geqo_main.c

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/*------------------------------------------------------------------------
 *
 * geqo_main.c
 *    solution to the query optimization problem
 *    by means of a Genetic Algorithm (GA)
 *
 * Portions Copyright (c) 1996-2026, PostgreSQL Global Development Group
 * Portions Copyright (c) 1994, Regents of the University of California
 *
 * src/backend/optimizer/geqo/geqo_main.c
 *
 *-------------------------------------------------------------------------
 */
 
/*
 * contributed by:
 * =*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=
 * *  Martin Utesch              * Institute of Automatic Control      *
 * =                             = University of Mining and Technology =
 * *  utesch@aut.tu-freiberg.de  * Freiberg, Germany                   *
 * =*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=
 */
 
/* -- parts of this are adapted from D. Whitley's Genitor algorithm -- */
 
#include "postgres.h"
 
#include <math.h>
 
#include "optimizer/geqo.h"
 
#include "optimizer/geqo_misc.h"
#if defined(CX)
#include "optimizer/geqo_mutation.h"
#endif
#include "optimizer/geqo_pool.h"
#include "optimizer/geqo_random.h"
#include "optimizer/geqo_recombination.h"
#include "optimizer/geqo_selection.h"
 
 
/*
 * Configuration options
 */
int         Geqo_effort;
int         Geqo_pool_size;
int         Geqo_generations;
double      Geqo_selection_bias;
double      Geqo_seed;
 
/* GEQO is treated as an in-core planner extension */
int         Geqo_planner_extension_id = -1;
 
static int  gimme_pool_size(int nr_rel);
static int  gimme_number_generations(int pool_size);
 
/* complain if no recombination mechanism is #define'd */
#if !defined(ERX) && \
    !defined(PMX) && \
    !defined(CX)  && \
    !defined(PX)  && \
    !defined(OX1) && \
    !defined(OX2)
#error "must choose one GEQO recombination mechanism in geqo.h"
#endif
 
 
/*
 * geqo
 *    solution of the query optimization problem
 *    similar to a constrained Traveling Salesman Problem (TSP)
 */
 
RelOptInfo *
geqo(PlannerInfo *root, int number_of_rels, List *initial_rels)
{
    GeqoPrivateData private;
    int         generation;
    Chromosome *momma;
    Chromosome *daddy;
    Chromosome *kid;
    Pool       *pool;
    int         pool_size,
                number_generations;
 
#ifdef GEQO_DEBUG
    int         status_interval;
#endif
    Gene       *best_tour;
    RelOptInfo *best_rel;
 
#if defined(ERX)
    Edge       *edge_table;     /* list of edges */
    int         edge_failures = 0;
#endif
#if defined(CX) || defined(PX) || defined(OX1) || defined(OX2)
    City       *city_table;     /* list of cities */
#endif
#if defined(CX)
    int         cycle_diffs = 0;
    int         mutations = 0;
#endif
 
    if (Geqo_planner_extension_id < 0)
        Geqo_planner_extension_id = GetPlannerExtensionId("geqo");
 
/* set up private information */
    SetPlannerInfoExtensionState(root, Geqo_planner_extension_id, &private);
    private.initial_rels = initial_rels;
 
/* inform core planner that we may replan */
    root->assumeReplanning = true;
 
/* initialize private number generator */
    geqo_set_seed(root, Geqo_seed);
 
/* set GA parameters */
    pool_size = gimme_pool_size(number_of_rels);
    number_generations = gimme_number_generations(pool_size);
#ifdef GEQO_DEBUG
    status_interval = 10;
#endif
 
/* allocate genetic pool memory */
    pool = alloc_pool(root, pool_size, number_of_rels);
 
/* random initialization of the pool */
    random_init_pool(root, pool);
 
/* sort the pool according to cheapest path as fitness */
    sort_pool(root, pool);      /* we have to do it only one time, since all
                                 * kids replace the worst individuals in
                                 * future (-> geqo_pool.c:spread_chromo ) */
 
#ifdef GEQO_DEBUG
    elog(DEBUG1, "GEQO selected %d pool entries, best %.2f, worst %.2f",
         pool_size,
         pool->data[0].worth,
         pool->data[pool_size - 1].worth);
#endif
 
/* allocate chromosome momma and daddy memory */
    momma = alloc_chromo(root, pool->string_length);
    daddy = alloc_chromo(root, pool->string_length);
 
#if defined (ERX)
#ifdef GEQO_DEBUG
    elog(DEBUG2, "using edge recombination crossover [ERX]");
#endif
/* allocate edge table memory */
    edge_table = alloc_edge_table(root, pool->string_length);
#elif defined(PMX)
#ifdef GEQO_DEBUG
    elog(DEBUG2, "using partially matched crossover [PMX]");
#endif
/* allocate chromosome kid memory */
    kid = alloc_chromo(root, pool->string_length);
#elif defined(CX)
#ifdef GEQO_DEBUG
    elog(DEBUG2, "using cycle crossover [CX]");
#endif
/* allocate city table memory */
    kid = alloc_chromo(root, pool->string_length);
    city_table = alloc_city_table(root, pool->string_length);
#elif defined(PX)
#ifdef GEQO_DEBUG
    elog(DEBUG2, "using position crossover [PX]");
#endif
/* allocate city table memory */
    kid = alloc_chromo(root, pool->string_length);
    city_table = alloc_city_table(root, pool->string_length);
#elif defined(OX1)
#ifdef GEQO_DEBUG
    elog(DEBUG2, "using order crossover [OX1]");
#endif
/* allocate city table memory */
    kid = alloc_chromo(root, pool->string_length);
    city_table = alloc_city_table(root, pool->string_length);
#elif defined(OX2)
#ifdef GEQO_DEBUG
    elog(DEBUG2, "using order crossover [OX2]");
#endif
/* allocate city table memory */
    kid = alloc_chromo(root, pool->string_length);
    city_table = alloc_city_table(root, pool->string_length);
#endif
 
