%0 Report
%9 Technical Report
%A Babu, Shivnath
%A Widom, Jennifer
%D 2003
%F ilprints:629
%I Stanford InfoLab
%T StreaMon: An Adaptive Engine for Stream Query Processing
%U http://ilpubs.stanford.edu:8090/629/
%X <i>StreaMon</i>  is the  adaptive query processing  engine of  the <i> STREAM</i> prototype Data Stream  Management System (DSMS).  A fundamental challenge in many DSMS applications (e.g.,  network monitoring, financial  monitoring over  stock tickers, sensor  processing) is  that  conditions may  vary significantly  over time.   Since queries in  these systems  are usually  long-running, or <i>continuous</i>, it  is important to consider <i> adaptive</i> approaches   to  query  processing.    Without  adaptivity, performance  may   drop  drastically   as  stream  data   and  arrival characteristics, query loads, and system conditions change over time.  StreaMon uses several techniques  to support adaptive query processing.  We   demonstrate three of them:  <ol> <li> Reducing  run-time  memory requirements  for  continuous queries  by exploiting stream data and arrival patterns. </li> <li> Adaptive  join  ordering for  pipelined  multiway  stream joins,  with strong quality guarantees. </li> <li>  Placing subresult caches adaptively in pipelined multiway stream joins to avoid recomputation of intermediate results. </li> </ol>