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addc42c339
into indexscans on matching indexes. For the moment, it only handles int4 and text datatypes; next step is to add a column to pg_aggregate so that all MIN/MAX aggregates can be handled. Per my recent proposal.
1576 lines
48 KiB
C
1576 lines
48 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) 1996-2005, 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 1.184 2005/04/11 23:06:55 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 "catalog/pg_type.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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#ifdef OPTIMIZER_DEBUG
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#include "nodes/print.h"
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#endif
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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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#include "parser/parsetree.h"
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#include "parser/parse_expr.h"
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#include "parser/parse_oper.h"
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#include "utils/selfuncs.h"
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#include "utils/syscache.h"
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ParamListInfo PlannerBoundParamList = NULL; /* current boundParams */
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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_LIMIT 3
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#define EXPRKIND_ININFO 4
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static Node *preprocess_expression(Query *parse, Node *expr, int kind);
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static void preprocess_qual_conditions(Query *parse, Node *jtnode);
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static Plan *inheritance_planner(Query *parse, List *inheritlist);
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static Plan *grouping_planner(Query *parse, double tuple_fraction);
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static bool choose_hashed_grouping(Query *parse, double tuple_fraction,
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Path *cheapest_path, Path *sorted_path,
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List *sort_pathkeys, List *group_pathkeys,
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double dNumGroups, AggClauseCounts *agg_counts);
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static bool hash_safe_grouping(Query *parse);
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static List *make_subplanTargetList(Query *parse, List *tlist,
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AttrNumber **groupColIdx, bool *need_tlist_eval);
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static void locate_grouping_columns(Query *parse,
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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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*****************************************************************************/
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Plan *
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planner(Query *parse, bool isCursor, int cursorOptions,
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ParamListInfo boundParams)
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{
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double tuple_fraction;
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Plan *result_plan;
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Index save_PlannerQueryLevel;
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List *save_PlannerParamList;
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ParamListInfo save_PlannerBoundParamList;
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/*
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* The planner can be called recursively (an example is when
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* eval_const_expressions tries to pre-evaluate an SQL function). So,
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* these global state variables must be saved and restored.
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*
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* Query level and the param list cannot be moved into the Query
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* structure since their whole purpose is communication across
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* multiple sub-Queries. Also, boundParams is explicitly info from
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* outside the Query, and so is likewise better handled as a global
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* variable.
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*
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* Note we do NOT save and restore PlannerPlanId: it exists to assign
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* unique IDs to SubPlan nodes, and we want those IDs to be unique for
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* the life of a backend. Also, PlannerInitPlan is saved/restored in
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* subquery_planner, not here.
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*/
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save_PlannerQueryLevel = PlannerQueryLevel;
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save_PlannerParamList = PlannerParamList;
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save_PlannerBoundParamList = PlannerBoundParamList;
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/* Initialize state for handling outer-level references and params */
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PlannerQueryLevel = 0; /* will be 1 in top-level subquery_planner */
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PlannerParamList = NIL;
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PlannerBoundParamList = boundParams;
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/* Determine what fraction of the plan is likely to be scanned */
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if (isCursor)
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{
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/*
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* We have no real idea how many tuples the user will ultimately
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* FETCH from a cursor, but it seems a good bet that he doesn't
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* want 'em all. Optimize for 10% retrieval (you gotta better
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* number? Should 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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result_plan = subquery_planner(parse, tuple_fraction);
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Assert(PlannerQueryLevel == 0);
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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 (isCursor && (cursorOptions & CURSOR_OPT_SCROLL))
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{
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if (!ExecSupportsBackwardScan(result_plan))
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result_plan = materialize_finished_plan(result_plan);
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}
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/* executor wants to know total number of Params used overall */
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result_plan->nParamExec = list_length(PlannerParamList);
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/* final cleanup of the plan */
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set_plan_references(result_plan, parse->rtable);
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/* restore state for outer planner, if any */
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PlannerQueryLevel = save_PlannerQueryLevel;
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PlannerParamList = save_PlannerParamList;
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PlannerBoundParamList = save_PlannerBoundParamList;
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return result_plan;
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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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* parse is the querytree produced by the parser & rewriter.
