From a536ed53bca40cb0d199824e358a86fcfd5db7f2 Mon Sep 17 00:00:00 2001
From: Tom Lane <tgl@sss.pgh.pa.us>
Date: Tue, 17 Feb 2004 00:52:53 +0000
Subject: [PATCH] Make use of statistics on index expressions. There are still
some corner cases that could stand improvement, but it does all the basic
stuff. A byproduct is that the selectivity routines are no longer
constrained to working on simple Vars; we might in future be able to improve
the behavior for subexpressions that don't match indexes.
---
src/backend/optimizer/path/costsize.c | 181 +--
src/backend/optimizer/util/relnode.c | 8 +-
src/backend/utils/adt/selfuncs.c | 1844 ++++++++++++++-----------
src/include/optimizer/pathnode.h | 3 +-
src/include/utils/selfuncs.h | 5 +-
5 files changed, 1062 insertions(+), 979 deletions(-)
diff --git a/src/backend/optimizer/path/costsize.c b/src/backend/optimizer/path/costsize.c
index c23cf4d2324..79674ac4b94 100644
--- a/src/backend/optimizer/path/costsize.c
+++ b/src/backend/optimizer/path/costsize.c
@@ -49,7 +49,7 @@
* Portions Copyright (c) 1994, Regents of the University of California
*
* IDENTIFICATION
- * $PostgreSQL: pgsql/src/backend/optimizer/path/costsize.c,v 1.124 2004/02/03 17:34:03 tgl Exp $
+ * $PostgreSQL: pgsql/src/backend/optimizer/path/costsize.c,v 1.125 2004/02/17 00:52:53 tgl Exp $
*
*-------------------------------------------------------------------------
*/
@@ -102,8 +102,6 @@ bool enable_mergejoin = true;
bool enable_hashjoin = true;
-static Selectivity estimate_hash_bucketsize(Query *root, Var *var,
- int nbuckets);
static bool cost_qual_eval_walker(Node *node, QualCost *total);
static Selectivity approx_selectivity(Query *root, List *quals,
JoinType jointype);
@@ -1152,7 +1150,7 @@ cost_hashjoin(HashPath *path, Query *root)
/* not cached yet */
thisbucketsize =
estimate_hash_bucketsize(root,
- (Var *) get_rightop(restrictinfo->clause),
+ get_rightop(restrictinfo->clause),
virtualbuckets);
restrictinfo->right_bucketsize = thisbucketsize;
}
@@ -1168,7 +1166,7 @@ cost_hashjoin(HashPath *path, Query *root)
/* not cached yet */
thisbucketsize =
estimate_hash_bucketsize(root,
- (Var *) get_leftop(restrictinfo->clause),
+ get_leftop(restrictinfo->clause),
virtualbuckets);
restrictinfo->left_bucketsize = thisbucketsize;
}
@@ -1249,179 +1247,6 @@ cost_hashjoin(HashPath *path, Query *root)
path->jpath.path.total_cost = startup_cost + run_cost;
}
-/*
- * Estimate hash bucketsize fraction (ie, number of entries in a bucket
- * divided by total tuples in relation) if the specified Var is used
- * as a hash key.
- *
- * XXX This is really pretty bogus since we're effectively assuming that the
- * distribution of hash keys will be the same after applying restriction
- * clauses as it was in the underlying relation. However, we are not nearly
- * smart enough to figure out how the restrict clauses might change the
- * distribution, so this will have to do for now.
- *
- * We are passed the number of buckets the executor will use for the given
- * input relation. If the data were perfectly distributed, with the same
- * number of tuples going into each available bucket, then the bucketsize
- * fraction would be 1/nbuckets. But this happy state of affairs will occur
- * only if (a) there are at least nbuckets distinct data values, and (b)
- * we have a not-too-skewed data distribution. Otherwise the buckets will
- * be nonuniformly occupied. If the other relation in the join has a key
- * distribution similar to this one's, then the most-loaded buckets are
- * exactly those that will be probed most often. Therefore, the "average"
- * bucket size for costing purposes should really be taken as something close
- * to the "worst case" bucket size. We try to estimate this by adjusting the
- * fraction if there are too few distinct data values, and then scaling up
- * by the ratio of the most common value's frequency to the average frequency.
- *
- * If no statistics are available, use a default estimate of 0.1. This will
- * discourage use of a hash rather strongly if the inner relation is large,
- * which is what we want. We do not want to hash unless we know that the
- * inner rel is well-dispersed (or the alternatives seem much worse).
- */
-static Selectivity
-estimate_hash_bucketsize(Query *root, Var *var, int nbuckets)
-{
- Oid relid;
- RelOptInfo *rel;
- HeapTuple tuple;
- Form_pg_statistic stats;
- double estfract,
- ndistinct,
- mcvfreq,
- avgfreq;
- float4 *numbers;
- int nnumbers;
-
- /* Ignore any binary-compatible relabeling */
- if (var && IsA(var, RelabelType))
- var = (Var *) ((RelabelType *) var)->arg;
-
- /*
- * Lookup info about var's relation and attribute; if none available,
- * return default estimate.
- */
- if (var == NULL || !IsA(var, Var))
- return 0.1;
-
- relid = getrelid(var->varno, root->rtable);
- if (relid == InvalidOid)
- return 0.1;
-
- rel = find_base_rel(root, var->varno);
-
- if (rel->tuples <= 0.0 || rel->rows <= 0.0)
- return 0.1; /* ensure we can divide below */
-
- tuple = SearchSysCache(STATRELATT,
- ObjectIdGetDatum(relid),
- Int16GetDatum(var->varattno),
- 0, 0);
- if (!HeapTupleIsValid(tuple))
- {
- /*
- * If the attribute is known unique because of an index,
- * we can treat it as well-distributed.
- */
- if (has_unique_index(rel, var->varattno))
- return 1.0 / (double) nbuckets;
-
- /*
- * Perhaps the Var is a system attribute; if so, it will have no
- * entry in pg_statistic, but we may be able to guess something
- * about its distribution anyway.
- */
- switch (var->varattno)
- {
- case ObjectIdAttributeNumber:
- case SelfItemPointerAttributeNumber:
- /* these are unique, so buckets should be well-distributed */
- return 1.0 / (double) nbuckets;
- case TableOidAttributeNumber:
- /* hashing this is a terrible idea... */
- return 1.0;
- }
- return 0.1;
- }
- stats = (Form_pg_statistic) GETSTRUCT(tuple);
-
- /*
- * Obtain number of distinct data values in raw relation.
- */
- ndistinct = stats->stadistinct;
- if (ndistinct < 0.0)
- ndistinct = -ndistinct * rel->tuples;
-
- if (ndistinct <= 0.0) /* ensure we can divide */
- {
- ReleaseSysCache(tuple);
- return 0.1;
- }
-
- /* Also compute avg freq of all distinct data values in raw relation */
- avgfreq = (1.0 - stats->stanullfrac) / ndistinct;
-
- /*
- * Adjust ndistinct to account for restriction clauses. Observe we
- * are assuming that the data distribution is affected uniformly by
- * the restriction clauses!
- *
- * XXX Possibly better way, but much more expensive: multiply by
- * selectivity of rel's restriction clauses that mention the target
- * Var.
- */
- ndistinct *= rel->rows / rel->tuples;
-
- /*
- * Initial estimate of bucketsize fraction is 1/nbuckets as long as
- * the number of buckets is less than the expected number of distinct
- * values; otherwise it is 1/ndistinct.
- */
- if (ndistinct > (double) nbuckets)
- estfract = 1.0 / (double) nbuckets;
- else
- estfract = 1.0 / ndistinct;
-
- /*
- * Look up the frequency of the most common value, if available.
- */
- mcvfreq = 0.0;
-
- if (get_attstatsslot(tuple, var->vartype, var->vartypmod,
- STATISTIC_KIND_MCV, InvalidOid,
- NULL, NULL, &numbers, &nnumbers))
- {
- /*
- * The first MCV stat is for the most common value.
- */
- if (nnumbers > 0)
- mcvfreq = numbers[0];
- free_attstatsslot(var->vartype, NULL, 0,
- numbers, nnumbers);
- }
-
- /*
- * Adjust estimated bucketsize upward to account for skewed
- * distribution.
- */
- if (avgfreq > 0.0 && mcvfreq > avgfreq)
- estfract *= mcvfreq / avgfreq;
-
- /*
- * Clamp bucketsize to sane range (the above adjustment could easily
- * produce an out-of-range result). We set the lower bound a little
- * above zero, since zero isn't a very sane result.
- */
- if (estfract < 1.0e-6)
- estfract = 1.0e-6;
- else if (estfract > 1.0)
- estfract = 1.0;
-
- ReleaseSysCache(tuple);
-
- return (Selectivity) estfract;
-}
-
/*
* cost_qual_eval
diff --git a/src/backend/optimizer/util/relnode.c b/src/backend/optimizer/util/relnode.c
index d6d093ea467..d5a5480c62e 100644
--- a/src/backend/optimizer/util/relnode.c
+++ b/src/backend/optimizer/util/relnode.c
@@ -8,7 +8,7 @@
*
*
* IDENTIFICATION
- * $PostgreSQL: pgsql/src/backend/optimizer/util/relnode.c,v 1.54 2003/12/08 18:19:58 tgl Exp $
+ * $PostgreSQL: pgsql/src/backend/optimizer/util/relnode.c,v 1.55 2004/02/17 00:52:53 tgl Exp $
*
*-------------------------------------------------------------------------
*/
@@ -214,12 +214,8 @@ find_base_rel(Query *root, int relid)
* find_join_rel
* Returns relation entry corresponding to 'relids' (a set of RT indexes),
* or NULL if none exists. This is for join relations.
- *
- * Note: there is probably no good reason for this to be called from
- * anywhere except build_join_rel, but keep it as a separate routine
- * just in case.
*/
-static RelOptInfo *
+RelOptInfo *
find_join_rel(Query *root, Relids relids)
{
List *joinrels;
diff --git a/src/backend/utils/adt/selfuncs.c b/src/backend/utils/adt/selfuncs.c
index 84f18dc9359..05473914097 100644
--- a/src/backend/utils/adt/selfuncs.c
+++ b/src/backend/utils/adt/selfuncs.c
@@ -15,7 +15,7 @@
*
*
* IDENTIFICATION
- * $PostgreSQL: pgsql/src/backend/utils/adt/selfuncs.c,v 1.156 2004/02/02 03:07:08 tgl Exp $
+ * $PostgreSQL: pgsql/src/backend/utils/adt/selfuncs.c,v 1.157 2004/02/17 00:52:53 tgl Exp $
*
*-------------------------------------------------------------------------
*/
@@ -136,7 +136,6 @@
/* default selectivity estimate for boolean and null test nodes */
#define DEFAULT_UNK_SEL 0.005
#define DEFAULT_NOT_UNK_SEL (1.0 - DEFAULT_UNK_SEL)
-#define DEFAULT_BOOL_SEL 0.5
/*
* Clamp a computed probability estimate (which may suffer from roundoff or
@@ -151,7 +150,25 @@
} while (0)
-static bool get_var_maximum(Query *root, Var *var, Oid sortop, Datum *max);
+/* Return data from examine_variable and friends */
+typedef struct
+{
+ Node *var; /* the Var or expression tree */
+ RelOptInfo *rel; /* Relation, or NULL if not identifiable */
+ HeapTuple statsTuple; /* pg_statistic tuple, or NULL if none */
+ /* NB: if statsTuple!=NULL, it must be freed when caller is done */
+ Oid atttype; /* type to pass to get_attstatsslot */
+ int32 atttypmod; /* typmod to pass to get_attstatsslot */
+ bool isunique; /* true if matched to a unique index */
+} VariableStatData;
+
+#define ReleaseVariableStats(vardata) \
+ do { \
+ if (HeapTupleIsValid((vardata).statsTuple)) \
+ ReleaseSysCache((vardata).statsTuple); \
+ } while(0)
+
+
static bool convert_to_scalar(Datum value, Oid valuetypid, double *scaledvalue,
Datum lobound, Datum hibound, Oid boundstypid,
double *scaledlobound, double *scaledhibound);
@@ -174,13 +191,18 @@ static double convert_one_bytea_to_scalar(unsigned char *value, int valuelen,
int rangelo, int rangehi);
static unsigned char *convert_string_datum(Datum value, Oid typid);
static double convert_timevalue_to_scalar(Datum value, Oid typid);
-static double get_att_numdistinct(Query *root, Var *var,
- Form_pg_statistic stats);
-static bool get_restriction_var(List *args, int varRelid,
- Var **var, Node **other,
+static bool get_restriction_variable(Query *root, List *args, int varRelid,
+ VariableStatData *vardata, Node **other,
bool *varonleft);
-static void get_join_vars(List *args, Var **var1, Var **var2);
-static Selectivity prefix_selectivity(Query *root, Var *var,
+static void get_join_variables(Query *root, List *args,
+ VariableStatData *vardata1,
+ VariableStatData *vardata2);
+static void examine_variable(Query *root, Node *node, int varRelid,
+ VariableStatData *vardata);
+static double get_variable_numdistinct(VariableStatData *vardata);
+static bool get_variable_maximum(Query *root, VariableStatData *vardata,
+ Oid sortop, Datum *max);
+static Selectivity prefix_selectivity(Query *root, VariableStatData *vardata,
Oid opclass, Const *prefix);
static Selectivity pattern_selectivity(Const *patt, Pattern_Type ptype);
static Datum string_to_datum(const char *str, Oid datatype);
@@ -203,11 +225,9 @@ eqsel(PG_FUNCTION_ARGS)
Oid operator = PG_GETARG_OID(1);
List *args = (List *) PG_GETARG_POINTER(2);
int varRelid = PG_GETARG_INT32(3);
- Var *var;
+ VariableStatData vardata;
Node *other;
bool varonleft;
- Oid relid;
- HeapTuple statsTuple;
Datum *values;
int nvalues;
float4 *numbers;
@@ -215,15 +235,11 @@ eqsel(PG_FUNCTION_ARGS)
double selec;
/*
- * If expression is not var = something or something = var for a
- * simple var of a real relation (no subqueries, for now), then punt
- * and return a default estimate.
