Proceedings of the 7th ACM International Conference on Distributed Event-Based Systems 2013
DOI: 10.1145/2488222.2488281
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Cited by 10 publications
(1 citation statement)
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“…These systems primarily focus on how queries can be executed and only support data transfers as a side effect, usually based on rudimentary mechanisms (e.g., simple event transfer over HTTP, TCP or UDP) or ignore this completely by delegating it to the data source. D-Streams [23] provides tools for scalable stream processing across clusters, building on the idea of handling small batches which can be processed using MapReduce; an idea also discussed in [45]. Here, the data acquisition is event driven: the system simply collects the events from the source.…”
Section: Data Stream Management Systems (Dsms)mentioning
confidence: 99%
“…These systems primarily focus on how queries can be executed and only support data transfers as a side effect, usually based on rudimentary mechanisms (e.g., simple event transfer over HTTP, TCP or UDP) or ignore this completely by delegating it to the data source. D-Streams [23] provides tools for scalable stream processing across clusters, building on the idea of handling small batches which can be processed using MapReduce; an idea also discussed in [45]. Here, the data acquisition is event driven: the system simply collects the events from the source.…”
Section: Data Stream Management Systems (Dsms)mentioning
confidence: 99%