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useless for an ungrouped-aggregate query holds regardless of whether optimize_minmax_aggregates succeeds. So we might as well apply the optimization in any case. I'll leave 8.3 as it was, since this version is a tad more invasive than my earlier patch.
1829 lines
56 KiB
C
1829 lines
56 KiB
C
/*-------------------------------------------------------------------------
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*
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* planner.c
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* The query optimizer external interface.
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*
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* Portions Copyright (c) 1996-2008, PostgreSQL Global Development Group
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* Portions Copyright (c) 1994, Regents of the University of California
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*
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*
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* IDENTIFICATION
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* $PostgreSQL: pgsql/src/backend/optimizer/plan/planner.c,v 1.229 2008/03/28 02:00:11 tgl Exp $
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*
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*-------------------------------------------------------------------------
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*/
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#include "postgres.h"
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#include <limits.h>
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#include "catalog/pg_operator.h"
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#include "executor/executor.h"
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#include "executor/nodeAgg.h"
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#include "miscadmin.h"
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#include "nodes/makefuncs.h"
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#include "optimizer/clauses.h"
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#include "optimizer/cost.h"
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#include "optimizer/pathnode.h"
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#include "optimizer/paths.h"
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#include "optimizer/planmain.h"
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#include "optimizer/planner.h"
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#include "optimizer/prep.h"
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#include "optimizer/subselect.h"
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#include "optimizer/tlist.h"
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#include "optimizer/var.h"
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#ifdef OPTIMIZER_DEBUG
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#include "nodes/print.h"
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#endif
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#include "parser/parse_expr.h"
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#include "parser/parse_oper.h"
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#include "parser/parsetree.h"
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#include "utils/lsyscache.h"
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#include "utils/syscache.h"
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/* Hook for plugins to get control in planner() */
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planner_hook_type planner_hook = NULL;
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/* Expression kind codes for preprocess_expression */
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#define EXPRKIND_QUAL 0
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#define EXPRKIND_TARGET 1
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#define EXPRKIND_RTFUNC 2
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#define EXPRKIND_VALUES 3
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#define EXPRKIND_LIMIT 4
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#define EXPRKIND_ININFO 5
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#define EXPRKIND_APPINFO 6
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static Node *preprocess_expression(PlannerInfo *root, Node *expr, int kind);
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static void preprocess_qual_conditions(PlannerInfo *root, Node *jtnode);
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static Plan *inheritance_planner(PlannerInfo *root);
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static Plan *grouping_planner(PlannerInfo *root, double tuple_fraction);
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static bool is_dummy_plan(Plan *plan);
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static double preprocess_limit(PlannerInfo *root,
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double tuple_fraction,
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int64 *offset_est, int64 *count_est);
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static Oid *extract_grouping_ops(List *groupClause);
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static bool choose_hashed_grouping(PlannerInfo *root,
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double tuple_fraction, double limit_tuples,
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Path *cheapest_path, Path *sorted_path,
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Oid *groupOperators, double dNumGroups,
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AggClauseCounts *agg_counts);
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static List *make_subplanTargetList(PlannerInfo *root, List *tlist,
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AttrNumber **groupColIdx, bool *need_tlist_eval);
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static void locate_grouping_columns(PlannerInfo *root,
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List *tlist,
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List *sub_tlist,
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AttrNumber *groupColIdx);
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static List *postprocess_setop_tlist(List *new_tlist, List *orig_tlist);
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/*****************************************************************************
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*
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* Query optimizer entry point
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*
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* To support loadable plugins that monitor or modify planner behavior,
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* we provide a hook variable that lets a plugin get control before and
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* after the standard planning process. The plugin would normally call
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* standard_planner().
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*
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* Note to plugin authors: standard_planner() scribbles on its Query input,
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* so you'd better copy that data structure if you want to plan more than once.
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*
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*****************************************************************************/
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PlannedStmt *
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planner(Query *parse, int cursorOptions, ParamListInfo boundParams)
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{
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PlannedStmt *result;
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if (planner_hook)
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result = (*planner_hook) (parse, cursorOptions, boundParams);
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else
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result = standard_planner(parse, cursorOptions, boundParams);
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return result;
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}
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PlannedStmt *
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standard_planner(Query *parse, int cursorOptions, ParamListInfo boundParams)
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{
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PlannedStmt *result;
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PlannerGlobal *glob;
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double tuple_fraction;
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PlannerInfo *root;
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Plan *top_plan;
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ListCell *lp,
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*lr;
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/* Cursor options may come from caller or from DECLARE CURSOR stmt */
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if (parse->utilityStmt &&
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IsA(parse->utilityStmt, DeclareCursorStmt))
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cursorOptions |= ((DeclareCursorStmt *) parse->utilityStmt)->options;
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/*
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* Set up global state for this planner invocation. This data is needed
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* across all levels of sub-Query that might exist in the given command,
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* so we keep it in a separate struct that's linked to by each per-Query
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* PlannerInfo.
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*/
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glob = makeNode(PlannerGlobal);
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glob->boundParams = boundParams;
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glob->paramlist = NIL;
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glob->subplans = NIL;
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glob->subrtables = NIL;
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glob->rewindPlanIDs = NULL;
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glob->finalrtable = NIL;
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glob->relationOids = NIL;
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glob->transientPlan = false;
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/* Determine what fraction of the plan is likely to be scanned */
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if (cursorOptions & CURSOR_OPT_FAST_PLAN)
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{
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/*
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* We have no real idea how many tuples the user will ultimately FETCH
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* from a cursor, but it seems a good bet that he doesn't want 'em
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* all. Optimize for 10% retrieval (you gotta better number? Should
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* this be a SETtable parameter?)
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*/
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tuple_fraction = 0.10;
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}
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else
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{
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/* Default assumption is we need all the tuples */
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tuple_fraction = 0.0;
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}
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/* primary planning entry point (may recurse for subqueries) */
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top_plan = subquery_planner(glob, parse, 1, tuple_fraction, &root);
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/*
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* If creating a plan for a scrollable cursor, make sure it can run
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* backwards on demand. Add a Material node at the top at need.
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*/
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if (cursorOptions & CURSOR_OPT_SCROLL)
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{
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if (!ExecSupportsBackwardScan(top_plan))
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top_plan = materialize_finished_plan(top_plan);
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}
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/* final cleanup of the plan */
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Assert(glob->finalrtable == NIL);
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top_plan = set_plan_references(glob, top_plan, root->parse->rtable);
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/* ... and the subplans (both regular subplans and initplans) */
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Assert(list_length(glob->subplans) == list_length(glob->subrtables));
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forboth(lp, glob->subplans, lr, glob->subrtables)
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{
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Plan *subplan = (Plan *) lfirst(lp);
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List *subrtable = (List *) lfirst(lr);
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lfirst(lp) = set_plan_references(glob, subplan, subrtable);
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}
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/* build the PlannedStmt result */
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result = makeNode(PlannedStmt);
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result->commandType = parse->commandType;
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result->canSetTag = parse->canSetTag;
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result->transientPlan = glob->transientPlan;
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result->planTree = top_plan;
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result->rtable = glob->finalrtable;
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result->resultRelations = root->resultRelations;
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result->utilityStmt = parse->utilityStmt;
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result->intoClause = parse->intoClause;
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result->subplans = glob->subplans;
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result->rewindPlanIDs = glob->rewindPlanIDs;
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result->returningLists = root->returningLists;
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result->rowMarks = parse->rowMarks;
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result->relationOids = glob->relationOids;
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result->nParamExec = list_length(glob->paramlist);
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return result;
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}
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/*--------------------
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* subquery_planner
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* Invokes the planner on a subquery. We recurse to here for each
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* sub-SELECT found in the query tree.
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*
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* glob is the global state for the current planner run.
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* parse is the querytree produced by the parser & rewriter.
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* level is the current recursion depth (1 at the top-level Query).
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* tuple_fraction is the fraction of tuples we expect will be retrieved.
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* tuple_fraction is interpreted as explained for grouping_planner, below.
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*
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* If subroot isn't NULL, we pass back the query's final PlannerInfo struct;
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* among other things this tells the output sort ordering of the plan.
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*
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* Basically, this routine does the stuff that should only be done once
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* per Query object. It then calls grouping_planner. At one time,
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* grouping_planner could be invoked recursively on the same Query object;
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* that's not currently true, but we keep the separation between the two
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* routines anyway, in case we need it again someday.
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*
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* subquery_planner will be called recursively to handle sub-Query nodes
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* found within the query's expressions and rangetable.
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*
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* Returns a query plan.
