* Determines and returns the cost of performing an Agg plan node,
* including the cost of its input.
*
+ * aggcosts can be NULL when there are no actual aggregate functions (i.e.,
+ * we are using a hashed Agg node just to do grouping).
+ *
* Note: when aggstrategy == AGG_SORTED, caller must ensure that input costs
* are for appropriately-sorted input.
*/
void
cost_agg(Path *path, PlannerInfo *root,
- AggStrategy aggstrategy, int numAggs,
+ AggStrategy aggstrategy, const AggClauseCosts *aggcosts,
int numGroupCols, double numGroups,
Cost input_startup_cost, Cost input_total_cost,
double input_tuples)
{
Cost startup_cost;
Cost total_cost;
+ AggClauseCosts dummy_aggcosts;
+
+ /* Use all-zero per-aggregate costs if NULL is passed */
+ if (aggcosts == NULL)
+ {
+ Assert(aggstrategy == AGG_HASHED);
+ MemSet(&dummy_aggcosts, 0, sizeof(AggClauseCosts));
+ aggcosts = &dummy_aggcosts;
+ }
/*
- * We charge one cpu_operator_cost per aggregate function per input tuple,
- * and another one per output tuple (corresponding to transfn and finalfn
- * calls respectively). If we are grouping, we charge an additional
- * cpu_operator_cost per grouping column per input tuple for grouping
- * comparisons.
+ * The transCost.per_tuple component of aggcosts should be charged once
+ * per input tuple, corresponding to the costs of evaluating the aggregate
+ * transfns and their input expressions (with any startup cost of course
+ * charged but once). The finalCost component is charged once per output
+ * tuple, corresponding to the costs of evaluating the finalfns.
+ *
+ * If we are grouping, we charge an additional cpu_operator_cost per
+ * grouping column per input tuple for grouping comparisons.
*
* We will produce a single output tuple if not grouping, and a tuple per
* group otherwise. We charge cpu_tuple_cost for each output tuple.
* there's roundoff error we might do the wrong thing. So be sure that
* the computations below form the same intermediate values in the same
* order.
- *
- * Note: ideally we should use the pg_proc.procost costs of each
- * aggregate's component functions, but for now that seems like an
- * excessive amount of work.
*/
if (aggstrategy == AGG_PLAIN)
{
startup_cost = input_total_cost;
- startup_cost += cpu_operator_cost * (input_tuples + 1) * numAggs;
+ startup_cost += aggcosts->transCost.startup;
+ startup_cost += aggcosts->transCost.per_tuple * input_tuples;
+ startup_cost += aggcosts->finalCost;
/* we aren't grouping */
total_cost = startup_cost + cpu_tuple_cost;
}
startup_cost = input_startup_cost;
total_cost = input_total_cost;
/* calcs phrased this way to match HASHED case, see note above */
- total_cost += cpu_operator_cost * input_tuples * numGroupCols;
- total_cost += cpu_operator_cost * input_tuples * numAggs;
- total_cost += cpu_operator_cost * numGroups * numAggs;
+ total_cost += aggcosts->transCost.startup;
+ total_cost += aggcosts->transCost.per_tuple * input_tuples;
+ total_cost += (cpu_operator_cost * numGroupCols) * input_tuples;
+ total_cost += aggcosts->finalCost * numGroups;
total_cost += cpu_tuple_cost * numGroups;
}
else
{
/* must be AGG_HASHED */
startup_cost = input_total_cost;
- startup_cost += cpu_operator_cost * input_tuples * numGroupCols;
- startup_cost += cpu_operator_cost * input_tuples * numAggs;
+ startup_cost += aggcosts->transCost.startup;
+ startup_cost += aggcosts->transCost.per_tuple * input_tuples;
+ startup_cost += (cpu_operator_cost * numGroupCols) * input_tuples;
total_cost = startup_cost;
- total_cost += cpu_operator_cost * numGroups * numAggs;
+ total_cost += aggcosts->finalCost * numGroups;
total_cost += cpu_tuple_cost * numGroups;
}
*/
void
cost_windowagg(Path *path, PlannerInfo *root,
- int numWindowFuncs, int numPartCols, int numOrderCols,
+ List *windowFuncs, int numPartCols, int numOrderCols,
Cost input_startup_cost, Cost input_total_cost,
double input_tuples)
{
Cost startup_cost;
Cost total_cost;
+ ListCell *lc;
startup_cost = input_startup_cost;
total_cost = input_total_cost;
/*
- * We charge one cpu_operator_cost per window function per tuple (often a
- * drastic underestimate, but without a way to gauge how many tuples the
- * window function will fetch, it's hard to do better). We also charge
- * cpu_operator_cost per grouping column per tuple for grouping
- * comparisons, plus cpu_tuple_cost per tuple for general overhead.
