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• W2030201711 abstract "Large amount of data and increased demand to extract, analyze and derive knowledge from data are impairing nowadays performance of enterprise mission-critical systems such as databases. For databases, the challenging problem is to manage complex and sometimes non-optimized queries executed on enormous data sets stored across several tables. This generally results in increased query response time and loss of employees productivity. In this paper, we investigate the problem of enterprise computing resources availability. Our goal is to minimize performance degradation arising from resource intensive queries. We propose a risk aware approach that decouples the process of analyzing resource requirements of sql queries from their execution. We leverage XACML to control users' requests and to monitor database loads. This allows us to adjust available resources in a database system to computing resource needs of queries. A query can therefore run in a database if it does not severely impact the performance of the database. Otherwise, we propose to the requester a replacement query denoted what-if-query. Such query proposes results that are similar to the results of the requester's query, is secure and provides acceptable answers when it executes without compromising the performance of the database." @default.
• W2030201711 created "2016-06-24" @default.
• W2030201711 creator A5056253313 @default.
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• W2030201711 date "2015-03-01" @default.
• W2030201711 modified "2023-09-27" @default.
• W2030201711 title "Risk Aware Query Replacement Approach for Secure Databases Performance Management" @default.
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• W2030201711 doi "https://doi.org/10.1109/tdsc.2014.2306675" @default.
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