+ * If expression is not variable = something or something = variable,
+ * then punt and return a default estimate.
*/
- if (!get_restriction_var(args, varRelid,
- &var, &other, &varonleft))
- PG_RETURN_FLOAT8(DEFAULT_EQ_SEL);
- relid = getrelid(var->varno, root->rtable);
- if (relid == InvalidOid)
+ if (!get_restriction_variable(root, args, varRelid,
+ &vardata, &other, &varonleft))
PG_RETURN_FLOAT8(DEFAULT_EQ_SEL);
/*
@@ -232,22 +248,20 @@ eqsel(PG_FUNCTION_ARGS)
*/
if (IsA(other, Const) &&
((Const *) other)->constisnull)
+ {
+ ReleaseVariableStats(vardata);
PG_RETURN_FLOAT8(0.0);
+ }
- /* get stats for the attribute, if available */
- statsTuple = SearchSysCache(STATRELATT,
- ObjectIdGetDatum(relid),
- Int16GetDatum(var->varattno),
- 0, 0);
- if (HeapTupleIsValid(statsTuple))
+ if (HeapTupleIsValid(vardata.statsTuple))
{
Form_pg_statistic stats;
- stats = (Form_pg_statistic) GETSTRUCT(statsTuple);
+ stats = (Form_pg_statistic) GETSTRUCT(vardata.statsTuple);
if (IsA(other, Const))
{
- /* Var is being compared to a known non-null constant */
+ /* Variable is being compared to a known non-null constant */
Datum constval = ((Const *) other)->constvalue;
bool match = false;
int i;
@@ -259,7 +273,8 @@ eqsel(PG_FUNCTION_ARGS)
* an appropriate test. If you don't like this, maybe you
* shouldn't be using eqsel for your operator...)
*/
- if (get_attstatsslot(statsTuple, var->vartype, var->vartypmod,
+ if (get_attstatsslot(vardata.statsTuple,
+ vardata.atttype, vardata.atttypmod,
STATISTIC_KIND_MCV, InvalidOid,
&values, &nvalues,
&numbers, &nnumbers))
@@ -321,7 +336,7 @@ eqsel(PG_FUNCTION_ARGS)
* remaining fraction equally, so we divide by the number
* of other distinct values.
*/
- otherdistinct = get_att_numdistinct(root, var, stats)
+ otherdistinct = get_variable_numdistinct(&vardata)
- nnumbers;
if (otherdistinct > 1)
selec /= otherdistinct;
@@ -334,7 +349,7 @@ eqsel(PG_FUNCTION_ARGS)
selec = numbers[nnumbers - 1];
}
- free_attstatsslot(var->vartype, values, nvalues,
+ free_attstatsslot(vardata.atttype, values, nvalues,
numbers, nnumbers);
}
else
@@ -352,7 +367,7 @@ eqsel(PG_FUNCTION_ARGS)
* frequency in the table. Is that a good idea?)
*/
selec = 1.0 - stats->stanullfrac;
- ndistinct = get_att_numdistinct(root, var, stats);
+ ndistinct = get_variable_numdistinct(&vardata);
if (ndistinct > 1)
selec /= ndistinct;
@@ -360,18 +375,17 @@ eqsel(PG_FUNCTION_ARGS)
* Cross-check: selectivity should never be estimated as more
* than the most common value's.
*/
- if (get_attstatsslot(statsTuple, var->vartype, var->vartypmod,
+ if (get_attstatsslot(vardata.statsTuple,
+ vardata.atttype, vardata.atttypmod,
STATISTIC_KIND_MCV, InvalidOid,
NULL, NULL,
&numbers, &nnumbers))
{
if (nnumbers > 0 && selec > numbers[0])
selec = numbers[0];
- free_attstatsslot(var->vartype, NULL, 0, numbers, nnumbers);
+ free_attstatsslot(vardata.atttype, NULL, 0, numbers, nnumbers);
}
}
-
- ReleaseSysCache(statsTuple);
}
else
{
@@ -381,9 +395,11 @@ eqsel(PG_FUNCTION_ARGS)
* equally common. (The guess is unlikely to be very good, but we
* do know a few special cases.)
*/
- selec = 1.0 / get_att_numdistinct(root, var, NULL);
+ selec = 1.0 / get_variable_numdistinct(&vardata);
}
+ ReleaseVariableStats(vardata);
+
/* result should be in range, but make sure... */
CLAMP_PROBABILITY(selec);
@@ -433,7 +449,7 @@ neqsel(PG_FUNCTION_ARGS)
* scalarineqsel - Selectivity of "<", "<=", ">", ">=" for scalars.
*
* This is the guts of both scalarltsel and scalargtsel. The caller has
- * commuted the clause, if necessary, so that we can treat the Var as
+ * commuted the clause, if necessary, so that we can treat the variable as
* being on the left. The caller must also make sure that the other side
* of the clause is a non-null Const, and dissect same into a value and
* datatype.
@@ -444,10 +460,8 @@ neqsel(PG_FUNCTION_ARGS)
*/
static double
scalarineqsel(Query *root, Oid operator, bool isgt,
- Var *var, Datum constval, Oid consttype)
+ VariableStatData *vardata, Datum constval, Oid consttype)
{
- Oid relid;
- HeapTuple statsTuple;
Form_pg_statistic stats;
FmgrInfo opproc;
Datum *values;
@@ -460,26 +474,12 @@ scalarineqsel(Query *root, Oid operator, bool isgt,
double selec;
int i;
- /*
- * If expression is not var op something or something op var for a
- * simple var of a real relation (no subqueries, for now), then punt
- * and return a default estimate.
- */
- relid = getrelid(var->varno, root->rtable);
- if (relid == InvalidOid)
- return DEFAULT_INEQ_SEL;
-
- /* get stats for the attribute */
- statsTuple = SearchSysCache(STATRELATT,
- ObjectIdGetDatum(relid),
- Int16GetDatum(var->varattno),
- 0, 0);
- if (!HeapTupleIsValid(statsTuple))
+ if (!HeapTupleIsValid(vardata->statsTuple))
{
/* no stats available, so default result */
return DEFAULT_INEQ_SEL;
}
- stats = (Form_pg_statistic) GETSTRUCT(statsTuple);
+ stats = (Form_pg_statistic) GETSTRUCT(vardata->statsTuple);
fmgr_info(get_opcode(operator), &opproc);
@@ -492,7 +492,8 @@ scalarineqsel(Query *root, Oid operator, bool isgt,
mcv_selec = 0.0;
sumcommon = 0.0;
- if (get_attstatsslot(statsTuple, var->vartype, var->vartypmod,
+ if (get_attstatsslot(vardata->statsTuple,
+ vardata->atttype, vardata->atttypmod,
STATISTIC_KIND_MCV, InvalidOid,
&values, &nvalues,
&numbers, &nnumbers))
@@ -505,7 +506,8 @@ scalarineqsel(Query *root, Oid operator, bool isgt,
mcv_selec += numbers[i];
sumcommon += numbers[i];
}
- free_attstatsslot(var->vartype, values, nvalues, numbers, nnumbers);
+ free_attstatsslot(vardata->atttype, values, nvalues,
+ numbers, nnumbers);
}
/*
@@ -523,7 +525,8 @@ scalarineqsel(Query *root, Oid operator, bool isgt,
*/
hist_selec = 0.0;
- if (get_attstatsslot(statsTuple, var->vartype, var->vartypmod,
+ if (get_attstatsslot(vardata->statsTuple,
+ vardata->atttype, vardata->atttypmod,
STATISTIC_KIND_HISTOGRAM, InvalidOid,
&values, &nvalues,
NULL, NULL))
@@ -582,7 +585,7 @@ scalarineqsel(Query *root, Oid operator, bool isgt,
*/
if (convert_to_scalar(constval, consttype, &val,
values[i - 1], values[i],
- var->vartype,
+ vardata->atttype,
&low, &high))
{
if (high <= low)
@@ -653,7 +656,7 @@ scalarineqsel(Query *root, Oid operator, bool isgt,
hist_selec = 0.9999;
}
- free_attstatsslot(var->vartype, values, nvalues, NULL, 0);
+ free_attstatsslot(vardata->atttype, values, nvalues, NULL, 0);
}
/*
@@ -676,8 +679,6 @@ scalarineqsel(Query *root, Oid operator, bool isgt,
selec += mcv_selec;
- ReleaseSysCache(statsTuple);
-
/* result should be in range, but make sure... */
CLAMP_PROBABILITY(selec);
@@ -694,21 +695,20 @@ scalarltsel(PG_FUNCTION_ARGS)
Oid operator = PG_GETARG_OID(1);
List *args = (List *) PG_GETARG_POINTER(2);
int varRelid = PG_GETARG_INT32(3);
- Var *var;
+ VariableStatData vardata;
Node *other;
+ bool varonleft;
Datum constval;
Oid consttype;
- bool varonleft;
bool isgt;
double selec;
/*
- * If expression is not var op something or something op var for a
- * simple var of a real relation (no subqueries, for now), then punt
- * and return a default estimate.
+ * If expression is not variable op something or something op variable,
+ * then punt and return a default estimate.
*/
- if (!get_restriction_var(args, varRelid,
- &var, &other, &varonleft))
+ if (!get_restriction_variable(root, args, varRelid,
+ &vardata, &other, &varonleft))
PG_RETURN_FLOAT8(DEFAULT_INEQ_SEL);
/*
@@ -716,14 +716,20 @@ scalarltsel(PG_FUNCTION_ARGS)
* either.
*/
if (!IsA(other, Const))
+ {
+ ReleaseVariableStats(vardata);
PG_RETURN_FLOAT8(DEFAULT_INEQ_SEL);
+ }
/*
* If the constant is NULL, assume operator is strict and return zero,
* ie, operator will never return TRUE.
*/
if (((Const *) other)->constisnull)
+ {
+ ReleaseVariableStats(vardata);
PG_RETURN_FLOAT8(0.0);
+ }
constval = ((Const *) other)->constvalue;
consttype = ((Const *) other)->consttype;
@@ -742,12 +748,15 @@ scalarltsel(PG_FUNCTION_ARGS)
if (!operator)
{
/* Use default selectivity (should we raise an error instead?) */
+ ReleaseVariableStats(vardata);
PG_RETURN_FLOAT8(DEFAULT_INEQ_SEL);
}
isgt = true;
}
- selec = scalarineqsel(root, operator, isgt, var, constval, consttype);
+ selec = scalarineqsel(root, operator, isgt, &vardata, constval, consttype);
+
+ ReleaseVariableStats(vardata);
PG_RETURN_FLOAT8((float8) selec);
}
@@ -762,21 +771,20 @@ scalargtsel(PG_FUNCTION_ARGS)
Oid operator = PG_GETARG_OID(1);
List *args = (List *) PG_GETARG_POINTER(2);
int varRelid = PG_GETARG_INT32(3);
- Var *var;
+ VariableStatData vardata;
Node *other;
+ bool varonleft;
Datum constval;
Oid consttype;
- bool varonleft;
bool isgt;
double selec;
/*
- * If expression is not var op something or something op var for a
- * simple var of a real relation (no subqueries, for now), then punt
- * and return a default estimate.
+ * If expression is not variable op something or something op variable,
+ * then punt and return a default estimate.
*/
- if (!get_restriction_var(args, varRelid,
- &var, &other, &varonleft))
+ if (!get_restriction_variable(root, args, varRelid,
+ &vardata, &other, &varonleft))
PG_RETURN_FLOAT8(DEFAULT_INEQ_SEL);
/*
@@ -784,14 +792,20 @@ scalargtsel(PG_FUNCTION_ARGS)
* either.