- */
- total_cost += cpu_operator_cost * input_tuples * numWindowFuncs;
- total_cost += cpu_operator_cost * input_tuples * (numPartCols + numOrderCols);
+ * Window functions are assumed to cost their stated execution cost, plus
+ * the cost of evaluating their input expressions, per tuple. Since they
+ * may in fact evaluate their inputs at multiple rows during each cycle,
+ * this could be a drastic underestimate; but without a way to know how
+ * many rows the window function will fetch, it's hard to do better. In
+ * any case, it's a good estimate for all the built-in window functions,
+ * so we'll just do this for now.
+ */
+ foreach(lc, windowFuncs)
+ {
+ WindowFunc *wfunc = (WindowFunc *) lfirst(lc);
+ Cost wfunccost;
+ QualCost argcosts;
+
+ Assert(IsA(wfunc, WindowFunc));
+
+ wfunccost = get_func_cost(wfunc->winfnoid) * cpu_operator_cost;
+
+ /* also add the input expressions' cost to per-input-row costs */
+ cost_qual_eval_node(&argcosts, (Node *) wfunc->args, root);
+ startup_cost += argcosts.startup;
+ wfunccost += argcosts.per_tuple;
+
+ total_cost += wfunccost * input_tuples;
+ }
+
+ /*
+ * We also charge cpu_operator_cost per grouping column per tuple for
+ * grouping comparisons, plus cpu_tuple_cost per tuple for general
+ * overhead.
+ *
+ * XXX this neglects costs of spooling the data to disk when it overflows
+ * work_mem. Sooner or later that should get accounted for.
+ */
+ total_cost += cpu_operator_cost * (numPartCols + numOrderCols) * input_tuples;
total_cost += cpu_tuple_cost * input_tuples;
path->startup_cost = startup_cost;
* Vars and Consts are charged zero, and so are boolean operators (AND,
* OR, NOT). Simplistic, but a lot better than no model at all.
*
- * Note that Aggref and WindowFunc nodes are (and should be) treated like
- * Vars --- whatever execution cost they have is absorbed into
- * plan-node-specific costing. As far as expression evaluation is
- * concerned they're just like Vars.
- *
* Should we try to account for the possibility of short-circuit
* evaluation of AND/OR? Probably *not*, because that would make the
* results depend on the clause ordering, and we are not in any position
* to expect that the current ordering of the clauses is the one that's
- * going to end up being used. (Is it worth applying order_qual_clauses
- * much earlier in the planning process to fix this?)
+ * going to end up being used. The above per-RestrictInfo caching would
+ * not mix well with trying to re-order clauses anyway.
*/
if (IsA(node, FuncExpr))
{
context->total.per_tuple += get_func_cost(saop->opfuncid) *
cpu_operator_cost * estimate_array_length(arraynode) * 0.5;
}
+ else if (IsA(node, Aggref) ||
+ IsA(node, WindowFunc))
+ {
+ /*
+ * Aggref and WindowFunc nodes are (and should be) treated like Vars,
+ * ie, zero execution cost in the current model, because they behave
+ * essentially like Vars in execQual.c. We disregard the costs of
+ * their input expressions for the same reason. The actual execution
+ * costs of the aggregate/window functions and their arguments have to
+ * be factored into plan-node-specific costing of the Agg or WindowAgg
+ * plan node.
