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postgresql/src/backend/statistics/dependencies.c

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/*-------------------------------------------------------------------------
*
* dependencies.c
* POSTGRES functional dependencies
*
* Portions Copyright (c) 1996-2022, PostgreSQL Global Development Group
* Portions Copyright (c) 1994, Regents of the University of California
*
* IDENTIFICATION
* src/backend/statistics/dependencies.c
*
*-------------------------------------------------------------------------
*/
#include "postgres.h"
#include "access/htup_details.h"
#include "access/sysattr.h"
#include "catalog/pg_operator.h"
#include "catalog/pg_statistic_ext.h"
#include "catalog/pg_statistic_ext_data.h"
#include "lib/stringinfo.h"
#include "nodes/nodeFuncs.h"
#include "nodes/nodes.h"
#include "nodes/pathnodes.h"
#include "optimizer/clauses.h"
#include "optimizer/optimizer.h"
#include "parser/parsetree.h"
#include "statistics/extended_stats_internal.h"
#include "statistics/statistics.h"
#include "utils/bytea.h"
#include "utils/fmgroids.h"
#include "utils/fmgrprotos.h"
#include "utils/lsyscache.h"
#include "utils/memutils.h"
#include "utils/selfuncs.h"
#include "utils/syscache.h"
#include "utils/typcache.h"
/* size of the struct header fields (magic, type, ndeps) */
#define SizeOfHeader (3 * sizeof(uint32))
/* size of a serialized dependency (degree, natts, atts) */
#define SizeOfItem(natts) \
(sizeof(double) + sizeof(AttrNumber) * (1 + (natts)))
/* minimal size of a dependency (with two attributes) */
#define MinSizeOfItem SizeOfItem(2)
/* minimal size of dependencies, when all deps are minimal */
#define MinSizeOfItems(ndeps) \
(SizeOfHeader + (ndeps) * MinSizeOfItem)
/*
* Internal state for DependencyGenerator of dependencies. Dependencies are similar to
* k-permutations of n elements, except that the order does not matter for the
* first (k-1) elements. That is, (a,b=>c) and (b,a=>c) are equivalent.
*/
typedef struct DependencyGeneratorData
{
int k; /* size of the dependency */
int n; /* number of possible attributes */
int current; /* next dependency to return (index) */
AttrNumber ndependencies; /* number of dependencies generated */
AttrNumber *dependencies; /* array of pre-generated dependencies */
} DependencyGeneratorData;
typedef DependencyGeneratorData *DependencyGenerator;
static void generate_dependencies_recurse(DependencyGenerator state,
int index, AttrNumber start, AttrNumber *current);
static void generate_dependencies(DependencyGenerator state);
static DependencyGenerator DependencyGenerator_init(int n, int k);
static void DependencyGenerator_free(DependencyGenerator state);
static AttrNumber *DependencyGenerator_next(DependencyGenerator state);
static double dependency_degree(StatsBuildData *data, int k, AttrNumber *dependency);
static bool dependency_is_fully_matched(MVDependency *dependency,
Bitmapset *attnums);
static bool dependency_is_compatible_clause(Node *clause, Index relid,
AttrNumber *attnum);
static bool dependency_is_compatible_expression(Node *clause, Index relid,
List *statlist, Node **expr);
static MVDependency *find_strongest_dependency(MVDependencies **dependencies,
int ndependencies, Bitmapset *attnums);
static Selectivity clauselist_apply_dependencies(PlannerInfo *root, List *clauses,
int varRelid, JoinType jointype,
SpecialJoinInfo *sjinfo,
MVDependency **dependencies,
int ndependencies,
AttrNumber *list_attnums,
Bitmapset **estimatedclauses);
static void
generate_dependencies_recurse(DependencyGenerator state, int index,
AttrNumber start, AttrNumber *current)
{
/*
* The generator handles the first (k-1) elements differently from the
* last element.
*/
if (index < (state->k - 1))
{
AttrNumber i;
/*
* The first (k-1) values have to be in ascending order, which we
* generate recursively.
*/
for (i = start; i < state->n; i++)
{
current[index] = i;
generate_dependencies_recurse(state, (index + 1), (i + 1), current);
}
}
else
{
int i;
/*
* the last element is the implied value, which does not respect the
* ascending order. We just need to check that the value is not in the
* first (k-1) elements.
*/
for (i = 0; i < state->n; i++)
{
int j;
bool match = false;
current[index] = i;
for (j = 0; j < index; j++)
{
if (current[j] == i)
{
match = true;
break;
}
}
/*
* If the value is not found in the first part of the dependency,
* we're done.
*/
if (!match)
{
state->dependencies = (AttrNumber *) repalloc(state->dependencies,
state->k * (state->ndependencies + 1) * sizeof(AttrNumber));
memcpy(&state->dependencies[(state->k * state->ndependencies)],
current, state->k * sizeof(AttrNumber));
state->ndependencies++;
}
}
}
}
/* generate all dependencies (k-permutations of n elements) */
static void
generate_dependencies(DependencyGenerator state)
{
AttrNumber *current = (AttrNumber *) palloc0(sizeof(AttrNumber) * state->k);
generate_dependencies_recurse(state, 0, 0, current);
pfree(current);
}
/*
* initialize the DependencyGenerator of variations, and prebuild the variations
*
* This pre-builds all the variations. We could also generate them in
* DependencyGenerator_next(), but this seems simpler.
*/
static DependencyGenerator
DependencyGenerator_init(int n, int k)
{
DependencyGenerator state;
Assert((n >= k) && (k > 0));
/* allocate the DependencyGenerator state */
state = (DependencyGenerator) palloc0(sizeof(DependencyGeneratorData));
state->dependencies = (AttrNumber *) palloc(k * sizeof(AttrNumber));
state->ndependencies = 0;
state->current = 0;
state->k = k;
state->n = n;
/* now actually pre-generate all the variations */
generate_dependencies(state);
return state;
}
/* free the DependencyGenerator state */
static void
DependencyGenerator_free(DependencyGenerator state)
{
pfree(state->dependencies);
pfree(state);
}
/* generate next combination */
static AttrNumber *
DependencyGenerator_next(DependencyGenerator state)
{
if (state->current == state->ndependencies)
return NULL;
return &state->dependencies[state->k * state->current++];
}
/*
* validates functional dependency on the data
*
* An actual work horse of detecting functional dependencies. Given a variation
* of k attributes, it checks that the first (k-1) are sufficient to determine
* the last one.
*/
static double
dependency_degree(StatsBuildData *data, int k, AttrNumber *dependency)
{
int i,
nitems;
MultiSortSupport mss;
SortItem *items;
AttrNumber *attnums_dep;
/* counters valid within a group */
int group_size = 0;
int n_violations = 0;
/* total number of rows supporting (consistent with) the dependency */
int n_supporting_rows = 0;
/* Make sure we have at least two input attributes. */
Assert(k >= 2);
/* sort info for all attributes columns */
mss = multi_sort_init(k);
/*
* Translate the array of indexes to regular attnums for the dependency
* (we will need this to identify the columns in StatsBuildData).
*/
attnums_dep = (AttrNumber *) palloc(k * sizeof(AttrNumber));
for (i = 0; i < k; i++)
attnums_dep[i] = data->attnums[dependency[i]];
/*
* Verify the dependency (a,b,...)->z, using a rather simple algorithm:
*
* (a) sort the data lexicographically
*
* (b) split the data into groups by first (k-1) columns
*
* (c) for each group count different values in the last column
*
* We use the column data types' default sort operators and collations;
* perhaps at some point it'd be worth using column-specific collations?
*/
/* prepare the sort function for the dimensions */
for (i = 0; i < k; i++)
{
VacAttrStats *colstat = data->stats[dependency[i]];
TypeCacheEntry *type;
type = lookup_type_cache(colstat->attrtypid, TYPECACHE_LT_OPR);
if (type->lt_opr == InvalidOid) /* shouldn't happen */
elog(ERROR, "cache lookup failed for ordering operator for type %u",
colstat->attrtypid);
/* prepare the sort function for this dimension */
multi_sort_add_dimension(mss, i, type->lt_opr, colstat->attrcollid);
}
/*
* build an array of SortItem(s) sorted using the multi-sort support
*
* XXX This relies on all stats entries pointing to the same tuple
* descriptor. For now that assumption holds, but it might change in the
* future for example if we support statistics on multiple tables.
*/
items = build_sorted_items(data, &nitems, mss, k, attnums_dep);
/*
* Walk through the sorted array, split it into rows according to the
* first (k-1) columns. If there's a single value in the last column, we
* count the group as 'supporting' the functional dependency. Otherwise we
* count it as contradicting.
*/
/* start with the first row forming a group */
group_size = 1;
/* loop 1 beyond the end of the array so that we count the final group */
for (i = 1; i <= nitems; i++)
{
/*
* Check if the group ended, which may be either because we processed
* all the items (i==nitems), or because the i-th item is not equal to
* the preceding one.
*/
if (i == nitems ||
multi_sort_compare_dims(0, k - 2, &items[i - 1], &items[i], mss) != 0)
{
/*
* If no violations were found in the group then track the rows of
* the group as supporting the functional dependency.
*/
if (n_violations == 0)
n_supporting_rows += group_size;
/* Reset counters for the new group */
n_violations = 0;
group_size = 1;
continue;
}
/* first columns match, but the last one does not (so contradicting) */
else if (multi_sort_compare_dim(k - 1, &items[i - 1], &items[i], mss) != 0)
n_violations++;
group_size++;
}
/* Compute the 'degree of validity' as (supporting/total). */
return (n_supporting_rows * 1.0 / data->numrows);
}
/*
* detects functional dependencies between groups of columns
*
* Generates all possible subsets of columns (variations) and computes
* the degree of validity for each one. For example when creating statistics
* on three columns (a,b,c) there are 9 possible dependencies
*
* two columns three columns
* ----------- -------------
* (a) -> b (a,b) -> c
* (a) -> c (a,c) -> b
* (b) -> a (b,c) -> a
* (b) -> c
* (c) -> a
* (c) -> b
*/
MVDependencies *
statext_dependencies_build(StatsBuildData *data)
{
int i,
k;
/* result */
MVDependencies *dependencies = NULL;
MemoryContext cxt;
Assert(data->nattnums >= 2);
/* tracks memory allocated by dependency_degree calls */
cxt = AllocSetContextCreate(CurrentMemoryContext,
"dependency_degree cxt",
ALLOCSET_DEFAULT_SIZES);
/*
* We'll try build functional dependencies starting from the smallest ones
* covering just 2 columns, to the largest ones, covering all columns
* included in the statistics object. We start from the smallest ones
* because we want to be able to skip already implied ones.
*/
for (k = 2; k <= data->nattnums; k++)
{
AttrNumber *dependency; /* array with k elements */
/* prepare a DependencyGenerator of variation */
DependencyGenerator DependencyGenerator = DependencyGenerator_init(data->nattnums, k);
/* generate all possible variations of k values (out of n) */
while ((dependency = DependencyGenerator_next(DependencyGenerator)))
{
double degree;
MVDependency *d;
MemoryContext oldcxt;
/* release memory used by dependency degree calculation */
oldcxt = MemoryContextSwitchTo(cxt);
/* compute how valid the dependency seems */
degree = dependency_degree(data, k, dependency);
MemoryContextSwitchTo(oldcxt);
MemoryContextReset(cxt);
/*
* if the dependency seems entirely invalid, don't store it
*/
if (degree == 0.0)
continue;
d = (MVDependency *) palloc0(offsetof(MVDependency, attributes)
+ k * sizeof(AttrNumber));
/* copy the dependency (and keep the indexes into stxkeys) */
d->degree = degree;
d->nattributes = k;
for (i = 0; i < k; i++)
d->attributes[i] = data->attnums[dependency[i]];
/* initialize the list of dependencies */
if (dependencies == NULL)
{
dependencies
= (MVDependencies *) palloc0(sizeof(MVDependencies));
dependencies->magic = STATS_DEPS_MAGIC;
dependencies->type = STATS_DEPS_TYPE_BASIC;
dependencies->ndeps = 0;
}
dependencies->ndeps++;
dependencies = (MVDependencies *) repalloc(dependencies,
offsetof(MVDependencies, deps)
+ dependencies->ndeps * sizeof(MVDependency *));
dependencies->deps[dependencies->ndeps - 1] = d;
}
/*
* we're done with variations of k elements, so free the
* DependencyGenerator
*/
DependencyGenerator_free(DependencyGenerator);
}
MemoryContextDelete(cxt);
return dependencies;
}
/*
* Serialize list of dependencies into a bytea value.
*/
bytea *
statext_dependencies_serialize(MVDependencies *dependencies)
{
int i;
bytea *output;
char *tmp;
Size len;
/* we need to store ndeps, with a number of attributes for each one */
len = VARHDRSZ + SizeOfHeader;
/* and also include space for the actual attribute numbers and degrees */
for (i = 0; i < dependencies->ndeps; i++)
len += SizeOfItem(dependencies->deps[i]->nattributes);
output = (bytea *) palloc0(len);
SET_VARSIZE(output, len);
tmp = VARDATA(output);
/* Store the base struct values (magic, type, ndeps) */
memcpy(tmp, &dependencies->magic, sizeof(uint32));
tmp += sizeof(uint32);
memcpy(tmp, &dependencies->type, sizeof(uint32));
tmp += sizeof(uint32);
memcpy(tmp, &dependencies->ndeps, sizeof(uint32));
tmp += sizeof(uint32);
/* store number of attributes and attribute numbers for each dependency */
for (i = 0; i < dependencies->ndeps; i++)
{
MVDependency *d = dependencies->deps[i];
memcpy(tmp, &d->degree, sizeof(double));
tmp += sizeof(double);
memcpy(tmp, &d->nattributes, sizeof(AttrNumber));
tmp += sizeof(AttrNumber);
memcpy(tmp, d->attributes, sizeof(AttrNumber) * d->nattributes);
tmp += sizeof(AttrNumber) * d->nattributes;
/* protect against overflow */
Assert(tmp <= ((char *) output + len));
}
/* make sure we've produced exactly the right amount of data */
Assert(tmp == ((char *) output + len));
return output;
}
/*
* Reads serialized dependencies into MVDependencies structure.
*/
MVDependencies *
statext_dependencies_deserialize(bytea *data)
{
int i;
Size min_expected_size;
MVDependencies *dependencies;
char *tmp;
if (data == NULL)
return NULL;
if (VARSIZE_ANY_EXHDR(data) < SizeOfHeader)
elog(ERROR, "invalid MVDependencies size %zd (expected at least %zd)",
VARSIZE_ANY_EXHDR(data), SizeOfHeader);
/* read the MVDependencies header */
dependencies = (MVDependencies *) palloc0(sizeof(MVDependencies));
/* initialize pointer to the data part (skip the varlena header) */
tmp = VARDATA_ANY(data);
/* read the header fields and perform basic sanity checks */
memcpy(&dependencies->magic, tmp, sizeof(uint32));
tmp += sizeof(uint32);
memcpy(&dependencies->type, tmp, sizeof(uint32));
tmp += sizeof(uint32);
memcpy(&dependencies->ndeps, tmp, sizeof(uint32));
tmp += sizeof(uint32);
if (dependencies->magic != STATS_DEPS_MAGIC)
elog(ERROR, "invalid dependency magic %d (expected %d)",
dependencies->magic, STATS_DEPS_MAGIC);
if (dependencies->type != STATS_DEPS_TYPE_BASIC)
elog(ERROR, "invalid dependency type %d (expected %d)",
dependencies->type, STATS_DEPS_TYPE_BASIC);
if (dependencies->ndeps == 0)
elog(ERROR, "invalid zero-length item array in MVDependencies");
/* what minimum bytea size do we expect for those parameters */
min_expected_size = SizeOfItem(dependencies->ndeps);
if (VARSIZE_ANY_EXHDR(data) < min_expected_size)
elog(ERROR, "invalid dependencies size %zd (expected at least %zd)",
VARSIZE_ANY_EXHDR(data), min_expected_size);
/* allocate space for the MCV items */
dependencies = repalloc(dependencies, offsetof(MVDependencies, deps)
+ (dependencies->ndeps * sizeof(MVDependency *)));
for (i = 0; i < dependencies->ndeps; i++)
{
double degree;
AttrNumber k;
MVDependency *d;
/* degree of validity */
memcpy(&degree, tmp, sizeof(double));
tmp += sizeof(double);
/* number of attributes */
memcpy(&k, tmp, sizeof(AttrNumber));
tmp += sizeof(AttrNumber);
/* is the number of attributes valid? */
Assert((k >= 2) && (k <= STATS_MAX_DIMENSIONS));
/* now that we know the number of attributes, allocate the dependency */
d = (MVDependency *) palloc0(offsetof(MVDependency, attributes)
+ (k * sizeof(AttrNumber)));
d->degree = degree;
d->nattributes = k;
/* copy attribute numbers */
memcpy(d->attributes, tmp, sizeof(AttrNumber) * d->nattributes);
tmp += sizeof(AttrNumber) * d->nattributes;
dependencies->deps[i] = d;
/* still within the bytea */
Assert(tmp <= ((char *) data + VARSIZE_ANY(data)));
}
/* we should have consumed the whole bytea exactly */
Assert(tmp == ((char *) data + VARSIZE_ANY(data)));
return dependencies;
}
/*
* dependency_is_fully_matched
* checks that a functional dependency is fully matched given clauses on
* attributes (assuming the clauses are suitable equality clauses)
*/
static bool
dependency_is_fully_matched(MVDependency *dependency, Bitmapset *attnums)
{
int j;
/*
* Check that the dependency actually is fully covered by clauses. We have
* to translate all attribute numbers, as those are referenced
*/
for (j = 0; j < dependency->nattributes; j++)
{
int attnum = dependency->attributes[j];
if (!bms_is_member(attnum, attnums))
return false;
}
return true;
}
/*
* statext_dependencies_load
* Load the functional dependencies for the indicated pg_statistic_ext tuple
*/
MVDependencies *
statext_dependencies_load(Oid mvoid, bool inh)
{
MVDependencies *result;
bool isnull;
Datum deps;
HeapTuple htup;
htup = SearchSysCache2(STATEXTDATASTXOID,
ObjectIdGetDatum(mvoid),
BoolGetDatum(inh));
if (!HeapTupleIsValid(htup))
elog(ERROR, "cache lookup failed for statistics object %u", mvoid);
deps = SysCacheGetAttr(STATEXTDATASTXOID, htup,
Anum_pg_statistic_ext_data_stxddependencies, &isnull);
if (isnull)
elog(ERROR,
"requested statistics kind \"%c\" is not yet built for statistics object %u",
STATS_EXT_DEPENDENCIES, mvoid);
result = statext_dependencies_deserialize(DatumGetByteaPP(deps));
ReleaseSysCache(htup);
return result;
}
/*
* pg_dependencies_in - input routine for type pg_dependencies.
*
* pg_dependencies is real enough to be a table column, but it has no operations
* of its own, and disallows input too
*/
Datum
pg_dependencies_in(PG_FUNCTION_ARGS)
{
/*
* pg_node_list stores the data in binary form and parsing text input is
* not needed, so disallow this.
*/
ereport(ERROR,
(errcode(ERRCODE_FEATURE_NOT_SUPPORTED),
errmsg("cannot accept a value of type %s", "pg_dependencies")));
PG_RETURN_VOID(); /* keep compiler quiet */
}
/*
* pg_dependencies - output routine for type pg_dependencies.
*/
Datum
pg_dependencies_out(PG_FUNCTION_ARGS)
{
bytea *data = PG_GETARG_BYTEA_PP(0);
MVDependencies *dependencies = statext_dependencies_deserialize(data);
int i,
j;
StringInfoData str;
initStringInfo(&str);
appendStringInfoChar(&str, '{');
for (i = 0; i < dependencies->ndeps; i++)
{
MVDependency *dependency = dependencies->deps[i];
if (i > 0)
appendStringInfoString(&str, ", ");
appendStringInfoChar(&str, '"');
for (j = 0; j < dependency->nattributes; j++)
{
if (j == dependency->nattributes - 1)
appendStringInfoString(&str, " => ");
else if (j > 0)
appendStringInfoString(&str, ", ");
appendStringInfo(&str, "%d", dependency->attributes[j]);
}
appendStringInfo(&str, "\": %f", dependency->degree);
}
appendStringInfoChar(&str, '}');
PG_RETURN_CSTRING(str.data);
}
/*
* pg_dependencies_recv - binary input routine for type pg_dependencies.
*/
Datum
pg_dependencies_recv(PG_FUNCTION_ARGS)
{
ereport(ERROR,
(errcode(ERRCODE_FEATURE_NOT_SUPPORTED),
errmsg("cannot accept a value of type %s", "pg_dependencies")));
PG_RETURN_VOID(); /* keep compiler quiet */
}
/*
* pg_dependencies_send - binary output routine for type pg_dependencies.
*
* Functional dependencies are serialized in a bytea value (although the type
* is named differently), so let's just send that.
*/
Datum
pg_dependencies_send(PG_FUNCTION_ARGS)
{
return byteasend(fcinfo);
}
/*
* dependency_is_compatible_clause
* Determines if the clause is compatible with functional dependencies
*
* Only clauses that have the form of equality to a pseudoconstant, or can be
* interpreted that way, are currently accepted. Furthermore the variable
* part of the clause must be a simple Var belonging to the specified
* relation, whose attribute number we return in *attnum on success.
*/
static bool
dependency_is_compatible_clause(Node *clause, Index relid, AttrNumber *attnum)
{
Var *var;
Node *clause_expr;
if (IsA(clause, RestrictInfo))
{
RestrictInfo *rinfo = (RestrictInfo *) clause;
/* Pseudoconstants are not interesting (they couldn't contain a Var) */
if (rinfo->pseudoconstant)
return false;
/* Clauses referencing multiple, or no, varnos are incompatible */
if (bms_membership(rinfo->clause_relids) != BMS_SINGLETON)
return false;
clause = (Node *) rinfo->clause;
}
if (is_opclause(clause))
{
/* If it's an opclause, check for Var = Const or Const = Var. */
OpExpr *expr = (OpExpr *) clause;
/* Only expressions with two arguments are candidates. */
if (list_length(expr->args) != 2)
return false;
/* Make sure non-selected argument is a pseudoconstant. */
if (is_pseudo_constant_clause(lsecond(expr->args)))
clause_expr = linitial(expr->args);
else if (is_pseudo_constant_clause(linitial(expr->args)))
clause_expr = lsecond(expr->args);
else
return false;
/*
* If it's not an "=" operator, just ignore the clause, as it's not
* compatible with functional dependencies.
*
* This uses the function for estimating selectivity, not the operator
* directly (a bit awkward, but well ...).
*
* XXX this is pretty dubious; probably it'd be better to check btree
* or hash opclass membership, so as not to be fooled by custom
* selectivity functions, and to be more consistent with decisions
* elsewhere in the planner.
*/
if (get_oprrest(expr->opno) != F_EQSEL)
return false;
/* OK to proceed with checking "var" */
}
else if (IsA(clause, ScalarArrayOpExpr))
{
/* If it's an scalar array operator, check for Var IN Const. */
ScalarArrayOpExpr *expr = (ScalarArrayOpExpr *) clause;
/*
* Reject ALL() variant, we only care about ANY/IN.
*
* XXX Maybe we should check if all the values are the same, and allow
* ALL in that case? Doesn't seem very practical, though.
*/
if (!expr->useOr)
return false;
/* Only expressions with two arguments are candidates. */
if (list_length(expr->args) != 2)
return false;
/*
* We know it's always (Var IN Const), so we assume the var is the
* first argument, and pseudoconstant is the second one.
*/
if (!is_pseudo_constant_clause(lsecond(expr->args)))
return false;
clause_expr = linitial(expr->args);
/*
* If it's not an "=" operator, just ignore the clause, as it's not
* compatible with functional dependencies. The operator is identified
* simply by looking at which function it uses to estimate
* selectivity. That's a bit strange, but it's what other similar
* places do.
*/
if (get_oprrest(expr->opno) != F_EQSEL)
return false;
/* OK to proceed with checking "var" */
}
else if (is_orclause(clause))
{
BoolExpr *bool_expr = (BoolExpr *) clause;
ListCell *lc;
/* start with no attribute number */
*attnum = InvalidAttrNumber;
foreach(lc, bool_expr->args)
{
AttrNumber clause_attnum;
/*
* Had we found incompatible clause in the arguments, treat the
* whole clause as incompatible.
*/
if (!dependency_is_compatible_clause((Node *) lfirst(lc),
relid, &clause_attnum))
return false;
if (*attnum == InvalidAttrNumber)
*attnum = clause_attnum;
/* ensure all the variables are the same (same attnum) */
if (*attnum != clause_attnum)
return false;
}
/* the Var is already checked by the recursive call */
return true;
}
else if (is_notclause(clause))
{
/*
* "NOT x" can be interpreted as "x = false", so get the argument and
* proceed with seeing if it's a suitable Var.
*/
clause_expr = (Node *) get_notclausearg(clause);
}
else
{
/*
* A boolean expression "x" can be interpreted as "x = true", so
* proceed with seeing if it's a suitable Var.
*/
clause_expr = (Node *) clause;
}
/*
* We may ignore any RelabelType node above the operand. (There won't be
* more than one, since eval_const_expressions has been applied already.)
*/
if (IsA(clause_expr, RelabelType))
clause_expr = (Node *) ((RelabelType *) clause_expr)->arg;
/* We only support plain Vars for now */
if (!IsA(clause_expr, Var))
return false;
/* OK, we know we have a Var */
var = (Var *) clause_expr;
/* Ensure Var is from the correct relation */
if (var->varno != relid)
return false;
/* We also better ensure the Var is from the current level */
if (var->varlevelsup != 0)
return false;
/* Also ignore system attributes (we don't allow stats on those) */
if (!AttrNumberIsForUserDefinedAttr(var->varattno))
return false;
*attnum = var->varattno;
return true;
}
/*
* find_strongest_dependency
* find the strongest dependency on the attributes
*
* When applying functional dependencies, we start with the strongest
* dependencies. That is, we select the dependency that:
*
* (a) has all attributes covered by equality clauses
*
* (b) has the most attributes
*
* (c) has the highest degree of validity
*
* This guarantees that we eliminate the most redundant conditions first
* (see the comment in dependencies_clauselist_selectivity).
*/
static MVDependency *
find_strongest_dependency(MVDependencies **dependencies, int ndependencies,
Bitmapset *attnums)
{
int i,
j;
MVDependency *strongest = NULL;
/* number of attnums in clauses */
int nattnums = bms_num_members(attnums);
/*
* Iterate over the MVDependency items and find the strongest one from the
* fully-matched dependencies. We do the cheap checks first, before
* matching it against the attnums.
*/
for (i = 0; i < ndependencies; i++)
{
for (j = 0; j < dependencies[i]->ndeps; j++)
{
MVDependency *dependency = dependencies[i]->deps[j];
/*
* Skip dependencies referencing more attributes than available
* clauses, as those can't be fully matched.
*/
if (dependency->nattributes > nattnums)
continue;
if (strongest)
{
/* skip dependencies on fewer attributes than the strongest. */
if (dependency->nattributes < strongest->nattributes)
continue;
/* also skip weaker dependencies when attribute count matches */
if (strongest->nattributes == dependency->nattributes &&
strongest->degree > dependency->degree)
continue;
}
/*
* this dependency is stronger, but we must still check that it's
* fully matched to these attnums. We perform this check last as
* it's slightly more expensive than the previous checks.
*/
if (dependency_is_fully_matched(dependency, attnums))
strongest = dependency; /* save new best match */
}
}
return strongest;
}
/*
* clauselist_apply_dependencies
* Apply the specified functional dependencies to a list of clauses and
* return the estimated selectivity of the clauses that are compatible
* with any of the given dependencies.
*
* This will estimate all not-already-estimated clauses that are compatible
* with functional dependencies, and which have an attribute mentioned by any
* of the given dependencies (either as an implying or implied attribute).
*
* Given (lists of) clauses on attributes (a,b) and a functional dependency
* (a=>b), the per-column selectivities P(a) and P(b) are notionally combined
* using the formula
*
* P(a,b) = f * P(a) + (1-f) * P(a) * P(b)
*
* where 'f' is the degree of dependency. This reflects the fact that we
* expect a fraction f of all rows to be consistent with the dependency
* (a=>b), and so have a selectivity of P(a), while the remaining rows are
* treated as independent.
*
* In practice, we use a slightly modified version of this formula, which uses
* a selectivity of Min(P(a), P(b)) for the dependent rows, since the result
* should obviously not exceed either column's individual selectivity. I.e.,
* we actually combine selectivities using the formula
*
* P(a,b) = f * Min(P(a), P(b)) + (1-f) * P(a) * P(b)
*
* This can make quite a difference if the specific values matching the
* clauses are not consistent with the functional dependency.
*/
static Selectivity
clauselist_apply_dependencies(PlannerInfo *root, List *clauses,
int varRelid, JoinType jointype,
SpecialJoinInfo *sjinfo,
MVDependency **dependencies, int ndependencies,
AttrNumber *list_attnums,
Bitmapset **estimatedclauses)
{
Bitmapset *attnums;
int i;
int j;
int nattrs;
Selectivity *attr_sel;
int attidx;
int listidx;
ListCell *l;
Selectivity s1;
/*
* Extract the attnums of all implying and implied attributes from all the
* given dependencies. Each of these attributes is expected to have at
* least 1 not-already-estimated compatible clause that we will estimate
* here.
*/
attnums = NULL;
for (i = 0; i < ndependencies; i++)
{
for (j = 0; j < dependencies[i]->nattributes; j++)
{
AttrNumber attnum = dependencies[i]->attributes[j];
attnums = bms_add_member(attnums, attnum);
}
}
/*
* Compute per-column selectivity estimates for each of these attributes,
* and mark all the corresponding clauses as estimated.
*/
nattrs = bms_num_members(attnums);
attr_sel = (Selectivity *) palloc(sizeof(Selectivity) * nattrs);
attidx = 0;
i = -1;
while ((i = bms_next_member(attnums, i)) >= 0)
{
List *attr_clauses = NIL;
Selectivity simple_sel;
listidx = -1;
foreach(l, clauses)
{
Node *clause = (Node *) lfirst(l);
listidx++;
if (list_attnums[listidx] == i)
{
attr_clauses = lappend(attr_clauses, clause);
*estimatedclauses = bms_add_member(*estimatedclauses, listidx);
}
}
simple_sel = clauselist_selectivity_ext(root, attr_clauses, varRelid,
jointype, sjinfo, false);
attr_sel[attidx++] = simple_sel;
}
/*
* Now combine these selectivities using the dependency information. For
* chains of dependencies such as a -> b -> c, the b -> c dependency will
* come before the a -> b dependency in the array, so we traverse the
* array backwards to ensure such chains are computed in the right order.
*
* As explained above, pairs of selectivities are combined using the
* formula
*
* P(a,b) = f * Min(P(a), P(b)) + (1-f) * P(a) * P(b)
*
* to ensure that the combined selectivity is never greater than either
* individual selectivity.
*
* Where multiple dependencies apply (e.g., a -> b -> c), we use
* conditional probabilities to compute the overall result as follows:
*
* P(a,b,c) = P(c|a,b) * P(a,b) = P(c|a,b) * P(b|a) * P(a)
*
* so we replace the selectivities of all implied attributes with
* conditional probabilities, that are conditional on all their implying
* attributes. The selectivities of all other non-implied attributes are
* left as they are.
*/
for (i = ndependencies - 1; i >= 0; i--)
{
MVDependency *dependency = dependencies[i];
AttrNumber attnum;
Selectivity s2;
double f;
/* Selectivity of all the implying attributes */
s1 = 1.0;
for (j = 0; j < dependency->nattributes - 1; j++)
{
attnum = dependency->attributes[j];
attidx = bms_member_index(attnums, attnum);
s1 *= attr_sel[attidx];
}
/* Original selectivity of the implied attribute */
attnum = dependency->attributes[j];
attidx = bms_member_index(attnums, attnum);
s2 = attr_sel[attidx];
/*
* Replace s2 with the conditional probability s2 given s1, computed
* using the formula P(b|a) = P(a,b) / P(a), which simplifies to
*
* P(b|a) = f * Min(P(a), P(b)) / P(a) + (1-f) * P(b)
*
* where P(a) = s1, the selectivity of the implying attributes, and
* P(b) = s2, the selectivity of the implied attribute.
*/
f = dependency->degree;
if (s1 <= s2)
attr_sel[attidx] = f + (1 - f) * s2;
else
attr_sel[attidx] = f * s2 / s1 + (1 - f) * s2;
}
/*
* The overall selectivity of all the clauses on all these attributes is
* then the product of all the original (non-implied) probabilities and
* the new conditional (implied) probabilities.
*/
s1 = 1.0;
for (i = 0; i < nattrs; i++)
s1 *= attr_sel[i];
CLAMP_PROBABILITY(s1);
pfree(attr_sel);
bms_free(attnums);
return s1;
}
/*
* dependency_is_compatible_expression
* Determines if the expression is compatible with functional dependencies
*
* Similar to dependency_is_compatible_clause, but doesn't enforce that the
* expression is a simple Var. OTOH we check that there's at least one
* statistics object matching the expression.
*/
static bool
dependency_is_compatible_expression(Node *clause, Index relid, List *statlist, Node **expr)
{
List *vars;
ListCell *lc,
*lc2;
Node *clause_expr;
if (IsA(clause, RestrictInfo))
{
RestrictInfo *rinfo = (RestrictInfo *) clause;
/* Pseudoconstants are not interesting (they couldn't contain a Var) */
if (rinfo->pseudoconstant)
return false;
/* Clauses referencing multiple, or no, varnos are incompatible */
if (bms_membership(rinfo->clause_relids) != BMS_SINGLETON)
return false;
clause = (Node *) rinfo->clause;
}
if (is_opclause(clause))
{
/* If it's an opclause, check for Var = Const or Const = Var. */
OpExpr *expr = (OpExpr *) clause;
/* Only expressions with two arguments are candidates. */
if (list_length(expr->args) != 2)
return false;
/* Make sure non-selected argument is a pseudoconstant. */
if (is_pseudo_constant_clause(lsecond(expr->args)))
clause_expr = linitial(expr->args);
else if (is_pseudo_constant_clause(linitial(expr->args)))
clause_expr = lsecond(expr->args);
else
return false;
/*
* If it's not an "=" operator, just ignore the clause, as it's not
* compatible with functional dependencies.
*
* This uses the function for estimating selectivity, not the operator
* directly (a bit awkward, but well ...).
*
* XXX this is pretty dubious; probably it'd be better to check btree
* or hash opclass membership, so as not to be fooled by custom
* selectivity functions, and to be more consistent with decisions
* elsewhere in the planner.
*/
if (get_oprrest(expr->opno) != F_EQSEL)
return false;
/* OK to proceed with checking "var" */
}
else if (IsA(clause, ScalarArrayOpExpr))
{
/* If it's an scalar array operator, check for Var IN Const. */
ScalarArrayOpExpr *expr = (ScalarArrayOpExpr *) clause;
/*
* Reject ALL() variant, we only care about ANY/IN.
*
* FIXME Maybe we should check if all the values are the same, and
* allow ALL in that case? Doesn't seem very practical, though.
*/
if (!expr->useOr)
return false;
/* Only expressions with two arguments are candidates. */
if (list_length(expr->args) != 2)
return false;
/*
* We know it's always (Var IN Const), so we assume the var is the
* first argument, and pseudoconstant is the second one.
*/
if (!is_pseudo_constant_clause(lsecond(expr->args)))
return false;
clause_expr = linitial(expr->args);
/*
* If it's not an "=" operator, just ignore the clause, as it's not
* compatible with functional dependencies. The operator is identified
* simply by looking at which function it uses to estimate
* selectivity. That's a bit strange, but it's what other similar
* places do.
*/
if (get_oprrest(expr->opno) != F_EQSEL)
return false;
/* OK to proceed with checking "var" */
}
else if (is_orclause(clause))
{
BoolExpr *bool_expr = (BoolExpr *) clause;
ListCell *lc;
/* start with no expression (we'll use the first match) */
*expr = NULL;
foreach(lc, bool_expr->args)
{
Node *or_expr = NULL;
/*
* Had we found incompatible expression in the arguments, treat
* the whole expression as incompatible.
*/
if (!dependency_is_compatible_expression((Node *) lfirst(lc), relid,
statlist, &or_expr))
return false;
if (*expr == NULL)
*expr = or_expr;
/* ensure all the expressions are the same */
if (!equal(or_expr, *expr))
return false;
}
/* the expression is already checked by the recursive call */
return true;
}
else if (is_notclause(clause))
{
/*
* "NOT x" can be interpreted as "x = false", so get the argument and
* proceed with seeing if it's a suitable Var.
*/
clause_expr = (Node *) get_notclausearg(clause);
}
else
{
/*
* A boolean expression "x" can be interpreted as "x = true", so
* proceed with seeing if it's a suitable Var.
*/
clause_expr = (Node *) clause;
}
/*
* We may ignore any RelabelType node above the operand. (There won't be
* more than one, since eval_const_expressions has been applied already.)
*/
if (IsA(clause_expr, RelabelType))
clause_expr = (Node *) ((RelabelType *) clause_expr)->arg;
vars = pull_var_clause(clause_expr, 0);
foreach(lc, vars)
{
Var *var = (Var *) lfirst(lc);
/* Ensure Var is from the correct relation */
if (var->varno != relid)
return false;
/* We also better ensure the Var is from the current level */
if (var->varlevelsup != 0)
return false;
/* Also ignore system attributes (we don't allow stats on those) */
if (!AttrNumberIsForUserDefinedAttr(var->varattno))
return false;
}
/*
* Check if we actually have a matching statistics for the expression.
*
* XXX Maybe this is an overkill. We'll eliminate the expressions later.
*/
foreach(lc, statlist)
{
StatisticExtInfo *info = (StatisticExtInfo *) lfirst(lc);
/* ignore stats without dependencies */
if (info->kind != STATS_EXT_DEPENDENCIES)
continue;
foreach(lc2, info->exprs)
{
Node *stat_expr = (Node *) lfirst(lc2);
if (equal(clause_expr, stat_expr))
{
*expr = stat_expr;
return true;
}
}
}
return false;
}
/*
* dependencies_clauselist_selectivity
* Return the estimated selectivity of (a subset of) the given clauses
* using functional dependency statistics, or 1.0 if no useful functional
* dependency statistic exists.
*
* 'estimatedclauses' is an input/output argument that gets a bit set
* corresponding to the (zero-based) list index of each clause that is included
* in the estimated selectivity.
*
* Given equality clauses on attributes (a,b) we find the strongest dependency
* between them, i.e. either (a=>b) or (b=>a). Assuming (a=>b) is the selected
* dependency, we then combine the per-clause selectivities using the formula
*
* P(a,b) = f * P(a) + (1-f) * P(a) * P(b)
*
* where 'f' is the degree of the dependency. (Actually we use a slightly
* modified version of this formula -- see clauselist_apply_dependencies()).
