8.3. Genetic Query Optimization (GEQO) in Postgres

The GEQO module is intended for the solution of the query optimization problem similar to a traveling salesman problem (TSP). Possible query plans are encoded as integer strings. Each string represents the join order from one relation of the query to the next. E. g., the query tree

   /\
  /\ 2
 /\ 3
4  1
    
is encoded by the integer string '4-1-3-2', which means, first join relation '4' and '1', then '3', and then '2', where 1, 2, 3, 4 are relids within the Postgres optimizer.

Parts of the GEQO module are adapted from D. Whitley's Genitor algorithm.

Specific characteristics of the GEQO implementation in Postgres are:

The GEQO module allows the Postgres query optimizer to support large join queries effectively through non-exhaustive search.

8.3.1. Future Implementation Tasks for PostgreSQL GEQO

Work is still needed to improve the genetic algorithm parameter settings. In file backend/optimizer/geqo/geqo_params.c, routines gimme_pool_size and gimme_number_generations, we have to find a compromise for the parameter settings to satisfy two competing demands:

References

Reference information for GEQ algorithms.

The Hitch-Hiker's Guide to Evolutionary Computation , Jörg Heitkötter and David Beasley, InterNet resource , The Design and Implementation of the Postgres Query Optimizer , Z. Fong, University of California, Berkeley Computer Science Department , Fundamentals of Database Systems , R. Elmasri and S. Navathe, The Benjamin/Cummings Pub., Inc. .

FAQ in comp.ai.genetic is available at Encore.

File planner/Report.ps in the 'postgres-papers' distribution.