We propose a novel admission control policy for database queries. Our methodology uses system measurements of CPU utilization and query backlogs to determine interference between queries in execution on the same database server. Query interference may arise due to the concurrent access of hardware and software resources and can affect performance in positive and negative ways. Specifically our admission control considers the mix of jobs in service and prioritizes the query classes consuming CPU resources more efficiently. The policy ignores I/O subsystems and is therefore highly appropriate for in-memory databases. We validate our approach in trace-driven simulation and show performance increases of query slowdowns and throughputs compared to first-come first-served and shortest expected processing time first scheduling. Simulation experiments are parameterized from system traces of a SAP HANA in-memory database installation with TPC-H type workloads.
|Title of host publication||Proceedings - 2012 IEEE 5th International Conference on Cloud Computing, CLOUD 2012|
|Number of pages||8|
|Publication status||Published - 01 Jan 2012|
Kraft, S., Casale, G., Jula, A., Kilpatrick, P., & Greer, D. (2012). WIQ: Work-intensive query scheduling for in-memory database systems. In Proceedings - 2012 IEEE 5th International Conference on Cloud Computing, CLOUD 2012 (pp. 33-40) https://doi.org/10.1109/CLOUD.2012.120