Efficient Computation of Quantiles over Joins
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| Titel: | Efficient Computation of Quantiles over Joins |
|---|---|
| Autoren: | Tziavelis, Nikolaos, Carmeli, Nofar, Gatterbauer, Wolfgang, Kimelfeld, Benny, Riedewald, Mirek |
| Weitere Verfasser: | Northeastern University Boston, Représentation de Connaissances et Langages à Base de Règles pour Raisonner sur les Données (BOREAL), Centre Inria d'Université Côte d'Azur, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), Université de Perpignan Via Domitia (UPVD)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Université de Montpellier Paul-Valéry (UMPV)-Université de Perpignan Via Domitia (UPVD)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Université de Montpellier Paul-Valéry (UMPV), Technion - Israel Institute of Technology Haifa |
| Quelle: | SIGMOD/PODS 2023 - International Conference on Management of Data ; https://hal-lirmm.ccsd.cnrs.fr/lirmm-04277973 ; SIGMOD/PODS 2023 - International Conference on Management of Data, Jun 2023, Seattle, WA, United States. pp.303-315, ⟨10.1145/3584372.3588670⟩ |
| Verlagsinformationen: | CCSD ACM |
| Publikationsjahr: | 2023 |
| Bestand: | HAL Université Côte d'Azur |
| Schlagwörter: | Approximation, Ranking functions, Median, Quantiles, Join queries, Database theory, Database query processing and optimization (theory), [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB] |
| Geographisches Schlagwort: | Seattle, WA, United States |
| Beschreibung: | International audience ; We present efficient algorithms for Quantile Join Queries, abbreviated as %JQ. A %JQ asks for the answer at a specified relative position (e.g., 50% for the median) under some ordering over the answers to a Join Query (JQ). Our goal is to avoid materializing the set of all join answers, and to achieve quasilinear time in the size of the database, regardless of the total number of answers. A recent dichotomy result rules out the existence of such an algorithm for a general family of queries and orders. Specifically, for acyclic JQs without self-joins, the problem becomes intractable for ordering by sum whenever we join more than two relations (and these joins are not trivial intersections). Moreover, even for basic ranking functions beyond sum, such as min or max over different attributes, so far it is not known whether there is any nontrivial tractable %JQ. In this work, we develop a new approach to solving %JQ and show how this approach allows not just to recover known results, but also generalize them and resolve open cases. Our solution uses two subroutines: The first one needs to select what we call a "pivot answer". The second subroutine partitions the space of query answers according to this pivot, and continues searching in one partition that is represented as new %JQ over a new database. For pivot selection, we develop an algorithm that works for a large class of ranking functions that are appropriately monotone. The second subroutine requires a customized construction for the specific ranking function at hand. We show the benefit and generality of our approach by using it to establish several new complexity results. First, we prove the tractability of min and max for all acyclic JQs, thereby resolving the above question. Second, we extend the previous %JQ dichotomy for sum to all partial sums (over all subsets of the attributes). Third, we handle the intractable cases of sum by devising a deterministic approximation scheme that applies to every acyclic JQ. |
| Publikationsart: | conference object |
| Sprache: | English |
| Relation: | info:eu-repo/semantics/altIdentifier/arxiv/2305.16525; ARXIV: 2305.16525 |
| DOI: | 10.1145/3584372.3588670 |
| Verfügbarkeit: | https://hal-lirmm.ccsd.cnrs.fr/lirmm-04277973 https://hal-lirmm.ccsd.cnrs.fr/lirmm-04277973v1/document https://hal-lirmm.ccsd.cnrs.fr/lirmm-04277973v1/file/2022_Quantile_Selection.pdf https://doi.org/10.1145/3584372.3588670 |
| Rights: | info:eu-repo/semantics/OpenAccess |
| Dokumentencode: | edsbas.1C917B2C |
| Datenbank: | BASE |
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