Stream processing systems have evolved into established solutions as standalone engines but they still lack flexibility in terms of large-scale deployment, integration, extensibility, and interoperability. In the last years, a substantial ecosystem of new applications has emerged that can potentially benefit from stream processing but introduces different requirements on how stream processing solutions can be integrated, deployed, extended, and federated. To address these needs, we present an exoengine architecture and the associated ExoP platform. Together, they provide the means for encapsulating components of stream processing systems as well as automating the data exchange between components and their distributed deployment. The proposed solution can be used, e.g., to connect heterogeneous streaming engines, replace operators at runtime, and migrate operators across machines with a negligible overhead. © 2011 IFIP International Federation for Information Processing.
CITATION STYLE
Duller, M., Rellermeyer, J. S., Alonso, G., & Tatbul, N. (2011). Virtualizing stream processing. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7049 LNCS, pp. 269–288). https://doi.org/10.1007/978-3-642-25821-3_14
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