The Free Termination Property of Queries Over Time
January 31, 2025 Β· Declared Dead Β· π International Conference on Database Theory
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Conor Power, Paraschos Koutris, Joseph M Hellerstein
arXiv ID
2502.00222
Category
cs.DB: Databases
Cross-listed
cs.DC,
cs.PL
Citations
4
Venue
International Conference on Database Theory
Last Checked
4 months ago
Abstract
Building on prior work on distributed databases and the CALM Theorem, we define and study the question of free termination: in the absence of distributed coordination, what query properties allow nodes in a distributed (database) system to unilaterally terminate execution even though they may receive additional data or messages in the future? This completeness question is complementary to the soundness questions studied in the CALM literature. We also develop a new model based on semiautomata that allows us to bridge from the relational transducer model of the CALM papers to algebraic models that are popular among software engineers (e.g. CRDTs) and of increasing interest to database theory for datalog extensions and incremental view maintenance.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Databases
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Untangling Blockchain: A Data Processing View of Blockchain Systems
R.I.P.
π»
Ghosted
Converting Static Image Datasets to Spiking Neuromorphic Datasets Using Saccades
R.I.P.
π»
Ghosted
BLOCKBENCH: A Framework for Analyzing Private Blockchains
R.I.P.
π»
Ghosted
Data Synthesis based on Generative Adversarial Networks
R.I.P.
π»
Ghosted
HoloClean: Holistic Data Repairs with Probabilistic Inference
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted