With large join queries the computing time spent for the genetic query optimization seems to be a mere fraction of the time Postgres needs for freeing memory via routine MemoryContextFree, file backend/utils/mmgr/mcxt.c. Debugging showed that it get stucked in a loop of routine OrderedElemPop, file backend/utils/mmgr/oset.c. The same problems arise with long queries when using the normal Postgres query optimization algorithm.
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:
Optimality of the query plan
In file backend/optimizer/geqo/geqo_eval.c, routine geqo_joinrel_size, the present hack for MAXINT overflow is to set the Postgres integer value of rel->size to its logarithm. Modifications of Rel in backend/nodes/relation.h will surely have severe impacts on the whole Postgres implementation.
Memory exhaustion may occur with more than 10 relations involved in a query. In file backend/optimizer/geqo/geqo_eval.c, routine gimme_tree is recursively called. Maybe I forgot something to be freed correctly, but I dunno what. Of course the rel data structure of the join keeps growing and growing the more relations are packed into it. Suggestions are welcome :-(
Reference information for GEQ algorithms.
The Hitch-Hiker's Guide to Evolutionary Computation, Jrg Heitktter 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..