+ */
+ return false; /* don't recurse into children */
+ }
else if (IsA(node, CoerceViaIO))
{
CoerceViaIO *iocoerce = (CoerceViaIO *) node;
build_relation_tlist(best_path->path.parent),
NIL,
AGG_HASHED,
+ NULL,
numGroupCols,
groupColIdx,
groupOperators,
numGroups,
- 0,
subplan);
}
else
Agg *
make_agg(PlannerInfo *root, List *tlist, List *qual,
- AggStrategy aggstrategy,
+ AggStrategy aggstrategy, const AggClauseCosts *aggcosts,
int numGroupCols, AttrNumber *grpColIdx, Oid *grpOperators,
- long numGroups, int numAggs,
+ long numGroups,
Plan *lefttree)
{
Agg *node = makeNode(Agg);
copy_plan_costsize(plan, lefttree); /* only care about copying size */
cost_agg(&agg_path, root,
- aggstrategy, numAggs,
+ aggstrategy, aggcosts,
numGroupCols, numGroups,
lefttree->startup_cost,
lefttree->total_cost,
WindowAgg *
make_windowagg(PlannerInfo *root, List *tlist,
- int numWindowFuncs, Index winref,
+ List *windowFuncs, Index winref,
int partNumCols, AttrNumber *partColIdx, Oid *partOperators,
int ordNumCols, AttrNumber *ordColIdx, Oid *ordOperators,
int frameOptions, Node *startOffset, Node *endOffset,
copy_plan_costsize(plan, lefttree); /* only care about copying size */
cost_windowagg(&windowagg_path, root,
- numWindowFuncs, partNumCols, ordNumCols,
+ windowFuncs, partNumCols, ordNumCols,
lefttree->startup_cost,
lefttree->total_cost,
lefttree->plan_rows);
* Should we skip even trying to build the standard plan, if
* preprocess_minmax_aggregates succeeds?
*
- * We are passed the preprocessed tlist, as well as the best path devised for
+ * We are passed the preprocessed tlist, as well as the estimated costs for
+ * doing the aggregates the regular way, and the best path devised for
* computing the input of a standard Agg node.
*/
Plan *
-optimize_minmax_aggregates(PlannerInfo *root, List *tlist, Path *best_path)
+optimize_minmax_aggregates(PlannerInfo *root, List *tlist,
+ const AggClauseCosts *aggcosts, Path *best_path)
{
Query *parse = root->parse;
Cost total_cost;
total_cost += mminfo->pathcost;
}
- cost_agg(&agg_p, root, AGG_PLAIN, list_length(root->minmax_aggs),
+ cost_agg(&agg_p, root, AGG_PLAIN, aggcosts,
0, 0,
best_path->startup_cost, best_path->total_cost,
best_path->parent->rows);
double tuple_fraction, double limit_tuples,
double path_rows, int path_width,
Path *cheapest_path, Path *sorted_path,
- double dNumGroups, AggClauseCounts *agg_counts);
+ double dNumGroups, AggClauseCosts *agg_costs);
static bool choose_hashed_distinct(PlannerInfo *root,
double tuple_fraction, double limit_tuples,
double path_rows, int path_width,
Path *sorted_path;
Path *best_path;
long numGroups = 0;
- AggClauseCounts agg_counts;
+ AggClauseCosts agg_costs;
int numGroupCols;
double path_rows;
int path_width;
WindowFuncLists *wflists = NULL;
List *activeWindows = NIL;
- MemSet(&agg_counts, 0, sizeof(AggClauseCounts));
+ MemSet(&agg_costs, 0, sizeof(AggClauseCosts));
/* A recursive query should always have setOperations */
Assert(!root->hasRecursion);
if (parse->hasAggs)
{
/*
- * Will need actual number of aggregates for estimating costs.
