An adaptive hash join algorithm on a network of workstations
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Bibliographic record
Abstract
Due to advances in computer technology, many organizations have a large number of workstation-class machines connected by LAN. Such a network of workstations (NOW) can be used for parallel processing, including database query processing. This paper proposes a new load sharing algorithm for hash join processing on NOWs. This new algorithm combines a chunking method with hash join to manage dynamic changes that occur in NOW environments. The algorithm is compared with two other algorithms: an adaptive nested-loop join and adaptive GRACE hash join. These three algorithms were evaluated on a Pentium-based heterogeneous NOW system with skewed data and various non-query background loads. The results show that the new algorithm is the best among the three in most of the cases and should be used for single join processing on NOWs.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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