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*--------------------
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*/
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Plan *
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subquery_planner(PlannerGlobal *glob, Query *parse,
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Index level, double tuple_fraction,
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PlannerInfo **subroot)
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{
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int num_old_subplans = list_length(glob->subplans);
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PlannerInfo *root;
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Plan *plan;
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List *newHaving;
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ListCell *l;
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/* Create a PlannerInfo data structure for this subquery */
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root = makeNode(PlannerInfo);
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root->parse = parse;
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root->glob = glob;
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root->query_level = level;
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root->planner_cxt = CurrentMemoryContext;
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root->init_plans = NIL;
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root->eq_classes = NIL;
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root->in_info_list = NIL;
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root->append_rel_list = NIL;
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/*
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* Look for IN clauses at the top level of WHERE, and transform them into
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* joins. Note that this step only handles IN clauses originally at top
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* level of WHERE; if we pull up any subqueries below, their INs are
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* processed just before pulling them up.
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*/
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if (parse->hasSubLinks)
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parse->jointree->quals = pull_up_IN_clauses(root,
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parse->jointree->quals);
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/*
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* Scan the rangetable for set-returning functions, and inline them
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* if possible (producing subqueries that might get pulled up next).
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* Recursion issues here are handled in the same way as for IN clauses.
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*/
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inline_set_returning_functions(root);
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/*
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* Check to see if any subqueries in the rangetable can be merged into
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* this query.
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*/
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parse->jointree = (FromExpr *)
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pull_up_subqueries(root, (Node *) parse->jointree, false, false);
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/*
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* Detect whether any rangetable entries are RTE_JOIN kind; if not, we can
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* avoid the expense of doing flatten_join_alias_vars(). Also check for
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* outer joins --- if none, we can skip reduce_outer_joins() and some
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* other processing. This must be done after we have done
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* pull_up_subqueries, of course.
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*
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* Note: if reduce_outer_joins manages to eliminate all outer joins,
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* root->hasOuterJoins is not reset currently. This is OK since its
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* purpose is merely to suppress unnecessary processing in simple cases.
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*/
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root->hasJoinRTEs = false;
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root->hasOuterJoins = false;
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foreach(l, parse->rtable)
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{
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RangeTblEntry *rte = (RangeTblEntry *) lfirst(l);
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if (rte->rtekind == RTE_JOIN)
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{
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root->hasJoinRTEs = true;
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if (IS_OUTER_JOIN(rte->jointype))
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{
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root->hasOuterJoins = true;
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/* Can quit scanning once we find an outer join */
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break;
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}
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}
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}
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/*
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* Expand any rangetable entries that are inheritance sets into "append
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* relations". This can add entries to the rangetable, but they must be
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* plain base relations not joins, so it's OK (and marginally more
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* efficient) to do it after checking for join RTEs. We must do it after
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* pulling up subqueries, else we'd fail to handle inherited tables in
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* subqueries.
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*/
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expand_inherited_tables(root);
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/*
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* Set hasHavingQual to remember if HAVING clause is present. Needed
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* because preprocess_expression will reduce a constant-true condition to
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* an empty qual list ... but "HAVING TRUE" is not a semantic no-op.
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*/
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root->hasHavingQual = (parse->havingQual != NULL);
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/* Clear this flag; might get set in distribute_qual_to_rels */
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root->hasPseudoConstantQuals = false;
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/*
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* Do expression preprocessing on targetlist and quals.
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*/
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parse->targetList = (List *)
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preprocess_expression(root, (Node *) parse->targetList,
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EXPRKIND_TARGET);
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parse->returningList = (List *)
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preprocess_expression(root, (Node *) parse->returningList,
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EXPRKIND_TARGET);
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preprocess_qual_conditions(root, (Node *) parse->jointree);
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parse->havingQual = preprocess_expression(root, parse->havingQual,
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EXPRKIND_QUAL);
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parse->limitOffset = preprocess_expression(root, parse->limitOffset,
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EXPRKIND_LIMIT);
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parse->limitCount = preprocess_expression(root, parse->limitCount,
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EXPRKIND_LIMIT);
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root->in_info_list = (List *)
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preprocess_expression(root, (Node *) root->in_info_list,
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EXPRKIND_ININFO);
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root->append_rel_list = (List *)
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preprocess_expression(root, (Node *) root->append_rel_list,
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EXPRKIND_APPINFO);
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/* Also need to preprocess expressions for function and values RTEs */
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foreach(l, parse->rtable)
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{
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RangeTblEntry *rte = (RangeTblEntry *) lfirst(l);
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if (rte->rtekind == RTE_FUNCTION)
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rte->funcexpr = preprocess_expression(root, rte->funcexpr,
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EXPRKIND_RTFUNC);
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else if (rte->rtekind == RTE_VALUES)
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rte->values_lists = (List *)
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preprocess_expression(root, (Node *) rte->values_lists,
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EXPRKIND_VALUES);
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}
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/*
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* In some cases we may want to transfer a HAVING clause into WHERE. We
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* cannot do so if the HAVING clause contains aggregates (obviously) or
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* volatile functions (since a HAVING clause is supposed to be executed
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* only once per group). Also, it may be that the clause is so expensive
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* to execute that we're better off doing it only once per group, despite
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* the loss of selectivity. This is hard to estimate short of doing the
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* entire planning process twice, so we use a heuristic: clauses
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* containing subplans are left in HAVING. Otherwise, we move or copy the
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* HAVING clause into WHERE, in hopes of eliminating tuples before
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* aggregation instead of after.
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*
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* If the query has explicit grouping then we can simply move such a
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* clause into WHERE; any group that fails the clause will not be in the
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* output because none of its tuples will reach the grouping or
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* aggregation stage. Otherwise we must have a degenerate (variable-free)
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* HAVING clause, which we put in WHERE so that query_planner() can use it
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* in a gating Result node, but also keep in HAVING to ensure that we
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* don't emit a bogus aggregated row. (This could be done better, but it
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* seems not worth optimizing.)
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*
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* Note that both havingQual and parse->jointree->quals are in
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* implicitly-ANDed-list form at this point, even though they are declared
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* as Node *.
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*/
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newHaving = NIL;
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foreach(l, (List *) parse->havingQual)
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{
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Node *havingclause = (Node *) lfirst(l);
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if (contain_agg_clause(havingclause) ||
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contain_volatile_functions(havingclause) ||
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contain_subplans(havingclause))
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{
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/* keep it in HAVING */
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newHaving = lappend(newHaving, havingclause);
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}
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else if (parse->groupClause)
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{
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/* move it to WHERE */
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parse->jointree->quals = (Node *)
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lappend((List *) parse->jointree->quals, havingclause);
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}
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else
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{
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/* put a copy in WHERE, keep it in HAVING */
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parse->jointree->quals = (Node *)
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lappend((List *) parse->jointree->quals,
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copyObject(havingclause));
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newHaving = lappend(newHaving, havingclause);
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}
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}
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parse->havingQual = (Node *) newHaving;
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/*
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* If we have any outer joins, try to reduce them to plain inner joins.
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* This step is most easily done after we've done expression
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* preprocessing.
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*/
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if (root->hasOuterJoins)
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reduce_outer_joins(root);
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/*
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* Do the main planning. If we have an inherited target relation, that
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* needs special processing, else go straight to grouping_planner.
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*/
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if (parse->resultRelation &&
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rt_fetch(parse->resultRelation, parse->rtable)->inh)
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plan = inheritance_planner(root);
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else
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plan = grouping_planner(root, tuple_fraction);
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/*
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* If any subplans were generated, or if we're inside a subplan, build
|
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* initPlan list and extParam/allParam sets for plan nodes, and attach the
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* initPlans to the top plan node.
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*/
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if (list_length(glob->subplans) != num_old_subplans ||
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root->query_level > 1)
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SS_finalize_plan(root, plan);
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/* Return internal info if caller wants it */
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if (subroot)
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*subroot = root;
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return plan;
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}
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|
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/*
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* preprocess_expression
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* Do subquery_planner's preprocessing work for an expression,
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* which can be a targetlist, a WHERE clause (including JOIN/ON
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* conditions), or a HAVING clause.
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*/
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static Node *
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preprocess_expression(PlannerInfo *root, Node *expr, int kind)
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{
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/*
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* Fall out quickly if expression is empty. This occurs often enough to
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* be worth checking. Note that null->null is the correct conversion for
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* implicit-AND result format, too.
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*/
|
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if (expr == NULL)
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return NULL;
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|
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/*
|
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* If the query has any join RTEs, replace join alias variables with
|
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* base-relation variables. We must do this before sublink processing,
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* else sublinks expanded out from join aliases wouldn't get processed. We
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* can skip it in VALUES lists, however, since they can't contain any Vars
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* at all.
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*/
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if (root->hasJoinRTEs && kind != EXPRKIND_VALUES)
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expr = flatten_join_alias_vars(root, expr);
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|
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/*
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* Simplify constant expressions.
