7406 lines
235 KiB
C
7406 lines
235 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) 1996-2019, 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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* src/backend/optimizer/plan/planner.c
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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 <math.h>
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#include "access/genam.h"
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#include "access/htup_details.h"
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#include "access/parallel.h"
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#include "access/sysattr.h"
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#include "access/table.h"
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#include "access/xact.h"
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#include "catalog/pg_constraint.h"
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#include "catalog/pg_inherits.h"
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#include "catalog/pg_proc.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 "foreign/fdwapi.h"
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#include "jit/jit.h"
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#include "lib/bipartite_match.h"
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#include "lib/knapsack.h"
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#include "miscadmin.h"
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#include "nodes/makefuncs.h"
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#include "nodes/nodeFuncs.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/appendinfo.h"
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#include "optimizer/clauses.h"
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#include "optimizer/cost.h"
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#include "optimizer/inherit.h"
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#include "optimizer/optimizer.h"
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#include "optimizer/paramassign.h"
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#include "optimizer/pathnode.h"
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#include "optimizer/paths.h"
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#include "optimizer/plancat.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 "parser/analyze.h"
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#include "parser/parse_agg.h"
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#include "parser/parsetree.h"
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#include "partitioning/partdesc.h"
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#include "rewrite/rewriteManip.h"
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#include "storage/dsm_impl.h"
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#include "utils/lsyscache.h"
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#include "utils/rel.h"
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#include "utils/selfuncs.h"
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#include "utils/syscache.h"
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/* GUC parameters */
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double cursor_tuple_fraction = DEFAULT_CURSOR_TUPLE_FRACTION;
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int force_parallel_mode = FORCE_PARALLEL_OFF;
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bool parallel_leader_participation = true;
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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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/* Hook for plugins to get control when grouping_planner() plans upper rels */
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create_upper_paths_hook_type create_upper_paths_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_RTFUNC_LATERAL 3
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#define EXPRKIND_VALUES 4
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#define EXPRKIND_VALUES_LATERAL 5
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#define EXPRKIND_LIMIT 6
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#define EXPRKIND_APPINFO 7
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#define EXPRKIND_PHV 8
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#define EXPRKIND_TABLESAMPLE 9
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#define EXPRKIND_ARBITER_ELEM 10
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#define EXPRKIND_TABLEFUNC 11
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#define EXPRKIND_TABLEFUNC_LATERAL 12
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/* Passthrough data for standard_qp_callback */
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typedef struct
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{
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List *activeWindows; /* active windows, if any */
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List *groupClause; /* overrides parse->groupClause */
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} standard_qp_extra;
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/*
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* Data specific to grouping sets
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*/
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typedef struct
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{
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List *rollups;
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List *hash_sets_idx;
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double dNumHashGroups;
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bool any_hashable;
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Bitmapset *unsortable_refs;
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Bitmapset *unhashable_refs;
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List *unsortable_sets;
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int *tleref_to_colnum_map;
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} grouping_sets_data;
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/*
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* Temporary structure for use during WindowClause reordering in order to be
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* able to sort WindowClauses on partitioning/ordering prefix.
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*/
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typedef struct
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{
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WindowClause *wc;
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List *uniqueOrder; /* A List of unique ordering/partitioning
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* clauses per Window */
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} WindowClauseSortData;
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/* Local functions */
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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 void inheritance_planner(PlannerInfo *root);
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static void grouping_planner(PlannerInfo *root, bool inheritance_update,
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double tuple_fraction);
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static grouping_sets_data *preprocess_grouping_sets(PlannerInfo *root);
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static List *remap_to_groupclause_idx(List *groupClause, List *gsets,
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int *tleref_to_colnum_map);
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static void preprocess_rowmarks(PlannerInfo *root);
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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 void remove_useless_groupby_columns(PlannerInfo *root);
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static List *preprocess_groupclause(PlannerInfo *root, List *force);
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static List *extract_rollup_sets(List *groupingSets);
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static List *reorder_grouping_sets(List *groupingSets, List *sortclause);
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static void standard_qp_callback(PlannerInfo *root, void *extra);
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static double get_number_of_groups(PlannerInfo *root,
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double path_rows,
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grouping_sets_data *gd,
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List *target_list);
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static RelOptInfo *create_grouping_paths(PlannerInfo *root,
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RelOptInfo *input_rel,
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PathTarget *target,
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bool target_parallel_safe,
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const AggClauseCosts *agg_costs,
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grouping_sets_data *gd);
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static bool is_degenerate_grouping(PlannerInfo *root);
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static void create_degenerate_grouping_paths(PlannerInfo *root,
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RelOptInfo *input_rel,
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RelOptInfo *grouped_rel);
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static RelOptInfo *make_grouping_rel(PlannerInfo *root, RelOptInfo *input_rel,
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PathTarget *target, bool target_parallel_safe,
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Node *havingQual);
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static void create_ordinary_grouping_paths(PlannerInfo *root,
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RelOptInfo *input_rel,
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RelOptInfo *grouped_rel,
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const AggClauseCosts *agg_costs,
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grouping_sets_data *gd,
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GroupPathExtraData *extra,
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RelOptInfo **partially_grouped_rel_p);
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static void consider_groupingsets_paths(PlannerInfo *root,
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RelOptInfo *grouped_rel,
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Path *path,
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bool is_sorted,
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bool can_hash,
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grouping_sets_data *gd,
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const AggClauseCosts *agg_costs,
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double dNumGroups);
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static RelOptInfo *create_window_paths(PlannerInfo *root,
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RelOptInfo *input_rel,
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PathTarget *input_target,
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PathTarget *output_target,
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bool output_target_parallel_safe,
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WindowFuncLists *wflists,
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List *activeWindows);
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static void create_one_window_path(PlannerInfo *root,
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RelOptInfo *window_rel,
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Path *path,
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PathTarget *input_target,
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PathTarget *output_target,
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WindowFuncLists *wflists,
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List *activeWindows);
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static RelOptInfo *create_distinct_paths(PlannerInfo *root,
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RelOptInfo *input_rel);
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static RelOptInfo *create_ordered_paths(PlannerInfo *root,
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RelOptInfo *input_rel,
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PathTarget *target,
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bool target_parallel_safe,
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double limit_tuples);
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static PathTarget *make_group_input_target(PlannerInfo *root,
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PathTarget *final_target);
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static PathTarget *make_partial_grouping_target(PlannerInfo *root,
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PathTarget *grouping_target,
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Node *havingQual);
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static List *postprocess_setop_tlist(List *new_tlist, List *orig_tlist);
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static List *select_active_windows(PlannerInfo *root, WindowFuncLists *wflists);
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static PathTarget *make_window_input_target(PlannerInfo *root,
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PathTarget *final_target,
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List *activeWindows);
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static List *make_pathkeys_for_window(PlannerInfo *root, WindowClause *wc,
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List *tlist);
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static PathTarget *make_sort_input_target(PlannerInfo *root,
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PathTarget *final_target,
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bool *have_postponed_srfs);
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static void adjust_paths_for_srfs(PlannerInfo *root, RelOptInfo *rel,
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List *targets, List *targets_contain_srfs);
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static void add_paths_to_grouping_rel(PlannerInfo *root, RelOptInfo *input_rel,
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RelOptInfo *grouped_rel,
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RelOptInfo *partially_grouped_rel,
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const AggClauseCosts *agg_costs,
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grouping_sets_data *gd,
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double dNumGroups,
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GroupPathExtraData *extra);
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static RelOptInfo *create_partial_grouping_paths(PlannerInfo *root,
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RelOptInfo *grouped_rel,
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RelOptInfo *input_rel,
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grouping_sets_data *gd,
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GroupPathExtraData *extra,
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bool force_rel_creation);
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static void gather_grouping_paths(PlannerInfo *root, RelOptInfo *rel);
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static bool can_partial_agg(PlannerInfo *root,
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const AggClauseCosts *agg_costs);
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static void apply_scanjoin_target_to_paths(PlannerInfo *root,
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RelOptInfo *rel,
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List *scanjoin_targets,
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List *scanjoin_targets_contain_srfs,
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bool scanjoin_target_parallel_safe,
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bool tlist_same_exprs);
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static void create_partitionwise_grouping_paths(PlannerInfo *root,
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RelOptInfo *input_rel,
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RelOptInfo *grouped_rel,
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RelOptInfo *partially_grouped_rel,
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const AggClauseCosts *agg_costs,
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grouping_sets_data *gd,
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PartitionwiseAggregateType patype,
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GroupPathExtraData *extra);
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static bool group_by_has_partkey(RelOptInfo *input_rel,
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List *targetList,
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List *groupClause);
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static int common_prefix_cmp(const void *a, const void *b);
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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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RelOptInfo *final_rel;
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Path *best_path;
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Plan *top_plan;
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ListCell *lp,
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*lr;
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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->subplans = NIL;
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glob->subroots = NIL;
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glob->rewindPlanIDs = NULL;
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glob->finalrtable = NIL;
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glob->finalrowmarks = NIL;
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glob->resultRelations = NIL;
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glob->rootResultRelations = NIL;
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glob->relationOids = NIL;
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glob->invalItems = NIL;
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glob->paramExecTypes = NIL;
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glob->lastPHId = 0;
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glob->lastRowMarkId = 0;
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glob->lastPlanNodeId = 0;
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glob->transientPlan = false;
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glob->dependsOnRole = false;
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/*
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* Assess whether it's feasible to use parallel mode for this query. We
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* can't do this in a standalone backend, or if the command will try to
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* modify any data, or if this is a cursor operation, or if GUCs are set
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* to values that don't permit parallelism, or if parallel-unsafe
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* functions are present in the query tree.
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*
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* (Note that we do allow CREATE TABLE AS, SELECT INTO, and CREATE
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* MATERIALIZED VIEW to use parallel plans, but this is safe only because
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* the command is writing into a completely new table which workers won't
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* be able to see. If the workers could see the table, the fact that
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* group locking would cause them to ignore the leader's heavyweight
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* relation extension lock and GIN page locks would make this unsafe.
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* We'll have to fix that somehow if we want to allow parallel inserts in
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* general; updates and deletes have additional problems especially around
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* combo CIDs.)
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*
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* For now, we don't try to use parallel mode if we're running inside a
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* parallel worker. We might eventually be able to relax this
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* restriction, but for now it seems best not to have parallel workers
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* trying to create their own parallel workers.
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*/
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if ((cursorOptions & CURSOR_OPT_PARALLEL_OK) != 0 &&
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IsUnderPostmaster &&
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parse->commandType == CMD_SELECT &&
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!parse->hasModifyingCTE &&
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max_parallel_workers_per_gather > 0 &&
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!IsParallelWorker())
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{
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/* all the cheap tests pass, so scan the query tree */
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glob->maxParallelHazard = max_parallel_hazard(parse);
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glob->parallelModeOK = (glob->maxParallelHazard != PROPARALLEL_UNSAFE);
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}
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else
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{
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/* skip the query tree scan, just assume it's unsafe */
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glob->maxParallelHazard = PROPARALLEL_UNSAFE;
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glob->parallelModeOK = false;
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}
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/*
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* glob->parallelModeNeeded is normally set to false here and changed to
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* true during plan creation if a Gather or Gather Merge plan is actually
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* created (cf. create_gather_plan, create_gather_merge_plan).
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*
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* However, if force_parallel_mode = on or force_parallel_mode = regress,
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* then we impose parallel mode whenever it's safe to do so, even if the
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* final plan doesn't use parallelism. It's not safe to do so if the
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* query contains anything parallel-unsafe; parallelModeOK will be false
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* in that case. Note that parallelModeOK can't change after this point.
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* Otherwise, everything in the query is either parallel-safe or
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* parallel-restricted, and in either case it should be OK to impose
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* parallel-mode restrictions. If that ends up breaking something, then
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* either some function the user included in the query is incorrectly
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* labelled as parallel-safe or parallel-restricted when in reality it's
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* parallel-unsafe, or else the query planner itself has a bug.
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*/
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glob->parallelModeNeeded = glob->parallelModeOK &&
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(force_parallel_mode != FORCE_PARALLEL_OFF);
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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 is often the case that he doesn't want 'em
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* all, or would prefer a fast-start plan anyway so that he can
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* process some of the tuples sooner. Use a GUC parameter to decide
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* what fraction to optimize for.
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*/
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tuple_fraction = cursor_tuple_fraction;
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/*
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* We document cursor_tuple_fraction as simply being a fraction, which
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* means the edge cases 0 and 1 have to be treated specially here. We
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* convert 1 to 0 ("all the tuples") and 0 to a very small fraction.
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*/
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if (tuple_fraction >= 1.0)
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tuple_fraction = 0.0;
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else if (tuple_fraction <= 0.0)
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tuple_fraction = 1e-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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root = subquery_planner(glob, parse, NULL,
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false, tuple_fraction);
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/* Select best Path and turn it into a Plan */
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final_rel = fetch_upper_rel(root, UPPERREL_FINAL, NULL);
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best_path = get_cheapest_fractional_path(final_rel, tuple_fraction);
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top_plan = create_plan(root, best_path);
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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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/*
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* Optionally add a Gather node for testing purposes, provided this is
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* actually a safe thing to do.
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*/
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if (force_parallel_mode != FORCE_PARALLEL_OFF && top_plan->parallel_safe)
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{
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Gather *gather = makeNode(Gather);
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/*
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* If there are any initPlans attached to the formerly-top plan node,
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* move them up to the Gather node; same as we do for Material node in
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* materialize_finished_plan.
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*/
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gather->plan.initPlan = top_plan->initPlan;
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top_plan->initPlan = NIL;
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gather->plan.targetlist = top_plan->targetlist;
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gather->plan.qual = NIL;
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gather->plan.lefttree = top_plan;
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gather->plan.righttree = NULL;
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gather->num_workers = 1;
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gather->single_copy = true;
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gather->invisible = (force_parallel_mode == FORCE_PARALLEL_REGRESS);
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/*
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* Since this Gather has no parallel-aware descendants to signal to,
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* we don't need a rescan Param.
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*/
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gather->rescan_param = -1;
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/*
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* Ideally we'd use cost_gather here, but setting up dummy path data
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* to satisfy it doesn't seem much cleaner than knowing what it does.
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*/
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gather->plan.startup_cost = top_plan->startup_cost +
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parallel_setup_cost;
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gather->plan.total_cost = top_plan->total_cost +
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parallel_setup_cost + parallel_tuple_cost * top_plan->plan_rows;
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gather->plan.plan_rows = top_plan->plan_rows;
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gather->plan.plan_width = top_plan->plan_width;
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gather->plan.parallel_aware = false;
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gather->plan.parallel_safe = false;
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/* use parallel mode for parallel plans. */
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root->glob->parallelModeNeeded = true;
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top_plan = &gather->plan;
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}
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|
|
/*
|
|
* If any Params were generated, run through the plan tree and compute
|
|
* each plan node's extParam/allParam sets. Ideally we'd merge this into
|
|
* set_plan_references' tree traversal, but for now it has to be separate
|
|
* because we need to visit subplans before not after main plan.
|
|
*/
|
|
if (glob->paramExecTypes != NIL)
|
|
{
|
|
Assert(list_length(glob->subplans) == list_length(glob->subroots));
|
|
forboth(lp, glob->subplans, lr, glob->subroots)
|
|
{
|
|
Plan *subplan = (Plan *) lfirst(lp);
|
|
PlannerInfo *subroot = lfirst_node(PlannerInfo, lr);
|
|
|
|
SS_finalize_plan(subroot, subplan);
|
|
}
|
|
SS_finalize_plan(root, top_plan);
|
|
}
|
|
|
|
/* final cleanup of the plan */
|
|
Assert(glob->finalrtable == NIL);
|
|
Assert(glob->finalrowmarks == NIL);
|
|
Assert(glob->resultRelations == NIL);
|
|
Assert(glob->rootResultRelations == NIL);
|
|
top_plan = set_plan_references(root, top_plan);
|
|
/* ... and the subplans (both regular subplans and initplans) */
|
|
Assert(list_length(glob->subplans) == list_length(glob->subroots));
|
|
forboth(lp, glob->subplans, lr, glob->subroots)
|
|
{
|
|
Plan *subplan = (Plan *) lfirst(lp);
|
|
PlannerInfo *subroot = lfirst_node(PlannerInfo, lr);
|
|
|
|
lfirst(lp) = set_plan_references(subroot, subplan);
|
|
}
|
|
|
|
/* build the PlannedStmt result */
|
|
result = makeNode(PlannedStmt);
|
|
|
|
result->commandType = parse->commandType;
|
|
result->queryId = parse->queryId;
|
|
result->hasReturning = (parse->returningList != NIL);
|
|
result->hasModifyingCTE = parse->hasModifyingCTE;
|
|
result->canSetTag = parse->canSetTag;
|
|
result->transientPlan = glob->transientPlan;
|
|
result->dependsOnRole = glob->dependsOnRole;
|
|
result->parallelModeNeeded = glob->parallelModeNeeded;
|
|
result->planTree = top_plan;
|
|
result->rtable = glob->finalrtable;
|
|
result->resultRelations = glob->resultRelations;
|
|
result->rootResultRelations = glob->rootResultRelations;
|
|
result->subplans = glob->subplans;
|
|
result->rewindPlanIDs = glob->rewindPlanIDs;
|
|
result->rowMarks = glob->finalrowmarks;
|
|
result->relationOids = glob->relationOids;
|
|
result->invalItems = glob->invalItems;
|
|
result->paramExecTypes = glob->paramExecTypes;
|
|
/* utilityStmt should be null, but we might as well copy it */
|
|
result->utilityStmt = parse->utilityStmt;
|
|
result->stmt_location = parse->stmt_location;
|
|
result->stmt_len = parse->stmt_len;
|
|
|
|
result->jitFlags = PGJIT_NONE;
|
|
if (jit_enabled && jit_above_cost >= 0 &&
|
|
top_plan->total_cost > jit_above_cost)
|
|
{
|
|
result->jitFlags |= PGJIT_PERFORM;
|
|
|
|
/*
|
|
* Decide how much effort should be put into generating better code.
|
|
*/
|
|
if (jit_optimize_above_cost >= 0 &&
|
|
top_plan->total_cost > jit_optimize_above_cost)
|
|
result->jitFlags |= PGJIT_OPT3;
|
|
if (jit_inline_above_cost >= 0 &&
|
|
top_plan->total_cost > jit_inline_above_cost)
|
|
result->jitFlags |= PGJIT_INLINE;
|
|
|
|
/*
|
|
* Decide which operations should be JITed.
|
|
*/
|
|
if (jit_expressions)
|
|
result->jitFlags |= PGJIT_EXPR;
|
|
if (jit_tuple_deforming)
|
|
result->jitFlags |= PGJIT_DEFORM;
|
|
}
|
|
|
|
if (glob->partition_directory != NULL)
|
|
DestroyPartitionDirectory(glob->partition_directory);
|
|
|
|
return result;
|
|
}
|
|
|
|
|
|
/*--------------------
|
|
* subquery_planner
|
|
* Invokes the planner on a subquery. We recurse to here for each
|
|
* sub-SELECT found in the query tree.
|
|
*
|
|
* glob is the global state for the current planner run.
|
|
* parse is the querytree produced by the parser & rewriter.
|
|
* parent_root is the immediate parent Query's info (NULL at the top level).
|
|
* hasRecursion is true if this is a recursive WITH query.
|
|
* tuple_fraction is the fraction of tuples we expect will be retrieved.
|
|
* tuple_fraction is interpreted as explained for grouping_planner, below.
|
|
*
|
|
* Basically, this routine does the stuff that should only be done once
|
|
* per Query object. It then calls grouping_planner. At one time,
|
|
* grouping_planner could be invoked recursively on the same Query object;
|
|
* that's not currently true, but we keep the separation between the two
|
|
* routines anyway, in case we need it again someday.
|
|
*
|
|
* subquery_planner will be called recursively to handle sub-Query nodes
|
|
* found within the query's expressions and rangetable.
|
|
*
|
|
* Returns the PlannerInfo struct ("root") that contains all data generated
|
|
* while planning the subquery. In particular, the Path(s) attached to
|
|
* the (UPPERREL_FINAL, NULL) upperrel represent our conclusions about the
|
|
* cheapest way(s) to implement the query. The top level will select the
|
|
* best Path and pass it through createplan.c to produce a finished Plan.
|
|
*--------------------
|
|
*/
|
|
PlannerInfo *
|
|
subquery_planner(PlannerGlobal *glob, Query *parse,
|
|
PlannerInfo *parent_root,
|
|
bool hasRecursion, double tuple_fraction)
|
|
{
|
|
PlannerInfo *root;
|
|
List *newWithCheckOptions;
|
|
List *newHaving;
|
|
bool hasOuterJoins;
|
|
bool hasResultRTEs;
|
|
RelOptInfo *final_rel;
|
|
ListCell *l;
|
|
|
|
/* Create a PlannerInfo data structure for this subquery */
|
|
root = makeNode(PlannerInfo);
|
|
root->parse = parse;
|
|
root->glob = glob;
|
|
root->query_level = parent_root ? parent_root->query_level + 1 : 1;
|
|
root->parent_root = parent_root;
|
|
root->plan_params = NIL;
|
|
root->outer_params = NULL;
|
|
root->planner_cxt = CurrentMemoryContext;
|
|
root->init_plans = NIL;
|
|
root->cte_plan_ids = NIL;
|
|
root->multiexpr_params = NIL;
|
|
root->eq_classes = NIL;
|
|
root->ec_merging_done = false;
|
|
root->append_rel_list = NIL;
|
|
root->rowMarks = NIL;
|
|
memset(root->upper_rels, 0, sizeof(root->upper_rels));
|
|
memset(root->upper_targets, 0, sizeof(root->upper_targets));
|
|
root->processed_tlist = NIL;
|
|
root->grouping_map = NULL;
|
|
root->minmax_aggs = NIL;
|
|
root->qual_security_level = 0;
|
|
root->inhTargetKind = INHKIND_NONE;
|
|
root->hasRecursion = hasRecursion;
|
|
if (hasRecursion)
|
|
root->wt_param_id = assign_special_exec_param(root);
|
|
else
|
|
root->wt_param_id = -1;
|
|
root->non_recursive_path = NULL;
|
|
root->partColsUpdated = false;
|
|
|
|
/*
|
|
* If there is a WITH list, process each WITH query and either convert it
|
|
* to RTE_SUBQUERY RTE(s) or build an initplan SubPlan structure for it.
|
|
*/
|
|
if (parse->cteList)
|
|
SS_process_ctes(root);
|
|
|
|
/*
|
|
* If the FROM clause is empty, replace it with a dummy RTE_RESULT RTE, so
|
|
* that we don't need so many special cases to deal with that situation.
|
|
*/
|
|
replace_empty_jointree(parse);
|
|
|
|
/*
|
|
* Look for ANY and EXISTS SubLinks in WHERE and JOIN/ON clauses, and try
|
|
* to transform them into joins. Note that this step does not descend
|
|
* into subqueries; if we pull up any subqueries below, their SubLinks are
|
|
* processed just before pulling them up.
|
|
*/
|
|
if (parse->hasSubLinks)
|
|
pull_up_sublinks(root);
|
|
|
|
/*
|
|
* Scan the rangetable for function RTEs, do const-simplification on them,
|
|
* and then inline them if possible (producing subqueries that might get
|
|
* pulled up next). Recursion issues here are handled in the same way as
|
|
* for SubLinks.
|
|
*/
|
|
preprocess_function_rtes(root);
|
|
|
|
/*
|
|
* Check to see if any subqueries in the jointree can be merged into this
|
|
* query.
|
|
*/
|
|
pull_up_subqueries(root);
|
|
|
|
/*
|
|
* If this is a simple UNION ALL query, flatten it into an appendrel. We
|
|
* do this now because it requires applying pull_up_subqueries to the leaf
|
|
* queries of the UNION ALL, which weren't touched above because they
|
|
* weren't referenced by the jointree (they will be after we do this).
|
|
*/
|
|
if (parse->setOperations)
|
|
flatten_simple_union_all(root);
|
|
|
|
/*
|
|
* Survey the rangetable to see what kinds of entries are present. We can
|
|
* skip some later processing if relevant SQL features are not used; for
|
|
* example if there are no JOIN RTEs we can avoid the expense of doing
|
|
* flatten_join_alias_vars(). This must be done after we have finished
|
|
* adding rangetable entries, of course. (Note: actually, processing of
|
|
* inherited or partitioned rels can cause RTEs for their child tables to
|
|
* get added later; but those must all be RTE_RELATION entries, so they
|
|
* don't invalidate the conclusions drawn here.)
|
|
*/
|
|
root->hasJoinRTEs = false;
|
|
root->hasLateralRTEs = false;
|
|
hasOuterJoins = false;
|
|
hasResultRTEs = false;
|
|
foreach(l, parse->rtable)
|
|
{
|
|
RangeTblEntry *rte = lfirst_node(RangeTblEntry, l);
|
|
|
|
switch (rte->rtekind)
|
|
{
|
|
case RTE_RELATION:
|
|
if (rte->inh)
|
|
{
|
|
/*
|
|
* Check to see if the relation actually has any children;
|
|
* if not, clear the inh flag so we can treat it as a
|
|
* plain base relation.
|
|
*
|
|
* Note: this could give a false-positive result, if the
|
|
* rel once had children but no longer does. We used to
|
|
* be able to clear rte->inh later on when we discovered
|
|
* that, but no more; we have to handle such cases as
|
|
* full-fledged inheritance.
|
|
*/
|
|
rte->inh = has_subclass(rte->relid);
|
|
}
|
|
break;
|
|
case RTE_JOIN:
|
|
root->hasJoinRTEs = true;
|
|
if (IS_OUTER_JOIN(rte->jointype))
|
|
hasOuterJoins = true;
|
|
break;
|
|
case RTE_RESULT:
|
|
hasResultRTEs = true;
|
|
break;
|
|
default:
|
|
/* No work here for other RTE types */
|
|
break;
|
|
}
|
|
|
|
if (rte->lateral)
|
|
root->hasLateralRTEs = true;
|
|
|
|
/*
|
|
* We can also determine the maximum security level required for any
|
|
* securityQuals now. Addition of inheritance-child RTEs won't affect
|
|
* this, because child tables don't have their own securityQuals; see
|
|
* expand_single_inheritance_child().
