311
R. Kuntschke, B. Stegmaier, A. Kemper, A. Reiser, Streamglobe: processing and sharing data streams in grid-based p2p infrastructures. in: Proceedings of the 31st International Conference on Very Large Data Bases, VLDB, pp. 1259–1262. ACM, 2005
M. Stonebraker, U. Çetintemel, S. Zdonik, The 8 requirements of real-time stream processing. SIGMOD Rec. 34(4), 42–47 (2005)
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Gorawski, M., Gorawska, A., Pasterak, K. (2014). A Survey of Data Stream Processing Tools. In: Czachórski, T., Gelenbe, E., Lent, R. (eds) Information Sciences and Systems 2014. Springer, Cham. https://doi.org/10.1007/978-3-319-09465-6_31
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DOI: https://doi.org/10.1007/978-3-319-09465-6_31
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