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*
|
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* Note: this also flattens nested AND and OR expressions into N-argument
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* form. All processing of a qual expression after this point must be
|
|
* careful to maintain AND/OR flatness --- that is, do not generate a tree
|
|
* with AND directly under AND, nor OR directly under OR.
|
|
*
|
|
* Because this is a relatively expensive process, we skip it when the
|
|
* query is trivial, such as "SELECT 2+2;" or "INSERT ... VALUES()". The
|
|
* expression will only be evaluated once anyway, so no point in
|
|
* pre-simplifying; we can't execute it any faster than the executor can,
|
|
* and we will waste cycles copying the tree. Notice however that we
|
|
* still must do it for quals (to get AND/OR flatness); and if we are in a
|
|
* subquery we should not assume it will be done only once.
|
|
*
|
|
* For VALUES lists we never do this at all, again on the grounds that we
|
|
* should optimize for one-time evaluation.
|
|
*/
|
|
if (kind != EXPRKIND_VALUES &&
|
|
(root->parse->jointree->fromlist != NIL ||
|
|
kind == EXPRKIND_QUAL ||
|
|
root->query_level > 1))
|
|
expr = eval_const_expressions(expr);
|
|
|
|
/*
|
|
* If it's a qual or havingQual, canonicalize it.
|
|
*/
|
|
if (kind == EXPRKIND_QUAL)
|
|
{
|
|
expr = (Node *) canonicalize_qual((Expr *) expr);
|
|
|
|
#ifdef OPTIMIZER_DEBUG
|
|
printf("After canonicalize_qual()\n");
|
|
pprint(expr);
|
|
#endif
|
|
}
|
|
|
|
/* Expand SubLinks to SubPlans */
|
|
if (root->parse->hasSubLinks)
|
|
expr = SS_process_sublinks(root, expr, (kind == EXPRKIND_QUAL));
|
|
|
|
/*
|
|
* XXX do not insert anything here unless you have grokked the comments in
|
|
* SS_replace_correlation_vars ...
|
|
*/
|
|
|
|
/* Replace uplevel vars with Param nodes (this IS possible in VALUES) */
|
|
if (root->query_level > 1)
|
|
expr = SS_replace_correlation_vars(root, expr);
|
|
|
|
/*
|
|
* If it's a qual or havingQual, convert it to implicit-AND format. (We
|
|
* don't want to do this before eval_const_expressions, since the latter
|
|
* would be unable to simplify a top-level AND correctly. Also,
|
|
* SS_process_sublinks expects explicit-AND format.)
|
|
*/
|
|
if (kind == EXPRKIND_QUAL)
|
|
expr = (Node *) make_ands_implicit((Expr *) expr);
|
|
|
|
return expr;
|
|
}
|
|
|
|
/*
|
|
* preprocess_qual_conditions
|
|
* Recursively scan the query's jointree and do subquery_planner's
|
|
* preprocessing work on each qual condition found therein.
|
|
*/
|
|
static void
|
|
preprocess_qual_conditions(PlannerInfo *root, Node *jtnode)
|
|
{
|
|
if (jtnode == NULL)
|
|
return;
|
|
if (IsA(jtnode, RangeTblRef))
|
|
{
|
|
/* nothing to do here */
|
|
}
|
|
else if (IsA(jtnode, FromExpr))
|
|
{
|
|
FromExpr *f = (FromExpr *) jtnode;
|
|
ListCell *l;
|
|
|
|
foreach(l, f->fromlist)
|
|
preprocess_qual_conditions(root, lfirst(l));
|
|
|
|
f->quals = preprocess_expression(root, f->quals, EXPRKIND_QUAL);
|
|
}
|
|
else if (IsA(jtnode, JoinExpr))
|
|
{
|
|
JoinExpr *j = (JoinExpr *) jtnode;
|
|
|
|
preprocess_qual_conditions(root, j->larg);
|
|
preprocess_qual_conditions(root, j->rarg);
|
|
|
|
j->quals = preprocess_expression(root, j->quals, EXPRKIND_QUAL);
|
|
}
|
|
else
|
|
elog(ERROR, "unrecognized node type: %d",
|
|
(int) nodeTag(jtnode));
|
|
}
|
|
|
|
/*
|
|
* inheritance_planner
|
|
* Generate a plan in the case where the result relation is an
|
|
* inheritance set.
|
|
*
|
|
* We have to handle this case differently from cases where a source relation
|
|
* is an inheritance set. Source inheritance is expanded at the bottom of the
|
|
* plan tree (see allpaths.c), but target inheritance has to be expanded at
|
|
* the top. The reason is that for UPDATE, each target relation needs a
|
|
* different targetlist matching its own column set. Also, for both UPDATE
|
|
* and DELETE, the executor needs the Append plan node at the top, else it
|
|
* can't keep track of which table is the current target table. Fortunately,
|
|
* the UPDATE/DELETE target can never be the nullable side of an outer join,
|
|
* so it's OK to generate the plan this way.
|
|
*
|
|
* Returns a query plan.
|
|
*/
|
|
static Plan *
|
|
inheritance_planner(PlannerInfo *root)
|
|
{
|
|
Query *parse = root->parse;
|
|
int parentRTindex = parse->resultRelation;
|
|
List *subplans = NIL;
|
|
List *resultRelations = NIL;
|
|
List *returningLists = NIL;
|
|
List *rtable = NIL;
|
|
List *tlist = NIL;
|
|
PlannerInfo subroot;
|
|
ListCell *l;
|
|
|
|
foreach(l, root->append_rel_list)
|
|
{
|
|
AppendRelInfo *appinfo = (AppendRelInfo *) lfirst(l);
|
|
Plan *subplan;
|
|
|
|
/* append_rel_list contains all append rels; ignore others */
|
|
if (appinfo->parent_relid != parentRTindex)
|
|
continue;
|
|
|
|
/*
|
|
* Generate modified query with this rel as target. We have to be
|
|
* prepared to translate varnos in in_info_list as well as in the
|
|
* Query proper.
|
|
*/
|
|
memcpy(&subroot, root, sizeof(PlannerInfo));
|
|
subroot.parse = (Query *)
|
|
adjust_appendrel_attrs((Node *) parse,
|
|
appinfo);
|
|
subroot.in_info_list = (List *)
|
|
adjust_appendrel_attrs((Node *) root->in_info_list,
|
|
appinfo);
|
|
subroot.init_plans = NIL;
|
|
/* There shouldn't be any OJ info to translate, as yet */
|
|
Assert(subroot.oj_info_list == NIL);
|
|
|
|
/* Generate plan */
|
|
subplan = grouping_planner(&subroot, 0.0 /* retrieve all tuples */ );
|
|
|
|
/*
|
|
* If this child rel was excluded by constraint exclusion, exclude it
|
|
* from the plan.
|
|
*/
|
|
if (is_dummy_plan(subplan))
|
|
continue;
|
|
|
|
/* Save rtable and tlist from first rel for use below */
|
|
if (subplans == NIL)
|
|
{
|
|
rtable = subroot.parse->rtable;
|
|
tlist = subplan->targetlist;
|
|
}
|
|
|
|
subplans = lappend(subplans, subplan);
|
|
|
|
/* Make sure any initplans from this rel get into the outer list */
|
|
root->init_plans = list_concat(root->init_plans, subroot.init_plans);
|
|
|
|
/* Build target-relations list for the executor */
|
|
resultRelations = lappend_int(resultRelations, appinfo->child_relid);
|
|
|
|
/* Build list of per-relation RETURNING targetlists */
|
|
if (parse->returningList)
|
|
{
|
|
Assert(list_length(subroot.returningLists) == 1);
|
|
returningLists = list_concat(returningLists,
|
|
subroot.returningLists);
|
|
}
|
|
}
|
|
|
|
root->resultRelations = resultRelations;
|
|
root->returningLists = returningLists;
|
|
|
|
/* Mark result as unordered (probably unnecessary) */
|
|
root->query_pathkeys = NIL;
|
|
|
|
/*
|
|
* If we managed to exclude every child rel, return a dummy plan
|
|
*/
|
|
if (subplans == NIL)
|
|
{
|
|
root->resultRelations = list_make1_int(parentRTindex);
|
|
/* although dummy, it must have a valid tlist for executor */
|
|
tlist = preprocess_targetlist(root, parse->targetList);
|
|
return (Plan *) make_result(root,
|
|
tlist,
|
|
(Node *) list_make1(makeBoolConst(false,
|
|
false)),
|
|
NULL);
|
|
}
|
|
|
|
/*
|
|
* Planning might have modified the rangetable, due to changes of the
|
|
* Query structures inside subquery RTEs. We have to ensure that this
|
|
* gets propagated back to the master copy. But can't do this until we
|
|
* are done planning, because all the calls to grouping_planner need
|
|
* virgin sub-Queries to work from. (We are effectively assuming that
|
|
* sub-Queries will get planned identically each time, or at least that
|
|
* the impacts on their rangetables will be the same each time.)
