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Record W4323343708 · doi:10.14778/3579075.3579080

Change Propagation Without Joins

2023· article· en· W4323343708 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueProceedings of the VLDB Endowment · 2023
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Database Systems and Queries
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsJoinsComputer scienceQuery planLatency (audio)Query optimizationConstant (computer programming)Operator (biology)Theoretical computer sciencePlan (archaeology)Space (punctuation)Distributed computingInformation retrievalSargableSearch engineWeb search queryTelecommunications

Abstract

fetched live from OpenAlex

We revisit the classical change propagation framework for query evaluation under updates. The standard framework takes a query plan and materializes the intermediate views, which incurs high polynomial costs in both space and time, with the join operator being the culprit. In this paper, we propose a new change propagation framework without joins, thus naturally avoiding this polynomial blowup. Meanwhile, we show that the new framework still supports constant-delay enumeration of both the deltas and the full query results, the same as in the standard framework. Furthermore, we provide a quantitative analysis of its update cost, which not only recovers many recent theoretical results on the problem, but also yields an effective approach to optimizing the query plan. The new framework is also easy to be integrated into an existing streaming database system. Experimental results show that our system prototype, implemented using Flink DataStream API, significantly outperforms other systems in terms of space, time, and latency.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.865
Threshold uncertainty score0.236

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.040
GPT teacher head0.261
Teacher spread0.220 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it