A framework for autonomic workload management in DBMSs
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract In today's database server environments, multiple types of workloads can be present in a system simultaneously. Workload types may include on-line transaction processing and business intelligence. Workloads may also have different levels of business importance and distinct performance objectives, which are typically derived from service level agreements. An autonomic workload management system for database management systems (DBMSs) dynamically monitors and controls the flow of the workloads to help DBMSs achieve the desired performance objectives. In this paper, we present a framework and a prototype implementation for autonomic workload management in DBMSs. The framework and the prototype provide the ability to achieve performance objectives of workloads with diverse characteristics, different levels of business importance and varying resource demands while protecting DBMSs against performance failure. The prototype system is implemented on top of IBM ® DB2 ® Workload Manager. Initial experiments using the prototype system are presented to demonstrate the effectiveness of the framework.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it