|
|
*/
|
|
if (rte->securityQuals)
|
|
root->qual_security_level = Max(root->qual_security_level,
|
|
list_length(rte->securityQuals));
|
|
}
|
|
|
|
/*
|
|
* Preprocess RowMark information. We need to do this after subquery
|
|
* pullup, so that all base relations are present.
|
|
*/
|
|
preprocess_rowmarks(root);
|
|
|
|
/*
|
|
* Set hasHavingQual to remember if HAVING clause is present. Needed
|
|
* because preprocess_expression will reduce a constant-true condition to
|
|
* an empty qual list ... but "HAVING TRUE" is not a semantic no-op.
|
|
*/
|
|
root->hasHavingQual = (parse->havingQual != NULL);
|
|
|
|
/* Clear this flag; might get set in distribute_qual_to_rels */
|
|
root->hasPseudoConstantQuals = false;
|
|
|
|
/*
|
|
* Do expression preprocessing on targetlist and quals, as well as other
|
|
* random expressions in the querytree. Note that we do not need to
|
|
* handle sort/group expressions explicitly, because they are actually
|
|
* part of the targetlist.
|
|
*/
|
|
parse->targetList = (List *)
|
|
preprocess_expression(root, (Node *) parse->targetList,
|
|
EXPRKIND_TARGET);
|
|
|
|
/* Constant-folding might have removed all set-returning functions */
|
|
if (parse->hasTargetSRFs)
|
|
parse->hasTargetSRFs = expression_returns_set((Node *) parse->targetList);
|
|
|
|
newWithCheckOptions = NIL;
|
|
foreach(l, parse->withCheckOptions)
|
|
{
|
|
WithCheckOption *wco = lfirst_node(WithCheckOption, l);
|
|
|
|
wco->qual = preprocess_expression(root, wco->qual,
|
|
EXPRKIND_QUAL);
|
|
if (wco->qual != NULL)
|
|
newWithCheckOptions = lappend(newWithCheckOptions, wco);
|
|
}
|
|
parse->withCheckOptions = newWithCheckOptions;
|
|
|
|
parse->returningList = (List *)
|
|
preprocess_expression(root, (Node *) parse->returningList,
|
|
EXPRKIND_TARGET);
|
|
|
|
preprocess_qual_conditions(root, (Node *) parse->jointree);
|
|
|
|
parse->havingQual = preprocess_expression(root, parse->havingQual,
|
|
EXPRKIND_QUAL);
|
|
|
|
foreach(l, parse->windowClause)
|
|
{
|
|
WindowClause *wc = lfirst_node(WindowClause, l);
|
|
|
|
/* partitionClause/orderClause are sort/group expressions */
|
|
wc->startOffset = preprocess_expression(root, wc->startOffset,
|
|
EXPRKIND_LIMIT);
|
|
wc->endOffset = preprocess_expression(root, wc->endOffset,
|
|
EXPRKIND_LIMIT);
|
|
}
|
|
|
|
parse->limitOffset = preprocess_expression(root, parse->limitOffset,
|
|
EXPRKIND_LIMIT);
|
|
parse->limitCount = preprocess_expression(root, parse->limitCount,
|
|
EXPRKIND_LIMIT);
|
|
|
|
if (parse->onConflict)
|
|
{
|
|
parse->onConflict->arbiterElems = (List *)
|
|
preprocess_expression(root,
|
|
(Node *) parse->onConflict->arbiterElems,
|
|
EXPRKIND_ARBITER_ELEM);
|
|
parse->onConflict->arbiterWhere =
|
|
preprocess_expression(root,
|
|
parse->onConflict->arbiterWhere,
|
|
EXPRKIND_QUAL);
|
|
parse->onConflict->onConflictSet = (List *)
|
|
preprocess_expression(root,
|
|
(Node *) parse->onConflict->onConflictSet,
|
|
EXPRKIND_TARGET);
|
|
parse->onConflict->onConflictWhere =
|
|
preprocess_expression(root,
|
|
parse->onConflict->onConflictWhere,
|
|
EXPRKIND_QUAL);
|
|
/* exclRelTlist contains only Vars, so no preprocessing needed */
|
|
}
|
|
|
|
root->append_rel_list = (List *)
|
|
preprocess_expression(root, (Node *) root->append_rel_list,
|
|
EXPRKIND_APPINFO);
|
|
|
|
/* Also need to preprocess expressions within RTEs */
|
|
foreach(l, parse->rtable)
|
|
{
|
|
RangeTblEntry *rte = lfirst_node(RangeTblEntry, l);
|
|
int kind;
|
|
ListCell *lcsq;
|
|
|
|
if (rte->rtekind == RTE_RELATION)
|
|
{
|
|
if (rte->tablesample)
|
|
rte->tablesample = (TableSampleClause *)
|
|
preprocess_expression(root,
|
|
(Node *) rte->tablesample,
|
|
EXPRKIND_TABLESAMPLE);
|
|
}
|
|
else if (rte->rtekind == RTE_SUBQUERY)
|
|
{
|
|
/*
|
|
* We don't want to do all preprocessing yet on the subquery's
|
|
* expressions, since that will happen when we plan it. But if it
|
|
* contains any join aliases of our level, those have to get
|
|
* expanded now, because planning of the subquery won't do it.
|
|
* That's only possible if the subquery is LATERAL.
|
|
*/
|
|
if (rte->lateral && root->hasJoinRTEs)
|
|
rte->subquery = (Query *)
|
|
flatten_join_alias_vars(root->parse,
|
|
(Node *) rte->subquery);
|
|
}
|
|
else if (rte->rtekind == RTE_FUNCTION)
|
|
{
|
|
/* Preprocess the function expression(s) fully */
|
|
kind = rte->lateral ? EXPRKIND_RTFUNC_LATERAL : EXPRKIND_RTFUNC;
|
|
rte->functions = (List *)
|
|
preprocess_expression(root, (Node *) rte->functions, kind);
|
|
}
|
|
else if (rte->rtekind == RTE_TABLEFUNC)
|
|
{
|
|
/* Preprocess the function expression(s) fully */
|
|
kind = rte->lateral ? EXPRKIND_TABLEFUNC_LATERAL : EXPRKIND_TABLEFUNC;
|
|
rte->tablefunc = (TableFunc *)
|
|
preprocess_expression(root, (Node *) rte->tablefunc, kind);
|
|
}
|
|
else if (rte->rtekind == RTE_VALUES)
|
|
{
|
|
/* Preprocess the values lists fully */
|
|
kind = rte->lateral ? EXPRKIND_VALUES_LATERAL : EXPRKIND_VALUES;
|
|
rte->values_lists = (List *)
|
|
preprocess_expression(root, (Node *) rte->values_lists, kind);
|
|
}
|
|
|
|
/*
|
|
* Process each element of the securityQuals list as if it were a
|
|
* separate qual expression (as indeed it is). We need to do it this
|
|
* way to get proper canonicalization of AND/OR structure. Note that
|
|
* this converts each element into an implicit-AND sublist.