|
|
*
|
|
* XXX should clean this up someday
|
|
*/
|
|
parse->rtable = rtable;
|
|
|
|
/* Suppress Append if there's only one surviving child rel */
|
|
if (list_length(subplans) == 1)
|
|
return (Plan *) linitial(subplans);
|
|
|
|
return (Plan *) make_append(subplans, true, tlist);
|
|
}
|
|
|
|
/*--------------------
|
|
* grouping_planner
|
|
* Perform planning steps related to grouping, aggregation, etc.
|
|
* This primarily means adding top-level processing to the basic
|
|
* query plan produced by query_planner.
|
|
*
|
|
* tuple_fraction is the fraction of tuples we expect will be retrieved
|
|
*
|
|
* tuple_fraction is interpreted as follows:
|
|
* 0: expect all tuples to be retrieved (normal case)
|
|
* 0 < tuple_fraction < 1: expect the given fraction of tuples available
|
|
* from the plan to be retrieved
|
|
* tuple_fraction >= 1: tuple_fraction is the absolute number of tuples
|
|
* expected to be retrieved (ie, a LIMIT specification)
|
|
*
|
|
* Returns a query plan. Also, root->query_pathkeys is returned as the
|
|
* actual output ordering of the plan (in pathkey format).
|
|
*--------------------
|
|
*/
|
|
static Plan *
|
|
grouping_planner(PlannerInfo *root, double tuple_fraction)
|
|
{
|
|
Query *parse = root->parse;
|
|
List *tlist = parse->targetList;
|
|
int64 offset_est = 0;
|
|
int64 count_est = 0;
|
|
double limit_tuples = -1.0;
|
|
Plan *result_plan;
|
|
List *current_pathkeys;
|
|
List *sort_pathkeys;
|
|
double dNumGroups = 0;
|
|
|
|
/* Tweak caller-supplied tuple_fraction if have LIMIT/OFFSET */
|
|
if (parse->limitCount || parse->limitOffset)
|
|
{
|
|
tuple_fraction = preprocess_limit(root, tuple_fraction,
|
|
&offset_est, &count_est);
|
|
|
|
/*
|
|
* If we have a known LIMIT, and don't have an unknown OFFSET, we can
|
|
* estimate the effects of using a bounded sort.
|
|
*/
|
|
if (count_est > 0 && offset_est >= 0)
|
|
limit_tuples = (double) count_est + (double) offset_est;
|
|
}
|
|
|
|
if (parse->setOperations)
|
|
{
|
|
List *set_sortclauses;
|
|
|
|
/*
|
|
* If there's a top-level ORDER BY, assume we have to fetch all the
|
|
* tuples. This might seem too simplistic given all the hackery below
|
|
* to possibly avoid the sort ... but a nonzero tuple_fraction is only
|
|
* of use to plan_set_operations() when the setop is UNION ALL, and
|
|
* the result of UNION ALL is always unsorted.
|
|
*/
|
|
if (parse->sortClause)
|
|
tuple_fraction = 0.0;
|
|
|
|
/*
|
|
* Construct the plan for set operations. The result will not need
|
|
* any work except perhaps a top-level sort and/or LIMIT.
|
|
*/
|
|
result_plan = plan_set_operations(root, tuple_fraction,
|
|
&set_sortclauses);
|
|
|
|
/*
|
|
* Calculate pathkeys representing the sort order (if any) of the set
|
|
* operation's result. We have to do this before overwriting the sort
|
|
* key information...
|
|
*/
|
|
current_pathkeys = make_pathkeys_for_sortclauses(root,
|
|
set_sortclauses,
|
|
result_plan->targetlist,
|
|
true);
|
|
|
|
/*
|
|
* We should not need to call preprocess_targetlist, since we must be
|
|
* in a SELECT query node. Instead, use the targetlist returned by
|
|
* plan_set_operations (since this tells whether it returned any
|
|
* resjunk columns!), and transfer any sort key information from the
|
|
* original tlist.
|
|
*/
|
|
Assert(parse->commandType == CMD_SELECT);
|
|
|
|
tlist = postprocess_setop_tlist(result_plan->targetlist, tlist);
|
|
|
|
/*
|
|
* Can't handle FOR UPDATE/SHARE here (parser should have checked
|
|
* already, but let's make sure).
|
|
*/
|
|
if (parse->rowMarks)
|
|
ereport(ERROR,
|
|
(errcode(ERRCODE_FEATURE_NOT_SUPPORTED),
|
|
errmsg("SELECT FOR UPDATE/SHARE is not allowed with UNION/INTERSECT/EXCEPT")));
|
|
|
|
/*
|
|
* Calculate pathkeys that represent result ordering requirements
|
|
*/
|
|
sort_pathkeys = make_pathkeys_for_sortclauses(root,
|
|
parse->sortClause,
|
|
tlist,
|
|
true);
|
|
}
|
|
else
|
|
{
|
|
/* No set operations, do regular planning */
|
|
List *sub_tlist;
|
|
List *group_pathkeys;
|
|
AttrNumber *groupColIdx = NULL;
|
|
Oid *groupOperators = NULL;
|
|
bool need_tlist_eval = true;
|
|
QualCost tlist_cost;
|
|
Path *cheapest_path;
|
|
Path *sorted_path;
|
|
Path *best_path;
|
|
long numGroups = 0;
|
|
AggClauseCounts agg_counts;
|
|
int numGroupCols = list_length(parse->groupClause);
|
|
bool use_hashed_grouping = false;
|
|
|
|
MemSet(&agg_counts, 0, sizeof(AggClauseCounts));
|
|
|
|
/*
|
|
* If the query involves ungrouped aggregation, then it can produce
|
|
* at most one row, so we can ignore any ORDER BY or DISTINCT
|
|
* request. This isn't all that exciting as an optimization, but it
|
|
* prevents a corner case when optimize_minmax_aggregates succeeds:
|
|
* if ORDER BY or DISTINCT were present we'd try, and fail, to match
|
|
* the EquivalenceClasses we're about to build with the modified
|
|
* targetlist entries it will create.
|
|
*/
|
|
if (parse->hasAggs && parse->groupClause == NIL)
|
|
{
|
|
parse->sortClause = NIL;
|
|
parse->distinctClause = NIL;
|
|
}
|
|
|
|
/* Preprocess targetlist */
|
|
tlist = preprocess_targetlist(root, tlist);
|
|
|
|
/*
|
|
* Generate appropriate target list for subplan; may be different from
|
|
* tlist if grouping or aggregation is needed.
|
|
*/
|
|
sub_tlist = make_subplanTargetList(root, tlist,
|
|
&groupColIdx, &need_tlist_eval);
|
|
|
|
/*
|
|
* Calculate pathkeys that represent grouping/ordering requirements.
|
|
* Stash them in PlannerInfo so that query_planner can canonicalize
|
|
* them after EquivalenceClasses have been formed.
|
|
*/
|
|
root->group_pathkeys =
|
|
make_pathkeys_for_sortclauses(root,
|
|
parse->groupClause,
|
|
tlist,
|
|
false);
|
|
root->sort_pathkeys =
|
|
make_pathkeys_for_sortclauses(root,
|
|
parse->sortClause,
|
|
tlist,
|
|
false);
|
|
|
|
/*
|
|
* Will need actual number of aggregates for estimating costs.
|
|
*
|
|
* Note: we do not attempt to detect duplicate aggregates here; a
|
|
* somewhat-overestimated count is okay for our present purposes.
|
|
*
|
|
* Note: think not that we can turn off hasAggs if we find no aggs. It
|
|
* is possible for constant-expression simplification to remove all
|
|
* explicit references to aggs, but we still have to follow the
|
|
* aggregate semantics (eg, producing only one output row).
|
|
*/
|
|
if (parse->hasAggs)
|
|
{
|
|
count_agg_clauses((Node *) tlist, &agg_counts);
|
|
count_agg_clauses(parse->havingQual, &agg_counts);
|
|
}
|
|
|
|
/*
|
|
* Figure out whether we need a sorted result from query_planner.
|
|
*
|
|
* If we have a GROUP BY clause, then we want a result sorted properly
|
|
* for grouping. Otherwise, if there is an ORDER BY clause, we want
|
|
* to sort by the ORDER BY clause. (Note: if we have both, and ORDER
|
|
* BY is a superset of GROUP BY, it would be tempting to request sort
|
|
* by ORDER BY --- but that might just leave us failing to exploit an
|
|
* available sort order at all. Needs more thought...)
|
|
*/
|
|
if (parse->groupClause)
|
|
root->query_pathkeys = root->group_pathkeys;
|
|
else if (parse->sortClause)
|
|
root->query_pathkeys = root->sort_pathkeys;
|
|
else
|
|
root->query_pathkeys = NIL;
|
|
|
|
/*
|
|
* Generate the best unsorted and presorted paths for this Query (but
|
|
* note there may not be any presorted path). query_planner will also
|
|
* estimate the number of groups in the query, and canonicalize all
|
|
* the pathkeys.