*/
if (!IsA(other, Const))
+ {
+ ReleaseVariableStats(vardata);
PG_RETURN_FLOAT8(DEFAULT_INEQ_SEL);
+ }
/*
* If the constant is NULL, assume operator is strict and return zero,
* ie, operator will never return TRUE.
*/
if (((Const *) other)->constisnull)
+ {
+ ReleaseVariableStats(vardata);
PG_RETURN_FLOAT8(0.0);
+ }
constval = ((Const *) other)->constvalue;
consttype = ((Const *) other)->consttype;
@@ -810,12 +824,15 @@ scalargtsel(PG_FUNCTION_ARGS)
if (!operator)
{
/* Use default selectivity (should we raise an error instead?) */
+ ReleaseVariableStats(vardata);
PG_RETURN_FLOAT8(DEFAULT_INEQ_SEL);
}
isgt = false;
}
- selec = scalarineqsel(root, operator, isgt, var, constval, consttype);
+ selec = scalarineqsel(root, operator, isgt, &vardata, constval, consttype);
+
+ ReleaseVariableStats(vardata);
PG_RETURN_FLOAT8((float8) selec);
}
@@ -833,10 +850,9 @@ patternsel(PG_FUNCTION_ARGS, Pattern_Type ptype)
#endif
List *args = (List *) PG_GETARG_POINTER(2);
int varRelid = PG_GETARG_INT32(3);
- Var *var;
+ VariableStatData vardata;
Node *other;
bool varonleft;
- Oid relid;
Datum constval;
Oid consttype;
Oid vartype;
@@ -848,25 +864,27 @@ patternsel(PG_FUNCTION_ARGS, Pattern_Type ptype)
double result;
/*
- * If expression is not var op constant for a simple var of a real
- * relation (no subqueries, for now), then punt and return a default
- * estimate.
+ * If expression is not variable op constant, then punt and return a
+ * default estimate.
*/
- if (!get_restriction_var(args, varRelid,
- &var, &other, &varonleft))
+ if (!get_restriction_variable(root, args, varRelid,
+ &vardata, &other, &varonleft))
return DEFAULT_MATCH_SEL;
if (!varonleft || !IsA(other, Const))
+ {
+ ReleaseVariableStats(vardata);
return DEFAULT_MATCH_SEL;
- relid = getrelid(var->varno, root->rtable);
- if (relid == InvalidOid)
- return DEFAULT_MATCH_SEL;
+ }
/*
* If the constant is NULL, assume operator is strict and return zero,
* ie, operator will never return TRUE.
*/
if (((Const *) other)->constisnull)
+ {
+ ReleaseVariableStats(vardata);
return 0.0;
+ }
constval = ((Const *) other)->constvalue;
consttype = ((Const *) other)->consttype;
@@ -877,14 +895,17 @@ patternsel(PG_FUNCTION_ARGS, Pattern_Type ptype)
* match the operator's declared type.
*/
if (consttype != TEXTOID && consttype != BYTEAOID)
+ {
+ ReleaseVariableStats(vardata);
return DEFAULT_MATCH_SEL;
+ }
/*
* The var, on the other hand, might be a binary-compatible type;
* particularly a domain. Try to fold it if it's not recognized
* immediately.
*/
- vartype = var->vartype;
+ vartype = vardata.atttype;
if (vartype != consttype)
vartype = getBaseType(vartype);
@@ -915,6 +936,7 @@ patternsel(PG_FUNCTION_ARGS, Pattern_Type ptype)
opclass = BYTEA_BTREE_OPS_OID;
break;
default:
+ ReleaseVariableStats(vardata);
return DEFAULT_MATCH_SEL;
}
@@ -943,6 +965,7 @@ patternsel(PG_FUNCTION_ARGS, Pattern_Type ptype)
default:
elog(ERROR, "unrecognized consttype: %u",
prefix->consttype);
+ ReleaseVariableStats(vardata);
return DEFAULT_MATCH_SEL;
}
prefix = string_to_const(prefixstr, vartype);
@@ -960,7 +983,7 @@ patternsel(PG_FUNCTION_ARGS, Pattern_Type ptype)
if (eqopr == InvalidOid)
elog(ERROR, "no = operator for opclass %u", opclass);
- eqargs = makeList2(var, prefix);
+ eqargs = makeList2(vardata.var, prefix);
result = DatumGetFloat8(DirectFunctionCall4(eqsel,
PointerGetDatum(root),
ObjectIdGetDatum(eqopr),
@@ -979,7 +1002,7 @@ patternsel(PG_FUNCTION_ARGS, Pattern_Type ptype)
Selectivity selec;
if (pstatus == Pattern_Prefix_Partial)
- prefixsel = prefix_selectivity(root, var, opclass, prefix);
+ prefixsel = prefix_selectivity(root, &vardata, opclass, prefix);
else
prefixsel = 1.0;
restsel = pattern_selectivity(rest, ptype);
@@ -995,6 +1018,8 @@ patternsel(PG_FUNCTION_ARGS, Pattern_Type ptype)
pfree(prefix);
}
+ ReleaseVariableStats(vardata);
+
return result;
}
@@ -1093,80 +1118,25 @@ Selectivity
booltestsel(Query *root, BoolTestType booltesttype, Node *arg,
int varRelid, JoinType jointype)
{
- Var *var;
- Oid relid;
- HeapTuple statsTuple;
- Datum *values;
- int nvalues;
- float4 *numbers;
- int nnumbers;
+ VariableStatData vardata;
double selec;
- /*
- * Ignore any binary-compatible relabeling (probably unnecessary, but
- * can't hurt)
- */
- if (IsA(arg, RelabelType))
- arg = (Node *) ((RelabelType *) arg)->arg;
-
- if (IsA(arg, Var) &&
- (varRelid == 0 || varRelid == ((Var *) arg)->varno))
- var = (Var *) arg;
- else
- {
- /*
- * If argument is not a Var, we can't get statistics for it, but
- * perhaps clause_selectivity can do something with it. We ignore
- * the possibility of a NULL value when using clause_selectivity,
- * and just assume the value is either TRUE or FALSE.
- */
- switch (booltesttype)
- {
- case IS_UNKNOWN:
- selec = DEFAULT_UNK_SEL;
- break;
- case IS_NOT_UNKNOWN:
- selec = DEFAULT_NOT_UNK_SEL;
- break;
- case IS_TRUE:
- case IS_NOT_FALSE:
- selec = (double) clause_selectivity(root, arg,
- varRelid, jointype);
- break;
- case IS_FALSE:
- case IS_NOT_TRUE:
- selec = 1.0 - (double) clause_selectivity(root, arg,
- varRelid, jointype);
- break;
- default:
- elog(ERROR, "unrecognized booltesttype: %d",
- (int) booltesttype);
- selec = 0.0; /* Keep compiler quiet */
- break;
- }
- return (Selectivity) selec;
- }
-
- /* get stats for the attribute, if available */
- relid = getrelid(var->varno, root->rtable);
- if (relid == InvalidOid)
- statsTuple = NULL;
- else
- statsTuple = SearchSysCache(STATRELATT,
- ObjectIdGetDatum(relid),
- Int16GetDatum(var->varattno),
- 0, 0);
+ examine_variable(root, arg, varRelid, &vardata);
- if (HeapTupleIsValid(statsTuple))
+ if (HeapTupleIsValid(vardata.statsTuple))
{
Form_pg_statistic stats;
double freq_null;
+ Datum *values;
+ int nvalues;
+ float4 *numbers;
+ int nnumbers;
- stats = (Form_pg_statistic) GETSTRUCT(statsTuple);
-
+ stats = (Form_pg_statistic) GETSTRUCT(vardata.statsTuple);
freq_null = stats->stanullfrac;
- if (get_attstatsslot(statsTuple, var->vartype, var->vartypmod,
+ if (get_attstatsslot(vardata.statsTuple,
+ vardata.atttype, vardata.atttypmod,
STATISTIC_KIND_MCV, InvalidOid,
&values, &nvalues,
&numbers, &nnumbers)
@@ -1184,7 +1154,7 @@ booltestsel(Query *root, BoolTestType booltesttype, Node *arg,
freq_true = 1.0 - numbers[0] - freq_null;
/*
- * Next derive freqency for false. Then use these as
+ * Next derive frequency for false. Then use these as
* appropriate to derive frequency for each case.
*/
freq_false = 1.0 - freq_true - freq_null;
@@ -1222,7 +1192,7 @@ booltestsel(Query *root, BoolTestType booltesttype, Node *arg,
break;
}
- free_attstatsslot(var->vartype, values, nvalues,
+ free_attstatsslot(vardata.atttype, values, nvalues,
numbers, nnumbers);
}
else
@@ -1263,14 +1233,14 @@ booltestsel(Query *root, BoolTestType booltesttype, Node *arg,
break;
}
}
-
- ReleaseSysCache(statsTuple);
}
else
{
/*
- * No VACUUM ANALYZE stats available, so use a default value.
- * (Note: not much point in recursing to clause_selectivity here.)
+ * If we can't get variable statistics for the argument, perhaps
+ * clause_selectivity can do something with it. We ignore
+ * the possibility of a NULL value when using clause_selectivity,
+ * and just assume the value is either TRUE or FALSE.
