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We introduce efficient ranked enumeration for theta-joins with inequalities. Our method delivers top-k results quickly, outperforming existing database systems in practice.

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Area of Science:

  • Database Systems
  • Theoretical Computer Science
  • Data Mining

Background:

  • Theta-joins, especially with complex inequality predicates, pose significant computational challenges.
  • Existing methods for ranked query processing are often limited to equi-joins or lack theoretical guarantees for more general join types.

Purpose of the Study:

  • To develop an efficient algorithm for ranked enumeration of theta-joins with inequality predicates.
  • To provide strong theoretical time and space complexity guarantees for this class of queries.
  • To demonstrate the practical efficiency and memory usage of the proposed approach.

Main Methods:

  • Developing a novel factorized representation of the query output.
  • Designing an on-the-fly construction method for this representation.
  • Analyzing the time and space complexity for acyclic full join queries with inequality conditions.

Main Results:

  • Achieving time complexity for returning the top-k ranked answers for acyclic full join queries with inequality conditions.
  • Demonstrating guarantees that are polylogarithmic factors away from the best known complexities for equi-joins and even output-sensitive complexities.
  • Extending guarantees to queries with selections and specific types of projections (free-connex, bag semantics).
  • Showing practical performance improvements of orders of magnitude over state-of-the-art systems.

Conclusions:

  • The proposed ranked enumeration approach offers the first non-trivial theoretical guarantees for theta-joins beyond equi-joins.
  • The method is both theoretically sound and practically efficient, providing significant speedups and memory savings.