*
* With clauses on more than two attributes, the dependencies are applied
* recursively, starting with the widest/strongest dependencies. For example
* P(a,b,c) is first split like this:
*
* P(a,b,c) = f * P(a,b) + (1-f) * P(a,b) * P(c)
*
* assuming (a,b=>c) is the strongest dependency.
*/
Selectivity
dependencies_clauselist_selectivity(PlannerInfo *root,
List *clauses,
int varRelid,
JoinType jointype,
SpecialJoinInfo *sjinfo,
RelOptInfo *rel,
Bitmapset **estimatedclauses)
{
Selectivity s1 = 1.0;
ListCell *l;
Bitmapset *clauses_attnums = NULL;
AttrNumber *list_attnums;
int listidx;
MVDependencies **func_dependencies;
int nfunc_dependencies;
int total_ndeps;
MVDependency **dependencies;
int ndependencies;
int i;
AttrNumber attnum_offset;
RangeTblEntry *rte = planner_rt_fetch(rel->relid, root);
/* unique expressions */
Node **unique_exprs;
int unique_exprs_cnt;
/* check if there's any stats that might be useful for us. */
if (!has_stats_of_kind(rel->statlist, STATS_EXT_DEPENDENCIES))
return 1.0;
list_attnums = (AttrNumber *) palloc(sizeof(AttrNumber) *
list_length(clauses));
/*
* We allocate space as if every clause was a unique expression, although
* that's probably overkill. Some will be simple column references that
* we'll translate to attnums, and there might be duplicates. But it's
* easier and cheaper to just do one allocation than repalloc later.
*/
unique_exprs = (Node **) palloc(sizeof(Node *) * list_length(clauses));
unique_exprs_cnt = 0;
/*
* Pre-process the clauses list to extract the attnums seen in each item.
* We need to determine if there's any clauses which will be useful for
* dependency selectivity estimations. Along the way we'll record all of
* the attnums for each clause in a list which we'll reference later so we
* don't need to repeat the same work again. We'll also keep track of all
* attnums seen.
*
* We also skip clauses that we already estimated using different types of
* statistics (we treat them as incompatible).
*
* To handle expressions, we assign them negative attnums, as if it was a
* system attribute (this is fine, as we only allow extended stats on user
* attributes). And then we offset everything by the number of
* expressions, so that we can store the values in a bitmapset.
*/
listidx = 0;
foreach(l, clauses)
{
Node *clause = (Node *) lfirst(l);
AttrNumber attnum;
Node *expr = NULL;
/* ignore clause by default */
list_attnums[listidx] = InvalidAttrNumber;
if (!bms_is_member(listidx, *estimatedclauses))
{
/*
* If it's a simple column reference, just extract the attnum. If
* it's an expression, assign a negative attnum as if it was a
* system attribute.
*/
if (dependency_is_compatible_clause(clause, rel->relid, &attnum))
{
list_attnums[listidx] = attnum;
}
else if (dependency_is_compatible_expression(clause, rel->relid,
rel->statlist,
&expr))
{
/* special attnum assigned to this expression */
attnum = InvalidAttrNumber;
Assert(expr != NULL);
/* If the expression is duplicate, use the same attnum. */
for (i = 0; i < unique_exprs_cnt; i++)
{
if (equal(unique_exprs[i], expr))
{
/* negative attribute number to expression */
attnum = -(i + 1);
break;
}
}
/* not found in the list, so add it */
if (attnum == InvalidAttrNumber)
{
unique_exprs[unique_exprs_cnt++] = expr;
/* after incrementing the value, to get -1, -2, ... */
attnum = (-unique_exprs_cnt);
}
/* remember which attnum was assigned to this clause */
list_attnums[listidx] = attnum;
}
}
listidx++;
}
Assert(listidx == list_length(clauses));
/*
* How much we need to offset the attnums? If there are no expressions,
* then no offset is needed. Otherwise we need to offset enough for the
* lowest value (-unique_exprs_cnt) to become 1.
*/
if (unique_exprs_cnt > 0)
attnum_offset = (unique_exprs_cnt + 1);
else
attnum_offset = 0;
/*
* Now that we know how many expressions there are, we can offset the
* values just enough to build the bitmapset.
*/
for (i = 0; i < list_length(clauses); i++)
{
AttrNumber attnum;
/* ignore incompatible or already estimated clauses */
if (list_attnums[i] == InvalidAttrNumber)
continue;
/* make sure the attnum is in the expected range */
Assert(list_attnums[i] >= (-unique_exprs_cnt));
Assert(list_attnums[i] <= MaxHeapAttributeNumber);
/* make sure the attnum is positive (valid AttrNumber) */
attnum = list_attnums[i] + attnum_offset;
/*
* Either it's a regular attribute, or it's an expression, in which
* case we must not have seen it before (expressions are unique).
*
* XXX Check whether it's a regular attribute has to be done using the
* original attnum, while the second check has to use the value with
* an offset.
*/
Assert(AttrNumberIsForUserDefinedAttr(list_attnums[i]) ||
!bms_is_member(attnum, clauses_attnums));
/*
* Remember the offset attnum, both for attributes and expressions.
* We'll pass list_attnums to clauselist_apply_dependencies, which
* uses it to identify clauses in a bitmap. We could also pass the
* offset, but this is more convenient.
*/
list_attnums[i] = attnum;
clauses_attnums = bms_add_member(clauses_attnums, attnum);
}
/*
* If there's not at least two distinct attnums and expressions, then
* reject the whole list of clauses. We must return 1.0 so the calling
* function's selectivity is unaffected.
*/
if (bms_membership(clauses_attnums) != BMS_MULTIPLE)
{
bms_free(clauses_attnums);
pfree(list_attnums);
return 1.0;
}
/*
* Load all functional dependencies matching at least two parameters. We
* can simply consider all dependencies at once, without having to search
* for the best statistics object.
*
* To not waste cycles and memory, we deserialize dependencies only for
* statistics that match at least two attributes. The array is allocated
* with the assumption that all objects match - we could grow the array to
* make it just the right size, but it's likely wasteful anyway thanks to
* moving the freed chunks to freelists etc.