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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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* 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(Query *parse, double tuple_fraction)
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{
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List *saved_initplan = PlannerInitPlan;
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int saved_planid = PlannerPlanId;
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bool hasOuterJoins;
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Plan *plan;
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List *newHaving;
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List *lst;
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ListCell *l;
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/* Set up for a new level of subquery */
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PlannerQueryLevel++;
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PlannerInitPlan = NIL;
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/*
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* Look for IN clauses at the top level of WHERE, and transform them
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* into joins. Note that this step only handles IN clauses originally
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* at top level of WHERE; if we pull up any subqueries in the next
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* step, their INs are processed just before pulling them up.
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*/
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parse->in_info_list = NIL;
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if (parse->hasSubLinks)
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parse->jointree->quals = pull_up_IN_clauses(parse,
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parse->jointree->quals);
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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(parse, (Node *) parse->jointree, false);
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/*
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* Detect whether any rangetable entries are RTE_JOIN kind; if not, we
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* can avoid the expense of doing flatten_join_alias_vars(). Also
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* check for outer joins --- if none, we can skip
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* reduce_outer_joins(). 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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parse->hasJoinRTEs = false;
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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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parse->hasJoinRTEs = true;
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if (IS_OUTER_JOIN(rte->jointype))
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{
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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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* Set hasHavingQual to remember if HAVING clause is present. Needed
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* because preprocess_expression will reduce a constant-true condition
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* to an empty qual list ... but "HAVING TRUE" is not a semantic no-op.
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*/
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parse->hasHavingQual = (parse->havingQual != NULL);
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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(parse, (Node *) parse->targetList,
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EXPRKIND_TARGET);
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preprocess_qual_conditions(parse, (Node *) parse->jointree);
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parse->havingQual = preprocess_expression(parse, parse->havingQual,
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EXPRKIND_QUAL);
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parse->limitOffset = preprocess_expression(parse, parse->limitOffset,
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EXPRKIND_LIMIT);
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parse->limitCount = preprocess_expression(parse, parse->limitCount,
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EXPRKIND_LIMIT);
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parse->in_info_list = (List *)
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preprocess_expression(parse, (Node *) parse->in_info_list,
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EXPRKIND_ININFO);
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/* Also need to preprocess expressions for function 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(parse, rte->funcexpr,
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EXPRKIND_RTFUNC);
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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.
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* We cannot do so if the HAVING clause contains aggregates (obviously)
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* or 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
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* the 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
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* in the output because none of its tuples will reach the grouping
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* or aggregation stage. Otherwise we must have a degenerate
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* (variable-free) HAVING clause, which we put in WHERE so that
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* query_planner() can use it in a gating Result node, but also keep
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* in HAVING to ensure that we don't emit a bogus aggregated row.
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* (This could be done better, but it 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
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* declared 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
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* joins. 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 (hasOuterJoins)
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reduce_outer_joins(parse);
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/*
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* See if we can simplify the jointree; opportunities for this may
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* come from having pulled up subqueries, or from flattening explicit
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* JOIN syntax. We must do this after flattening JOIN alias
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* variables, since eliminating explicit JOIN nodes from the jointree
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* will cause get_relids_for_join() to fail. But it should happen
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* after reduce_outer_joins, anyway.
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*/
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parse->jointree = (FromExpr *)
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simplify_jointree(parse, (Node *) parse->jointree);
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/*
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* Do the main planning. If we have an inherited target relation,
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* that needs special processing, else go straight to
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* grouping_planner.
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*/
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if (parse->resultRelation &&
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(lst = expand_inherited_rtentry(parse, parse->resultRelation)) != NIL)
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plan = inheritance_planner(parse, lst);
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else
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plan = grouping_planner(parse, 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
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* the initPlans to the top plan node.
