Abstract
We propose a system combining stream processing engines and big data storages for analyzing large amounts of data streams. It allows us to analyze data online and to store data for later offline analysis. An emphasis is laid on designing a system to facilitate simple implementations of data analysis algorithms.
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Abadi, D.J., Ahmad, Y., Balazinska, M., Cetintemel, U., Cherniack, M., Hwang, J.-H., Lindner, W., Maskey, A.S., Rasin, A., Ryvkina, E., et al.: The design of the borealis stream processing engine. In: CIDR (2005)
Abadi, D.J., Carney, D., Çetintemel, U., Cherniack, M., Convey, C., Lee, S., Stonebraker, M., Tatbul, N., Zdonik, S.: Aurora: a new model and architecture for data stream management. The VLDB Journal 12(2), 120–139 (2003)
Chang, F., Dean, J., Ghemawat, S., Hsieh, W.C., Wallach, D.A., Burrows, M., Chandra, T., Fikes, A., Gruber, R.E.: Bigtable: A distributed storage system for structured data. ACM Trans. Comput. Syst. 26(2) (2008)
Chu, C.-T., Kim, S.K., Lin, Y.-A., Yu, Y., Bradski, G.R., Ng, A.Y., Olukotun, K.: Map-Reduce for machine learning on multicore. In: Schölkopf, B., Platt, J.C., Hoffman, T. (eds.) NIPS, pp. 281–288. MIT Press (2006)
Condie, T., Conway, N., Alvaro, P., Hellerstein, J.M., Elmeleegy, K., Sears, R.: Map-Reduce online. In: NSDI, pp. 313–328. USENIX Association (2010)
Condie, T., Conway, N., Alvaro, P., Hellerstein, J.M., Gerth, J., Talbot, J., Elmeleegy, K., Sears, R.: Online aggregation and continuous query support in mapReduce. In: Elmagarmid, A.K., Agrawal, D. (eds.) SIGMOD Conference, pp. 1115–1118. ACM (2010)
Dean, J., Ghemawat, S.: Map-Reduce: a flexible data processing tool. Commun. ACM 53(1), 72–77 (2010)
EsperTech. Esper – complex event processing. Website (2013) esper.codehaus.org
The Apache Software Foundation. Apache Hadoop. Website (2013), hadoop.apache.org
The Apache Software Foundation. Mahout: Scalable machine-learning and data-mining library (2013) mahout.apache.org
Franklin, M.J., Jeffery, S.R., Krishnamurthy, S., Reiss, F., Rizvi, S., Wu, E., Cooper, O., Edakkunni, A., Hong, W.: Design considerations for high fan-in systems: The HiFi approach. In: CIDR (2005)
Ghemawat, S., Gobioff, H., Leung, S.-T.: The Google file system. In: Scott, M.L., Peterson, L.L. (eds.) SOSP, pp. 29–43. ACM (2003)
Motwani, R., Widom, J., Arasu, A., Babcock, B., Babu, S., Datar, M., Manku, G., Olston, C., Rosenstein, J., Varma, R.: Query processing, resource management, and approximation in a data stream management system. In: CIDR (2003)
Neumeyer, L., Robbins, B., Nair, A., Kesari, A.: S4: Distributed stream computing platform. In: Fan, W., Hsu, W., Webb, G.I., Liu, B., Zhang, C., Gunopulos, D., Wu, X. (eds.) ICDM Workshops, pp. 170–177. IEEE Computer Society (2010)
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Steinmaurer, T., Traxler, P., Zwick, M., Stumptner, R., Lettner, C. (2014). Combining Stream Processing Engines and Big Data Storages for Data Analysis. In: Andreasen, T., Christiansen, H., Cubero, JC., Raś, Z.W. (eds) Foundations of Intelligent Systems. ISMIS 2014. Lecture Notes in Computer Science(), vol 8502. Springer, Cham. https://doi.org/10.1007/978-3-319-08326-1_48
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DOI: https://doi.org/10.1007/978-3-319-08326-1_48
Publisher Name: Springer, Cham
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