Workload-independent data-driven vertical partitioning

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

2 Scopus citations

Abstract

Vertical partitioning is a well-explored area of automatic physical database design. The classic approach is as follows: Derive an optimal vertical partitioning scheme for a given database and a workload. The workload describes queries, their frequencies, and involved attributes. In this paper we identify a novel class of vertical partitioning algorithms. The algorithms of this class do not rely on knowledge of the workload, but instead use data properties that are contained in the workload itself. We propose such algorithm that uses a logical scheme represented by functional dependencies, which are derived from stored data. In order to discover functional dependencies we use TANE — a popular functional dependency extraction algorithm. We evaluate our algorithm using an industrial DBMS (PostgreSQL) on number of workloads. We compare the performance of an unpartitioned configuration with partitions produced by our algorithm and several state-of-the-art workload-aware algorithms.

Original languageEnglish
Title of host publicationNew Trends in Databases and Information Systems - ADBIS 2017 Short Papers and Workshops AMSD, BigNovelTI, DAS, SW4CH, DC, Proceedings
EditorsJerome Darmont, Marite Kirikova, Kjetil Norvag, Robert Wrembel, George A. Papadopoulos, Johann Gamper, Stefano Rizzi
PublisherSpringer Nature
Pages275-284
Number of pages10
ISBN (Print)9783319671611
DOIs
StatePublished - 1 Oct 2017
Event21st European Conference on Advances in Databases and Information Systems, ADBIS 2017 and 1st workshop on Data Driven Approaches for Analyzing and Managing Scholarly Data, AMSD 2017, 1st workshop on Novel Techniques for Integrating Big Data, BigNovelTI 2017, 1st International workshop on Data Science: Methodologies and Use-Cases, DaS 2017, 2nd International workshop on Semantic Web for Cultural Heritage, SW4CH 2017 - Nicosia, Cyprus
Duration: 24 Sep 201727 Sep 2017

Publication series

NameCommunications in Computer and Information Science
Volume767
ISSN (Print)1865-0929

Conference

Conference21st European Conference on Advances in Databases and Information Systems, ADBIS 2017 and 1st workshop on Data Driven Approaches for Analyzing and Managing Scholarly Data, AMSD 2017, 1st workshop on Novel Techniques for Integrating Big Data, BigNovelTI 2017, 1st International workshop on Data Science: Methodologies and Use-Cases, DaS 2017, 2nd International workshop on Semantic Web for Cultural Heritage, SW4CH 2017
CountryCyprus
CityNicosia
Period24/09/1727/09/17

Scopus subject areas

  • Computer Science(all)
  • Mathematics(all)

Keywords

  • Functional dependency
  • Physical design
  • Vertical partitioning

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