|
|
*/
|
|
foreach(lcsq, rte->securityQuals)
|
|
{
|
|
lfirst(lcsq) = preprocess_expression(root,
|
|
(Node *) lfirst(lcsq),
|
|
EXPRKIND_QUAL);
|
|
}
|
|
}
|
|
|
|
/*
|
|
* Now that we are done preprocessing expressions, and in particular done
|
|
* flattening join alias variables, get rid of the joinaliasvars lists.
|
|
* They no longer match what expressions in the rest of the tree look
|
|
* like, because we have not preprocessed expressions in those lists (and
|
|
* do not want to; for example, expanding a SubLink there would result in
|
|
* a useless unreferenced subplan). Leaving them in place simply creates
|
|
* a hazard for later scans of the tree. We could try to prevent that by
|
|
* using QTW_IGNORE_JOINALIASES in every tree scan done after this point,
|
|
* but that doesn't sound very reliable.
|
|
*/
|
|
if (root->hasJoinRTEs)
|
|
{
|
|
foreach(l, parse->rtable)
|
|
{
|
|
RangeTblEntry *rte = lfirst_node(RangeTblEntry, l);
|
|
|
|
rte->joinaliasvars = NIL;
|
|
}
|
|
}
|
|
|
|
/*
|
|
* In some cases we may want to transfer a HAVING clause into WHERE. We
|
|
* cannot do so if the HAVING clause contains aggregates (obviously) or
|
|
* volatile functions (since a HAVING clause is supposed to be executed
|
|
* only once per group). We also can't do this if there are any nonempty
|
|
* grouping sets; moving such a clause into WHERE would potentially change
|
|
* the results, if any referenced column isn't present in all the grouping
|
|
* sets. (If there are only empty grouping sets, then the HAVING clause
|
|
* must be degenerate as discussed below.)
|
|
*
|
|
* Also, it may be that the clause is so expensive to execute that we're
|
|
* better off doing it only once per group, despite the loss of
|
|
* selectivity. This is hard to estimate short of doing the entire
|
|
* planning process twice, so we use a heuristic: clauses containing
|
|
* subplans are left in HAVING. Otherwise, we move or copy the HAVING
|
|
* clause into WHERE, in hopes of eliminating tuples before aggregation
|
|
* instead of after.
|
|
*
|
|
* If the query has explicit grouping then we can simply move such a
|
|
* clause into WHERE; any group that fails the clause will not be in the
|
|
* output because none of its tuples will reach the grouping or
|
|
* aggregation stage. Otherwise we must have a degenerate (variable-free)
|
|
* HAVING clause, which we put in WHERE so that query_planner() can use it
|
|
* in a gating Result node, but also keep in HAVING to ensure that we
|
|
* don't emit a bogus aggregated row. (This could be done better, but it
|
|
* seems not worth optimizing.)
|
|
*
|
|
* Note that both havingQual and parse->jointree->quals are in
|
|
* implicitly-ANDed-list form at this point, even though they are declared
|
|
* as Node *.
|
|
*/
|
|
newHaving = NIL;
|
|
foreach(l, (List *) parse->havingQual)
|
|
{
|
|
Node *havingclause = (Node *) lfirst(l);
|
|
|
|
if ((parse->groupClause && parse->groupingSets) ||
|
|
contain_agg_clause(havingclause) ||
|
|
contain_volatile_functions(havingclause) ||
|
|
contain_subplans(havingclause))
|
|
{
|
|
/* keep it in HAVING */
|
|
newHaving = lappend(newHaving, havingclause);
|
|
}
|
|
else if (parse->groupClause && !parse->groupingSets)
|
|
{
|
|
/* move it to WHERE */
|
|
parse->jointree->quals = (Node *)
|
|
lappend((List *) parse->jointree->quals, havingclause);
|
|
}
|
|
else
|
|
{
|
|
/* put a copy in WHERE, keep it in HAVING */
|
|
parse->jointree->quals = (Node *)
|
|
lappend((List *) parse->jointree->quals,
|
|
copyObject(havingclause));
|
|
newHaving = lappend(newHaving, havingclause);
|
|
}
|
|
}
|
|
parse->havingQual = (Node *) newHaving;
|
|
|
|
/* Remove any redundant GROUP BY columns */
|
|
remove_useless_groupby_columns(root);
|
|
|
|
/*
|
|
* If we have any outer joins, try to reduce them to plain inner joins.
|
|
* This step is most easily done after we've done expression
|
|
* preprocessing.
|
|
*/
|
|
if (hasOuterJoins)
|
|
reduce_outer_joins(root);
|
|
|
|
/*
|
|
* If we have any RTE_RESULT relations, see if they can be deleted from
|
|
* the jointree. This step is most effectively done after we've done
|
|
* expression preprocessing and outer join reduction.
|
|
*/
|
|
if (hasResultRTEs)
|
|
remove_useless_result_rtes(root);
|
|
|
|
/*
|
|
* Do the main planning. If we have an inherited target relation, that
|
|
* needs special processing, else go straight to grouping_planner.
|
|
*/
|
|
if (parse->resultRelation &&
|
|
rt_fetch(parse->resultRelation, parse->rtable)->inh)
|
|
inheritance_planner(root);
|
|
else
|
|
grouping_planner(root, false, tuple_fraction);
|
|
|
|
/*
|
|
* Capture the set of outer-level param IDs we have access to, for use in
|
|
* extParam/allParam calculations later.
|
|
*/
|
|
SS_identify_outer_params(root);
|
|
|
|
/*
|
|
* If any initPlans were created in this query level, adjust the surviving
|
|
* Paths' costs and parallel-safety flags to account for them. The
|
|
* initPlans won't actually get attached to the plan tree till
|
|
* create_plan() runs, but we must include their effects now.
|
|
*/
|
|
final_rel = fetch_upper_rel(root, UPPERREL_FINAL, NULL);
|
|
SS_charge_for_initplans(root, final_rel);
|
|
|
|
/*
|
|
* Make sure we've identified the cheapest Path for the final rel. (By
|
|
* doing this here not in grouping_planner, we include initPlan costs in
|
|
* the decision, though it's unlikely that will change anything.)
