DocumentCode :
1196935
Title :
Exploiting punctuation semantics in continuous data streams
Author :
Tucker, Peter A. ; Maier, David ; Sheard, Tim ; Fegaras, Leonidas
Author_Institution :
OGI Sch. of Sci. & Eng., OHSU, Beaverton, OR, USA
Volume :
15
Issue :
3
fYear :
2003
Firstpage :
555
Lastpage :
568
Abstract :
As most current query processing architectures are already pipelined, it seems logical to apply them to data streams. However, two classes of query operators are impractical for processing long or infinite data streams. Unbounded stateful operators maintain state with no upper bound in size and, so, run out of memory. Blocking operators read an entire input before emitting a single output and, so, might never produce a result. We believe that a priori knowledge of a data stream can permit the use of such operators in some cases. We discuss a kind of stream semantics called punctuated streams. Punctuations in a stream mark the end of substreams allowing us to view an infinite stream as a mixture of finite streams. We introduce three kinds of invariants to specify the proper behavior of operators in the presence of punctuation. Pass invariants define when results can be passed on. Keep invariants define what must be kept in local state to continue successful operation. Propagation invariants define when punctuation can be passed on. We report on our initial implementation and show a strategy for proving implementations of these invariants are faithful to their relational counterparts.
Keywords :
pipeline processing; query processing; blocking operators; continuous data streams; infinite data streams; keep invariants; long data streams; pass invariants; pipelined architectures; propagation invariants; punctuated streams; punctuation semantics exploitation; query processing architectures; stream semantics; substreams; Condition monitoring; Marketing and sales; Merchandise; Portals; Query processing; Road transportation; Telephony; Temperature measurement; Temperature sensors; Upper bound;
fLanguage :
English
Journal_Title :
Knowledge and Data Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
1041-4347
Type :
jour
DOI :
10.1109/TKDE.2003.1198390
Filename :
1198390
Link To Document :
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