+ * Collect statistics about aggregates for estimating costs.
* Note: we do not attempt to detect duplicate aggregates here; a
- * somewhat-overestimated count is okay for our present purposes.
+ * somewhat-overestimated cost is okay for our present purposes.
*/
- count_agg_clauses((Node *) tlist, &agg_counts);
- count_agg_clauses(parse->havingQual, &agg_counts);
+ count_agg_clauses(root, (Node *) tlist, &agg_costs);
+ count_agg_clauses(root, parse->havingQual, &agg_costs);
/*
* Preprocess MIN/MAX aggregates, if any. Note: be careful about
tuple_fraction, limit_tuples,
path_rows, path_width,
cheapest_path, sorted_path,
- dNumGroups, &agg_counts);
+ dNumGroups, &agg_costs);
/* Also convert # groups to long int --- but 'ware overflow! */
numGroups = (long) Min(dNumGroups, (double) LONG_MAX);
}
*/
result_plan = optimize_minmax_aggregates(root,
tlist,
+ &agg_costs,
best_path);
if (result_plan != NULL)
{
tlist,
(List *) parse->havingQual,
AGG_HASHED,
+ &agg_costs,
numGroupCols,
groupColIdx,
extract_grouping_ops(parse->groupClause),
numGroups,
- agg_counts.numAggs,
result_plan);
/* Hashed aggregation produces randomly-ordered results */
current_pathkeys = NIL;
tlist,
(List *) parse->havingQual,
aggstrategy,
+ &agg_costs,
numGroupCols,
groupColIdx,
extract_grouping_ops(parse->groupClause),
numGroups,
- agg_counts.numAggs,
result_plan);
}
else if (parse->groupClause)
result_plan = (Plan *)
make_windowagg(root,
(List *) copyObject(window_tlist),
- list_length(wflists->windowFuncs[wc->winref]),
+ wflists->windowFuncs[wc->winref],
wc->winref,
partNumCols,
partColIdx,
result_plan->targetlist,
NIL,
AGG_HASHED,
+ NULL,
list_length(parse->distinctClause),
extract_grouping_cols(parse->distinctClause,
result_plan->targetlist),
extract_grouping_ops(parse->distinctClause),
numDistinctRows,
- 0,
result_plan);
/* Hashed aggregation produces randomly-ordered results */
current_pathkeys = NIL;
double tuple_fraction, double limit_tuples,
double path_rows, int path_width,
Path *cheapest_path, Path *sorted_path,
- double dNumGroups, AggClauseCounts *agg_counts)
+ double dNumGroups, AggClauseCosts *agg_costs)
{
Query *parse = root->parse;
int numGroupCols = list_length(parse->groupClause);
* the hash table, and/or running many sorts in parallel, either of which
* seems like a certain loser.)
*/
- can_hash = (agg_counts->numOrderedAggs == 0 &&
+ can_hash = (agg_costs->numOrderedAggs == 0 &&
grouping_is_hashable(parse->groupClause));
can_sort = grouping_is_sortable(parse->groupClause);
/* Estimate per-hash-entry space at tuple width... */
hashentrysize = MAXALIGN(path_width) + MAXALIGN(sizeof(MinimalTupleData));
/* plus space for pass-by-ref transition values... */
- hashentrysize += agg_counts->transitionSpace;
+ hashentrysize += agg_costs->transitionSpace;
/* plus the per-hash-entry overhead */
- hashentrysize += hash_agg_entry_size(agg_counts->numAggs);
+ hashentrysize += hash_agg_entry_size(agg_costs->numAggs);
if (hashentrysize * dNumGroups > work_mem * 1024L)
return false;
* These path variables are dummies that just hold cost fields; we don't
* make actual Paths for these steps.