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*/
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if (PlannerPlanId != saved_planid || PlannerQueryLevel > 1)
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SS_finalize_plan(plan, parse->rtable);
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/* Return to outer subquery context */
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PlannerQueryLevel--;
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PlannerInitPlan = saved_initplan;
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/* we do NOT restore PlannerPlanId; that's not an oversight! */
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return plan;
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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(Query *parse, Node *expr, int kind)
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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
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* processed.
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*/
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if (parse->hasJoinRTEs)
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expr = flatten_join_alias_vars(parse, expr);
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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
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* careful to maintain AND/OR flatness --- that is, do not generate a tree
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* with AND directly under AND, nor OR directly under OR.
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*/
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expr = eval_const_expressions(expr);
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/*
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* If it's a qual or havingQual, canonicalize it.
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*/
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if (kind == EXPRKIND_QUAL)
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{
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expr = (Node *) canonicalize_qual((Expr *) expr);
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#ifdef OPTIMIZER_DEBUG
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printf("After canonicalize_qual()\n");
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pprint(expr);
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#endif
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}
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/* Expand SubLinks to SubPlans */
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if (parse->hasSubLinks)
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expr = SS_process_sublinks(expr, (kind == EXPRKIND_QUAL));
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/*
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* XXX do not insert anything here unless you have grokked the
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* comments in SS_replace_correlation_vars ...
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*/
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/* Replace uplevel vars with Param nodes */
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if (PlannerQueryLevel > 1)
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expr = SS_replace_correlation_vars(expr);
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/*
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* If it's a qual or havingQual, convert it to implicit-AND format.
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* (We don't want to do this before eval_const_expressions, since the
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* latter would be unable to simplify a top-level AND correctly. Also,
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* SS_process_sublinks expects explicit-AND format.)
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*/
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if (kind == EXPRKIND_QUAL)
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expr = (Node *) make_ands_implicit((Expr *) expr);
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return expr;
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}
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/*
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* preprocess_qual_conditions
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* Recursively scan the query's jointree and do subquery_planner's
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* preprocessing work on each qual condition found therein.
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*/
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static void
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preprocess_qual_conditions(Query *parse, Node *jtnode)
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{
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if (jtnode == NULL)
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return;
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if (IsA(jtnode, RangeTblRef))
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{
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/* nothing to do here */
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}
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else if (IsA(jtnode, FromExpr))
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{
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FromExpr *f = (FromExpr *) jtnode;
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ListCell *l;
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foreach(l, f->fromlist)
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preprocess_qual_conditions(parse, lfirst(l));
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f->quals = preprocess_expression(parse, f->quals, EXPRKIND_QUAL);
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}
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else if (IsA(jtnode, JoinExpr))
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{
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JoinExpr *j = (JoinExpr *) jtnode;
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preprocess_qual_conditions(parse, j->larg);
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preprocess_qual_conditions(parse, j->rarg);
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j->quals = preprocess_expression(parse, j->quals, EXPRKIND_QUAL);
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}
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else
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elog(ERROR, "unrecognized node type: %d",
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(int) nodeTag(jtnode));
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}
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/*--------------------
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* inheritance_planner
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* Generate a plan in the case where the result relation is an
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* inheritance set.
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*
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* We have to handle this case differently from cases where a source
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* relation is an inheritance set. Source inheritance is expanded at
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* the bottom of the plan tree (see allpaths.c), but target inheritance
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* has to be expanded at the top. The reason is that for UPDATE, each
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* target relation needs a different targetlist matching its own column
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* set. (This is not so critical for DELETE, but for simplicity we treat
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* inherited DELETE the same way.) Fortunately, the UPDATE/DELETE target
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* can never be the nullable side of an outer join, so it's OK to generate
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* the plan this way.
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*
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* parse is the querytree produced by the parser & rewriter.
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* inheritlist is an integer list of RT indexes for the result relation set.