|
|
*/
|
|
query_planner(root, sub_tlist, tuple_fraction, limit_tuples,
|
|
&cheapest_path, &sorted_path, &dNumGroups);
|
|
|
|
group_pathkeys = root->group_pathkeys;
|
|
sort_pathkeys = root->sort_pathkeys;
|
|
|
|
/*
|
|
* If grouping, extract the grouping operators and decide whether we
|
|
* want to use hashed grouping.
|
|
*/
|
|
if (parse->groupClause)
|
|
{
|
|
groupOperators = extract_grouping_ops(parse->groupClause);
|
|
use_hashed_grouping =
|
|
choose_hashed_grouping(root, tuple_fraction, limit_tuples,
|
|
cheapest_path, sorted_path,
|
|
groupOperators, dNumGroups,
|
|
&agg_counts);
|
|
|
|
/* Also convert # groups to long int --- but 'ware overflow! */
|
|
numGroups = (long) Min(dNumGroups, (double) LONG_MAX);
|
|
}
|
|
|
|
/*
|
|
* Select the best path. If we are doing hashed grouping, we will
|
|
* always read all the input tuples, so use the cheapest-total path.
|
|
* Otherwise, trust query_planner's decision about which to use.
|
|
*/
|
|
if (use_hashed_grouping || !sorted_path)
|
|
best_path = cheapest_path;
|
|
else
|
|
best_path = sorted_path;
|
|
|
|
/*
|
|
* Check to see if it's possible to optimize MIN/MAX aggregates. If
|
|
* so, we will forget all the work we did so far to choose a "regular"
|
|
* path ... but we had to do it anyway to be able to tell which way is
|
|
* cheaper.
|
|
*/
|
|
result_plan = optimize_minmax_aggregates(root,
|
|
tlist,
|
|
best_path);
|
|
if (result_plan != NULL)
|
|
{
|
|
/*
|
|
* optimize_minmax_aggregates generated the full plan, with the
|
|
* right tlist, and it has no sort order.
|
|
*/
|
|
current_pathkeys = NIL;
|
|
}
|
|
else
|
|
{
|
|
/*
|
|
* Normal case --- create a plan according to query_planner's
|
|
* results.
|
|
*/
|
|
result_plan = create_plan(root, best_path);
|
|
current_pathkeys = best_path->pathkeys;
|
|
|
|
/*
|
|
* create_plan() returns a plan with just a "flat" tlist of
|
|
* required Vars. Usually we need to insert the sub_tlist as the
|
|
* tlist of the top plan node. However, we can skip that if we
|
|
* determined that whatever query_planner chose to return will be
|
|
* good enough.
|
|
*/
|
|
if (need_tlist_eval)
|
|
{
|
|
/*
|
|
* If the top-level plan node is one that cannot do expression
|
|
* evaluation, we must insert a Result node to project the
|
|
* desired tlist.
|
|
*/
|
|
if (!is_projection_capable_plan(result_plan))
|
|
{
|
|
result_plan = (Plan *) make_result(root,
|
|
sub_tlist,
|
|
NULL,
|
|
result_plan);
|
|
}
|
|
else
|
|
{
|
|
/*
|
|
* Otherwise, just replace the subplan's flat tlist with
|
|
* the desired tlist.
|
|
*/
|
|
result_plan->targetlist = sub_tlist;
|
|
}
|
|
|
|
/*
|
|
* Also, account for the cost of evaluation of the sub_tlist.
|
|
*
|
|
* Up to now, we have only been dealing with "flat" tlists,
|
|
* containing just Vars. So their evaluation cost is zero
|
|
* according to the model used by cost_qual_eval() (or if you
|
|
* prefer, the cost is factored into cpu_tuple_cost). Thus we
|
|
* can avoid accounting for tlist cost throughout
|
|
* query_planner() and subroutines. But now we've inserted a
|
|
* tlist that might contain actual operators, sub-selects, etc
|
|
* --- so we'd better account for its cost.
|
|
*
|
|
* Below this point, any tlist eval cost for added-on nodes
|
|
* should be accounted for as we create those nodes.
|
|
* Presently, of the node types we can add on, only Agg and
|
|
* Group project new tlists (the rest just copy their input
|
|
* tuples) --- so make_agg() and make_group() are responsible
|
|
* for computing the added cost.
|
|
*/
|
|
cost_qual_eval(&tlist_cost, sub_tlist, root);
|
|
result_plan->startup_cost += tlist_cost.startup;
|
|
result_plan->total_cost += tlist_cost.startup +
|
|
tlist_cost.per_tuple * result_plan->plan_rows;
|
|
}
|
|
else
|
|
{
|
|
/*
|
|
* Since we're using query_planner's tlist and not the one
|
|
* make_subplanTargetList calculated, we have to refigure any
|
|
* grouping-column indexes make_subplanTargetList computed.
|
|
*/
|
|
locate_grouping_columns(root, tlist, result_plan->targetlist,
|
|
groupColIdx);
|
|
}
|
|
|
|
/*
|
|
* Insert AGG or GROUP node if needed, plus an explicit sort step
|
|
* if necessary.
|
|
*
|
|
* HAVING clause, if any, becomes qual of the Agg or Group node.
|
|
*/
|
|
if (use_hashed_grouping)
|
|
{
|
|
/* Hashed aggregate plan --- no sort needed */
|
|
result_plan = (Plan *) make_agg(root,
|
|
tlist,
|
|
(List *) parse->havingQual,
|
|
AGG_HASHED,
|
|
numGroupCols,
|
|
groupColIdx,
|
|
groupOperators,
|
|
numGroups,
|
|
agg_counts.numAggs,
|
|
result_plan);
|
|
/* Hashed aggregation produces randomly-ordered results */
|
|
current_pathkeys = NIL;
|
|
}
|
|
else if (parse->hasAggs)
|
|
{
|
|
/* Plain aggregate plan --- sort if needed */
|
|
AggStrategy aggstrategy;
|
|
|
|
if (parse->groupClause)
|
|
{
|
|
if (!pathkeys_contained_in(group_pathkeys,
|
|
current_pathkeys))
|
|
{
|
|
result_plan = (Plan *)
|
|
make_sort_from_groupcols(root,
|
|
parse->groupClause,
|
|
groupColIdx,
|
|
result_plan);
|
|
current_pathkeys = group_pathkeys;
|
|
}
|
|
aggstrategy = AGG_SORTED;
|
|
|
|
/*
|
|
* The AGG node will not change the sort ordering of its
|
|
* groups, so current_pathkeys describes the result too.
|
|
*/
|
|
}
|
|
else
|
|
{
|
|
aggstrategy = AGG_PLAIN;
|
|
/* Result will be only one row anyway; no sort order */
|
|
current_pathkeys = NIL;
|
|
}
|
|
|
|
result_plan = (Plan *) make_agg(root,
|
|
tlist,
|
|
(List *) parse->havingQual,
|
|
aggstrategy,
|
|
numGroupCols,
|
|
groupColIdx,
|
|
groupOperators,
|
|
numGroups,
|
|
agg_counts.numAggs,
|
|
result_plan);
|
|
}
|
|
else if (parse->groupClause)
|
|
{
|
|
/*
|
|
* GROUP BY without aggregation, so insert a group node (plus
|
|
* the appropriate sort node, if necessary).
|
|
*
|
|
* Add an explicit sort if we couldn't make the path come out
|
|
* the way the GROUP node needs it.
|
|
*/
|
|
if (!pathkeys_contained_in(group_pathkeys, current_pathkeys))
|
|
{
|
|
result_plan = (Plan *)
|
|
make_sort_from_groupcols(root,
|
|
parse->groupClause,
|
|
groupColIdx,
|
|
result_plan);
|
|
current_pathkeys = group_pathkeys;
|
|
}
|
|
|
|
result_plan = (Plan *) make_group(root,
|
|
tlist,
|
|
(List *) parse->havingQual,
|
|
numGroupCols,
|
|
groupColIdx,
|
|
groupOperators,
|
|
dNumGroups,
|
|
result_plan);
|
|
/* The Group node won't change sort ordering */
|
|
}
|
|
else if (root->hasHavingQual)
|
|
{
|
|
/*
|
|
* No aggregates, and no GROUP BY, but we have a HAVING qual.
|
|
* This is a degenerate case in which we are supposed to emit
|
|
* either 0 or 1 row depending on whether HAVING succeeds.
|
|
* Furthermore, there cannot be any variables in either HAVING
|
|
* or the targetlist, so we actually do not need the FROM
|
|
* table at all! We can just throw away the plan-so-far and
|
|
* generate a Result node. This is a sufficiently unusual
|
|
* corner case that it's not worth contorting the structure of
|
|
* this routine to avoid having to generate the plan in the
|
|
* first place.
|
|
*/
|
|
result_plan = (Plan *) make_result(root,
|
|
tlist,
|
|
parse->havingQual,
|
|
NULL);
|
|
}
|
|
} /* end of non-minmax-aggregate case */
|
|
} /* end of if (setOperations) */
|
|
|
|
/*
|
|
* If we were not able to make the plan come out in the right order, add
|
|
* an explicit sort step.