*/
- cost_agg(&hashed_p, root, AGG_HASHED, agg_counts->numAggs,
+ cost_agg(&hashed_p, root, AGG_HASHED, agg_costs,
numGroupCols, dNumGroups,
cheapest_path->startup_cost, cheapest_path->total_cost,
path_rows);
}
if (parse->hasAggs)
- cost_agg(&sorted_p, root, AGG_SORTED, agg_counts->numAggs,
+ cost_agg(&sorted_p, root, AGG_SORTED, agg_costs,
numGroupCols, dNumGroups,
sorted_p.startup_cost, sorted_p.total_cost,
path_rows);
* These path variables are dummies that just hold cost fields; we don't
* make actual Paths for these steps.
*/
- cost_agg(&hashed_p, root, AGG_HASHED, 0,
+ cost_agg(&hashed_p, root, AGG_HASHED, NULL,
numDistinctCols, dNumDistinctRows,
cheapest_startup_cost, cheapest_total_cost,
path_rows);
plan->targetlist,
NIL,
AGG_HASHED,
+ NULL,
list_length(groupList),
extract_grouping_cols(groupList,
plan->targetlist),
extract_grouping_ops(groupList),
numGroups,
- 0,
plan);
/* Hashed aggregation produces randomly-ordered results */
*sortClauses = NIL;
* These path variables are dummies that just hold cost fields; we don't
* make actual Paths for these steps.
*/
- cost_agg(&hashed_p, root, AGG_HASHED, 0,
+ cost_agg(&hashed_p, root, AGG_HASHED, NULL,
numGroupCols, dNumGroups,
input_plan->startup_cost, input_plan->total_cost,
input_plan->plan_rows);
#include "utils/typcache.h"
+typedef struct
+{
+ PlannerInfo *root;
+ AggClauseCosts *costs;
+} count_agg_clauses_context;
+
typedef struct
{
ParamListInfo boundParams;
static bool contain_agg_clause_walker(Node *node, void *context);
static bool pull_agg_clause_walker(Node *node, List **context);
-static bool count_agg_clauses_walker(Node *node, AggClauseCounts *counts);
+static bool count_agg_clauses_walker(Node *node,
+ count_agg_clauses_context *context);
static bool find_window_functions_walker(Node *node, WindowFuncLists *lists);
static bool expression_returns_set_rows_walker(Node *node, double *count);
static bool contain_subplans_walker(Node *node, void *context);
/*
* count_agg_clauses
- * Recursively count the Aggref nodes in an expression tree.
+ * Recursively count the Aggref nodes in an expression tree, and
+ * accumulate other cost information about them too.
*
* Note: this also checks for nested aggregates, which are an error.
*
- * We not only count the nodes, but attempt to estimate the total space
- * needed for their transition state values if all are evaluated in parallel
- * (as would be done in a HashAgg plan). See AggClauseCounts for the exact
- * set of statistics returned.
+ * We not only count the nodes, but estimate their execution costs, and
+ * attempt to estimate the total space needed for their transition state
+ * values if all are evaluated in parallel (as would be done in a HashAgg
+ * plan). See AggClauseCosts for the exact set of statistics collected.
*
- * NOTE that the counts are ADDED to those already in *counts ... so the
- * caller is responsible for zeroing the struct initially.
+ * NOTE that the counts/costs are ADDED to those already in *costs ... so
+ * the caller is responsible for zeroing the struct initially.
*
* This does not descend into subqueries, and so should be used only after
* reduction of sublinks to subplans, or in contexts where it's known there
* are no subqueries. There mustn't be outer-aggregate references either.
