Babu, Shivnath and Munagala, Kamesh and Widom, Jennifer and Motwani, Rajeev (2004) Adaptive Caching for Continuous Queries. Technical Report. Stanford.
We address the problem of executing continuous multiway join queries in unpredictable and volatile environments. Our query class captures windowed join queries in data stream systems as well as conventional maintenance of materialized join views. Our adaptive approach handles streams of updates whose rates and data characteristics may change over time, as well as changes in system conditions such as memory availability. In this paper we focus specifically on the problem of adaptive placement and removal of <i>caches</i> to optimize join performance. Our approach automatically considers conventional tree-shaped join plans with materialized subresults at every intermediate node, subresult-free <i>MJoins</i>, and the entire spectrum between them. We provide a family of algorithms for selecting candidate caches, monitoring their cost and benefits in current conditions, allocating memory to caches, and adapting as conditions change. All of our algorithms are implemented in the STREAM prototype Data Stream Management System and a thorough experimental evaluation is included.
|Item Type:||Techreport (Technical Report)|
|Uncontrolled Keywords:||Caching; data streams; adaptive optimization|
|Subjects:||Computer Science > Data Streams|
|Related URLs:||Project Homepage||http://infolab.stanford.edu/stream/|
|Deposited By:||Import Account|
|Deposited On:||08 Mar 2004 16:00|
|Last Modified:||23 Dec 2008 08:41|
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