|
|
*/
|
|
if (parse->sortClause)
|
|
{
|
|
if (!pathkeys_contained_in(sort_pathkeys, current_pathkeys))
|
|
{
|
|
result_plan = (Plan *) make_sort_from_pathkeys(root,
|
|
result_plan,
|
|
sort_pathkeys,
|
|
limit_tuples);
|
|
current_pathkeys = sort_pathkeys;
|
|
}
|
|
}
|
|
|
|
/*
|
|
* If there is a DISTINCT clause, add the UNIQUE node.
|
|
*/
|
|
if (parse->distinctClause)
|
|
{
|
|
result_plan = (Plan *) make_unique(result_plan, parse->distinctClause);
|
|
|
|
/*
|
|
* If there was grouping or aggregation, leave plan_rows as-is (ie,
|
|
* assume the result was already mostly unique). If not, use the
|
|
* number of distinct-groups calculated by query_planner.
|
|
*/
|
|
if (!parse->groupClause && !root->hasHavingQual && !parse->hasAggs)
|
|
result_plan->plan_rows = dNumGroups;
|
|
}
|
|
|
|
/*
|
|
* Finally, if there is a LIMIT/OFFSET clause, add the LIMIT node.
|
|
*/
|
|
if (parse->limitCount || parse->limitOffset)
|
|
{
|
|
result_plan = (Plan *) make_limit(result_plan,
|
|
parse->limitOffset,
|
|
parse->limitCount,
|
|
offset_est,
|
|
count_est);
|
|
}
|
|
|
|
/*
|
|
* Deal with the RETURNING clause if any. It's convenient to pass the
|
|
* returningList through setrefs.c now rather than at top level (if we
|
|
* waited, handling inherited UPDATE/DELETE would be much harder).
|
|
*/
|
|
if (parse->returningList)
|
|
{
|
|
List *rlist;
|
|
|
|
Assert(parse->resultRelation);
|
|
rlist = set_returning_clause_references(root->glob,
|
|
parse->returningList,
|
|
result_plan,
|
|
parse->resultRelation);
|
|
root->returningLists = list_make1(rlist);
|
|
}
|
|
else
|
|
root->returningLists = NIL;
|
|
|
|
/* Compute result-relations list if needed */
|
|
if (parse->resultRelation)
|
|
root->resultRelations = list_make1_int(parse->resultRelation);
|
|
else
|
|
root->resultRelations = NIL;
|
|
|
|
/*
|
|
* Return the actual output ordering in query_pathkeys for possible use by
|
|
* an outer query level.
|
|
*/
|
|
root->query_pathkeys = current_pathkeys;
|
|
|
|
return result_plan;
|
|
}
|
|
|
|
/*
|
|
* Detect whether a plan node is a "dummy" plan created when a relation
|
|
* is deemed not to need scanning due to constraint exclusion.
|
|
*
|
|
* Currently, such dummy plans are Result nodes with constant FALSE
|
|
* filter quals.
|
|
*/
|
|
static bool
|
|
is_dummy_plan(Plan *plan)
|
|
{
|
|
if (IsA(plan, Result))
|
|
{
|
|
List *rcqual = (List *) ((Result *) plan)->resconstantqual;
|
|
|
|
if (list_length(rcqual) == 1)
|
|
{
|
|
Const *constqual = (Const *) linitial(rcqual);
|
|
|
|
if (constqual && IsA(constqual, Const))
|
|
{
|
|
if (!constqual->constisnull &&
|
|
!DatumGetBool(constqual->constvalue))
|
|
return true;
|
|
}
|
|
}
|
|
}
|
|
return false;
|
|
}
|
|
|
|
/*
|
|
* preprocess_limit - do pre-estimation for LIMIT and/or OFFSET clauses
|
|
*
|
|
* We try to estimate the values of the LIMIT/OFFSET clauses, and pass the
|
|
* results back in *count_est and *offset_est. These variables are set to
|
|
* 0 if the corresponding clause is not present, and -1 if it's present
|
|
* but we couldn't estimate the value for it. (The "0" convention is OK
|
|
* for OFFSET but a little bit bogus for LIMIT: effectively we estimate
|
|
* LIMIT 0 as though it were LIMIT 1. But this is in line with the planner's
|
|
* usual practice of never estimating less than one row.) These values will
|
|
* be passed to make_limit, which see if you change this code.
|
|
*
|
|
* The return value is the suitably adjusted tuple_fraction to use for
|
|
* planning the query. This adjustment is not overridable, since it reflects
|
|
* plan actions that grouping_planner() will certainly take, not assumptions
|
|
* about context.
|
|
*/
|
|
static double
|
|
preprocess_limit(PlannerInfo *root, double tuple_fraction,
|
|
int64 *offset_est, int64 *count_est)
|
|
{
|
|
Query *parse = root->parse;
|
|
Node *est;
|
|
double limit_fraction;
|
|
|
|
/* Should not be called unless LIMIT or OFFSET */
|
|
Assert(parse->limitCount || parse->limitOffset);
|
|
|
|
/*
|
|
* Try to obtain the clause values. We use estimate_expression_value
|
|
* primarily because it can sometimes do something useful with Params.
|
|
*/
|
|
if (parse->limitCount)
|
|
{
|
|
est = estimate_expression_value(root, parse->limitCount);
|
|
if (est && IsA(est, Const))
|
|
{
|
|
if (((Const *) est)->constisnull)
|
|
{
|
|
/* NULL indicates LIMIT ALL, ie, no limit */
|
|
*count_est = 0; /* treat as not present */
|
|
}
|
|
else
|
|
{
|
|
*count_est = DatumGetInt64(((Const *) est)->constvalue);
|
|
if (*count_est <= 0)
|
|
*count_est = 1; /* force to at least 1 */
|
|
}
|
|
}
|
|
else
|
|
*count_est = -1; /* can't estimate */
|
|
}
|
|
else
|
|
*count_est = 0; /* not present */
|
|
|
|
if (parse->limitOffset)
|
|
{
|
|
est = estimate_expression_value(root, parse->limitOffset);
|
|
if (est && IsA(est, Const))
|
|
{
|
|
if (((Const *) est)->constisnull)
|
|
{
|
|
/* Treat NULL as no offset; the executor will too */
|
|
*offset_est = 0; /* treat as not present */
|
|
}
|
|
else
|
|
{
|
|
*offset_est = DatumGetInt64(((Const *) est)->constvalue);
|
|
if (*offset_est < 0)
|
|
*offset_est = 0; /* less than 0 is same as 0 */
|
|
}
|
|
}
|
|
else
|
|
*offset_est = -1; /* can't estimate */
|
|
}
|
|
else
|
|
*offset_est = 0; /* not present */
|
|
|
|
if (*count_est != 0)
|
|
{
|
|
/*
|
|
* A LIMIT clause limits the absolute number of tuples returned.
|
|
* However, if it's not a constant LIMIT then we have to guess; for
|
|
* lack of a better idea, assume 10% of the plan's result is wanted.
|
|
*/
|
|
if (*count_est < 0 || *offset_est < 0)
|
|
{
|
|
/* LIMIT or OFFSET is an expression ... punt ... */
|
|
limit_fraction = 0.10;
|
|
}
|
|
else
|
|
{
|
|
/* LIMIT (plus OFFSET, if any) is max number of tuples needed */
|
|
limit_fraction = (double) *count_est + (double) *offset_est;
|
|
}
|
|
|
|
/*
|
|
* If we have absolute limits from both caller and LIMIT, use the
|
|
* smaller value; likewise if they are both fractional. If one is
|
|
* fractional and the other absolute, we can't easily determine which
|
|
* is smaller, but we use the heuristic that the absolute will usually
|
|
* be smaller.
|
|
*/
|
|
if (tuple_fraction >= 1.0)
|
|
{
|
|
if (limit_fraction >= 1.0)
|
|
{
|
|
/* both absolute */
|
|
tuple_fraction = Min(tuple_fraction, limit_fraction);
|
|
}
|
|
else
|
|
{
|
|
/* caller absolute, limit fractional; use caller's value */
|
|
}
|
|
}
|
|
else if (tuple_fraction > 0.0)
|
|
{
|
|
if (limit_fraction >= 1.0)
|
|
{
|
|
/* caller fractional, limit absolute; use limit */
|
|
tuple_fraction = limit_fraction;
|
|
}
|
|
else
|
|
{
|
|
/* both fractional */
|
|
tuple_fraction = Min(tuple_fraction, limit_fraction);
|
|
}
|
|
}
|
|
else
|
|
{
|
|
/* no info from caller, just use limit */
|
|
tuple_fraction = limit_fraction;
|
|
}
|
|
}
|
|
else if (*offset_est != 0 && tuple_fraction > 0.0)
|
|
{
|
|
/*
|
|
* We have an OFFSET but no LIMIT. This acts entirely differently
|
|
* from the LIMIT case: here, we need to increase rather than decrease
|
|
* the caller's tuple_fraction, because the OFFSET acts to cause more
|
|
* tuples to be fetched instead of fewer. This only matters if we got
|
|
* a tuple_fraction > 0, however.