*/
void
-count_agg_clauses(Node *clause, AggClauseCounts *counts)
+count_agg_clauses(PlannerInfo *root, Node *clause, AggClauseCosts *costs)
{
- /* no setup needed */
- count_agg_clauses_walker(clause, counts);
+ count_agg_clauses_context context;
+
+ context.root = root;
+ context.costs = costs;
+ (void) count_agg_clauses_walker(clause, &context);
}
static bool
-count_agg_clauses_walker(Node *node, AggClauseCounts *counts)
+count_agg_clauses_walker(Node *node, count_agg_clauses_context *context)
{
if (node == NULL)
return false;
if (IsA(node, Aggref))
{
Aggref *aggref = (Aggref *) node;
- Oid *inputTypes;
- int numArguments;
+ AggClauseCosts *costs = context->costs;
HeapTuple aggTuple;
Form_pg_aggregate aggform;
+ Oid aggtransfn;
+ Oid aggfinalfn;
Oid aggtranstype;
+ QualCost argcosts;
+ Oid *inputTypes;
+ int numArguments;
ListCell *l;
Assert(aggref->agglevelsup == 0);
- counts->numAggs++;
+
+ /* fetch info about aggregate from pg_aggregate */
+ aggTuple = SearchSysCache1(AGGFNOID,
+ ObjectIdGetDatum(aggref->aggfnoid));
+ if (!HeapTupleIsValid(aggTuple))
+ elog(ERROR, "cache lookup failed for aggregate %u",
+ aggref->aggfnoid);
+ aggform = (Form_pg_aggregate) GETSTRUCT(aggTuple);
+ aggtransfn = aggform->aggtransfn;
+ aggfinalfn = aggform->aggfinalfn;
+ aggtranstype = aggform->aggtranstype;
+ ReleaseSysCache(aggTuple);
+
+ /* count it */
+ costs->numAggs++;
if (aggref->aggorder != NIL || aggref->aggdistinct != NIL)
- counts->numOrderedAggs++;
+ costs->numOrderedAggs++;
+
+ /* add component function execution costs to appropriate totals */
+ costs->transCost.per_tuple += get_func_cost(aggtransfn) * cpu_operator_cost;
+ if (OidIsValid(aggfinalfn))
+ costs->finalCost += get_func_cost(aggfinalfn) * cpu_operator_cost;
+
+ /* also add the input expressions' cost to per-input-row costs */
+ cost_qual_eval_node(&argcosts, (Node *) aggref->args, context->root);
+ costs->transCost.startup += argcosts.startup;
+ costs->transCost.per_tuple += argcosts.per_tuple;
/* extract argument types (ignoring any ORDER BY expressions) */
inputTypes = (Oid *) palloc(sizeof(Oid) * list_length(aggref->args));
inputTypes[numArguments++] = exprType((Node *) tle->expr);
}
- /* fetch aggregate transition datatype from pg_aggregate */
- aggTuple = SearchSysCache1(AGGFNOID,
- ObjectIdGetDatum(aggref->aggfnoid));
- if (!HeapTupleIsValid(aggTuple))
- elog(ERROR, "cache lookup failed for aggregate %u",
- aggref->aggfnoid);
- aggform = (Form_pg_aggregate) GETSTRUCT(aggTuple);
- aggtranstype = aggform->aggtranstype;
- ReleaseSysCache(aggTuple);
-
/* resolve actual type of transition state, if polymorphic */
if (IsPolymorphicType(aggtranstype))
{
avgwidth = get_typavgwidth(aggtranstype, aggtranstypmod);
avgwidth = MAXALIGN(avgwidth);
- counts->transitionSpace += avgwidth + 2 * sizeof(void *);
+ costs->transitionSpace += avgwidth + 2 * sizeof(void *);
}
else if (aggtranstype == INTERNALOID)
{
* being kept in a private memory context, as is done by
* array_agg() for instance.
