Daisy Seminar

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20111125 [2011/11/24 13:08] – siksnys20111125 [2011/11/25 11:15] (current) – root
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 **Presentation (discussion)** \\ **Presentation (discussion)** \\
  
-This Friday Laurynas will give the presentation of the paper [[http://www.public.asu.edu/~ynsilva/publications/SimilarityDB.pdf|Similarity-aware Query Processing and Optimization]].+This Friday Laurynas will give the paper presentation on [[http://www.public.asu.edu/~ynsilva/publications/SimilarityDB.pdf|Similarity-aware Query Processing and Optimization]].
  
-***Abstract***\\+**Abstract**\\
 Many application scenarios, e.g., marketing analysis, sensor networks, and medical and biological applications, require or can significantly benefit from the identification and processing of similarities in the data. Even though some work has been done to extend the semantics of some operators, e.g., join and selection, to be aware of data similarities; there has not been much study on the role, interaction, and implementation of similarity-aware operators as first-class database operators. The focus of the thesis work presented in this paper is the proposal and study of several similarity-aware database operators and a systematic analysis of their role as query operators, interactions, optimizations, and implementation techniques. This paper presents the core research Many application scenarios, e.g., marketing analysis, sensor networks, and medical and biological applications, require or can significantly benefit from the identification and processing of similarities in the data. Even though some work has been done to extend the semantics of some operators, e.g., join and selection, to be aware of data similarities; there has not been much study on the role, interaction, and implementation of similarity-aware operators as first-class database operators. The focus of the thesis work presented in this paper is the proposal and study of several similarity-aware database operators and a systematic analysis of their role as query operators, interactions, optimizations, and implementation techniques. This paper presents the core research
 questions that drive our research work and the physical database operators that were studied as part of this thesis work so far, i.e., Similarity Group-by and Similarity Join. We describe multiple optimization techniques for the introduced operators. Specifically, we present: (1) multiple non-trivial equivalence rules that enable similarity query transformations, (2) Eager and Lazy aggregation questions that drive our research work and the physical database operators that were studied as part of this thesis work so far, i.e., Similarity Group-by and Similarity Join. We describe multiple optimization techniques for the introduced operators. Specifically, we present: (1) multiple non-trivial equivalence rules that enable similarity query transformations, (2) Eager and Lazy aggregation
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 **Attendance:**\\ **Attendance:**\\
 +  * Andreas Weisberg
 +  * Benjamin Krogh
 +  * Chaithanya
 +  * Darius Sidlauskas
 +  * Mohamed Khalefa
 +  * Rene Hansen
 +  * Saulius
 +  * Laurynas Siksnys
 +  * Simonas Saltenis
 +  * Liu Xiufeng
 +  * Yoann Pitarch
 +  * 3 students
  
  
  
  
20111125.1322140131.txt.gz · Last modified: by siksnys