*/
switch (booltesttype)
{
@@ -1281,10 +1251,14 @@ booltestsel(Query *root, BoolTestType booltesttype, Node *arg,
selec = DEFAULT_NOT_UNK_SEL;
break;
case IS_TRUE:
- case IS_NOT_TRUE:
- case IS_FALSE:
case IS_NOT_FALSE:
- selec = DEFAULT_BOOL_SEL;
+ selec = (double) clause_selectivity(root, arg,
+ varRelid, jointype);
+ break;
+ case IS_FALSE:
+ case IS_NOT_TRUE:
+ selec = 1.0 - (double) clause_selectivity(root, arg,
+ varRelid, jointype);
break;
default:
elog(ERROR, "unrecognized booltesttype: %d",
@@ -1294,6 +1268,8 @@ booltestsel(Query *root, BoolTestType booltesttype, Node *arg,
}
}
+ ReleaseVariableStats(vardata);
+
/* result should be in range, but make sure... */
CLAMP_PROBABILITY(selec);
@@ -1306,56 +1282,17 @@ booltestsel(Query *root, BoolTestType booltesttype, Node *arg,
Selectivity
nulltestsel(Query *root, NullTestType nulltesttype, Node *arg, int varRelid)
{
- Var *var;
- Oid relid;
- HeapTuple statsTuple;
+ VariableStatData vardata;
double selec;
- double defselec;
- double freq_null;
-
- switch (nulltesttype)
- {
- case IS_NULL:
- defselec = DEFAULT_UNK_SEL;
- break;
- case IS_NOT_NULL:
- defselec = DEFAULT_NOT_UNK_SEL;
- break;
- default:
- elog(ERROR, "unrecognized nulltesttype: %d",
- (int) nulltesttype);
- return (Selectivity) 0; /* keep compiler quiet */
- }
-
- /*
- * Ignore any binary-compatible relabeling
- */
- if (IsA(arg, RelabelType))
- arg = (Node *) ((RelabelType *) arg)->arg;
-
- if (IsA(arg, Var) &&
- (varRelid == 0 || varRelid == ((Var *) arg)->varno))
- var = (Var *) arg;
- else
- {
- /* punt if non-Var argument */
- return (Selectivity) defselec;
- }
- relid = getrelid(var->varno, root->rtable);
- if (relid == InvalidOid)
- return (Selectivity) defselec;
+ examine_variable(root, arg, varRelid, &vardata);
- /* get stats for the attribute, if available */
- statsTuple = SearchSysCache(STATRELATT,
- ObjectIdGetDatum(relid),
- Int16GetDatum(var->varattno),
- 0, 0);
- if (HeapTupleIsValid(statsTuple))
+ if (HeapTupleIsValid(vardata.statsTuple))
{
Form_pg_statistic stats;
+ double freq_null;
- stats = (Form_pg_statistic) GETSTRUCT(statsTuple);
+ stats = (Form_pg_statistic) GETSTRUCT(vardata.statsTuple);
freq_null = stats->stanullfrac;
switch (nulltesttype)
@@ -1380,17 +1317,29 @@ nulltestsel(Query *root, NullTestType nulltesttype, Node *arg, int varRelid)
(int) nulltesttype);
return (Selectivity) 0; /* keep compiler quiet */
}
-
- ReleaseSysCache(statsTuple);
}
else
{
/*
* No VACUUM ANALYZE stats available, so make a guess
*/
- selec = defselec;
+ switch (nulltesttype)
+ {
+ case IS_NULL:
+ selec = DEFAULT_UNK_SEL;
+ break;
+ case IS_NOT_NULL:
+ selec = DEFAULT_NOT_UNK_SEL;
+ break;
+ default:
+ elog(ERROR, "unrecognized nulltesttype: %d",
+ (int) nulltesttype);
+ return (Selectivity) 0; /* keep compiler quiet */
+ }
}
+ ReleaseVariableStats(vardata);
+
/* result should be in range, but make sure... */
CLAMP_PROBABILITY(selec);
@@ -1407,293 +1356,257 @@ eqjoinsel(PG_FUNCTION_ARGS)
Oid operator = PG_GETARG_OID(1);
List *args = (List *) PG_GETARG_POINTER(2);
JoinType jointype = (JoinType) PG_GETARG_INT16(3);
- Var *var1;
- Var *var2;
double selec;
+ VariableStatData vardata1;
+ VariableStatData vardata2;
+ double nd1;
+ double nd2;
+ Form_pg_statistic stats1 = NULL;
+ Form_pg_statistic stats2 = NULL;
+ bool have_mcvs1 = false;
+ Datum *values1 = NULL;
+ int nvalues1 = 0;
+ float4 *numbers1 = NULL;
+ int nnumbers1 = 0;
+ bool have_mcvs2 = false;
+ Datum *values2 = NULL;
+ int nvalues2 = 0;
+ float4 *numbers2 = NULL;
+ int nnumbers2 = 0;
+
+ get_join_variables(root, args, &vardata1, &vardata2);
+
+ nd1 = get_variable_numdistinct(&vardata1);
+ nd2 = get_variable_numdistinct(&vardata2);
+
+ if (HeapTupleIsValid(vardata1.statsTuple))
+ {
+ stats1 = (Form_pg_statistic) GETSTRUCT(vardata1.statsTuple);
+ have_mcvs1 = get_attstatsslot(vardata1.statsTuple,
+ vardata1.atttype,
+ vardata1.atttypmod,
+ STATISTIC_KIND_MCV,
+ InvalidOid,
+ &values1, &nvalues1,
+ &numbers1, &nnumbers1);
+ }
- get_join_vars(args, &var1, &var2);
+ if (HeapTupleIsValid(vardata2.statsTuple))
+ {
+ stats2 = (Form_pg_statistic) GETSTRUCT(vardata2.statsTuple);
+ have_mcvs2 = get_attstatsslot(vardata2.statsTuple,
+ vardata2.atttype,
+ vardata2.atttypmod,
+ STATISTIC_KIND_MCV,
+ InvalidOid,
+ &values2, &nvalues2,
+ &numbers2, &nnumbers2);
+ }
- if (var1 == NULL && var2 == NULL)
- selec = DEFAULT_EQ_SEL;
- else
+ if (have_mcvs1 && have_mcvs2)
{
- HeapTuple statsTuple1 = NULL;
- HeapTuple statsTuple2 = NULL;
- Form_pg_statistic stats1 = NULL;
- Form_pg_statistic stats2 = NULL;
- double nd1 = DEFAULT_NUM_DISTINCT;
- double nd2 = DEFAULT_NUM_DISTINCT;
- bool have_mcvs1 = false;
- Datum *values1 = NULL;
- int nvalues1 = 0;
- float4 *numbers1 = NULL;
- int nnumbers1 = 0;
- bool have_mcvs2 = false;
- Datum *values2 = NULL;
- int nvalues2 = 0;
- float4 *numbers2 = NULL;
- int nnumbers2 = 0;
-
- if (var1 != NULL)
- {
- /* get stats for the attribute, if available */
- Oid relid1 = getrelid(var1->varno, root->rtable);
+ /*
+ * We have most-common-value lists for both relations. Run
+ * through the lists to see which MCVs actually join to each
+ * other with the given operator. This allows us to determine
+ * the exact join selectivity for the portion of the relations
+ * represented by the MCV lists. We still have to estimate
+ * for the remaining population, but in a skewed distribution
+ * this gives us a big leg up in accuracy. For motivation see
+ * the analysis in Y. Ioannidis and S. Christodoulakis, "On
+ * the propagation of errors in the size of join results",
+ * Technical Report 1018, Computer Science Dept., University
+ * of Wisconsin, Madison, March 1991 (available from
+ * ftp.cs.wisc.edu).
+ */
+ FmgrInfo eqproc;
+ bool *hasmatch1;
+ bool *hasmatch2;
+ double nullfrac1 = stats1->stanullfrac;
+ double nullfrac2 = stats2->stanullfrac;
+ double matchprodfreq,
+ matchfreq1,
+ matchfreq2,
+ unmatchfreq1,
+ unmatchfreq2,
+ otherfreq1,
+ otherfreq2,
+ totalsel1,
+ totalsel2;
+ int i,
+ nmatches;
+
+ fmgr_info(get_opcode(operator), &eqproc);
+ hasmatch1 = (bool *) palloc0(nvalues1 * sizeof(bool));
+ hasmatch2 = (bool *) palloc0(nvalues2 * sizeof(bool));
- if (relid1 != InvalidOid)
- {
- statsTuple1 = SearchSysCache(STATRELATT,
- ObjectIdGetDatum(relid1),
- Int16GetDatum(var1->varattno),
- 0, 0);
- if (HeapTupleIsValid(statsTuple1))
- {
- stats1 = (Form_pg_statistic) GETSTRUCT(statsTuple1);
- have_mcvs1 = get_attstatsslot(statsTuple1,
- var1->vartype,
- var1->vartypmod,
- STATISTIC_KIND_MCV,
- InvalidOid,
- &values1, &nvalues1,
- &numbers1, &nnumbers1);
- }
+ /*
+ * If we are doing any variant of JOIN_IN, pretend all the
+ * values of the righthand relation are unique (ie, act as if
+ * it's been DISTINCT'd).
+ *
+ * NOTE: it might seem that we should unique-ify the lefthand
+ * input when considering JOIN_REVERSE_IN. But this is not
+ * so, because the join clause we've been handed has not been
+ * commuted from the way the parser originally wrote it. We
+ * know that the unique side of the IN clause is *always* on
+ * the right.
+ *
+ * NOTE: it would be dangerous to try to be smart about JOIN_LEFT
+ * or JOIN_RIGHT here, because we do not have enough
+ * information to determine which var is really on which side
+ * of the join. Perhaps someday we should pass in more
+ * information.
+ */
+ if (jointype == JOIN_IN ||
+ jointype == JOIN_REVERSE_IN ||
+ jointype == JOIN_UNIQUE_INNER ||
+ jointype == JOIN_UNIQUE_OUTER)
+ {
+ float4 oneovern = 1.0 / nd2;
- nd1 = get_att_numdistinct(root, var1, stats1);
- }
+ for (i = 0; i < nvalues2; i++)
+ numbers2[i] = oneovern;
+ nullfrac2 = oneovern;
}
- if (var2 != NULL)
+ /*
+ * Note we assume that each MCV will match at most one member
+ * of the other MCV list. If the operator isn't really
+ * equality, there could be multiple matches --- but we don't
+ * look for them, both for speed and because the math wouldn't
+ * add up...
+ */
+ matchprodfreq = 0.0;
+ nmatches = 0;
+ for (i = 0; i < nvalues1; i++)
{
- /* get stats for the attribute, if available */
- Oid relid2 = getrelid(var2->varno, root->rtable);
+ int j;
- if (relid2 != InvalidOid)
+ for (j = 0; j < nvalues2; j++)
{
- statsTuple2 = SearchSysCache(STATRELATT,
- ObjectIdGetDatum(relid2),
- Int16GetDatum(var2->varattno),
- 0, 0);
- if (HeapTupleIsValid(statsTuple2))
+ if (hasmatch2[j])
+ continue;
+ if (DatumGetBool(FunctionCall2(&eqproc,
+ values1[i],
+ values2[j])))
{
- stats2 = (Form_pg_statistic) GETSTRUCT(statsTuple2);
- have_mcvs2 = get_attstatsslot(statsTuple2,
- var2->vartype,
- var2->vartypmod,
- STATISTIC_KIND_MCV,
- InvalidOid,
- &values2, &nvalues2,
- &numbers2, &nnumbers2);
+ hasmatch1[i] = hasmatch2[j] = true;
+ matchprodfreq += numbers1[i] * numbers2[j];
+ nmatches++;
+ break;
}
-
- nd2 = get_att_numdistinct(root, var2, stats2);
}
}
-
- if (have_mcvs1 && have_mcvs2)
+ CLAMP_PROBABILITY(matchprodfreq);
+ /* Sum up frequencies of matched and unmatched MCVs */
+ matchfreq1 = unmatchfreq1 = 0.0;
+ for (i = 0; i < nvalues1; i++)
{
- /*
- * We have most-common-value lists for both relations. Run
- * through the lists to see which MCVs actually join to each
- * other with the given operator. This allows us to determine
- * the exact join selectivity for the portion of the relations
- * represented by the MCV lists. We still have to estimate
- * for the remaining population, but in a skewed distribution
- * this gives us a big leg up in accuracy. For motivation see
- * the analysis in Y. Ioannidis and S. Christodoulakis, "On
- * the propagation of errors in the size of join results",
- * Technical Report 1018, Computer Science Dept., University
- * of Wisconsin, Madison, March 1991 (available from
- * ftp.cs.wisc.edu).
- */
- FmgrInfo eqproc;
- bool *hasmatch1;
- bool *hasmatch2;
- double nullfrac1 = stats1->stanullfrac;
- double nullfrac2 = stats2->stanullfrac;
- double matchprodfreq,
- matchfreq1,
- matchfreq2,
- unmatchfreq1,
- unmatchfreq2,
- otherfreq1,
- otherfreq2,
- totalsel1,
- totalsel2;
- int i,
- nmatches;
-
- fmgr_info(get_opcode(operator), &eqproc);
- hasmatch1 = (bool *) palloc0(nvalues1 * sizeof(bool));
- hasmatch2 = (bool *) palloc0(nvalues2 * sizeof(bool));
-
- /*
- * If we are doing any variant of JOIN_IN, pretend all the
- * values of the righthand relation are unique (ie, act as if
- * it's been DISTINCT'd).
- *
- * NOTE: it might seem that we should unique-ify the lefthand
- * input when considering JOIN_REVERSE_IN. But this is not
- * so, because the join clause we've been handed has not been
- * commuted from the way the parser originally wrote it. We
- * know that the unique side of the IN clause is *always* on
- * the right.
- *
- * NOTE: it would be dangerous to try to be smart about JOIN_LEFT
- * or JOIN_RIGHT here, because we do not have enough
- * information to determine which var is really on which side
- * of the join. Perhaps someday we should pass in more
- * information.
- */
- if (jointype == JOIN_IN ||
- jointype == JOIN_REVERSE_IN ||
- jointype == JOIN_UNIQUE_INNER ||
- jointype == JOIN_UNIQUE_OUTER)
- {
- float4 oneovern = 1.0 / nd2;
-
- for (i = 0; i < nvalues2; i++)
- numbers2[i] = oneovern;
- nullfrac2 = oneovern;
- }
-
- /*
- * Note we assume that each MCV will match at most one member
- * of the other MCV list. If the operator isn't really
- * equality, there could be multiple matches --- but we don't
- * look for them, both for speed and because the math wouldn't
- * add up...
- */
- matchprodfreq = 0.0;
- nmatches = 0;
- for (i = 0; i < nvalues1; i++)
- {
- int j;
+ if (hasmatch1[i])
+ matchfreq1 += numbers1[i];
+ else
+ unmatchfreq1 += numbers1[i];
+ }
+ CLAMP_PROBABILITY(matchfreq1);
+ CLAMP_PROBABILITY(unmatchfreq1);
+ matchfreq2 = unmatchfreq2 = 0.0;
+ for (i = 0; i < nvalues2; i++)
+ {
+ if (hasmatch2[i])
+ matchfreq2 += numbers2[i];
+ else
+ unmatchfreq2 += numbers2[i];
+ }
+ CLAMP_PROBABILITY(matchfreq2);
+ CLAMP_PROBABILITY(unmatchfreq2);
+ pfree(hasmatch1);
+ pfree(hasmatch2);
- for (j = 0; j < nvalues2; j++)
- {
- if (hasmatch2[j])
- continue;
- if (DatumGetBool(FunctionCall2(&eqproc,
- values1[i],
- values2[j])))
- {
- hasmatch1[i] = hasmatch2[j] = true;
- matchprodfreq += numbers1[i] * numbers2[j];
- nmatches++;
- break;
- }
- }
- }
- CLAMP_PROBABILITY(matchprodfreq);
- /* Sum up frequencies of matched and unmatched MCVs */
- matchfreq1 = unmatchfreq1 = 0.0;
- for (i = 0; i < nvalues1; i++)
- {
- if (hasmatch1[i])
- matchfreq1 += numbers1[i];
- else
- unmatchfreq1 += numbers1[i];
- }
- CLAMP_PROBABILITY(matchfreq1);
- CLAMP_PROBABILITY(unmatchfreq1);
- matchfreq2 = unmatchfreq2 = 0.0;
- for (i = 0; i < nvalues2; i++)
- {
- if (hasmatch2[i])
- matchfreq2 += numbers2[i];
- else
- unmatchfreq2 += numbers2[i];
- }
- CLAMP_PROBABILITY(matchfreq2);
- CLAMP_PROBABILITY(unmatchfreq2);
- pfree(hasmatch1);
- pfree(hasmatch2);
+ /*
+ * Compute total frequency of non-null values that are not in
+ * the MCV lists.