 
/* my pain main part: */
/* iterative optimization */
 
    for (generation = 0; generation < number_generations; generation++)
    {
        /* SELECTION: using linear bias function */
        geqo_selection(root, momma, daddy, pool, Geqo_selection_bias);
 
#if defined (ERX)
        /* EDGE RECOMBINATION CROSSOVER */
        gimme_edge_table(root, momma->string, daddy->string, pool->string_length, edge_table);
 
        kid = momma;
 
        /* are there any edge failures ? */
        edge_failures += gimme_tour(root, edge_table, kid->string, pool->string_length);
#elif defined(PMX)
        /* PARTIALLY MATCHED CROSSOVER */
        pmx(root, momma->string, daddy->string, kid->string, pool->string_length);
#elif defined(CX)
        /* CYCLE CROSSOVER */
        cycle_diffs = cx(root, momma->string, daddy->string, kid->string, pool->string_length, city_table);
        /* mutate the child */
        if (cycle_diffs == 0)
        {
            mutations++;
            geqo_mutation(root, kid->string, pool->string_length);
        }
#elif defined(PX)
        /* POSITION CROSSOVER */
        px(root, momma->string, daddy->string, kid->string, pool->string_length, city_table);
#elif defined(OX1)
        /* ORDER CROSSOVER */
        ox1(root, momma->string, daddy->string, kid->string, pool->string_length, city_table);
#elif defined(OX2)
        /* ORDER CROSSOVER */
        ox2(root, momma->string, daddy->string, kid->string, pool->string_length, city_table);
#endif
 
 
        /* EVALUATE FITNESS */
        kid->worth = geqo_eval(root, kid->string, pool->string_length);
 
        /* push the kid into the wilderness of life according to its worth */
        spread_chromo(root, kid, pool);
 
 
#ifdef GEQO_DEBUG
        if (status_interval && !(generation % status_interval))
            print_gen(stdout, pool, generation);
#endif
 
    }
 
 
#if defined(ERX)
#if defined(GEQO_DEBUG)
    if (edge_failures != 0)
        elog(LOG, "[GEQO] failures: %d, average: %d",
             edge_failures, (int) number_generations / edge_failures);
    else
        elog(LOG, "[GEQO] no edge failures detected");
#else
    /* suppress variable-set-but-not-used warnings from some compilers */
    (void) edge_failures;
#endif
#endif
 
#if defined(CX) && defined(GEQO_DEBUG)
    if (mutations != 0)
        elog(LOG, "[GEQO] mutations: %d, generations: %d",
             mutations, number_generations);
    else
        elog(LOG, "[GEQO] no mutations processed");
#endif
 
#ifdef GEQO_DEBUG
    print_pool(stdout, pool, 0, pool_size - 1);
#endif
 
#ifdef GEQO_DEBUG
    elog(DEBUG1, "GEQO best is %.2f after %d generations",
         pool->data[0].worth, number_generations);
#endif
 
 
    /*
     * got the cheapest query tree processed by geqo; first element of the
     * population indicates the best query tree
     */
    best_tour = (Gene *) pool->data[0].string;
 
    best_rel = gimme_tree(root, best_tour, pool->string_length);
 
    if (best_rel == NULL)
        elog(ERROR, "geqo failed to make a valid plan");
 
    /* DBG: show the query plan */
#ifdef NOT_USED
    print_plan(best_plan, root);
#endif
 
    /* ... free memory stuff */
    free_chromo(root, momma);
    free_chromo(root, daddy);
 
#if defined (ERX)
    free_edge_table(root, edge_table);
#elif defined(PMX)
    free_chromo(root, kid);
#elif defined(CX)
    free_chromo(root, kid);
    free_city_table(root, city_table);
#elif defined(PX)
    free_chromo(root, kid);
    free_city_table(root, city_table);
#elif defined(OX1)
    free_chromo(root, kid);
    free_city_table(root, city_table);
#elif defined(OX2)
    free_chromo(root, kid);
    free_city_table(root, city_table);
#endif
 
    free_pool(root, pool);
 
    /* ... clear root pointer to our private storage */
    SetPlannerInfoExtensionState(root, Geqo_planner_extension_id, NULL);
 
    return best_rel;
}
 
 
/*
 * Return either configured pool size or a good default
 *
 * The default is based on query size (no. of relations) = 2^(QS+1),
 * but constrained to a range based on the effort value.
 */
static int
gimme_pool_size(int nr_rel)
{
    double      size;
    int         minsize;
    int         maxsize;
 
    /* Legal pool size *must* be at least 2, so ignore attempt to select 1 */
    if (Geqo_pool_size >= 2)
        return Geqo_pool_size;
 
    size = pow(2.0, nr_rel + 1.0);
 
    maxsize = 50 * Geqo_effort; /* 50 to 500 individuals */
    if (size > maxsize)
        return maxsize;
 
    minsize = 10 * Geqo_effort; /* 10 to 100 individuals */
    if (size < minsize)
        return minsize;
 
    return (int) ceil(size);
}
 
 
/*
 * Return either configured number of generations or a good default
 *
 * The default is the same as the pool size, which allows us to be
 * sure that less-fit individuals get pushed out of the breeding
 * population before the run finishes.
 */
static int
gimme_number_generations(int pool_size)
{
    if (Geqo_generations > 0)
        return Geqo_generations;
 
    return pool_size;
}