|
|
*
|
|
* As above, use 10% if OFFSET is present but unestimatable.
|
|
*/
|
|
if (*offset_est < 0)
|
|
limit_fraction = 0.10;
|
|
else
|
|
limit_fraction = (double) *offset_est;
|
|
|
|
/*
|
|
* If we have absolute counts from both caller and OFFSET, add them
|
|
* together; likewise if they are both fractional. If one is
|
|
* fractional and the other absolute, we want to take the larger, and
|
|
* we heuristically assume that's the fractional one.
|
|
*/
|
|
if (tuple_fraction >= 1.0)
|
|
{
|
|
if (limit_fraction >= 1.0)
|
|
{
|
|
/* both absolute, so add them together */
|
|
tuple_fraction += limit_fraction;
|
|
}
|
|
else
|
|
{
|
|
/* caller absolute, limit fractional; use limit */
|
|
tuple_fraction = limit_fraction;
|
|
}
|
|
}
|
|
else
|
|
{
|
|
if (limit_fraction >= 1.0)
|
|
{
|
|
/* caller fractional, limit absolute; use caller's value */
|
|
}
|
|
else
|
|
{
|
|
/* both fractional, so add them together */
|
|
tuple_fraction += limit_fraction;
|
|
if (tuple_fraction >= 1.0)
|
|
tuple_fraction = 0.0; /* assume fetch all */
|
|
}
|
|
}
|
|
}
|
|
|
|
return tuple_fraction;
|
|
}
|
|
|
|
/*
|
|
* extract_grouping_ops - make an array of the equality operator OIDs
|
|
* for the GROUP BY clause
|
|
*/
|
|
static Oid *
|
|
extract_grouping_ops(List *groupClause)
|
|
{
|
|
int numCols = list_length(groupClause);
|
|
int colno = 0;
|
|
Oid *groupOperators;
|
|
ListCell *glitem;
|
|
|
|
groupOperators = (Oid *) palloc(sizeof(Oid) * numCols);
|
|
|
|
foreach(glitem, groupClause)
|
|
{
|
|
GroupClause *groupcl = (GroupClause *) lfirst(glitem);
|
|
|
|
groupOperators[colno] = get_equality_op_for_ordering_op(groupcl->sortop);
|
|
if (!OidIsValid(groupOperators[colno])) /* shouldn't happen */
|
|
elog(ERROR, "could not find equality operator for ordering operator %u",
|
|
groupcl->sortop);
|
|
colno++;
|
|
}
|
|
|
|
return groupOperators;
|
|
}
|
|
|
|
/*
|
|
* choose_hashed_grouping - should we use hashed grouping?
|
|
*/
|
|
static bool
|
|
choose_hashed_grouping(PlannerInfo *root,
|
|
double tuple_fraction, double limit_tuples,
|
|
Path *cheapest_path, Path *sorted_path,
|
|
Oid *groupOperators, double dNumGroups,
|
|
AggClauseCounts *agg_counts)
|
|
{
|
|
int numGroupCols = list_length(root->parse->groupClause);
|
|
double cheapest_path_rows;
|
|
int cheapest_path_width;
|
|
Size hashentrysize;
|
|
List *current_pathkeys;
|
|
Path hashed_p;
|
|
Path sorted_p;
|
|
int i;
|
|
|
|
/*
|
|
* Check can't-do-it conditions, including whether the grouping operators
|
|
* are hashjoinable. (We assume hashing is OK if they are marked
|
|
* oprcanhash. If there isn't actually a supporting hash function, the
|
|
* executor will complain at runtime.)
|
|
*
|
|
* Executor doesn't support hashed aggregation with DISTINCT aggregates.
|
|
* (Doing so would imply storing *all* the input values in the hash table,
|
|
* which seems like a certain loser.)
|
|
*/
|
|
if (!enable_hashagg)
|
|
return false;
|
|
if (agg_counts->numDistinctAggs != 0)
|
|
return false;
|
|
for (i = 0; i < numGroupCols; i++)
|
|
{
|
|
if (!op_hashjoinable(groupOperators[i]))
|
|
return false;
|
|
}
|
|
|
|
/*
|
|
* Don't do it if it doesn't look like the hashtable will fit into
|
|
* work_mem.
|
|
*
|
|
* Beware here of the possibility that cheapest_path->parent is NULL. This
|
|
* could happen if user does something silly like SELECT 'foo' GROUP BY 1;
|
|
*/
|
|
if (cheapest_path->parent)
|
|
{
|
|
cheapest_path_rows = cheapest_path->parent->rows;
|
|
cheapest_path_width = cheapest_path->parent->width;
|
|
}
|
|
else
|
|
{
|
|
cheapest_path_rows = 1; /* assume non-set result */
|
|
cheapest_path_width = 100; /* arbitrary */
|
|
}
|
|
|
|
/* Estimate per-hash-entry space at tuple width... */
|
|
hashentrysize = MAXALIGN(cheapest_path_width) + MAXALIGN(sizeof(MinimalTupleData));
|
|
/* plus space for pass-by-ref transition values... */
|
|
hashentrysize += agg_counts->transitionSpace;
|
|
/* plus the per-hash-entry overhead */
|
|
hashentrysize += hash_agg_entry_size(agg_counts->numAggs);
|
|
|
|
if (hashentrysize * dNumGroups > work_mem * 1024L)
|
|
return false;
|
|
|
|
/*
|
|
* See if the estimated cost is no more than doing it the other way. While
|
|
* avoiding the need for sorted input is usually a win, the fact that the
|
|
* output won't be sorted may be a loss; so we need to do an actual cost
|
|
* comparison.
|
|
*
|
|
* We need to consider cheapest_path + hashagg [+ final sort] versus
|
|
* either cheapest_path [+ sort] + group or agg [+ final sort] or
|
|
* presorted_path + group or agg [+ final sort] where brackets indicate a
|
|
* step that may not be needed. We assume query_planner() will have
|
|
* returned a presorted path only if it's a winner compared to
|
|
* cheapest_path for this purpose.
|
|
*
|
|
* 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,
|
|
numGroupCols, dNumGroups,
|
|
cheapest_path->startup_cost, cheapest_path->total_cost,
|
|
cheapest_path_rows);
|
|
/* Result of hashed agg is always unsorted */
|
|
if (root->sort_pathkeys)
|
|
cost_sort(&hashed_p, root, root->sort_pathkeys, hashed_p.total_cost,
|
|
dNumGroups, cheapest_path_width, limit_tuples);
|
|
|
|
if (sorted_path)
|
|
{
|
|
sorted_p.startup_cost = sorted_path->startup_cost;
|
|
sorted_p.total_cost = sorted_path->total_cost;
|
|
current_pathkeys = sorted_path->pathkeys;
|
|
}
|
|
else
|
|
{
|
|
sorted_p.startup_cost = cheapest_path->startup_cost;
|
|
sorted_p.total_cost = cheapest_path->total_cost;
|
|
current_pathkeys = cheapest_path->pathkeys;
|
|
}
|
|
if (!pathkeys_contained_in(root->group_pathkeys, current_pathkeys))
|
|
{
|
|
cost_sort(&sorted_p, root, root->group_pathkeys, sorted_p.total_cost,
|
|
cheapest_path_rows, cheapest_path_width, -1.0);
|
|
current_pathkeys = root->group_pathkeys;
|
|
}
|
|
|
|
if (root->parse->hasAggs)
|
|
cost_agg(&sorted_p, root, AGG_SORTED, agg_counts->numAggs,
|
|
numGroupCols, dNumGroups,
|
|
sorted_p.startup_cost, sorted_p.total_cost,
|
|
cheapest_path_rows);
|
|
else
|
|
cost_group(&sorted_p, root, numGroupCols, dNumGroups,
|
|
sorted_p.startup_cost, sorted_p.total_cost,
|
|
cheapest_path_rows);
|
|
/* The Agg or Group node will preserve ordering */
|
|
if (root->sort_pathkeys &&
|
|
!pathkeys_contained_in(root->sort_pathkeys, current_pathkeys))
|
|
cost_sort(&sorted_p, root, root->sort_pathkeys, sorted_p.total_cost,
|
|
dNumGroups, cheapest_path_width, limit_tuples);
|
|
|
|
/*
|
|
* Now make the decision using the top-level tuple fraction. First we
|
|
* have to convert an absolute count (LIMIT) into fractional form.
