PAQO: a preference-aware query optimizer for PostgreSQL

  • Authors:
  • Nicholas L. Farnan;Adam J. Lee;Panos K. Chrysanthis;Ting Yu

  • Affiliations:
  • Department of Computer Science, University of Pittsburgh, Pittsburgh, PA;Department of Computer Science, University of Pittsburgh, Pittsburgh, PA;Department of Computer Science, University of Pittsburgh, Pittsburgh, PA;Department of Computer Science, North Carolina State University Raleigh, NC and Qatar Computing Research Institute, Doha, Qatar

  • Venue:
  • Proceedings of the VLDB Endowment
  • Year:
  • 2013

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Abstract

Although the declarative nature of SQL provides great utility to database users, its use in distributed database management systems can leave users unaware of which servers in the system are evaluating portions of their queries. By allowing users to merely say what data they are interested in accessing without providing guidance regarding how to retrieve it, query optimizers can generate plans with unintended consequences to the user (e.g., violating user privacy by revealing sensitive portions of a user's query to untrusted servers, or impacting result freshness by pulling data from stale data stores). To address these types of issues, we have created a framework that empowers users with the ability to specify constraints on the kinds of plans that can be produced by the optimizer to evaluate their queries. Such constraints are specified through an extended version of SQL that we have developed which we call PASQL. With this proposal, we aim to demonstrate PAQO, a version of PostgreSQL's query optimizer that we have modified to produce plans that respect constraints specified through PASQL while optimizing user-specified SQL queries in terms of performance.