Join order optimization improves double star graphs but not helix shapes
Join Order Enumeration and Optimization for Double-Star and Helix Join Graphs
Databases
Summary
Deciding the best way to connect multiple tables in a database query is a long-standing challenge. The authors looked at specific shapes of these connections called double-star and helix graphs to see how many ways the tables can be joined. They found that understanding these shapes helps make smarter choices for double-star patterns, speeding up the process. But for helix shapes, their specialized approach didn’t outperform general methods. This work suggests that some special graph shapes allow better optimization techniques than others.
What this means in practice
- •For database engineers: Improve query planning for systems handling double-star shaped joins by using the new enumeration-based search method.
- •For software architects: Decide when specialized join order algorithms are worth implementing based on the join graph’s shape to balance effort and benefit.
Authors
Ansh Taneja, Ryan Marcus
Abstract
Join ordering is classic problem in data management. We highlight the connection between structure-specific dynamic programming algorithms and the mathematical enumeration of the possible merge trees from a join graph. We present two case studies, on double-star and helix shaped join graphs, that we believe carry useful techniques for a toolbox of building structure-specific join optimizers. For the double-star case, we show how the enumeration leads directly to a significantly improved search algorithm, whereas for the helix case we show that a algorithm derived from the mathematical enumeration is not necessarily better than structure-agnostic algorithms.