|
|
*/
|
|
if (tuple_fraction >= 1.0)
|
|
tuple_fraction /= dNumGroups;
|
|
|
|
if (compare_fractional_path_costs(&hashed_p, &sorted_p,
|
|
tuple_fraction) < 0)
|
|
{
|
|
/* Hashed is cheaper, so use it */
|
|
return true;
|
|
}
|
|
return false;
|
|
}
|
|
|
|
/*---------------
|
|
* make_subplanTargetList
|
|
* Generate appropriate target list when grouping is required.
|
|
*
|
|
* When grouping_planner inserts Aggregate, Group, or Result plan nodes
|
|
* above the result of query_planner, we typically want to pass a different
|
|
* target list to query_planner than the outer plan nodes should have.
|
|
* This routine generates the correct target list for the subplan.
|
|
*
|
|
* The initial target list passed from the parser already contains entries
|
|
* for all ORDER BY and GROUP BY expressions, but it will not have entries
|
|
* for variables used only in HAVING clauses; so we need to add those
|
|
* variables to the subplan target list. Also, we flatten all expressions
|
|
* except GROUP BY items into their component variables; the other expressions
|
|
* will be computed by the inserted nodes rather than by the subplan.
|
|
* For example, given a query like
|
|
* SELECT a+b,SUM(c+d) FROM table GROUP BY a+b;
|
|
* we want to pass this targetlist to the subplan:
|
|
* a,b,c,d,a+b
|
|
* where the a+b target will be used by the Sort/Group steps, and the
|
|
* other targets will be used for computing the final results. (In the
|
|
* above example we could theoretically suppress the a and b targets and
|
|
* pass down only c,d,a+b, but it's not really worth the trouble to
|
|
* eliminate simple var references from the subplan. We will avoid doing
|
|
* the extra computation to recompute a+b at the outer level; see
|
|
* fix_upper_expr() in setrefs.c.)
|
|
*
|
|
* If we are grouping or aggregating, *and* there are no non-Var grouping
|
|
* expressions, then the returned tlist is effectively dummy; we do not
|
|
* need to force it to be evaluated, because all the Vars it contains
|
|
* should be present in the output of query_planner anyway.
|
|
*
|
|
* 'tlist' is the query's target list.
|
|
* 'groupColIdx' receives an array of column numbers for the GROUP BY
|
|
* expressions (if there are any) in the subplan's target list.
|
|
* 'need_tlist_eval' is set true if we really need to evaluate the
|
|
* result tlist.
|
|
*
|
|
* The result is the targetlist to be passed to the subplan.
|
|
*---------------
|
|
*/
|
|
static List *
|
|
make_subplanTargetList(PlannerInfo *root,
|
|
List *tlist,
|
|
AttrNumber **groupColIdx,
|
|
bool *need_tlist_eval)
|
|
{
|
|
Query *parse = root->parse;
|
|
List *sub_tlist;
|
|
List *extravars;
|
|
int numCols;
|
|
|
|
*groupColIdx = NULL;
|
|
|
|
/*
|
|
* If we're not grouping or aggregating, there's nothing to do here;
|
|
* query_planner should receive the unmodified target list.
|
|
*/
|
|
if (!parse->hasAggs && !parse->groupClause && !root->hasHavingQual)
|
|
{
|
|
*need_tlist_eval = true;
|
|
return tlist;
|
|
}
|
|
|
|
/*
|
|
* Otherwise, start with a "flattened" tlist (having just the vars
|
|
* mentioned in the targetlist and HAVING qual --- but not upper- level
|
|
* Vars; they will be replaced by Params later on).
|
|
*/
|
|
sub_tlist = flatten_tlist(tlist);
|
|
extravars = pull_var_clause(parse->havingQual, false);
|
|
sub_tlist = add_to_flat_tlist(sub_tlist, extravars);
|
|
list_free(extravars);
|
|
*need_tlist_eval = false; /* only eval if not flat tlist */
|
|
|
|
/*
|
|
* If grouping, create sub_tlist entries for all GROUP BY expressions
|
|
* (GROUP BY items that are simple Vars should be in the list already),
|
|
* and make an array showing where the group columns are in the sub_tlist.
|
|
*/
|
|
numCols = list_length(parse->groupClause);
|
|
if (numCols > 0)
|
|
{
|
|
int keyno = 0;
|
|
AttrNumber *grpColIdx;
|
|
ListCell *gl;
|
|
|
|
grpColIdx = (AttrNumber *) palloc(sizeof(AttrNumber) * numCols);
|
|
*groupColIdx = grpColIdx;
|
|
|
|
foreach(gl, parse->groupClause)
|
|
{
|
|
GroupClause *grpcl = (GroupClause *) lfirst(gl);
|
|
Node *groupexpr = get_sortgroupclause_expr(grpcl, tlist);
|
|
TargetEntry *te = NULL;
|
|
ListCell *sl;
|
|
|
|
/* Find or make a matching sub_tlist entry */
|
|
foreach(sl, sub_tlist)
|
|
{
|
|
te = (TargetEntry *) lfirst(sl);
|
|
if (equal(groupexpr, te->expr))
|
|
break;
|
|
}
|
|
if (!sl)
|
|
{
|
|
te = makeTargetEntry((Expr *) groupexpr,
|
|
list_length(sub_tlist) + 1,
|
|
NULL,
|
|
false);
|
|
sub_tlist = lappend(sub_tlist, te);
|
|
*need_tlist_eval = true; /* it's not flat anymore */
|
|
}
|
|
|
|
/* and save its resno */
|
|
grpColIdx[keyno++] = te->resno;
|
|
}
|
|
}
|
|
|
|
return sub_tlist;
|
|
}
|
|
|
|
/*
|
|
* locate_grouping_columns
|
|
* Locate grouping columns in the tlist chosen by query_planner.
|
|
*
|
|
* This is only needed if we don't use the sub_tlist chosen by
|
|
* make_subplanTargetList. We have to forget the column indexes found
|
|
* by that routine and re-locate the grouping vars in the real sub_tlist.
|
|
*/
|
|
static void
|
|
locate_grouping_columns(PlannerInfo *root,
|
|
List *tlist,
|
|
List *sub_tlist,
|
|
AttrNumber *groupColIdx)
|
|
{
|
|
int keyno = 0;
|
|
ListCell *gl;
|
|
|
|
/*
|
|
* No work unless grouping.
|
|
*/
|
|
if (!root->parse->groupClause)
|
|
{
|
|
Assert(groupColIdx == NULL);
|
|
return;
|
|
}
|
|
Assert(groupColIdx != NULL);
|
|
|
|
foreach(gl, root->parse->groupClause)
|
|
{
|
|
GroupClause *grpcl = (GroupClause *) lfirst(gl);
|
|
Node *groupexpr = get_sortgroupclause_expr(grpcl, tlist);
|
|
TargetEntry *te = NULL;
|
|
ListCell *sl;
|
|
|
|
foreach(sl, sub_tlist)
|
|
{
|
|
te = (TargetEntry *) lfirst(sl);
|
|
if (equal(groupexpr, te->expr))
|
|
break;
|
|
}
|
|
if (!sl)
|
|
elog(ERROR, "failed to locate grouping columns");
|
|
|
|
groupColIdx[keyno++] = te->resno;
|
|
}
|
|
}
|
|
|
|
/*
|
|
* postprocess_setop_tlist
|
|
* Fix up targetlist returned by plan_set_operations().
|
|
*
|
|
* We need to transpose sort key info from the orig_tlist into new_tlist.
|
|
* NOTE: this would not be good enough if we supported resjunk sort keys
|
|
* for results of set operations --- then, we'd need to project a whole
|
|
* new tlist to evaluate the resjunk columns. For now, just ereport if we
|
|
* find any resjunk columns in orig_tlist.
|
|
*/
|
|
static List *
|
|
postprocess_setop_tlist(List *new_tlist, List *orig_tlist)
|
|
{
|
|
ListCell *l;
|
|
ListCell *orig_tlist_item = list_head(orig_tlist);
|
|
|
|
foreach(l, new_tlist)
|
|
{
|
|
TargetEntry *new_tle = (TargetEntry *) lfirst(l);
|
|
TargetEntry *orig_tle;
|
|
|
|
/* ignore resjunk columns in setop result */
|
|
if (new_tle->resjunk)
|
|
continue;
|
|
|
|
Assert(orig_tlist_item != NULL);
|
|
orig_tle = (TargetEntry *) lfirst(orig_tlist_item);
|
|
orig_tlist_item = lnext(orig_tlist_item);
|
|
if (orig_tle->resjunk) /* should not happen */
|
|
elog(ERROR, "resjunk output columns are not implemented");
|
|
Assert(new_tle->resno == orig_tle->resno);
|
|
new_tle->ressortgroupref = orig_tle->ressortgroupref;
|
|
}
|
|
if (orig_tlist_item != NULL)
|
|
elog(ERROR, "resjunk output columns are not implemented");
|
|
return new_tlist;
|
|
}
|