Data stream management systems (DSMSs) are conceived for running continuous queries (CQs) on the most recently streamed data. This model does not completely fit the needs of several modern data-intensive applications that require to manage recent/historical/static data and execute both CQs and OTQs joining such data. In order to cope with these new needs, some DSMSs have moved toward the integration of database management systems (DBMSs) functionalities to augment their capabilities. In this paper we adopt the opposite perspective and we lay the groundwork for extending DBMSs to natively support streaming facilities. To this end, we introduce a new kind of table, the streaming table, as a persistent structure where streaming data enters and remains stored for a long period, ideally forever. Streaming tables feature a novel access paradigm: continuous writes and one-time as well as continuous reads. We present a streaming table implementation and two novel types of indices that efficiently support both update and scan high rates. A detailed experimental evaluation shows the effectiveness of the proposed technology.
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|Data di pubblicazione:||2017|
|Titolo:||Streaming Tables: Native Support to Streaming Data in DBMSs|
|Autori:||Carafoli, Luca; Mandreoli, Federica; Martoglia, Riccardo; Penzo, Wilma|
|Digital Object Identifier (DOI):||10.1109/TSMC.2017.2664585|
|Appare nelle tipologie:||Articolo su rivista|
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