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 relation IDs within the
PostgreSQL optimizer.
Parts of the GEQO module are adapted from D. Whitley's Genitor
algorithm.
Specific characteristics of the GEQO
implementation in PostgreSQL
are:
Usage of a steady state GA (replacement of the least fit
individuals in a population, not whole-generational replacement)
allows fast convergence towards improved query plans. This is
essential for query handling with reasonable time;
Usage of edge recombination crossover which is
especially suited
to keep edge losses low for the solution of the
TSP by means of a GA;
Mutation as genetic operator is deprecated so that no repair
mechanisms are needed to generate legal TSP tours.
The GEQO module allows
the PostgreSQL query optimizer to
support large join queries effectively through
non-exhaustive search.
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:
