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Fix estimate_num_groups to be able to use expression-index statistics 

when there is an expressional index matching a GROUP BY item.
This commit is contained in:
Tom Lane 2004-09-18 19:39:50 +00:00
parent 089fb6c4ce
commit 84c7cef5eb
1 changed files with 113 additions and 73 deletions
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186
src/backend/utils/adt/selfuncs.c
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@ -15,7 +15,7 @@
*
*
* IDENTIFICATION
* $PostgreSQL: pgsql/src/backend/utils/adt/selfuncs.c,v 1.165 2004/08/30 02:54:39 momjian Exp $
* $PostgreSQL: pgsql/src/backend/utils/adt/selfuncs.c,v 1.166 2004/09/18 19:39:50 tgl Exp $
*
*-------------------------------------------------------------------------
*/
@ -1869,6 +1869,71 @@ fail:
ReleaseVariableStats(rightvar);
}
/*
* Helper routine for estimate_num_groups: add an item to a list of
* GroupVarInfos, but only if it's not known equal to any of the existing
* entries.
*/
typedef struct
{
Node *var; /* might be an expression, not just a Var */
RelOptInfo *rel; /* relation it belongs to */
double ndistinct; /* # distinct values */
} GroupVarInfo;
static List *
add_unique_group_var(Query *root, List *varinfos,
Node *var, VariableStatData *vardata)
{
GroupVarInfo *varinfo;
double ndistinct;
ListCell *lc;
ndistinct = get_variable_numdistinct(vardata);
/* cannot use foreach here because of possible list_delete */
lc = list_head(varinfos);
while (lc)
{
varinfo = (GroupVarInfo *) lfirst(lc);
/* must advance lc before list_delete possibly pfree's it */
lc = lnext(lc);
/* Drop exact duplicates */
if (equal(var, varinfo->var))
return varinfos;
/*
* Drop known-equal vars, but only if they belong to different
* relations (see comments for estimate_num_groups)
*/
if (vardata->rel != varinfo->rel &&
exprs_known_equal(root, var, varinfo->var))
{
if (varinfo->ndistinct <= ndistinct)
{
/* Keep older item, forget new one */
return varinfos;
}
else
{
/* Delete the older item */
varinfos = list_delete_ptr(varinfos, varinfo);
}
}
}
varinfo = (GroupVarInfo *) palloc(sizeof(GroupVarInfo));
varinfo->var = var;
varinfo->rel = vardata->rel;
varinfo->ndistinct = ndistinct;
varinfos = lappend(varinfos, varinfo);
return varinfos;
}
/*
* estimate_num_groups - Estimate number of groups in a grouped query
*
@ -1900,6 +1965,9 @@ fail:
* increase the number of distinct values (unless it is volatile,
* which we consider unlikely for grouping), but it probably won't
* reduce the number of distinct values much either.
* As a special case, if a GROUP BY expression can be matched to an
* expressional index for which we have statistics, then we treat the
* whole expression as though it were just a Var.
* 2. If the list contains Vars of different relations that are known equal
* due to equijoin clauses, then drop all but one of the Vars from each
* known-equal set, keeping the one with smallest estimated # of values
@ -1926,25 +1994,44 @@ fail:
double
estimate_num_groups(Query *root, List *groupExprs, double input_rows)
{
List *allvars = NIL;
List *varinfos = NIL;
double numdistinct;
ListCell *l;
typedef struct
{ /* varinfos is a List of these */
Var *var;
double ndistinct;
} MyVarInfo;
/* We should not be called unless query has GROUP BY (or DISTINCT) */
Assert(groupExprs != NIL);
/* Step 1: get the unique Vars used */
/*
* Steps 1/2: find the unique Vars used, treating an expression as a Var
* if we can find stats for it. For each one, record the statistical
* estimate of number of distinct values (total in its table, without
* regard for filtering).
*/
foreach(l, groupExprs)
{
Node *groupexpr = (Node *) lfirst(l);
VariableStatData vardata;
List *varshere;
ListCell *l2;
/*
* If examine_variable is able to deduce anything about the GROUP BY
* expression, treat it as a single variable even if it's really more
* complicated.
*/
examine_variable(root, groupexpr, 0, &vardata);
if (vardata.statsTuple != NULL || vardata.isunique)
{
varinfos = add_unique_group_var(root, varinfos,
groupexpr, &vardata);
ReleaseVariableStats(vardata);
continue;
}
ReleaseVariableStats(vardata);
/*
* Else pull out the component Vars
*/
varshere = pull_var_clause(groupexpr, false);
/*
@ -1959,70 +2046,24 @@ estimate_num_groups(Query *root, List *groupExprs, double input_rows)
return input_rows;
continue;
}
allvars = list_concat(allvars, varshere);
/*
* Else add variables to varinfos list
*/
foreach(l2, varshere)
{
Node *var = (Node *) lfirst(l2);
examine_variable(root, var, 0, &vardata);
varinfos = add_unique_group_var(root, varinfos, var, &vardata);
ReleaseVariableStats(vardata);
}
}
/* If now no Vars, we must have an all-constant GROUP BY list. */
if (allvars == NIL)
if (varinfos == NIL)
return 1.0;
/* Use list_union() to discard duplicates */
allvars = list_union(NIL, allvars);
/*
* Step 2: acquire statistical estimate of number of distinct values
* of each Var (total in its table, without regard for filtering).
* Also, detect known-equal Vars and discard the ones we don't want.
*/
foreach(l, allvars)
{
Var *var = (Var *) lfirst(l);
VariableStatData vardata;
double ndistinct;
bool keep = true;
ListCell *l2;
examine_variable(root, (Node *) var, 0, &vardata);
ndistinct = get_variable_numdistinct(&vardata);
ReleaseVariableStats(vardata);
/* cannot use foreach here because of possible list_delete */
l2 = list_head(varinfos);
while (l2)
{
MyVarInfo *varinfo = (MyVarInfo *) lfirst(l2);
/* must advance l2 before list_delete possibly pfree's it */
l2 = lnext(l2);
if (var->varno != varinfo->var->varno &&
exprs_known_equal(root, (Node *) var, (Node *) varinfo->var))
{
/* Found a match */
if (varinfo->ndistinct <= ndistinct)
{
/* Keep older item, forget new one */
keep = false;
break;
}
else
{
/* Delete the older item */
varinfos = list_delete_ptr(varinfos, varinfo);
}
}
}
if (keep)
{
MyVarInfo *varinfo = (MyVarInfo *) palloc(sizeof(MyVarInfo));
varinfo->var = var;
varinfo->ndistinct = ndistinct;
varinfos = lcons(varinfo, varinfos);
}
}
/*
* Steps 3/4: group Vars by relation and estimate total numdistinct.
*
@ -2031,25 +2072,24 @@ estimate_num_groups(Query *root, List *groupExprs, double input_rows)
* these Vars from the newvarinfos list for the next iteration. This
* is the easiest way to group Vars of same rel together.
*/
Assert(varinfos != NIL);
numdistinct = 1.0;
do
{
MyVarInfo *varinfo1 = (MyVarInfo *) linitial(varinfos);
RelOptInfo *rel = find_base_rel(root, varinfo1->var->varno);
GroupVarInfo *varinfo1 = (GroupVarInfo *) linitial(varinfos);
RelOptInfo *rel = varinfo1->rel;
double reldistinct = varinfo1->ndistinct;
List *newvarinfos = NIL;
/*
* Get the largest numdistinct estimate of the Vars for this rel.
* Get the product of numdistinct estimates of the Vars for this rel.
* Also, construct new varinfos list of remaining Vars.
*/
for_each_cell(l, lnext(list_head(varinfos)))
{
MyVarInfo *varinfo2 = (MyVarInfo *) lfirst(l);
GroupVarInfo *varinfo2 = (GroupVarInfo *) lfirst(l);
if (varinfo2->var->varno == varinfo1->var->varno)
if (varinfo2->rel == varinfo1->rel)
reldistinct *= varinfo2->ndistinct;
else
{