|
|
*/
|
|
set_cheapest(final_rel);
|
|
|
|
return root;
|
|
}
|
|
|
|
/*
|
|
* preprocess_expression
|
|
* Do subquery_planner's preprocessing work for an expression,
|
|
* which can be a targetlist, a WHERE clause (including JOIN/ON
|
|
* conditions), a HAVING clause, or a few other things.
|
|
*/
|
|
static Node *
|
|
preprocess_expression(PlannerInfo *root, Node *expr, int kind)
|
|
{
|
|
/*
|
|
* Fall out quickly if expression is empty. This occurs often enough to
|
|
* be worth checking. Note that null->null is the correct conversion for
|
|
* implicit-AND result format, too.
|
|
*/
|
|
if (expr == NULL)
|
|
return NULL;
|
|
|
|
/*
|
|
* If the query has any join RTEs, replace join alias variables with
|
|
* base-relation variables. We must do this first, since any expressions
|
|
* we may extract from the joinaliasvars lists have not been preprocessed.
|
|
* For example, if we did this after sublink processing, sublinks expanded
|
|
* out from join aliases would not get processed. But we can skip this in
|
|
* non-lateral RTE functions, VALUES lists, and TABLESAMPLE clauses, since
|
|
* they can't contain any Vars of the current query level.
|
|
*/
|
|
if (root->hasJoinRTEs &&
|
|
!(kind == EXPRKIND_RTFUNC ||
|
|
kind == EXPRKIND_VALUES ||
|
|
kind == EXPRKIND_TABLESAMPLE ||
|
|
kind == EXPRKIND_TABLEFUNC))
|
|
expr = flatten_join_alias_vars(root->parse, expr);
|
|
|
|
/*
|
|
* Simplify constant expressions. For function RTEs, this was already
|
|
* done by preprocess_function_rtes ... but we have to do it again if the
|
|
* RTE is LATERAL and might have contained join alias variables.
|
|
*
|
|
* Note: an essential effect of this is to convert named-argument function
|
|
* calls to positional notation and insert the current actual values of
|
|
* any default arguments for functions. To ensure that happens, we *must*
|
|
* process all expressions here. Previous PG versions sometimes skipped
|
|
* const-simplification if it didn't seem worth the trouble, but we can't
|
|
* do that anymore.
|
|
*
|
|
* Note: this also flattens nested AND and OR expressions into N-argument
|
|
* 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.
|
|
*/
|
|
if (!(kind == EXPRKIND_RTFUNC ||
|
|
(kind == EXPRKIND_RTFUNC_LATERAL && !root->hasJoinRTEs)))
|
|
expr = eval_const_expressions(root, expr);
|
|
|
|
/*
|
|
* If it's a qual or havingQual, canonicalize it.
|
|
*/
|
|
if (kind == EXPRKIND_QUAL)
|
|
{
|
|
expr = (Node *) canonicalize_qual((Expr *) expr, false);
|
|
|
|
#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));
|
|
}
|
|
|
|
/*
|
|
* preprocess_phv_expression
|
|
* Do preprocessing on a PlaceHolderVar expression that's been pulled up.
|
|
*
|
|
* If a LATERAL subquery references an output of another subquery, and that
|
|
* output must be wrapped in a PlaceHolderVar because of an intermediate outer
|
|
* join, then we'll push the PlaceHolderVar expression down into the subquery
|
|
* and later pull it back up during find_lateral_references, which runs after
|
|
* subquery_planner has preprocessed all the expressions that were in the
|
|
* current query level to start with. So we need to preprocess it then.
|
|
*/
|
|
Expr *
|
|
preprocess_phv_expression(PlannerInfo *root, Expr *expr)
|
|
{
|
|
return (Expr *) preprocess_expression(root, (Node *) expr, EXPRKIND_PHV);
|
|
}
|
|
|
|
/*
|
|
* inheritance_planner
|
|
* Generate Paths 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. 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 nothing; the useful output is in the Paths we attach to
|
|
* the (UPPERREL_FINAL, NULL) upperrel stored in *root.
|
|
*
|
|
* Note that we have not done set_cheapest() on the final rel; it's convenient
|
|
* to leave this to the caller.
|
|
*/
|
|
static void
|
|
inheritance_planner(PlannerInfo *root)
|
|
{
|
|
Query *parse = root->parse;
|
|
int top_parentRTindex = parse->resultRelation;
|
|
List *select_rtable;
|
|
List *select_appinfos;
|
|
List *child_appinfos;
|
|
List *old_child_rtis;
|
|
List *new_child_rtis;
|
|
Bitmapset *subqueryRTindexes;
|
|
Index next_subquery_rti;
|
|
int nominalRelation = -1;
|
|
Index rootRelation = 0;
|
|
List *final_rtable = NIL;
|
|
List *final_rowmarks = NIL;
|
|
int save_rel_array_size = 0;
|
|
RelOptInfo **save_rel_array = NULL;
|
|
AppendRelInfo **save_append_rel_array = NULL;
|
|
List *subpaths = NIL;
|
|
List *subroots = NIL;
|
|
List *resultRelations = NIL;
|
|
List *withCheckOptionLists = NIL;
|
|
List *returningLists = NIL;
|
|
List *rowMarks;
|
|
RelOptInfo *final_rel;
|
|
ListCell *lc;
|
|
ListCell *lc2;
|
|
Index rti;
|
|
RangeTblEntry *parent_rte;
|
|
Bitmapset *parent_relids;
|
|
Query **parent_parses;
|
|
|
|
/* Should only get here for UPDATE or DELETE */
|
|
Assert(parse->commandType == CMD_UPDATE ||
|
|
parse->commandType == CMD_DELETE);
|
|
|
|
/*
|
|
* We generate a modified instance of the original Query for each target
|
|
* relation, plan that, and put all the plans into a list that will be
|
|
* controlled by a single ModifyTable node. All the instances share the
|
|
* same rangetable, but each instance must have its own set of subquery
|
|
* RTEs within the finished rangetable because (1) they are likely to get
|
|
* scribbled on during planning, and (2) it's not inconceivable that
|
|
* subqueries could get planned differently in different cases. We need
|
|
* not create duplicate copies of other RTE kinds, in particular not the
|
|
* target relations, because they don't have either of those issues. Not
|
|
* having to duplicate the target relations is important because doing so
|
|
* (1) would result in a rangetable of length O(N^2) for N targets, with
|
|
* at least O(N^3) work expended here; and (2) would greatly complicate
|
|
* management of the rowMarks list.