+ */
+ otherfreq1 = 1.0 - nullfrac1 - matchfreq1 - unmatchfreq1;
+ otherfreq2 = 1.0 - nullfrac2 - matchfreq2 - unmatchfreq2;
+ CLAMP_PROBABILITY(otherfreq1);
+ CLAMP_PROBABILITY(otherfreq2);
- /*
- * Compute total frequency of non-null values that are not in
- * the MCV lists.
- */
- otherfreq1 = 1.0 - nullfrac1 - matchfreq1 - unmatchfreq1;
- otherfreq2 = 1.0 - nullfrac2 - matchfreq2 - unmatchfreq2;
- CLAMP_PROBABILITY(otherfreq1);
- CLAMP_PROBABILITY(otherfreq2);
+ /*
+ * We can estimate the total selectivity from the point of
+ * view of relation 1 as: the known selectivity for matched
+ * MCVs, plus unmatched MCVs that are assumed to match against
+ * random members of relation 2's non-MCV population, plus
+ * non-MCV values that are assumed to match against random
+ * members of relation 2's unmatched MCVs plus non-MCV values.
+ */
+ totalsel1 = matchprodfreq;
+ if (nd2 > nvalues2)
+ totalsel1 += unmatchfreq1 * otherfreq2 / (nd2 - nvalues2);
+ if (nd2 > nmatches)
+ totalsel1 += otherfreq1 * (otherfreq2 + unmatchfreq2) /
+ (nd2 - nmatches);
+ /* Same estimate from the point of view of relation 2. */
+ totalsel2 = matchprodfreq;
+ if (nd1 > nvalues1)
+ totalsel2 += unmatchfreq2 * otherfreq1 / (nd1 - nvalues1);
+ if (nd1 > nmatches)
+ totalsel2 += otherfreq2 * (otherfreq1 + unmatchfreq1) /
+ (nd1 - nmatches);
- /*
- * We can estimate the total selectivity from the point of
- * view of relation 1 as: the known selectivity for matched
- * MCVs, plus unmatched MCVs that are assumed to match against
- * random members of relation 2's non-MCV population, plus
- * non-MCV values that are assumed to match against random
- * members of relation 2's unmatched MCVs plus non-MCV values.
- */
- totalsel1 = matchprodfreq;
- if (nd2 > nvalues2)
- totalsel1 += unmatchfreq1 * otherfreq2 / (nd2 - nvalues2);
- if (nd2 > nmatches)
- totalsel1 += otherfreq1 * (otherfreq2 + unmatchfreq2) /
- (nd2 - nmatches);
- /* Same estimate from the point of view of relation 2. */
- totalsel2 = matchprodfreq;
- if (nd1 > nvalues1)
- totalsel2 += unmatchfreq2 * otherfreq1 / (nd1 - nvalues1);
- if (nd1 > nmatches)
- totalsel2 += otherfreq2 * (otherfreq1 + unmatchfreq1) /
- (nd1 - nmatches);
+ /*
+ * Use the smaller of the two estimates. This can be
+ * justified in essentially the same terms as given below for
+ * the no-stats case: to a first approximation, we are
+ * estimating from the point of view of the relation with
+ * smaller nd.
+ */
+ selec = (totalsel1 < totalsel2) ? totalsel1 : totalsel2;
+ }
+ else
+ {
+ /*
+ * We do not have MCV lists for both sides. Estimate the join
+ * selectivity as
+ * MIN(1/nd1,1/nd2)*(1-nullfrac1)*(1-nullfrac2). This is
+ * plausible if we assume that the join operator is strict and
+ * the non-null values are about equally distributed: a given
+ * non-null tuple of rel1 will join to either zero or
+ * N2*(1-nullfrac2)/nd2 rows of rel2, so total join rows are
+ * at most N1*(1-nullfrac1)*N2*(1-nullfrac2)/nd2 giving a join
+ * selectivity of not more than
+ * (1-nullfrac1)*(1-nullfrac2)/nd2. By the same logic it is
+ * not more than (1-nullfrac1)*(1-nullfrac2)/nd1, so the
+ * expression with MIN() is an upper bound. Using the MIN()
+ * means we estimate from the point of view of the relation
+ * with smaller nd (since the larger nd is determining the
+ * MIN). It is reasonable to assume that most tuples in this
+ * rel will have join partners, so the bound is probably
+ * reasonably tight and should be taken as-is.
+ *
+ * XXX Can we be smarter if we have an MCV list for just one
+ * side? It seems that if we assume equal distribution for the
+ * other side, we end up with the same answer anyway.
+ */
+ double nullfrac1 = stats1 ? stats1->stanullfrac : 0.0;
+ double nullfrac2 = stats2 ? stats2->stanullfrac : 0.0;
- /*
- * Use the smaller of the two estimates. This can be
- * justified in essentially the same terms as given below for
- * the no-stats case: to a first approximation, we are
- * estimating from the point of view of the relation with
- * smaller nd.
- */
- selec = (totalsel1 < totalsel2) ? totalsel1 : totalsel2;
- }
+ selec = (1.0 - nullfrac1) * (1.0 - nullfrac2);
+ if (nd1 > nd2)
+ selec /= nd1;
else
- {
- /*
- * We do not have MCV lists for both sides. Estimate the join
- * selectivity as
- * MIN(1/nd1,1/nd2)*(1-nullfrac1)*(1-nullfrac2). This is
- * plausible if we assume that the join operator is strict and
- * the non-null values are about equally distributed: a given
- * non-null tuple of rel1 will join to either zero or
- * N2*(1-nullfrac2)/nd2 rows of rel2, so total join rows are
- * at most N1*(1-nullfrac1)*N2*(1-nullfrac2)/nd2 giving a join
- * selectivity of not more than
- * (1-nullfrac1)*(1-nullfrac2)/nd2. By the same logic it is
- * not more than (1-nullfrac1)*(1-nullfrac2)/nd1, so the
- * expression with MIN() is an upper bound. Using the MIN()
- * means we estimate from the point of view of the relation
- * with smaller nd (since the larger nd is determining the
- * MIN). It is reasonable to assume that most tuples in this
- * rel will have join partners, so the bound is probably
- * reasonably tight and should be taken as-is.
- *
- * XXX Can we be smarter if we have an MCV list for just one
- * side? It seems that if we assume equal distribution for the
- * other side, we end up with the same answer anyway.
- */
- double nullfrac1 = stats1 ? stats1->stanullfrac : 0.0;
- double nullfrac2 = stats2 ? stats2->stanullfrac : 0.0;
+ selec /= nd2;
+ }
- selec = (1.0 - nullfrac1) * (1.0 - nullfrac2);
- if (nd1 > nd2)
- selec /= nd1;
- else
- selec /= nd2;
- }
+ if (have_mcvs1)
+ free_attstatsslot(vardata1.atttype, values1, nvalues1,
+ numbers1, nnumbers1);
+ if (have_mcvs2)
+ free_attstatsslot(vardata2.atttype, values2, nvalues2,
+ numbers2, nnumbers2);
- if (have_mcvs1)
- free_attstatsslot(var1->vartype, values1, nvalues1,
- numbers1, nnumbers1);
- if (have_mcvs2)
- free_attstatsslot(var2->vartype, values2, nvalues2,
- numbers2, nnumbers2);
- if (HeapTupleIsValid(statsTuple1))
- ReleaseSysCache(statsTuple1);
- if (HeapTupleIsValid(statsTuple2))
- ReleaseSysCache(statsTuple2);
- }
+ ReleaseVariableStats(vardata1);
+ ReleaseVariableStats(vardata2);
CLAMP_PROBABILITY(selec);
@@ -1860,8 +1773,10 @@ mergejoinscansel(Query *root, Node *clause,
Selectivity *leftscan,
Selectivity *rightscan)
{
- Var *left,
+ Node *left,
*right;
+ VariableStatData leftvar,
+ rightvar;
Oid lefttype,
righttype;
Oid opno,
@@ -1883,42 +1798,31 @@ mergejoinscansel(Query *root, Node *clause,
if (!is_opclause(clause))
return; /* shouldn't happen */
opno = ((OpExpr *) clause)->opno;
- left = (Var *) get_leftop((Expr *) clause);
- right = (Var *) get_rightop((Expr *) clause);
+ left = get_leftop((Expr *) clause);
+ right = get_rightop((Expr *) clause);
if (!right)
return; /* shouldn't happen */
- /* Save the direct input types of the operator */
- lefttype = exprType((Node *) left);
- righttype = exprType((Node *) right);
+ /* Look for stats for the inputs */
+ examine_variable(root, left, 0, &leftvar);
+ examine_variable(root, right, 0, &rightvar);
- /*
- * Now skip any binary-compatible relabeling; there can only be one
- * level since constant-expression folder eliminates adjacent
- * RelabelTypes.
- */
- if (IsA(left, RelabelType))
- left = (Var *) ((RelabelType *) left)->arg;
- if (IsA(right, RelabelType))
- right = (Var *) ((RelabelType *) right)->arg;
-
- /* Can't do anything if inputs are not Vars */
- if (!IsA(left, Var) ||
- !IsA(right, Var))
- return;
+ /* Get the direct input types of the operator */
+ lefttype = exprType(left);
+ righttype = exprType(right);
/* Verify mergejoinability and get left and right "<" operators */
if (!op_mergejoinable(opno,
&lsortop,
&rsortop))
- return; /* shouldn't happen */
+ goto fail; /* shouldn't happen */
- /* Try to get maximum values of both vars */
- if (!get_var_maximum(root, left, lsortop, &leftmax))
- return; /* no max available from stats */
+ /* Try to get maximum values of both inputs */
+ if (!get_variable_maximum(root, &leftvar, lsortop, &leftmax))
+ goto fail; /* no max available from stats */
- if (!get_var_maximum(root, right, rsortop, &rightmax))
- return; /* no max available from stats */
+ if (!get_variable_maximum(root, &rightvar, rsortop, &rightmax))
+ goto fail; /* no max available from stats */
/* Look up the "left < right" and "left > right" operators */
op_mergejoin_crossops(opno, <op, >op, NULL, NULL);
@@ -1926,30 +1830,30 @@ mergejoinscansel(Query *root, Node *clause,
/* Look up the "left <= right" operator */
leop = get_negator(gtop);
if (!OidIsValid(leop))
- return; /* insufficient info in catalogs */
+ goto fail; /* insufficient info in catalogs */
/* Look up the "right > left" operator */
revgtop = get_commutator(ltop);
if (!OidIsValid(revgtop))
- return; /* insufficient info in catalogs */
+ goto fail; /* insufficient info in catalogs */
/* Look up the "right <= left" operator */
revleop = get_negator(revgtop);
if (!OidIsValid(revleop))
- return; /* insufficient info in catalogs */
+ goto fail; /* insufficient info in catalogs */
/*
* Now, the fraction of the left variable that will be scanned is the
* fraction that's <= the right-side maximum value. But only believe
* non-default estimates, else stick with our 1.0.
*/
- selec = scalarineqsel(root, leop, false, left,
+ selec = scalarineqsel(root, leop, false, &leftvar,
rightmax, righttype);
if (selec != DEFAULT_INEQ_SEL)
*leftscan = selec;
/* And similarly for the right variable. */
- selec = scalarineqsel(root, revleop, false, right,
+ selec = scalarineqsel(root, revleop, false, &rightvar,
leftmax, lefttype);
if (selec != DEFAULT_INEQ_SEL)
*rightscan = selec;
@@ -1966,6 +1870,10 @@ mergejoinscansel(Query *root, Node *clause,
*rightscan = 1.0;
else
*leftscan = *rightscan = 1.0;
+
+fail:
+ ReleaseVariableStats(leftvar);
+ ReleaseVariableStats(rightvar);
}
/*
@@ -2076,25 +1984,14 @@ estimate_num_groups(Query *root, List *groupExprs, double input_rows)
foreach(l, allvars)
{
Var *var = (Var *) lfirst(l);
- Oid relid = getrelid(var->varno, root->rtable);
- HeapTuple statsTuple = NULL;
- Form_pg_statistic stats = NULL;
+ VariableStatData vardata;
double ndistinct;
bool keep = true;
List *l2;
- if (OidIsValid(relid))
- {
- statsTuple = SearchSysCache(STATRELATT,
- ObjectIdGetDatum(relid),
- Int16GetDatum(var->varattno),
- 0, 0);
- if (HeapTupleIsValid(statsTuple))
- stats = (Form_pg_statistic) GETSTRUCT(statsTuple);
- }
- ndistinct = get_att_numdistinct(root, var, stats);
- if (HeapTupleIsValid(statsTuple))
- ReleaseSysCache(statsTuple);
+ examine_variable(root, (Node *) var, 0, &vardata);
+ ndistinct = get_variable_numdistinct(&vardata);
+ ReleaseVariableStats(vardata);
/* cannot use foreach here because of possible lremove */
l2 = varinfos;
@@ -2201,143 +2098,152 @@ estimate_num_groups(Query *root, List *groupExprs, double input_rows)
return numdistinct;
}
-
-/*-------------------------------------------------------------------------
+/*
+ * Estimate hash bucketsize fraction (ie, number of entries in a bucket
+ * divided by total tuples in relation) if the specified expression is used
+ * as a hash key.