*/
func_dependencies = (MVDependencies **) palloc(sizeof(MVDependencies *) *
list_length(rel->statlist));
nfunc_dependencies = 0;
total_ndeps = 0;
foreach(l, rel->statlist)
{
StatisticExtInfo *stat = (StatisticExtInfo *) lfirst(l);
int nmatched;
int nexprs;
int k;
MVDependencies *deps;
/* skip statistics that are not of the correct type */
if (stat->kind != STATS_EXT_DEPENDENCIES)
continue;
/* skip statistics with mismatching stxdinherit value */
if (stat->inherit != rte->inh)
continue;
/*
* Count matching attributes - we have to undo the attnum offsets. The
* input attribute numbers are not offset (expressions are not
* included in stat->keys, so it's not necessary). But we need to
* offset it before checking against clauses_attnums.
*/
nmatched = 0;
k = -1;
while ((k = bms_next_member(stat->keys, k)) >= 0)
{
AttrNumber attnum = (AttrNumber) k;
/* skip expressions */
if (!AttrNumberIsForUserDefinedAttr(attnum))
continue;
/* apply the same offset as above */
attnum += attnum_offset;
if (bms_is_member(attnum, clauses_attnums))
nmatched++;
}
/* count matching expressions */
nexprs = 0;
for (i = 0; i < unique_exprs_cnt; i++)
{
ListCell *lc;
foreach(lc, stat->exprs)
{
Node *stat_expr = (Node *) lfirst(lc);
/* try to match it */
if (equal(stat_expr, unique_exprs[i]))
nexprs++;
}
}
/*
* Skip objects matching fewer than two attributes/expressions from
* clauses.
*/
if (nmatched + nexprs < 2)
continue;
deps = statext_dependencies_load(stat->statOid, rte->inh);
/*
* The expressions may be represented by different attnums in the
* stats, we need to remap them to be consistent with the clauses.
* That will make the later steps (e.g. picking the strongest item and
* so on) much simpler and cheaper, because it won't need to care
* about the offset at all.
*
* When we're at it, we can ignore dependencies that are not fully
* matched by clauses (i.e. referencing attributes or expressions that
* are not in the clauses).
*
* We have to do this for all statistics, as long as there are any
* expressions - we need to shift the attnums in all dependencies.
*
* XXX Maybe we should do this always, because it also eliminates some
* of the dependencies early. It might be cheaper than having to walk
* the longer list in find_strongest_dependency later, especially as
* we need to do that repeatedly?
*
* XXX We have to do this even when there are no expressions in
* clauses, otherwise find_strongest_dependency may fail for stats
* with expressions (due to lookup of negative value in bitmap). So we
* need to at least filter out those dependencies. Maybe we could do
* it in a cheaper way (if there are no expr clauses, we can just
* discard all negative attnums without any lookups).
*/
if (unique_exprs_cnt > 0 || stat->exprs != NIL)
{
int ndeps = 0;
for (i = 0; i < deps->ndeps; i++)
{
bool skip = false;
MVDependency *dep = deps->deps[i];
int j;
for (j = 0; j < dep->nattributes; j++)
{
int idx;
Node *expr;
int k;
AttrNumber unique_attnum = InvalidAttrNumber;
AttrNumber attnum;
/* undo the per-statistics offset */
attnum = dep->attributes[j];
/*
* For regular attributes we can simply check if it
* matches any clause. If there's no matching clause, we
* can just ignore it. We need to offset the attnum
* though.
*/
if (AttrNumberIsForUserDefinedAttr(attnum))
{
dep->attributes[j] = attnum + attnum_offset;
if (!bms_is_member(dep->attributes[j], clauses_attnums))
{
skip = true;
break;
}
continue;
}
/*
* the attnum should be a valid system attnum (-1, -2,
* ...)
*/
Assert(AttributeNumberIsValid(attnum));
/*
* For expressions, we need to do two translations. First
* we have to translate the negative attnum to index in
* the list of expressions (in the statistics object).
* Then we need to see if there's a matching clause. The
* index of the unique expression determines the attnum
* (and we offset it).
*/
idx = -(1 + attnum);
/* Is the expression index is valid? */
Assert((idx >= 0) && (idx < list_length(stat->exprs)));
expr = (Node *) list_nth(stat->exprs, idx);
/* try to find the expression in the unique list */
for (k = 0; k < unique_exprs_cnt; k++)
{
/*
* found a matching unique expression, use the attnum
* (derived from index of the unique expression)
*/
if (equal(unique_exprs[k], expr))
{
unique_attnum = -(k + 1) + attnum_offset;
break;
}
}
/*
* Found no matching expression, so we can simply skip
* this dependency, because there's no chance it will be
* fully covered.
*/
if (unique_attnum == InvalidAttrNumber)
{
skip = true;
break;
}
/* otherwise remap it to the new attnum */
dep->attributes[j] = unique_attnum;
}
/* if found a matching dependency, keep it */
if (!skip)
{
/* maybe we've skipped something earlier, so move it */
if (ndeps != i)
deps->deps[ndeps] = deps->deps[i];
ndeps++;
}
}
deps->ndeps = ndeps;
}
/*
* It's possible we've removed all dependencies, in which case we
* don't bother adding it to the list.
*/
if (deps->ndeps > 0)
{
func_dependencies[nfunc_dependencies] = deps;
total_ndeps += deps->ndeps;
nfunc_dependencies++;
}
}
/* if no matching stats could be found then we've nothing to do */
if (nfunc_dependencies == 0)
{
pfree(func_dependencies);
bms_free(clauses_attnums);
pfree(list_attnums);
pfree(unique_exprs);
return 1.0;
}
/*
* Work out which dependencies we can apply, starting with the
* widest/strongest ones, and proceeding to smaller/weaker ones.
*/
dependencies = (MVDependency **) palloc(sizeof(MVDependency *) *
total_ndeps);
ndependencies = 0;
while (true)
{
MVDependency *dependency;
AttrNumber attnum;
/* the widest/strongest dependency, fully matched by clauses */
dependency = find_strongest_dependency(func_dependencies,
nfunc_dependencies,
clauses_attnums);
if (!dependency)
break;
dependencies[ndependencies++] = dependency;
/* Ignore dependencies using this implied attribute in later loops */
attnum = dependency->attributes[dependency->nattributes - 1];
clauses_attnums = bms_del_member(clauses_attnums, attnum);
}
/*
* If we found applicable dependencies, use them to estimate all
* compatible clauses on attributes that they refer to.
*/
if (ndependencies != 0)
s1 = clauselist_apply_dependencies(root, clauses, varRelid, jointype,
sjinfo, dependencies, ndependencies,
list_attnums, estimatedclauses);
/* free deserialized functional dependencies (and then the array) */
for (i = 0; i < nfunc_dependencies; i++)
pfree(func_dependencies[i]);
pfree(dependencies);
pfree(func_dependencies);
bms_free(clauses_attnums);
pfree(list_attnums);
pfree(unique_exprs);
return s1;
}
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