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Parallelizing Datalog Programs by Generalized Pivoting

Summary: Parallelizes bottom-up Datalog by identifying decomposable programs that allow partitioned, communication- and synchronization-free fixpoint evaluation. Introduces generalized pivoting as a sufficient condition (and necessary for complete decomposability) and defines completely decomposable programs. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
941
Venue
PODS
Year
1991
Pagerank
5.2717743e-05
Overall Rank
5,925 | 58.79%
DOI
-

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 4 of 4 citing papers.

Rank Citing Paper Year Venue Pagerank
3,200 Big Data Analytics with Datalog Queries on Spark 2016 SIGMOD 7.3912411e-05
3,958 MLog: Towards Declarative In-Database Machine Learning 2017 VLDB 6.5897636e-05
8,883 Optimizing Parallel Recursive Datalog Evaluation on Multicore Machines 2022 SIGMOD 4.4285471e-05
11,130 The Vadalog Parallel System: Distributed Reasoning with Datalog+/- 2024 VLDB 4.1945683e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 7 of 7 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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