*
- * Support routines
+ * XXX This is really pretty bogus since we're effectively assuming that the
+ * distribution of hash keys will be the same after applying restriction
+ * clauses as it was in the underlying relation. However, we are not nearly
+ * smart enough to figure out how the restrict clauses might change the
+ * distribution, so this will have to do for now.
*
- *-------------------------------------------------------------------------
- */
-
-/*
- * get_var_maximum
- * Estimate the maximum value of the specified variable.
- * If successful, store value in *max and return TRUE.
- * If no data available, return FALSE.
+ * We are passed the number of buckets the executor will use for the given
+ * input relation. If the data were perfectly distributed, with the same
+ * number of tuples going into each available bucket, then the bucketsize
+ * fraction would be 1/nbuckets. But this happy state of affairs will occur
+ * only if (a) there are at least nbuckets distinct data values, and (b)
+ * we have a not-too-skewed data distribution. Otherwise the buckets will
+ * be nonuniformly occupied. If the other relation in the join has a key
+ * distribution similar to this one's, then the most-loaded buckets are
+ * exactly those that will be probed most often. Therefore, the "average"
+ * bucket size for costing purposes should really be taken as something close
+ * to the "worst case" bucket size. We try to estimate this by adjusting the
+ * fraction if there are too few distinct data values, and then scaling up
+ * by the ratio of the most common value's frequency to the average frequency.
*
- * sortop is the "<" comparison operator to use. (To extract the
- * minimum instead of the maximum, just pass the ">" operator instead.)
+ * If no statistics are available, use a default estimate of 0.1. This will
+ * discourage use of a hash rather strongly if the inner relation is large,
+ * which is what we want. We do not want to hash unless we know that the
+ * inner rel is well-dispersed (or the alternatives seem much worse).
*/
-static bool
-get_var_maximum(Query *root, Var *var, Oid sortop, Datum *max)
+Selectivity
+estimate_hash_bucketsize(Query *root, Node *hashkey, int nbuckets)
{
- Datum tmax = 0;
- bool have_max = false;
- Oid relid;
- HeapTuple statsTuple;
- Form_pg_statistic stats;
- int16 typLen;
- bool typByVal;
- Datum *values;
- int nvalues;
- int i;
+ VariableStatData vardata;
+ double estfract,
+ ndistinct,
+ stanullfrac,
+ mcvfreq,
+ avgfreq;
+ float4 *numbers;
+ int nnumbers;
- relid = getrelid(var->varno, root->rtable);
- if (relid == InvalidOid)
- return false;
+ examine_variable(root, hashkey, 0, &vardata);
- /* get stats for the attribute */
- statsTuple = SearchSysCache(STATRELATT,
- ObjectIdGetDatum(relid),
- Int16GetDatum(var->varattno),
- 0, 0);
- if (!HeapTupleIsValid(statsTuple))
+ /* Get number of distinct values and fraction that are null */
+ ndistinct = get_variable_numdistinct(&vardata);
+
+ if (HeapTupleIsValid(vardata.statsTuple))
{
- /* no stats available, so default result */
- return false;
+ Form_pg_statistic stats;
+
+ stats = (Form_pg_statistic) GETSTRUCT(vardata.statsTuple);
+ stanullfrac = stats->stanullfrac;
+ }
+ else
+ {
+ /*
+ * Believe a default ndistinct only if it came from stats.
+ * Otherwise punt and return 0.1, per comments above.
+ */
+ if (ndistinct == DEFAULT_NUM_DISTINCT)
+ {
+ ReleaseVariableStats(vardata);
+ return (Selectivity) 0.1;
+ }
+
+ stanullfrac = 0.0;
}
- stats = (Form_pg_statistic) GETSTRUCT(statsTuple);
- get_typlenbyval(var->vartype, &typLen, &typByVal);
+ /* Compute avg freq of all distinct data values in raw relation */
+ avgfreq = (1.0 - stanullfrac) / ndistinct;
/*
- * If there is a histogram, grab the last or first value as
- * appropriate.
+ * Adjust ndistinct to account for restriction clauses. Observe we
+ * are assuming that the data distribution is affected uniformly by
+ * the restriction clauses!
*
- * If there is a histogram that is sorted with some other operator than
- * the one we want, fail --- this suggests that there is data we can't
- * use.
+ * XXX Possibly better way, but much more expensive: multiply by
+ * selectivity of rel's restriction clauses that mention the target
+ * Var.
*/
- if (get_attstatsslot(statsTuple, var->vartype, var->vartypmod,
- STATISTIC_KIND_HISTOGRAM, sortop,
- &values, &nvalues,
- NULL, NULL))
- {
- if (nvalues > 0)
- {
- tmax = datumCopy(values[nvalues - 1], typByVal, typLen);
- have_max = true;
- }
- free_attstatsslot(var->vartype, values, nvalues, NULL, 0);
- }
+ if (vardata.rel)
+ ndistinct *= vardata.rel->rows / vardata.rel->tuples;
+
+ /*
+ * Initial estimate of bucketsize fraction is 1/nbuckets as long as
+ * the number of buckets is less than the expected number of distinct
+ * values; otherwise it is 1/ndistinct.
+ */
+ if (ndistinct > (double) nbuckets)
+ estfract = 1.0 / (double) nbuckets;
else
- {
- Oid rsortop = get_commutator(sortop);
+ estfract = 1.0 / ndistinct;
- if (OidIsValid(rsortop) &&
- get_attstatsslot(statsTuple, var->vartype, var->vartypmod,
- STATISTIC_KIND_HISTOGRAM, rsortop,
- &values, &nvalues,
- NULL, NULL))
- {
- if (nvalues > 0)
- {
- tmax = datumCopy(values[0], typByVal, typLen);
- have_max = true;
- }
- free_attstatsslot(var->vartype, values, nvalues, NULL, 0);
- }
- else if (get_attstatsslot(statsTuple, var->vartype, var->vartypmod,
- STATISTIC_KIND_HISTOGRAM, InvalidOid,
- &values, &nvalues,
- NULL, NULL))
+ /*
+ * Look up the frequency of the most common value, if available.
+ */
+ mcvfreq = 0.0;
+
+ if (HeapTupleIsValid(vardata.statsTuple))
+ {
+ if (get_attstatsslot(vardata.statsTuple,
+ vardata.atttype, vardata.atttypmod,
+ STATISTIC_KIND_MCV, InvalidOid,
+ NULL, NULL, &numbers, &nnumbers))
{
- free_attstatsslot(var->vartype, values, nvalues, NULL, 0);
- ReleaseSysCache(statsTuple);
- return false;
+ /*
+ * The first MCV stat is for the most common value.
+ */
+ if (nnumbers > 0)
+ mcvfreq = numbers[0];
+ free_attstatsslot(vardata.atttype, NULL, 0,
+ numbers, nnumbers);
}
}
/*
- * If we have most-common-values info, look for a large MCV. This is
- * needed even if we also have a histogram, since the histogram
- * excludes the MCVs. However, usually the MCVs will not be the
- * extreme values, so avoid unnecessary data copying.
+ * Adjust estimated bucketsize upward to account for skewed
+ * distribution.
*/
- if (get_attstatsslot(statsTuple, var->vartype, var->vartypmod,
- STATISTIC_KIND_MCV, InvalidOid,
- &values, &nvalues,
- NULL, NULL))
- {
- bool large_mcv = false;
- FmgrInfo opproc;
-
- fmgr_info(get_opcode(sortop), &opproc);
+ if (avgfreq > 0.0 && mcvfreq > avgfreq)
+ estfract *= mcvfreq / avgfreq;
- for (i = 0; i < nvalues; i++)
- {
- if (!have_max)
- {
- tmax = values[i];
- large_mcv = have_max = true;
- }
- else if (DatumGetBool(FunctionCall2(&opproc, tmax, values[i])))
- {
- tmax = values[i];
- large_mcv = true;
- }
- }
- if (large_mcv)
- tmax = datumCopy(tmax, typByVal, typLen);
- free_attstatsslot(var->vartype, values, nvalues, NULL, 0);
- }
+ /*
+ * Clamp bucketsize to sane range (the above adjustment could easily
+ * produce an out-of-range result). We set the lower bound a little
+ * above zero, since zero isn't a very sane result.
+ */
+ if (estfract < 1.0e-6)
+ estfract = 1.0e-6;
+ else if (estfract > 1.0)
+ estfract = 1.0;
- ReleaseSysCache(statsTuple);
+ ReleaseVariableStats(vardata);
- *max = tmax;
- return have_max;
+ return (Selectivity) estfract;
}
+
+/*-------------------------------------------------------------------------
+ *
+ * Support routines
+ *
+ *-------------------------------------------------------------------------
+ */
+
/*
* convert_to_scalar
* Convert non-NULL values of the indicated types to the comparison
@@ -2903,185 +2809,522 @@ convert_timevalue_to_scalar(Datum value, Oid typid)
/*
- * get_att_numdistinct
- * Estimate the number of distinct values of an attribute.
+ * get_restriction_variable
+ * Examine the args of a restriction clause to see if it's of the
+ * form (variable op pseudoconstant) or (pseudoconstant op variable),
+ * where "variable" could be either a Var or an expression in vars of a
+ * single relation. If so, extract information about the variable,
+ * and also indicate which side it was on and the other argument.
*
- * var: identifies the attribute to examine.
- * stats: pg_statistic tuple for attribute, or NULL if not available.
+ * Inputs:
+ * root: the Query
+ * args: clause argument list
+ * varRelid: see specs for restriction selectivity functions
*
- * NB: be careful to produce an integral result, since callers may compare
- * the result to exact integer counts.
+ * Outputs: (these are valid only if TRUE is returned)
+ * *vardata: gets information about variable (see examine_variable)
+ * *other: gets other clause argument, stripped of binary relabeling
+ * *varonleft: set TRUE if variable is on the left, FALSE if on the right
+ *
+ * Returns TRUE if a variable is identified, otherwise FALSE.
+ *
+ * Note: if there are Vars on both sides of the clause, we must fail, because
+ * callers are expecting that the other side will act like a pseudoconstant.
*/
-static double
-get_att_numdistinct(Query *root, Var *var, Form_pg_statistic stats)
+static bool
+get_restriction_variable(Query *root, List *args, int varRelid,
+ VariableStatData *vardata, Node **other,
+ bool *varonleft)
{
- RelOptInfo *rel;
- double ntuples;
-
- /*
- * Special-case boolean columns: presumably, two distinct values.
- *
- * Are there any other cases we should wire in special estimates for?
- */
- if (var->vartype == BOOLOID)
- return 2.0;
+ Node *left,
+ *right;
+ VariableStatData rdata;
- /*
- * Otherwise we need to get the relation size.
- */
- rel = find_base_rel(root, var->varno);
- ntuples = rel->tuples;
+ /* Fail if not a binary opclause (probably shouldn't happen) */
+ if (length(args) != 2)
+ return false;
- if (ntuples <= 0.0)
- return DEFAULT_NUM_DISTINCT; /* no data available; return a
- * default */
+ left = (Node *) lfirst(args);
+ right = (Node *) lsecond(args);
/*
- * Look to see if there is a unique index on the attribute. If so, we
- * assume it's distinct, ignoring pg_statistic info which could be out
- * of date.
+ * Examine both sides. Note that when varRelid is nonzero, Vars of
+ * other relations will be treated as pseudoconstants.
*/
- if (has_unique_index(rel, var->varattno))
- return ntuples;
+ examine_variable(root, left, varRelid, vardata);
+ examine_variable(root, right, varRelid, &rdata);
/*
- * If ANALYZE determined a fixed or scaled estimate, use it.
+ * If one side is a variable and the other not, we win.
*/
- if (stats)
+ if (vardata->rel && rdata.rel == NULL)
{
- if (stats->stadistinct > 0.0)
- return stats->stadistinct;
- if (stats->stadistinct < 0.0)
- return floor((-stats->stadistinct * ntuples) + 0.5);
+ *varonleft = true;
+ *other = rdata.var;
+ /* Assume we need no ReleaseVariableStats(rdata) here */
+ return true;
}
- /*
- * ANALYZE does not compute stats for system attributes, but some of
- * them can reasonably be assumed unique anyway.
