Streams and Tables
Matthias J. Sax, Guozhang Wang, Matthias Weidlich, Johann-Christoph Freytag · 2018
Stream processing has emerged as a paradigm for applications that require low-latency evaluation of operators over unbounded sequences of data. Defining the semantics of stream processing is challenging in the presence of distributed data sources. The physical and logical order of data in a stream may become inconsistent in such a setting. Existing models either neglect these inconsistencies or handle them by means of data buffering and reordering techniques, thereby compromising processing latency.