Performance and resource modeling in highly-concurrent OLTP workloads

Proceedings of the ACM SIGMOD International Conference on Management of Data

Volumn , Issue , 2013, Pages 301-312

  Mozafari, Barzan ^a   Curino, Carlo ^b   Jindal, Alekh ^a   Madden, Samuel ^a  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^b MICROSOFT   (United States)

Author keywords

Multi tenancy; OLTP; Performance Predictions

Indexed keywords

DATABASE ADMINISTRATORS; MAXIMUM THROUGH-PUT; MULTI TENANCIES; OLTP; ONLINE TRANSACTION PROCESSING SYSTEMS; PERFORMANCE ANALYSIS; PERFORMANCE PREDICTION; RESOURCE CONSUMPTION;

DATABASE SYSTEMS; ONLINE SYSTEMS;

C (PROGRAMMING LANGUAGE);

EID: 84880556592     PISSN: 07308078     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2463676.2467800     Document Type: Conference Paper

References (22)

1. OLTP Benchmark. http://oltpbenchmark.com.
2. M. Ahmad and I. T. Bowman. Predicting system performance for multi-tenant database workloads. In DBTest. 2011.
3. M. Ahmad, et al Predicting completion times of batch query workloads using interaction-aware models and simulation. In EDBT. 2011.
4. F. R. Bach and M. I. Jordan. Kernel Independent Component Analysis. Journal of Machine Learning Research, 3:1-48, 2002.
5. C. Curino, et al Workload-aware database monitoring and consolidation. In SIGMOD. 2011.
6. C. Curino, et al Update Rewriting and Integrity Constraint Maintenance in a Schema Evolution Support System: PRISM++. PVLDB, 2010.
7. P. Di Sanzo, et al Analytical modeling of lock-based concurrency control with arbitrary transaction data access patterns. In ICPE. 2010.
8. J. Duggan, et al Performance prediction for concurrent database workloads. In SIGMOD. 2011.
9. M. Ester, et al A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise. In KDD. 1996.
10. A. Ganapathi, et al Predicting Multiple Metrics for Queries: Better Decisions Enabled by Machine Learning. In ICDE. 2009.
11. J. Gray, et al The dangers of replication and a solution. SIGMOD Rec., 25(2), June 1996.
12. C. Gupta, A. Mehta, and U. Dayal. PQR: Predicting Query Execution Times for Autonomous Workload Management. In ICAC. 2008.
13. G. Luo, J. F. Naughton, and P. S. Yu. Multi-query SQL progress indicators. In EDBT. 2006.
14. A. Mehta et al. BI batch manager: a system for managing batch workloads on enterprise data-warehouses. In EDBT. 2008.
15. B. Mozafari, et al DBSeer: Performance and Resource Modeling in Highly-Concurrent OLTP Workloads. Technical report, MIT, 2013.
16. B. Mozafari, C. Curino, and S. Madden. Resource and performance prediction for building a next generation database cloud. CIDR, 2013.
17. I. K. Ryu and A. Tomasian. Analysis of database performance with dynamic locking. J. ACM, 37, 1990.
18. S. Salza and M. Renzetti. Performance Modeling of Paralled Database System. Informatica (Slovenia), 22(2), 1998.
19. V. Singhal and A. J. Smith. Analysis of locking behavior in three real database systems. VLDBJ, 6, 1997.
20. Y. C. Tay, R. Suri, and N. Goodman. A Mean Value Performance Model for Locking in Databases: The Waiting Case. In SIGMOD. 1984.
21. A. Tomasian. On a More Realistic Lock Contention Model and Its Analysis. In ICDE. 1994.
22. P. S. Yu, D. M. Dias, and S. S. Lavenberg. On the analytical modeling of database concurrency control. J. ACM, 40, 1993.