*/
- counts->transitionSpace += ALLOCSET_DEFAULT_INITSIZE;
+ costs->transitionSpace += ALLOCSET_DEFAULT_INITSIZE;
}
/*
}
Assert(!IsA(node, SubLink));
return expression_tree_walker(node, count_agg_clauses_walker,
- (void *) counts);
+ (void *) context);
}
all_hash = false; /* don't try to hash */
else
cost_agg(&agg_path, root,
- AGG_HASHED, 0,
+ AGG_HASHED, NULL,
numCols, pathnode->rows,
subpath->startup_cost,
subpath->total_cost,
Cost per_tuple; /* per-evaluation cost */
} QualCost;
+/*
+ * Costing aggregate function execution requires these statistics about
+ * the aggregates to be executed by a given Agg node. Note that transCost
+ * includes the execution costs of the aggregates' input expressions.
+ */
+typedef struct AggClauseCosts
+{
+ int numAggs; /* total number of aggregate functions */
+ int numOrderedAggs; /* number that use DISTINCT or ORDER BY */
+ QualCost transCost; /* total per-input-row execution costs */
+ Cost finalCost; /* total costs of agg final functions */
+ Size transitionSpace; /* space for pass-by-ref transition data */
+} AggClauseCosts;
+
/*----------
* PlannerGlobal
#define is_opclause(clause) ((clause) != NULL && IsA(clause, OpExpr))
#define is_funcclause(clause) ((clause) != NULL && IsA(clause, FuncExpr))
-typedef struct
-{
- int numAggs; /* total number of aggregate calls */
- int numOrderedAggs; /* number that use DISTINCT or ORDER BY */
- Size transitionSpace; /* for pass-by-ref transition data */
-} AggClauseCounts;
-
typedef struct
{
int numWindowFuncs; /* total number of WindowFuncs found */
extern bool contain_agg_clause(Node *clause);
extern List *pull_agg_clause(Node *clause);
-extern void count_agg_clauses(Node *clause, AggClauseCounts *counts);
+extern void count_agg_clauses(PlannerInfo *root, Node *clause,
+ AggClauseCosts *costs);
extern bool contain_window_function(Node *clause);
extern WindowFuncLists *find_window_functions(Node *clause, Index maxWinRef);
Cost input_startup_cost, Cost input_total_cost,
double tuples, int width);
extern void cost_agg(Path *path, PlannerInfo *root,
- AggStrategy aggstrategy, int numAggs,
+ AggStrategy aggstrategy, const AggClauseCosts *aggcosts,
int numGroupCols, double numGroups,
Cost input_startup_cost, Cost input_total_cost,
double input_tuples);
extern void cost_windowagg(Path *path, PlannerInfo *root,
- int numWindowFuncs, int numPartCols, int numOrderCols,
+ List *windowFuncs, int numPartCols, int numOrderCols,
Cost input_startup_cost, Cost input_total_cost,
double input_tuples);
extern void cost_group(Path *path, PlannerInfo *root,
*/
extern void preprocess_minmax_aggregates(PlannerInfo *root, List *tlist);
extern Plan *optimize_minmax_aggregates(PlannerInfo *root, List *tlist,
- Path *best_path);
+ const AggClauseCosts *aggcosts, Path *best_path);
/*
* prototypes for plan/createplan.c
extern Sort *make_sort_from_groupcols(PlannerInfo *root, List *groupcls,
AttrNumber *grpColIdx, Plan *lefttree);
extern Agg *make_agg(PlannerInfo *root, List *tlist, List *qual,
- AggStrategy aggstrategy,
+ AggStrategy aggstrategy, const AggClauseCosts *aggcosts,
int numGroupCols, AttrNumber *grpColIdx, Oid *grpOperators,
- long numGroups, int numAggs,
+ long numGroups,
Plan *lefttree);
extern WindowAgg *make_windowagg(PlannerInfo *root, List *tlist,
- int numWindowFuncs, Index winref,
+ List *windowFuncs, Index winref,
int partNumCols, AttrNumber *partColIdx, Oid *partOperators,
int ordNumCols, AttrNumber *ordColIdx, Oid *ordOperators,
int frameOptions, Node *startOffset, Node *endOffset,
projects / users / hanada / postgres.git / commitdiff