Abstract
Systems with heavy workloads run many queries concurrently. Modern database workloads—as those incurred by business intelligence applications—involve ad-hoc, highly complex, expensive queries. While query plans are optimized individually, the workload overall is not. Plans running together incur resource contention, resulting in sub-optimal performance. To address this, we introduce the idea of alternative-objective query optimization. Multiple query plans for the same query are generated, each optimized for an alternative resource usage. At runtime, the workload manager then can choose the plan for the query that works best for runtime conditions. This balances the system load, reducing contention, to increase overall workload throughput.
This work was supported by NSERC Discovery Grants, IBM CAS Fellowships, the National Natural Science Foundation of China Grants (No. 61070018, No. 60903108), the Program for New Century Excellent Talents in University (NCET-10-0532), the Independent Innovation Foundation of Shandong University (2012ZD012, 2009TB016), and the SAICT Experts Program.
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© 2012 Springer-Verlag Berlin Heidelberg
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Abul-Basher, Z. et al. (2012). Alternative Query Optimization for Workload Management. In: Liddle, S.W., Schewe, KD., Tjoa, A.M., Zhou, X. (eds) Database and Expert Systems Applications. DEXA 2012. Lecture Notes in Computer Science, vol 7447. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32597-7_37
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DOI: https://doi.org/10.1007/978-3-642-32597-7_37
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