- */
- switch (var->varattno)
+ if (vardata->rel == NULL && rdata.rel)
{
- case ObjectIdAttributeNumber:
- case SelfItemPointerAttributeNumber:
- return ntuples;
- case TableOidAttributeNumber:
- return 1.0;
+ *varonleft = false;
+ *other = vardata->var;
+ /* Assume we need no ReleaseVariableStats(*vardata) here */
+ *vardata = rdata;
+ return true;
}
- /*
- * Estimate ndistinct = ntuples if the table is small, else use
- * default.
- */
- if (ntuples < DEFAULT_NUM_DISTINCT)
- return ntuples;
+ /* Ooops, clause has wrong structure (probably var op var) */
+ ReleaseVariableStats(*vardata);
+ ReleaseVariableStats(rdata);
- return DEFAULT_NUM_DISTINCT;
+ return false;
}
/*
- * get_restriction_var
- * Examine the args of a restriction clause to see if it's of the
- * form (var op something) or (something op var). If so, extract
- * and return the var and the other argument.
- *
- * Inputs:
- * args: clause argument list
- * varRelid: see specs for restriction selectivity functions
- *
- * Outputs: (these are set only if TRUE is returned)
- * *var: gets Var node
- * *other: gets other clause argument
- * *varonleft: set TRUE if var is on the left, FALSE if on the right
- *
- * Returns TRUE if a Var is identified, otherwise FALSE.
+ * get_join_variables
+ * Apply examine_variable() to each side of a join clause.
*/
-static bool
-get_restriction_var(List *args,
- int varRelid,
- Var **var,
- Node **other,
- bool *varonleft)
+static void
+get_join_variables(Query *root, List *args,
+ VariableStatData *vardata1, VariableStatData *vardata2)
{
Node *left,
*right;
if (length(args) != 2)
- return false;
+ elog(ERROR, "join operator should take two arguments");
left = (Node *) lfirst(args);
right = (Node *) lsecond(args);
+ examine_variable(root, left, 0, vardata1);
+ examine_variable(root, right, 0, vardata2);
+}
+
+/*
+ * examine_variable
+ * Try to look up statistical data about an expression.
+ * Fill in a VariableStatData struct to describe the expression.
+ *
+ * Inputs:
+ * root: the Query
+ * node: the expression tree to examine
+ * varRelid: see specs for restriction selectivity functions
+ *
+ * Outputs: *vardata is filled as follows:
+ * var: the input expression (with any binary relabeling stripped)
+ * rel: RelOptInfo for relation containing variable; NULL if expression
+ * contains no Vars (NOTE this could point to a RelOptInfo of a
+ * subquery, not one in the current query).
+ * statsTuple: the pg_statistic entry for the variable, if one exists;
+ * otherwise NULL.
+ * atttype, atttypmod: type data to pass to get_attstatsslot(). This is
+ * commonly the same as the exposed type of the variable argument,
+ * but can be different in binary-compatible-type cases.
+ *
+ * Caller is responsible for doing ReleaseVariableStats() before exiting.
+ */
+static void
+examine_variable(Query *root, Node *node, int varRelid,
+ VariableStatData *vardata)
+{
+ Relids varnos;
+ RelOptInfo *onerel;
+
+ /* Make sure we don't return dangling pointers in vardata */
+ MemSet(vardata, 0, sizeof(VariableStatData));
+
/* Ignore any binary-compatible relabeling */
- if (IsA(left, RelabelType))
- left = (Node *) ((RelabelType *) left)->arg;
- if (IsA(right, RelabelType))
- right = (Node *) ((RelabelType *) right)->arg;
+ if (IsA(node, RelabelType))
+ node = (Node *) ((RelabelType *) node)->arg;
- /* Look for the var */
+ vardata->var = node;
- if (IsA(left, Var) &&
- (varRelid == 0 || varRelid == ((Var *) left)->varno))
+ /* Fast path for a simple Var */
+
+ if (IsA(node, Var) &&
+ (varRelid == 0 || varRelid == ((Var *) node)->varno))
{
- *var = (Var *) left;
- *other = right;
- *varonleft = true;
+ Var *var = (Var *) node;
+ Oid relid;
+
+ vardata->rel = find_base_rel(root, var->varno);
+ vardata->atttype = var->vartype;
+ vardata->atttypmod = var->vartypmod;
+
+ relid = getrelid(var->varno, root->rtable);
+
+ if (OidIsValid(relid))
+ {
+ vardata->statsTuple = SearchSysCache(STATRELATT,
+ ObjectIdGetDatum(relid),
+ Int16GetDatum(var->varattno),
+ 0, 0);
+ }
+ else
+ {
+ /*
+ * XXX This means the Var comes from a JOIN or sub-SELECT. Later
+ * add code to dig down into the join etc and see if we can trace
+ * the variable to something with stats. (But beware of
+ * sub-SELECTs with DISTINCT/GROUP BY/etc. Perhaps there are
+ * no cases where this would really be useful, because we'd have
+ * flattened the subselect if it is??)
+ */
+ }
+
+ return;
}
- else if (IsA(right, Var) &&
- (varRelid == 0 || varRelid == ((Var *) right)->varno))
+
+ /*
+ * Okay, it's a more complicated expression. Determine variable
+ * membership. Note that when varRelid isn't zero, only vars of
+ * that relation are considered "real" vars.
+ */
+ varnos = pull_varnos(node);
+
+ onerel = NULL;
+
+ switch (bms_membership(varnos))
{
- *var = (Var *) right;
- *other = left;
- *varonleft = false;
+ case BMS_EMPTY_SET:
+ /* No Vars at all ... must be pseudo-constant clause */
+ break;
+ case BMS_SINGLETON:
+ if (varRelid == 0 || bms_is_member(varRelid, varnos))
+ {
+ onerel = find_base_rel(root,
+ (varRelid ? varRelid : bms_singleton_member(varnos)));
+ vardata->rel = onerel;
+ }
+ /* else treat it as a constant */
+ break;
+ case BMS_MULTIPLE:
+ if (varRelid == 0)
+ {
+ /* treat it as a variable of a join relation */
+ vardata->rel = find_join_rel(root, varnos);
+ }
+ else if (bms_is_member(varRelid, varnos))
+ {
+ /* ignore the vars belonging to other relations */
+ vardata->rel = find_base_rel(root, varRelid);
+ /* note: no point in expressional-index search here */
+ }
+ /* else treat it as a constant */
+ break;
+ }
+
+ bms_free(varnos);
+
+ vardata->atttype = exprType(node);
+ vardata->atttypmod = exprTypmod(node);
+
+ if (onerel)
+ {
+ /*
+ * We have an expression in vars of a single relation. Try to
+ * match it to expressional index columns, in hopes of finding
+ * some statistics.
+ *
+ * XXX it's conceivable that there are multiple matches with
+ * different index opclasses; if so, we need to pick one that
+ * matches the operator we are estimating for. FIXME later.
+ */
+ List *ilist;
+
+ foreach(ilist, onerel->indexlist)
+ {
+ IndexOptInfo *index = (IndexOptInfo *) lfirst(ilist);
+ List *indexprs;
+ int pos;
+
+ indexprs = index->indexprs;
+ if (indexprs == NIL)
+ continue; /* no expressions here... */
+
+ /*
+ * Ignore partial indexes since they probably don't reflect
+ * whole-relation statistics. Possibly reconsider this later.
+ */
+ if (index->indpred)
+ continue;
+
+ for (pos = 0; pos < index->ncolumns; pos++)
+ {
+ if (index->indexkeys[pos] == 0)
+ {
+ Node *indexkey;
+
+ if (indexprs == NIL)
+ elog(ERROR, "too few entries in indexprs list");
+ indexkey = (Node *) lfirst(indexprs);
+ if (indexkey && IsA(indexkey, RelabelType))
+ indexkey = (Node *) ((RelabelType *) indexkey)->arg;
+ if (equal(node, indexkey))
+ {
+ /*
+ * Found a match ... is it a unique index?
+ * Tests here should match has_unique_index().
+ */
+ if (index->unique &&
+ index->ncolumns == 1 &&
+ index->indpred == NIL)
+ vardata->isunique = true;
+ /* Has it got stats? */
+ vardata->statsTuple = SearchSysCache(STATRELATT,
+ ObjectIdGetDatum(index->indexoid),
+ Int16GetDatum(pos + 1),
+ 0, 0);
+ if (vardata->statsTuple)
+ break;
+ }
+ indexprs = lnext(indexprs);
+ }
+ }
+ if (vardata->statsTuple)
+ break;
+ }
+ }
+}
+
+/*
+ * get_variable_numdistinct
+ * Estimate the number of distinct values of a variable.
+ *
+ * vardata: results of examine_variable
+ *
+ * NB: be careful to produce an integral result, since callers may compare
+ * the result to exact integer counts.
+ */
+static double
+get_variable_numdistinct(VariableStatData *vardata)
+{
+ double stadistinct;
+ double ntuples;
+
+ /*
+ * Determine the stadistinct value to use. There are cases where
+ * we can get an estimate even without a pg_statistic entry, or
+ * can get a better value than is in pg_statistic.
+ */
+ if (HeapTupleIsValid(vardata->statsTuple))
+ {
+ /* Use the pg_statistic entry */
+ Form_pg_statistic stats;
+
+ stats = (Form_pg_statistic) GETSTRUCT(vardata->statsTuple);
+ stadistinct = stats->stadistinct;
+ }
+ else if (vardata->atttype == BOOLOID)
+ {
+ /*
+ * Special-case boolean columns: presumably, two distinct values.
+ *
+ * Are there any other datatypes we should wire in special
+ * estimates for?
+ */
+ stadistinct = 2.0;
}
else
{
- /* Duh, it's too complicated for me... */
- return false;
+ /*
+ * We don't keep statistics for system columns, but in some
+ * cases we can infer distinctness anyway.
+ */
+ if (vardata->var && IsA(vardata->var, Var))
+ {
+ switch (((Var *) vardata->var)->varattno)
+ {
+ case ObjectIdAttributeNumber:
+ case SelfItemPointerAttributeNumber:
+ stadistinct = -1.0; /* unique */
+ break;
+ case TableOidAttributeNumber:
+ stadistinct = 1.0; /* only 1 value */
+ break;
+ default:
+ stadistinct = 0.0; /* means "unknown" */
+ break;
+ }
+ }
+ else
+ stadistinct = 0.0; /* means "unknown" */
+ /*
+ * XXX consider using estimate_num_groups on expressions?
+ */
+ }
+
+ /*
+ * If there is a unique index for the variable, assume it is unique
+ * no matter what pg_statistic says (the statistics could be out
+ * of date). Can skip search if we already think it's unique.
+ */
+ if (stadistinct != -1.0)
+ {
+ if (vardata->isunique)
+ stadistinct = -1.0;
+ else if (vardata->var && IsA(vardata->var, Var) &&
+ vardata->rel &&
+ has_unique_index(vardata->rel,
+ ((Var *) vardata->var)->varattno))
+ stadistinct = -1.0;
}
- return true;
+ /*
+ * If we had an absolute estimate, use that.
+ */
+ if (stadistinct > 0.0)
+ return stadistinct;
+
+ /*
+ * Otherwise we need to get the relation size; punt if not available.
+ */
+ if (vardata->rel == NULL)
+ return DEFAULT_NUM_DISTINCT;
+ ntuples = vardata->rel->tuples;
+ if (ntuples <= 0.0)
+ return DEFAULT_NUM_DISTINCT;
+
+ /*
+ * If we had a relative estimate, use that.
+ */
+ if (stadistinct < 0.0)
+ return floor((-stadistinct * ntuples) + 0.5);
+
+ /*
+ * With no data, estimate ndistinct = ntuples if the table is small,
+ * else use default.
+ */
+ if (ntuples < DEFAULT_NUM_DISTINCT)
+ return ntuples;
+
+ return DEFAULT_NUM_DISTINCT;
}
/*
- * get_join_vars
+ * get_variable_maximum
+ * Estimate the maximum value of the specified variable.
+ * If successful, store value in *max and return TRUE.
+ * If no data available, return FALSE.
*
- * Extract the two Vars from a join clause's argument list. Returns
- * NULL for arguments that are not simple vars.
+ * sortop is the "<" comparison operator to use. (To extract the
+ * minimum instead of the maximum, just pass the ">" operator instead.)
