Skip to main content
SpringerLink
Log in

Heuristics-Based Workload Analysis for Relational DBMSs

  • Conference paper
Information Systems: Methods, Models, and Applications (UNISCON 2012)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 137))

Included in the following conference series:

Abstract

Database systems are widely used in heterogeneous applications. However, it is difficult to decide which database management system meets requirements of a certain application best. This observation is even more true for scientific and statistical data management, because new application and research fields are often first observed in this domain. New requirements are often implied to data management while discovering unknown research and applications areas. That is, heuristics and tools do not exist to select an optimal database management system. We develop a decision support framework to support application-performance analyses on database management systems. We use mappings and merge workload information to patterns. We present heuristics for performance estimation to select the optimal database management system for a given workload. We show, these heuristics improve our decision framework by complexity reduction without loss of accuracy. Finally, we evaluate our heuristics considering standard database benchmarks.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 49.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Daniel, J.: Abadi. Query execution in column-oriented database systems. PhD thesis, Cambridge, MA, USA, Adviser: Madden, Samuel (2008)

    Google Scholar 

  2. Astrahan, M.M., Blasgen, M.W., Chamberlin, D.D., Eswaran, K.P., Gray, J., Griffiths, P.P., Frank King III, W., Lorie, R.A., McJones, P.R., Mehl, J.W., Putzolu, G.R., Traiger, I.L., Wade, B.W., Watson, V.: System R: Relational Approach to Database Management. ACM Trans. Database Syst. 1(2), 97–137 (1976)

    Article  Google Scholar 

  3. Armbrust, M., Fox, A., Griffith, R., Joseph, A.D., Katz, R.H., Konwinski, A., Lee, G., Patterson, D.A., Rabkin, A., Stoica, I., Zaharia, M.: Above the Clouds: A Berkeley View of Cloud Computing. Technical Report UCB/EECS-2009-28, EECS Department, University of California, Berkeley (February 2009)

    Google Scholar 

  4. Abadi, D.J., Madden, S.R., Hachem, N.: Column-stores vs. row-stores: How different are they really?. In: SIGMOD 2008, pp. 967–980 (2008)

    Google Scholar 

  5. Buyya, R., Yeo, C.S., Venugopal, S.: Market-Oriented Cloud Computing: Vision, Hype, and Reality for Delivering IT Services as Computing Utilities. In: HPCC 2008, pp. 5–13 (2008)

    Google Scholar 

  6. Codd, E.F., Codd, S.B., Salley, C.T.: Providing OLAP to User-Analysts: An IT Mandate. Ann ArborMichigan 24 (1993)

    Google Scholar 

  7. Chang, F., Dean, J., Ghemawat, S., Hsieh, W.C., Wallach, D.A., Burrows, M., Chandra, T., Fikes, A., Gruber, R.: Bigtable: A Distributed Storage System for Structured Data. In: OSDI 2006, pp. 205–218 (2006)

    Google Scholar 

  8. Chaudhuri, S., Narasayya, V.: Self-tuning database systems: A decade of progress. In: VLDB 2007, pp. 3–14 (2007)

    Google Scholar 

  9. Dean, J., Ghemawat, S.: MapReduce: Simplified Data Processing on Large Clusters. In: OSDI 2004, pp. 137–150 (2004)

    Google Scholar 

  10. Dean, J., Ghemawat, S.: MapReduce: simplified data processing on large clusters. Commun. ACM 51(1), 107–113 (2008)

    Article  Google Scholar 

  11. DeCandia, G., Hastorun, D., Jampani, M., Kakulapati, G., Lakshman, A., Pilchin, A., Sivasubramanian, S., Vosshall, P., Vogels, W.: Dynamo: amazon’s highly available key-value store. In: SOSP 2007, pp. 205–220 (2007)

    Google Scholar 

  12. Ferraris, D.R.L.: TPCC-UVa: an open-source TPC-C implementation for global performance measurement of computer systems. SIGMOD Record 35(4), 6–15 (2006)

    Article  Google Scholar 

  13. French, C.D.: Teaching an OLTP database kernel advanced datawarehousing techniques. In: ICDE 1997, pp. 194–198 (1997)

    Google Scholar 

  14. Foster, I.T., Zhao, Y., Raicu, I., Lu, S.: Cloud Computing and Grid Computing 360-Degree Compared. CoRR 2009, abs/0901.0131 (2009)

    Google Scholar 

  15. Graefe, G., DeWitt, D.J.: The EXODUS Optimizer Generator. In: SIGMOD 1987, pp. 160–172 (1987)

    Google Scholar 

  16. Holze, M., Gaidies, C., Ritter, N.: Consistent on-line classification of DBS workload events. In: CIKM 2009, pp. 1641–1644 (2009)