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*
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* Returns a query plan.
|
|
*--------------------
|
|
*/
|
|
static Plan *
|
|
inheritance_planner(Query *parse, List *inheritlist)
|
|
{
|
|
int parentRTindex = parse->resultRelation;
|
|
Oid parentOID = getrelid(parentRTindex, parse->rtable);
|
|
int mainrtlength = list_length(parse->rtable);
|
|
List *subplans = NIL;
|
|
List *tlist = NIL;
|
|
ListCell *l;
|
|
|
|
foreach(l, inheritlist)
|
|
{
|
|
int childRTindex = lfirst_int(l);
|
|
Oid childOID = getrelid(childRTindex, parse->rtable);
|
|
Query *subquery;
|
|
Plan *subplan;
|
|
|
|
/* Generate modified query with this rel as target */
|
|
subquery = (Query *) adjust_inherited_attrs((Node *) parse,
|
|
parentRTindex, parentOID,
|
|
childRTindex, childOID);
|
|
/* Generate plan */
|
|
subplan = grouping_planner(subquery, 0.0 /* retrieve all tuples */ );
|
|
subplans = lappend(subplans, subplan);
|
|
|
|
/*
|
|
* XXX my goodness this next bit is ugly. Really need to think about
|
|
* ways to rein in planner's habit of scribbling on its input.
|
|
*
|
|
* Planning of the subquery might have modified the rangetable,
|
|
* either by addition of RTEs due to expansion of inherited source
|
|
* tables, or by changes of the Query structures inside subquery
|
|
* RTEs. We have to ensure that this gets propagated back to the
|
|
* master copy. However, if we aren't done planning yet, we also
|
|
* need to ensure that subsequent calls to grouping_planner have
|
|
* virgin sub-Queries to work from. So, if we are at the last
|
|
* list entry, just copy the subquery rangetable back to the master
|
|
* copy; if we are not, then extend the master copy by adding
|
|
* whatever the subquery added. (We assume these added entries
|
|
* will go untouched by the future grouping_planner calls. We are
|
|
* also 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. Did I say this is ugly?)
|
|
*/
|
|
if (lnext(l) == NULL)
|
|
parse->rtable = subquery->rtable;
|
|
else
|
|
{
|
|
int subrtlength = list_length(subquery->rtable);
|
|
|
|
if (subrtlength > mainrtlength)
|
|
{
|
|
List *subrt;
|
|
|
|
subrt = list_copy_tail(subquery->rtable, mainrtlength);
|
|
parse->rtable = list_concat(parse->rtable, subrt);
|
|
mainrtlength = subrtlength;
|
|
}
|
|
}
|
|
|
|
/* Save preprocessed tlist from first rel for use in Append */
|
|
if (tlist == NIL)
|
|
tlist = subplan->targetlist;
|
|
}
|
|
|
|
/* Save the target-relations list for the executor, too */
|
|
parse->resultRelations = inheritlist;
|
|
|
|
/* Mark result as unordered (probably unnecessary) */
|
|
parse->query_pathkeys = NIL;
|
|
|
|
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.
|
|
*
|
|
* parse is the querytree produced by the parser & rewriter.
|
|
* 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, parse->query_pathkeys is returned as the
|
|
* actual output ordering of the plan (in pathkey format).