*/
-static void
-get_join_vars(List *args, Var **var1, Var **var2)
+static bool
+get_variable_maximum(Query *root, VariableStatData *vardata,
+ Oid sortop, Datum *max)
{
- Node *left,
- *right;
+ Datum tmax = 0;
+ bool have_max = false;
+ Form_pg_statistic stats;
+ int16 typLen;
+ bool typByVal;
+ Datum *values;
+ int nvalues;
+ int i;
- if (length(args) != 2)
+ if (!HeapTupleIsValid(vardata->statsTuple))
{
- *var1 = NULL;
- *var2 = NULL;
- return;
+ /* no stats available, so default result */
+ return false;
}
+ stats = (Form_pg_statistic) GETSTRUCT(vardata->statsTuple);
- left = (Node *) lfirst(args);
- right = (Node *) lsecond(args);
+ get_typlenbyval(vardata->atttype, &typLen, &typByVal);
- /* Ignore any binary-compatible relabeling */
- if (IsA(left, RelabelType))
- left = (Node *) ((RelabelType *) left)->arg;
- if (IsA(right, RelabelType))
- right = (Node *) ((RelabelType *) right)->arg;
-
- if (IsA(left, Var))
- *var1 = (Var *) left;
+ /*
+ * If there is a histogram, grab the last or first value as
+ * appropriate.
+ *
+ * If there is a histogram that is sorted with some other operator than
+ * the one we want, fail --- this suggests that there is data we can't
+ * use.
+ */
+ if (get_attstatsslot(vardata->statsTuple,
+ vardata->atttype, vardata->atttypmod,
+ STATISTIC_KIND_HISTOGRAM, sortop,
+ &values, &nvalues,
+ NULL, NULL))
+ {
+ if (nvalues > 0)
+ {
+ tmax = datumCopy(values[nvalues - 1], typByVal, typLen);
+ have_max = true;
+ }
+ free_attstatsslot(vardata->atttype, values, nvalues, NULL, 0);
+ }
else
- *var1 = NULL;
+ {
+ Oid rsortop = get_commutator(sortop);
- if (IsA(right, Var))
- *var2 = (Var *) right;
- else
- *var2 = NULL;
+ if (OidIsValid(rsortop) &&
+ get_attstatsslot(vardata->statsTuple,
+ vardata->atttype, vardata->atttypmod,
+ STATISTIC_KIND_HISTOGRAM, rsortop,
+ &values, &nvalues,
+ NULL, NULL))
+ {
+ if (nvalues > 0)
+ {
+ tmax = datumCopy(values[0], typByVal, typLen);
+ have_max = true;
+ }
+ free_attstatsslot(vardata->atttype, values, nvalues, NULL, 0);
+ }
+ else if (get_attstatsslot(vardata->statsTuple,
+ vardata->atttype, vardata->atttypmod,
+ STATISTIC_KIND_HISTOGRAM, InvalidOid,
+ &values, &nvalues,
+ NULL, NULL))
+ {
+ free_attstatsslot(vardata->atttype, values, nvalues, NULL, 0);
+ return false;
+ }
+ }
+
+ /*
+ * If we have most-common-values info, look for a large MCV. This is
+ * needed even if we also have a histogram, since the histogram
+ * excludes the MCVs. However, usually the MCVs will not be the
+ * extreme values, so avoid unnecessary data copying.
+ */
+ if (get_attstatsslot(vardata->statsTuple,
+ vardata->atttype, vardata->atttypmod,
+ STATISTIC_KIND_MCV, InvalidOid,
+ &values, &nvalues,
+ NULL, NULL))
+ {
+ bool large_mcv = false;
+ FmgrInfo opproc;
+
+ fmgr_info(get_opcode(sortop), &opproc);
+
+ for (i = 0; i < nvalues; i++)
+ {
+ if (!have_max)
+ {
+ tmax = values[i];
+ large_mcv = have_max = true;
+ }
+ else if (DatumGetBool(FunctionCall2(&opproc, tmax, values[i])))
+ {
+ tmax = values[i];
+ large_mcv = true;
+ }
+ }
+ if (large_mcv)
+ tmax = datumCopy(tmax, typByVal, typLen);
+ free_attstatsslot(vardata->atttype, values, nvalues, NULL, 0);
+ }
+
+ *max = tmax;
+ return have_max;
}
+
/*-------------------------------------------------------------------------
*
* Pattern analysis functions
@@ -3387,10 +3630,11 @@ pattern_fixed_prefix(Const *patt, Pattern_Type ptype,
* Estimate the selectivity of a fixed prefix for a pattern match.
*
* A fixed prefix "foo" is estimated as the selectivity of the expression
- * "var >= 'foo' AND var < 'fop'" (see also indxqual.c).
+ * "variable >= 'foo' AND variable < 'fop'" (see also indxqual.c).
*
* We use the >= and < operators from the specified btree opclass to do the
- * estimation. The given Var and Const must be of the associated datatype.
+ * estimation. The given variable and Const must be of the associated
+ * datatype.
*
* XXX Note: we make use of the upper bound to estimate operator selectivity
* even if the locale is such that we cannot rely on the upper-bound string.
@@ -3398,7 +3642,8 @@ pattern_fixed_prefix(Const *patt, Pattern_Type ptype,
* more useful to use the upper-bound code than not.
*/
static Selectivity
-prefix_selectivity(Query *root, Var *var, Oid opclass, Const *prefixcon)
+prefix_selectivity(Query *root, VariableStatData *vardata,
+ Oid opclass, Const *prefixcon)
{
Selectivity prefixsel;
Oid cmpopr;
@@ -3409,7 +3654,7 @@ prefix_selectivity(Query *root, Var *var, Oid opclass, Const *prefixcon)
BTGreaterEqualStrategyNumber);
if (cmpopr == InvalidOid)
elog(ERROR, "no >= operator for opclass %u", opclass);
- cmpargs = makeList2(var, prefixcon);
+ cmpargs = makeList2(vardata->var, prefixcon);
/* Assume scalargtsel is appropriate for all supported types */
prefixsel = DatumGetFloat8(DirectFunctionCall4(scalargtsel,
PointerGetDatum(root),
@@ -3431,7 +3676,7 @@ prefix_selectivity(Query *root, Var *var, Oid opclass, Const *prefixcon)
BTLessStrategyNumber);
if (cmpopr == InvalidOid)
elog(ERROR, "no < operator for opclass %u", opclass);
- cmpargs = makeList2(var, greaterstrcon);
+ cmpargs = makeList2(vardata->var, greaterstrcon);
/* Assume scalarltsel is appropriate for all supported types */
topsel = DatumGetFloat8(DirectFunctionCall4(scalarltsel,
PointerGetDatum(root),
@@ -3446,7 +3691,7 @@ prefix_selectivity(Query *root, Var *var, Oid opclass, Const *prefixcon)
prefixsel = topsel + prefixsel - 1.0;
/* Adjust for double-exclusion of NULLs */
- prefixsel += nulltestsel(root, IS_NULL, (Node *) var, var->varno);
+ prefixsel += nulltestsel(root, IS_NULL, vardata->var, 0);
/*
* A zero or slightly negative prefixsel should be converted into
@@ -4034,56 +4279,69 @@ btcostestimate(PG_FUNCTION_ARGS)
Cost *indexTotalCost = (Cost *) PG_GETARG_POINTER(5);
Selectivity *indexSelectivity = (Selectivity *) PG_GETARG_POINTER(6);
double *indexCorrelation = (double *) PG_GETARG_POINTER(7);
+ Oid relid;
+ AttrNumber colnum;
+ HeapTuple tuple;
genericcostestimate(root, rel, index, indexQuals,
indexStartupCost, indexTotalCost,
indexSelectivity, indexCorrelation);
/*
- * If the first column is a simple variable, and we can get an
- * estimate for its ordering correlation C from pg_statistic, estimate
- * the index correlation as C / number-of-columns. (The idea here is
+ * If we can get an estimate of the first column's ordering correlation C
+ * from pg_statistic, estimate the index correlation as C for a single-
+ * column index, or C * 0.75 for multiple columns. (The idea here is
* that multiple columns dilute the importance of the first column's
- * ordering, but don't negate it entirely.)
+ * ordering, but don't negate it entirely. Before 7.5 we divided the
+ * correlation by the number of columns, but that seems too strong.)
*/
if (index->indexkeys[0] != 0)
{
- Oid relid;
- HeapTuple tuple;
-
+ /* Simple variable --- look to stats for the underlying table */
relid = getrelid(rel->relid, root->rtable);
Assert(relid != InvalidOid);
- tuple = SearchSysCache(STATRELATT,
- ObjectIdGetDatum(relid),
- Int16GetDatum(index->indexkeys[0]),
- 0, 0);
- if (HeapTupleIsValid(tuple))
+ colnum = index->indexkeys[0];
+ }
+ else
+ {
+ /* Expression --- maybe there are stats for the index itself */
+ relid = index->indexoid;
+ colnum = 1;
+ }
+
+ tuple = SearchSysCache(STATRELATT,
+ ObjectIdGetDatum(relid),
+ Int16GetDatum(colnum),
+ 0, 0);
+
+ if (HeapTupleIsValid(tuple))
+ {
+ Oid typid;
+ int32 typmod;
+ float4 *numbers;
+ int nnumbers;
+
+ /* XXX this code would break with different storage type */
+ get_atttypetypmod(relid, colnum, &typid, &typmod);
+
+ if (get_attstatsslot(tuple, typid, typmod,
+ STATISTIC_KIND_CORRELATION,
+ index->ordering[0],
+ NULL, NULL, &numbers, &nnumbers))
{
- Oid typid;
- int32 typmod;
- float4 *numbers;
- int nnumbers;
-
- get_atttypetypmod(relid, index->indexkeys[0],
- &typid, &typmod);
- if (get_attstatsslot(tuple, typid, typmod,
- STATISTIC_KIND_CORRELATION,
- index->ordering[0],
- NULL, NULL, &numbers, &nnumbers))
- {
- double varCorrelation;
- int nKeys;
+ double varCorrelation;
- Assert(nnumbers == 1);
- varCorrelation = numbers[0];
- nKeys = index->ncolumns;
+ Assert(nnumbers == 1);
+ varCorrelation = numbers[0];
- *indexCorrelation = varCorrelation / nKeys;
+ if (index->ncolumns > 1)
+ *indexCorrelation = varCorrelation * 0.75;
+ else
+ *indexCorrelation = varCorrelation;
- free_attstatsslot(typid, NULL, 0, numbers, nnumbers);
- }
- ReleaseSysCache(tuple);
+ free_attstatsslot(typid, NULL, 0, numbers, nnumbers);
}
+ ReleaseSysCache(tuple);
}
PG_RETURN_VOID();
diff --git a/src/include/optimizer/pathnode.h b/src/include/optimizer/pathnode.h
index 379e2ba7a5e..3186b8d1c1f 100644
--- a/src/include/optimizer/pathnode.h
+++ b/src/include/optimizer/pathnode.h
@@ -7,7 +7,7 @@
* Portions Copyright (c) 1996-2003, PostgreSQL Global Development Group
* Portions Copyright (c) 1994, Regents of the University of California
*
- * $PostgreSQL: pgsql/src/include/optimizer/pathnode.h,v 1.53 2003/11/29 22:41:07 pgsql Exp $
+ * $PostgreSQL: pgsql/src/include/optimizer/pathnode.h,v 1.54 2004/02/17 00:52:53 tgl Exp $
*
*-------------------------------------------------------------------------
*/
@@ -77,6 +77,7 @@ extern HashPath *create_hashjoin_path(Query *root,
extern void build_base_rel(Query *root, int relid);
extern RelOptInfo *build_other_rel(Query *root, int relid);
extern RelOptInfo *find_base_rel(Query *root, int relid);
+extern RelOptInfo *find_join_rel(Query *root, Relids relids);
extern RelOptInfo *build_join_rel(Query *root,
Relids joinrelids,
RelOptInfo *outer_rel,
diff --git a/src/include/utils/selfuncs.h b/src/include/utils/selfuncs.h
index 873af8b9876..797e0a4c700 100644
--- a/src/include/utils/selfuncs.h
+++ b/src/include/utils/selfuncs.h
@@ -8,7 +8,7 @@
* Portions Copyright (c) 1996-2003, PostgreSQL Global Development Group
* Portions Copyright (c) 1994, Regents of the University of California
*
- * $PostgreSQL: pgsql/src/include/utils/selfuncs.h,v 1.16 2003/11/29 22:41:16 pgsql Exp $
+ * $PostgreSQL: pgsql/src/include/utils/selfuncs.h,v 1.17 2004/02/17 00:52:53 tgl Exp $
*
*-------------------------------------------------------------------------
*/
@@ -77,6 +77,9 @@ extern void mergejoinscansel(Query *root, Node *clause,
extern double estimate_num_groups(Query *root, List *groupExprs,
double input_rows);
+extern Selectivity estimate_hash_bucketsize(Query *root, Node *hashkey,
+ int nbuckets);
+
extern Datum btcostestimate(PG_FUNCTION_ARGS);
extern Datum rtcostestimate(PG_FUNCTION_ARGS);
extern Datum hashcostestimate(PG_FUNCTION_ARGS);
--
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