Postgres-R(SI): Combining Replica Control with Concurrency Control Based on Snapshot Isolation
Why this work is in the frame
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Bibliographic record
Abstract
Replicating data over a cluster of workstations is a powerful tool to increase performance, and provide fault-tolerance for demanding database applications. The big challenge in such systems is to combine replica control (keeping the copies consistent) with concurrency control. Most of the research so far has focused on providing the traditional correctness criteria serializability. However, more and more database systems, e.g., Oracle and PostgreSQL, use multi-version concurrency control providing the isolation level snapshot isolation. In this paper, we present Postgres-R(SI), an extension of PostgreSQL offering transparent replication. Our replication tool is designed to work smoothly with PostgreSQL's concurrency control providing snapshot isolation for the entire replicated system. We present a detailed description of the replica control algorithm, and how it is combined with PostgreSQL's concurrency control component. Furthermore, we discuss some challenges we encountered when implementing the protocol. Our performance analysis based on the TPC-W benchmark shows that this approach exhibits excellent performance for real-life applications even if they are update intensive.
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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 | 0.000 |
| 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