|
|
*--------------------
|
|
*/
|
|
static Plan *
|
|
grouping_planner(Query *parse, double tuple_fraction)
|
|
{
|
|
List *tlist = parse->targetList;
|
|
Plan *result_plan;
|
|
List *current_pathkeys;
|
|
List *sort_pathkeys;
|
|
|
|
if (parse->setOperations)
|
|
{
|
|
List *set_sortclauses;
|
|
|
|
/*
|
|
* 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(parse,
|
|
&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(set_sortclauses,
|
|
result_plan->targetlist);
|
|
current_pathkeys = canonicalize_pathkeys(parse, current_pathkeys);
|
|
|
|
/*
|
|
* 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 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 is not allowed with UNION/INTERSECT/EXCEPT")));
|
|
|
|
/*
|
|
* Calculate pathkeys that represent result ordering requirements
|
|
*/
|
|
sort_pathkeys = make_pathkeys_for_sortclauses(parse->sortClause,
|
|
tlist);
|
|
sort_pathkeys = canonicalize_pathkeys(parse, sort_pathkeys);
|
|
}
|
|
else
|
|
{
|
|
/* No set operations, do regular planning */
|
|
List *sub_tlist;
|
|
List *group_pathkeys;
|
|
AttrNumber *groupColIdx = NULL;
|
|
bool need_tlist_eval = true;
|
|
QualCost tlist_cost;
|
|
double sub_tuple_fraction;
|
|
Path *cheapest_path;
|
|
Path *sorted_path;
|
|
Path *best_path;
|
|
double dNumGroups = 0;
|
|
long numGroups = 0;
|
|
AggClauseCounts agg_counts;
|
|
int numGroupCols = list_length(parse->groupClause);
|
|
bool use_hashed_grouping = false;
|
|
|
|
MemSet(&agg_counts, 0, sizeof(AggClauseCounts));
|
|
|
|
/* Preprocess targetlist */
|
|
tlist = preprocess_targetlist(parse, tlist);
|
|
|
|
/*
|
|
* Generate appropriate target list for subplan; may be different
|
|
* from tlist if grouping or aggregation is needed.
|
|
*/
|
|
sub_tlist = make_subplanTargetList(parse, tlist,
|
|
&groupColIdx, &need_tlist_eval);
|
|
|
|
/*
|
|
* Calculate pathkeys that represent grouping/ordering
|
|
* requirements
|
|
*/
|
|
group_pathkeys = make_pathkeys_for_sortclauses(parse->groupClause,
|
|
tlist);
|
|
sort_pathkeys = make_pathkeys_for_sortclauses(parse->sortClause,
|
|
tlist);
|
|
|
|
/*
|
|
* 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)
|
|
parse->query_pathkeys = group_pathkeys;
|
|
else if (parse->sortClause)
|
|
parse->query_pathkeys = sort_pathkeys;
|
|
else
|
|
parse->query_pathkeys = NIL;
|
|
|
|
/*
|
|
* Adjust tuple_fraction if we see that we are going to apply
|
|
* limiting/grouping/aggregation/etc. This is not overridable by
|
|
* the caller, since it reflects plan actions that this routine
|
|
* will certainly take, not assumptions about context.
|
|
*/
|
|
if (parse->limitCount != NULL)
|
|
{
|
|
/*
|
|
* A LIMIT clause limits the absolute number of tuples
|
|
* returned. However, if it's not a constant LIMIT then we
|
|
* have to punt; for lack of a better idea, assume 10% of the
|
|
* plan's result is wanted.
|
|
*/
|
|
double limit_fraction = 0.0;
|
|
|
|
if (IsA(parse->limitCount, Const))
|
|
{
|
|
Const *limitc = (Const *) parse->limitCount;
|
|
int32 count = DatumGetInt32(limitc->constvalue);
|
|
|
|
/*
|
|
* A NULL-constant LIMIT represents "LIMIT ALL", which we
|
|
* treat the same as no limit (ie, expect to retrieve all
|
|
* the tuples).
|
|
*/
|
|
if (!limitc->constisnull && count > 0)
|
|
{
|
|
limit_fraction = (double) count;
|
|
/* We must also consider the OFFSET, if present */
|
|
if (parse->limitOffset != NULL)
|
|
{
|
|
if (IsA(parse->limitOffset, Const))
|
|
{
|
|
int32 offset;
|
|
|
|
limitc = (Const *) parse->limitOffset;
|
|
offset = DatumGetInt32(limitc->constvalue);
|
|
if (!limitc->constisnull && offset > 0)
|
|
limit_fraction += (double) offset;
|
|
}
|
|
else
|
|
{
|
|
/* OFFSET is an expression ... punt ... */
|
|
limit_fraction = 0.10;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
else
|
|
{
|
|
/* LIMIT is an expression ... punt ... */
|
|
limit_fraction = 0.10;
|
|
}
|
|
|
|
if (limit_fraction > 0.0)
|
|
{
|
|
/*
|
|
* If we have absolute limits from both caller and LIMIT,
|
|
* use the smaller value; if one is fractional and the
|
|
* other absolute, treat the fraction as a fraction of the
|
|
* absolute value; else we can multiply the two fractions
|
|
* together.