    Google Scholar 

  17. Idreos, S.: Database Cracking: Torwards Auto-tuning Database Kernels. PhD thesis (2010)

    Google Scholar 

  18. Kemper, A., Neumann, T.: HyPer: A hybrid OLTP&OLAP main memory database system based on virtual memory snapshots. In: ICDE 2011, pp. 195–206 (2011)

    Google Scholar 

  19. Korth, H.F., Silberschatz, A.: Database Research Faces the Information Explosion. Commun. ACM 40(2), 139–142 (1997)

    Article  Google Scholar 

  20. Lübcke, A., Köppen, V., Saake, G.: A Decision Model to Select the Optimal Storage Architecture for Relational Databases. In: Proceedings of the Fifth IEEE International Conference on Research Challenges in Information Science, RCIS 2011, pp. 74–84 (2011)

    Google Scholar 

  21. Lübcke, A., Saake, G.: A Framework for Optimal Selection of a Storage Architecture in RDBMS. In: DB&IS 2010, pp. 65–76 (2010)

    Google Scholar 

  22. Lübcke, A., Schäler, M., Köppen, V., Saake, G.: Workload-based Heuristics for Evaluation of Physical Database Architectures. In: DB&IS 2012, pp. 3–10 (2012)

    Google Scholar 

  23. Lübcke, A.: Challenges in Workload Analyses for Column and Row Storess. In: Grundlagen von Datenbanken (2010)

    Google Scholar 

  24. Naydenova, I., Kaloyanova, K.: Sparsity Handling and Data Explosion in OLAP Systems. In: MCIS 2010, pp. 62–70 (2010)

    Google Scholar 

  25. Tamer Özsu, M., Valdurie, P.: Principles of Distributed Database Systems, 3rd edn. Springer (2011)

    Google Scholar 

  26. Plattner, H.: A common database approach for OLTP and OLAP using an in-memory column database. In: SIGMOD 2009, pp. 1–2. ACM (2009)

    Google Scholar 

  27. Raatikainen, K.E.E.: Cluster Analysis and Workload Classification. SIGMETRICS Performance Evaluation Review 20(4), 24–30 (1993)

    Article  Google Scholar 

  28. Stonebraker, M., Abadi, D.J., Batkin, A., Chen, X., Cherniack, M., Ferreira, M., Lau, E., Lin, A., Madden, S., O’Neil, E.J., O’Neil, P.E., Rasin, A., Tran, N., Zdonik, S.B.: C-Store: A column-oriented DBMS. In: VLDB 2005, pp. 553–564. VLDB Endowment (2005)

    Google Scholar 

  29. Santos, R.J., Bernardino, J.: Real-time data warehouse loading methodology. In: IDEAS 2008, pp. 49–58 (2008)

    Google Scholar 

  30. Transaction Processing Performance Council. TPC BENCHMARKTM H. White Paper, Decision Support Standard Specification,Revision 2.11.0 (April 2010)

    Google Scholar 

  31. Vaisman, A.A., Mendelzon, A.O., Ruaro, W., Cymerman, S.G.: Supporting dimension updates in an OLAP server. Information Systems 29(2), 165–185 (2004)

    Article  Google Scholar 

  32. Zhu, Y., An, L., Liu, S.: Data Updating and Query in Real-Time Data Warehouse System. In: CSSE 2008, pp. 1295–1297 (2008)

    Google Scholar 

  33. Zukowski, M., Nes, N., Boncz, P.A.: DSM vs. NSM: CPU performance tradeoffs in block-oriented query processing. In: DaMoN 2008, pp. 47–54 (2008)

    Google Scholar 

  34. Zilio, D.C., Rao, J., Lightstone, S., Lohman, G.M., Storm, A.J., Garcia-Arellano, C., Fadden, S.: DB2 Design Advisor: Integrated automatic physical database design. In: VLDB 2004, pp. 1087–1097. VLDB Endowment (2004)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. University of Magdeburg, Magdeburg, Germany

    Andreas Lübcke, Veit Köppen & Gunter Saake

Authors
  1. Andreas Lübcke
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Veit Köppen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Gunter Saake
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Institute for Applied Informatics, Alpen-Adria-Universität Klagenfurt, Klagenfurt, Austria

    Heinrich C. Mayr  & Christian Kop  & 

  2. Brigham Young University, Provo, UT, USA

    Stephen Liddle

  3. School of Computing, Engineering & Mathematics, University of Western Sydney, Penrith, NSW, Australia

    Athula Ginige

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Lübcke, A., Köppen, V., Saake, G. (2013). Heuristics-Based Workload Analysis for Relational DBMSs. In: Mayr, H.C., Kop, C., Liddle, S., Ginige, A. (eds) Information Systems: Methods, Models, and Applications. UNISCON 2012. Lecture Notes in Business Information Processing, vol 137. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38370-0_3

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-38370-0_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38369-4

  • Online ISBN: 978-3-642-38370-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation