SPRINT: A Scalable Parallel Classifier for Data Mining
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
A methodology for auto-recognizing DBMS workloads
CASCON '02 Proceedings of the 2002 conference of the Centre for Advanced Studies on Collaborative research
Online data migration for autonomic provisioning of databases in dynamic content web servers
CASCON '05 Proceedings of the 2005 conference of the Centre for Advanced Studies on Collaborative research
Database replication policies for dynamic content applications
Proceedings of the 1st ACM SIGOPS/EuroSys European Conference on Computer Systems 2006
Primitives for workload summarization and implications for SQL
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Autonomic Databases: Detection of Workload Shifts with n-Gram-Models
ADBIS '08 Proceedings of the 12th East European conference on Advances in Databases and Information Systems
Managing operational business intelligence workloads
ACM SIGOPS Operating Systems Review
The Psychic-Skeptic Prediction framework for effective monitoring of DBMS workloads
Data & Knowledge Engineering
Consistent on-line classification of dbs workload events
Proceedings of the 18th ACM conference on Information and knowledge management
The selection of tunable DBMS resources using the incremental/decremental relationship
APWeb/WAIM'07 Proceedings of the joint 9th Asia-Pacific web and 8th international conference on web-age information management conference on Advances in data and web management
SLA-tree: a framework for efficiently supporting SLA-based decisions in cloud computing
Proceedings of the 14th International Conference on Extending Database Technology
Managing dynamic mixed workloads for operational business intelligence
DNIS'10 Proceedings of the 6th international conference on Databases in Networked Information Systems
Surveying the landscape: an in-depth analysis of spatial database workloads
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
| Hi-index | 0.00 |
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.