|
|
*/
|
|
if (tuple_fraction >= 1.0)
|
|
{
|
|
if (limit_fraction >= 1.0)
|
|
{
|
|
/* both absolute */
|
|
tuple_fraction = Min(tuple_fraction, limit_fraction);
|
|
}
|
|
else
|
|
{
|
|
/* caller absolute, limit fractional */
|
|
tuple_fraction *= limit_fraction;
|
|
if (tuple_fraction < 1.0)
|
|
tuple_fraction = 1.0;
|
|
}
|
|
}
|
|
else if (tuple_fraction > 0.0)
|
|
{
|
|
if (limit_fraction >= 1.0)
|
|
{
|
|
/* caller fractional, limit absolute */
|
|
tuple_fraction *= limit_fraction;
|
|
if (tuple_fraction < 1.0)
|
|
tuple_fraction = 1.0;
|
|
}
|
|
else
|
|
{
|
|
/* both fractional */
|
|
tuple_fraction *= limit_fraction;
|
|
}
|
|
}
|
|
else
|
|
{
|
|
/* no info from caller, just use limit */
|
|
tuple_fraction = limit_fraction;
|
|
}
|
|
}
|
|
}
|
|
|
|
/*
|
|
* With grouping or aggregation, the tuple fraction to pass to
|
|
* query_planner() may be different from what it is at top level.
|
|
*/
|
|
sub_tuple_fraction = tuple_fraction;
|
|
|
|
if (parse->groupClause)
|
|
{
|
|
/*
|
|
* In GROUP BY mode, we have the little problem that we don't
|
|
* really know how many input tuples will be needed to make a
|
|
* group, so we can't translate an output LIMIT count into an
|
|
* input count. For lack of a better idea, assume 25% of the
|
|
* input data will be processed if there is any output limit.
|
|
* However, if the caller gave us a fraction rather than an
|
|
* absolute count, we can keep using that fraction (which
|
|
* amounts to assuming that all the groups are about the same
|
|
* size).
|
|
*/
|
|
if (sub_tuple_fraction >= 1.0)
|
|
sub_tuple_fraction = 0.25;
|
|
|
|
/*
|
|
* If both GROUP BY and ORDER BY are specified, we will need
|
|
* two levels of sort --- and, therefore, certainly need to
|
|
* read all the input tuples --- unless ORDER BY is a subset
|
|
* of GROUP BY. (We have not yet canonicalized the pathkeys,
|
|
* so must use the slower noncanonical comparison method.)
|
|
*/
|
|
if (parse->groupClause && parse->sortClause &&
|
|
!noncanonical_pathkeys_contained_in(sort_pathkeys,
|
|
group_pathkeys))
|
|
sub_tuple_fraction = 0.0;
|
|
}
|
|
else if (parse->hasAggs)
|
|
{
|
|
/*
|
|
* Ungrouped aggregate will certainly want all the input
|
|
* tuples.
|
|
*/
|
|
sub_tuple_fraction = 0.0;
|
|
}
|
|
else if (parse->distinctClause)
|
|
{
|
|
/*
|
|
* SELECT DISTINCT, like GROUP, will absorb an unpredictable
|
|
* number of input tuples per output tuple. Handle the same
|
|
* way.
|
|
*/
|
|
if (sub_tuple_fraction >= 1.0)
|
|
sub_tuple_fraction = 0.25;
|
|
}
|
|
|
|
/*
|
|
* Generate the best unsorted and presorted paths for this Query
|
|
* (but note there may not be any presorted path).
|
|
*/
|
|
query_planner(parse, sub_tlist, sub_tuple_fraction,
|
|
&cheapest_path, &sorted_path);
|
|
|
|
/*
|
|
* We couldn't canonicalize group_pathkeys and sort_pathkeys
|
|
* before running query_planner(), so do it now.
|
|
*/
|
|
group_pathkeys = canonicalize_pathkeys(parse, group_pathkeys);
|
|
sort_pathkeys = canonicalize_pathkeys(parse, sort_pathkeys);
|
|
|
|
/*
|
|
* If grouping, estimate the number of groups. (We can't do this
|
|
* until after running query_planner(), either.) Then decide
|
|
* whether we want to use hashed grouping.
|
|
*/
|
|
if (parse->groupClause)
|
|
{
|
|
List *groupExprs;
|
|
double cheapest_path_rows;
|
|
|
|
/*
|
|
* Beware 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;
|
|
else
|
|
cheapest_path_rows = 1; /* assume non-set result */
|
|
|
|
groupExprs = get_sortgrouplist_exprs(parse->groupClause,
|
|
parse->targetList);
|
|
dNumGroups = estimate_num_groups(parse,
|
|
groupExprs,
|
|
cheapest_path_rows);
|
|
/* Also want it as a long int --- but 'ware overflow! */
|
|
numGroups = (long) Min(dNumGroups, (double) LONG_MAX);
|
|
|
|
use_hashed_grouping =
|
|
choose_hashed_grouping(parse, tuple_fraction,
|
|
cheapest_path, sorted_path,
|
|
sort_pathkeys, group_pathkeys,
|
|
dNumGroups, &agg_counts);
|
|
}
|
|
|
|
/*
|
|
* 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(parse,
|
|
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(parse, 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(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);
|
|
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(parse, 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(parse,
|
|
tlist,
|
|
(List *) parse->havingQual,
|
|
AGG_HASHED,
|
|
numGroupCols,
|
|
groupColIdx,
|
|
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(parse,
|
|
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(parse,
|
|
tlist,
|
|
(List *) parse->havingQual,
|
|
aggstrategy,
|
|
numGroupCols,
|
|
groupColIdx,
|
|
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(parse,
|
|
parse->groupClause,
|
|
groupColIdx,
|
|
result_plan);
|
|
current_pathkeys = group_pathkeys;
|
|
}
|
|
|
|
result_plan = (Plan *) make_group(parse,
|
|
tlist,
|
|
(List *) parse->havingQual,
|
|
numGroupCols,
|
|
groupColIdx,
|
|
dNumGroups,
|
|
result_plan);
|
|
/* The Group node won't change sort ordering */
|
|
}
|
|
else if (parse->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(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_sortclauses(parse,
|
|
parse->sortClause,
|
|
result_plan);
|
|
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,
|
|
* it's reasonable to assume the UNIQUE filter has effects
|
|
* comparable to GROUP BY.
|
|
*/
|
|
if (!parse->groupClause && !parse->hasHavingQual && !parse->hasAggs)
|
|
{
|
|
List *distinctExprs;
|
|
|
|
distinctExprs = get_sortgrouplist_exprs(parse->distinctClause,
|
|
parse->targetList);
|
|
result_plan->plan_rows = estimate_num_groups(parse,
|
|
distinctExprs,
|
|
result_plan->plan_rows);
|
|
}
|
|
}
|
|
|
|
/*
|
|
* Finally, if there is a LIMIT/OFFSET clause, add the LIMIT node.
|
|
*/
|
|
if (parse->limitOffset || parse->limitCount)
|
|
{
|
|
result_plan = (Plan *) make_limit(result_plan,
|
|
parse->limitOffset,
|
|
parse->limitCount);
|
|
}
|
|
|
|
/*
|
|
* Return the actual output ordering in query_pathkeys for possible
|
|
* use by an outer query level.
|
|
*/
|
|
parse->query_pathkeys = current_pathkeys;
|
|
|
|
return result_plan;
|
|
}
|
|
|
|
/*
|
|
* choose_hashed_grouping - should we use hashed grouping?
|
|
*/
|
|
static bool
|
|
choose_hashed_grouping(Query *parse, double tuple_fraction,
|
|
Path *cheapest_path, Path *sorted_path,
|
|
List *sort_pathkeys, List *group_pathkeys,
|
|
double dNumGroups, AggClauseCounts *agg_counts)
|
|
{
|
|
int numGroupCols = list_length(parse->groupClause);
|
|
double cheapest_path_rows;
|
|
int cheapest_path_width;
|
|
Size hashentrysize;
|
|
List *current_pathkeys;
|
|
Path hashed_p;
|
|
Path sorted_p;
|
|
|
|
/*
|
|
* Check can't-do-it conditions, including whether the grouping operators
|
|
* are hashjoinable.
|
|
*
|
|
* 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;
|
|
if (!hash_safe_grouping(parse))
|
|
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 = cheapest_path_width;
|
|
/* 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, parse, 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 (sort_pathkeys)
|
|
cost_sort(&hashed_p, parse, sort_pathkeys, hashed_p.total_cost,
|
|
dNumGroups, cheapest_path_width);
|
|
|
|
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(group_pathkeys,
|
|
current_pathkeys))
|
|
{
|
|
cost_sort(&sorted_p, parse, group_pathkeys, sorted_p.total_cost,
|
|
cheapest_path_rows, cheapest_path_width);
|
|
current_pathkeys = group_pathkeys;
|
|
}
|
|
|
|
if (parse->hasAggs)
|
|
cost_agg(&sorted_p, parse, AGG_SORTED, agg_counts->numAggs,
|
|
numGroupCols, dNumGroups,
|
|
sorted_p.startup_cost, sorted_p.total_cost,
|
|
cheapest_path_rows);
|
|
else
|
|
cost_group(&sorted_p, parse, numGroupCols, dNumGroups,
|
|
sorted_p.startup_cost, sorted_p.total_cost,
|
|
cheapest_path_rows);
|
|
/* The Agg or Group node will preserve ordering */
|
|
if (sort_pathkeys &&
|
|
!pathkeys_contained_in(sort_pathkeys, current_pathkeys))
|
|
cost_sort(&sorted_p, parse, sort_pathkeys, sorted_p.total_cost,
|
|
dNumGroups, cheapest_path_width);
|
|
|
|
/*
|
|
* 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;
|
|
}
|
|
|
|
/*
|
|
* hash_safe_grouping - are grouping operators hashable?
|
|
*
|
|
* We assume hashed aggregation will work if the datatype's equality operator
|
|
* is marked hashjoinable.
|
|
*/
|
|
static bool
|
|
hash_safe_grouping(Query *parse)
|
|
{
|
|
ListCell *gl;
|
|
|
|
foreach(gl, parse->groupClause)
|
|
{
|
|
GroupClause *grpcl = (GroupClause *) lfirst(gl);
|
|
TargetEntry *tle = get_sortgroupclause_tle(grpcl, parse->targetList);
|
|
Operator optup;
|
|
bool oprcanhash;
|
|
|
|
optup = equality_oper(exprType((Node *) tle->expr), true);
|
|
if (!optup)
|
|
return false;
|
|
oprcanhash = ((Form_pg_operator) GETSTRUCT(optup))->oprcanhash;
|
|
ReleaseSysCache(optup);
|
|
if (!oprcanhash)
|
|
return false;
|
|
}
|
|
return true;
|
|
}
|
|
|
|
/*---------------
|
|
* 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
|
|
* replace_vars_with_subplan_refs() 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.
|
|
*
|
|
* 'parse' is the query being processed.
|
|
* '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(Query *parse,
|
|
List *tlist,
|
|
AttrNumber **groupColIdx,
|
|
bool *need_tlist_eval)
|
|
{
|
|
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 && !parse->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(Query *parse,
|
|
List *tlist,
|
|
List *sub_tlist,
|
|
AttrNumber *groupColIdx)
|
|
{
|
|
int keyno = 0;
|
|
ListCell *gl;
|
|
|
|
/*
|
|
* No work unless grouping.
|
|
*/
|
|
if (!parse->groupClause)
|
|
{
|
|
Assert(groupColIdx == NULL);
|
|
return;
|
|
}
|
|
Assert(groupColIdx != NULL);
|
|
|
|
foreach(gl, 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;
|
|
}
|