Automatically classifying database workloads

ABSTRACT

The type of the workload on a database management system (DBMS) is a key consideration in tuning the system. Allocations for resources such as main memory can be very different depending on whether the workload type is Online Transaction Processing (OLTP) or Decision Support System (DSS). In this paper, we present an approach to automatically identifying a DBMS workload as either OLTP or DSS. We build a classification model based on the most significant workload characteristics that differentiate OLTP from DSS, and then use the model to identify any change in the workload type. We construct a workload classifier from the Browsing and Ordering profiles of the TPC-W benchmark. Experiments with an industry-supplied workload show that our classifier accurately identifies the mix of OLTP and DSS work within an application workload.

REFERENCES

• 1: Elnaffar, S., Martin, P. Characterizing Computer Systems' Workloads. Submitted to ACM Computing Surveys Journal.
• 2: Said S. Elnaffar, A methodology for auto-recognizing DBMS workloads, Proceedings of the 2002 conference of the Centre for Advanced Studies on Collaborative research, p.2, September 30-October 03, 2002, Toronto, Ontario, Canada
• 3: IBM, DB2 Intelligent Miner for Data, http://www-4.ibm.com/software/data/iminer/fordata/about.html, IBM (1999).
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INDEX TERMS

Primary Classification:
  C. Computer Systems Organization
  C.4 PERFORMANCE OF SYSTEMS
      Subjects: Measurement techniques

Additional Classification:
  C. Computer Systems Organization
  C.4 PERFORMANCE OF SYSTEMS
      Subjects: Modeling techniques; Performance attributes

General Terms:
Experimentation, Management, Measurement, Performance

Keywords:
DSS, OLTP, autonomic databases, classification, data mining, self-managed DBMSs, workload characterization