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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 in Postgres.
Parts of the GEQO module are adapted from D. Whitley's Genitor
algorithm.
Specific characteristics of the GEQO implementation in Postgres
are:
Usage of a steady stateGA (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 gives the following benefits to the Postgres DBMS
compared to the Postgres query optimizer implementation:
Handling of large join queries through non-exhaustive search;
Improved cost size approximation of query plans since no longer
plan merging is needed (the GEQO module evaluates the cost for a
query plan as an individual).
