%0 Conference Paper %1 1055596 %A Srivastava, Utkarsh %A Widom, Jennifer %B PODS '04: Proceedings of the twenty-third ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems %C New York, NY, USA %D 2004 %I ACM %K event late timestamp %P 263--274 %R http://doi.acm.org/10.1145/1055558.1055596 %T Flexible time management in data stream systems %U http://portal.acm.org/citation.cfm?id=1055596&dl=GUIDE&coll=GUIDE&CFID=47069440&CFTOKEN=95752043 %X Continuous queries in a Data Stream Management System (DSMS) rely on time as a basis for windows on streams and for defining a consistent semantics for multiple streams and updatable relations. The system clock in a centralized DSMS provides a convenient and well-behaved notion of time, but often it is more appropriate for a DSMS application to define its own notion of time---its own clock(s), sequence numbers, or other forms of ordering and times-tamping. Flexible application-defined time poses challenges to the DSMS, since streams may be out of order and uncoordinated with each other, they may incur latency reaching the DSMS, and they may pause or stop. We formalize these challenges and specify how to generate heartbeats so that queries can be evaluated correctly and continuously in an application-defined time domain. Our heartbeat generation algorithm is based on parameters capturing skew between streams, unordering within streams, and latency in streams reaching the DSMS. We also describe how to estimate these parameters at run-time, and we discuss how heartbeats can be used for processing continuous queries. %@ 158113858X

@inproceedings{1055596, abstract = {Continuous queries in a Data Stream Management System (DSMS) rely on time as a basis for windows on streams and for defining a consistent semantics for multiple streams and updatable relations. The system clock in a centralized DSMS provides a convenient and well-behaved notion of time, but often it is more appropriate for a DSMS application to define its own notion of time---its own clock(s), sequence numbers, or other forms of ordering and times-tamping. Flexible application-defined time poses challenges to the DSMS, since streams may be out of order and uncoordinated with each other, they may incur latency reaching the DSMS, and they may pause or stop. We formalize these challenges and specify how to generate heartbeats so that queries can be evaluated correctly and continuously in an application-defined time domain. Our heartbeat generation algorithm is based on parameters capturing skew between streams, unordering within streams, and latency in streams reaching the DSMS. We also describe how to estimate these parameters at run-time, and we discuss how heartbeats can be used for processing continuous queries.}, added-at = {2007-12-19T16:23:33.000+0100}, address = {New York, NY, USA}, author = {Srivastava, Utkarsh and Widom, Jennifer}, biburl = {https://www.bibsonomy.org/bibtex/22f64c7d8099b3599ac2ed2f8bb45beae/brainmachine}, booktitle = {PODS '04: Proceedings of the twenty-third ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems}, description = {Flexible time management in data stream systems}, doi = {http://doi.acm.org/10.1145/1055558.1055596}, interhash = {77e93142de7741d6752ae7cadd9d8c35}, intrahash = {2f64c7d8099b3599ac2ed2f8bb45beae}, isbn = {158113858X}, keywords = {event late timestamp}, location = {Paris, France}, pages = {263--274}, publisher = {ACM}, timestamp = {2007-12-19T16:23:33.000+0100}, title = {Flexible time management in data stream systems}, url = {http://portal.acm.org/citation.cfm?id=1055596&dl=GUIDE&coll=GUIDE&CFID=47069440&CFTOKEN=95752043}, year = 2004 }