=Paper=
{{Paper
|id=Vol-3203/invited1
|storemode=property
|title=Novel Techniques in Datalog Optimization (Abstract)
|pdfUrl=https://ceur-ws.org/Vol-3203/invited1.pdf
|volume=Vol-3203
|authors=Reinhard Pichler
|dblpUrl=https://dblp.org/rec/conf/datalog/Pichler22
}}
==Novel Techniques in Datalog Optimization (Abstract)==
<pdf width="1500px">https://ceur-ws.org/Vol-3203/invited1.pdf</pdf>
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Novel Techniques in Datalog Optimization (Abstract)
Reinhard Pichler
TU Wien, Institut für Logic and Computation, Favoritenstraße 9, A-1040 Wien, Austria


                                      Abstract
                                      Datalog has been specifically designed for processing recursive queries. As such it seems the perfect
                                      fit for today’s data analytics applications, which typically require some kind of iteration or recursion.
                                      However, basic analytical tasks such as computing shortest paths, betweenness centrality, or connected
                                      components in a graph as well as solving optimization problems by gradient descent or other methods
                                      crucially depend on aggregation. For Datalog, this poses new challenges due to the loss of the usual
                                      monotonicity properties in case of aggregation.
                                      In this talk, I will present recent work in which
                                        • we have studied a generalization of Datalog that allows for recursive computations over general
                                          semirings (with classical Datalog corresponding to the special case of the Boolean semiring),
                                        • we have analyzed the convergence of this generalization of Datalog, and
                                        • we have introduced a powerful new optimization technique that covers known optimizations such
                                          as magic-set rewriting as well as new ones.

                                      This talk is mainly based on the following papers:
                                       1. Mahmoud Abo Khamis, Hung Q. Ngo, Reinhard Pichler, Dan Suciu, Yisu Remy Wang: Convergence
                                          of Datalog over (Pre-) Semirings. PODS 2022.
                                       2. Yisu Remy Wang, Mahmoud Abo Khamis, Hung Q. Ngo, Reinhard Pichler, Dan Suciu: Optimizing
                                          Recursive Queries with Progam Synthesis. SIGMOD Conference 2022.




Datalog 2.0 2022: 4th International Workshop on the Resurgence of Datalog in Academia and Industry, September 05,
2022, Genova - Nervi, Italy
$ pichler@dbai.tuwien.ac.at (R. Pichler)
€ https://www.dbai.tuwien.ac.at/staff/pichler/ (R. Pichler)
 0000-0002-1760-122X (R. Pichler)
                                    © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
 CEUR
 Workshop
 Proceedings
               http://ceur-ws.org
               ISSN 1613-0073
                                    CEUR Workshop Proceedings (CEUR-WS.org)



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