|
|
*
|
|
* To begin with, generate a bitmapset of the relids of the subquery RTEs.
|
|
*/
|
|
subqueryRTindexes = NULL;
|
|
rti = 1;
|
|
foreach(lc, parse->rtable)
|
|
{
|
|
RangeTblEntry *rte = lfirst_node(RangeTblEntry, lc);
|
|
|
|
if (rte->rtekind == RTE_SUBQUERY)
|
|
subqueryRTindexes = bms_add_member(subqueryRTindexes, rti);
|
|
rti++;
|
|
}
|
|
|
|
/*
|
|
* If the parent RTE is a partitioned table, we should use that as the
|
|
* nominal target relation, because the RTEs added for partitioned tables
|
|
* (including the root parent) as child members of the inheritance set do
|
|
* not appear anywhere else in the plan, so the confusion explained below
|
|
* for non-partitioning inheritance cases is not possible.
|
|
*/
|
|
parent_rte = rt_fetch(top_parentRTindex, parse->rtable);
|
|
Assert(parent_rte->inh);
|
|
if (parent_rte->relkind == RELKIND_PARTITIONED_TABLE)
|
|
{
|
|
nominalRelation = top_parentRTindex;
|
|
rootRelation = top_parentRTindex;
|
|
}
|
|
|
|
/*
|
|
* Before generating the real per-child-relation plans, do a cycle of
|
|
* planning as though the query were a SELECT. The objective here is to
|
|
* find out which child relations need to be processed, using the same
|
|
* expansion and pruning logic as for a SELECT. We'll then pull out the
|
|
* RangeTblEntry-s generated for the child rels, and make use of the
|
|
* AppendRelInfo entries for them to guide the real planning. (This is
|
|
* rather inefficient; we could perhaps stop short of making a full Path
|
|
* tree. But this whole function is inefficient and slated for
|
|
* destruction, so let's not contort query_planner for that.)
|
|
*/
|
|
{
|
|
PlannerInfo *subroot;
|
|
|
|
/*
|
|
* Flat-copy the PlannerInfo to prevent modification of the original.
|
|
*/
|
|
subroot = makeNode(PlannerInfo);
|
|
memcpy(subroot, root, sizeof(PlannerInfo));
|
|
|
|
/*
|
|
* Make a deep copy of the parsetree for this planning cycle to mess
|
|
* around with, and change it to look like a SELECT. (Hack alert: the
|
|
* target RTE still has updatedCols set if this is an UPDATE, so that
|
|
* expand_partitioned_rtentry will correctly update
|
|
* subroot->partColsUpdated.)
|
|
*/
|
|
subroot->parse = copyObject(root->parse);
|
|
|
|
subroot->parse->commandType = CMD_SELECT;
|
|
subroot->parse->resultRelation = 0;
|
|
|
|
/*
|
|
* Ensure the subroot has its own copy of the original
|
|
* append_rel_list, since it'll be scribbled on. (Note that at this
|
|
* point, the list only contains AppendRelInfos for flattened UNION
|
|
* ALL subqueries.)
|
|
*/
|
|
subroot->append_rel_list = copyObject(root->append_rel_list);
|
|
|
|
/*
|
|
* Better make a private copy of the rowMarks, too.
|
|
*/
|
|
subroot->rowMarks = copyObject(root->rowMarks);
|
|
|
|
/* There shouldn't be any OJ info to translate, as yet */
|
|
Assert(subroot->join_info_list == NIL);
|
|
/* and we haven't created PlaceHolderInfos, either */
|
|
Assert(subroot->placeholder_list == NIL);
|
|
|
|
/* Generate Path(s) for accessing this result relation */
|
|
grouping_planner(subroot, true, 0.0 /* retrieve all tuples */ );
|
|
|
|
/* Extract the info we need. */
|
|
select_rtable = subroot->parse->rtable;
|
|
select_appinfos = subroot->append_rel_list;
|
|
|
|
/*
|
|
* We need to propagate partColsUpdated back, too. (The later
|
|
* planning cycles will not set this because they won't run
|
|
* expand_partitioned_rtentry for the UPDATE target.)
|
|
*/
|
|
root->partColsUpdated = subroot->partColsUpdated;
|
|
}
|
|
|
|
/*----------
|
|
* Since only one rangetable can exist in the final plan, we need to make
|
|
* sure that it contains all the RTEs needed for any child plan. This is
|
|
* complicated by the need to use separate subquery RTEs for each child.
|
|
* We arrange the final rtable as follows:
|
|
* 1. All original rtable entries (with their original RT indexes).
|
|
* 2. All the relation RTEs generated for children of the target table.
|
|
* 3. Subquery RTEs for children after the first. We need N * (K - 1)
|
|
* RT slots for this, if there are N subqueries and K child tables.
|
|
* 4. Additional RTEs generated during the child planning runs, such as
|
|
* children of inheritable RTEs other than the target table.
|
|
* We assume that each child planning run will create an identical set
|
|
* of type-4 RTEs.
|
|
*
|
|
* So the next thing to do is append the type-2 RTEs (the target table's
|
|
* children) to the original rtable. We look through select_appinfos
|
|
* to find them.
|
|
*
|
|
* To identify which AppendRelInfos are relevant as we thumb through
|
|
* select_appinfos, we need to look for both direct and indirect children
|
|
* of top_parentRTindex, so we use a bitmap of known parent relids.
|
|
* expand_inherited_rtentry() always processes a parent before any of that
|
|
* parent's children, so we should see an intermediate parent before its
|
|
* children.
|
|
*----------
|
|
*/
|
|
child_appinfos = NIL;
|
|
old_child_rtis = NIL;
|
|
new_child_rtis = NIL;
|
|
parent_relids = bms_make_singleton(top_parentRTindex);
|
|
foreach(lc, select_appinfos)
|
|
{
|
|
AppendRelInfo *appinfo = lfirst_node(AppendRelInfo, lc);
|
|
RangeTblEntry *child_rte;
|
|
|
|
/* append_rel_list contains all append rels; ignore others */
|
|
if (!bms_is_member(appinfo->parent_relid, parent_relids))
|
|
continue;
|
|
|
|
/* remember relevant AppendRelInfos for use below */
|
|
child_appinfos = lappend(child_appinfos, appinfo);
|
|
|
|
/* extract RTE for this child rel */
|
|
child_rte = rt_fetch(appinfo->child_relid, select_rtable);
|
|
|
|
/* and append it to the original rtable */
|
|
parse->rtable = lappend(parse->rtable, child_rte);
|
|
|
|
/* remember child's index in the SELECT rtable */
|
|
old_child_rtis = lappend_int(old_child_rtis, appinfo->child_relid);
|
|
|
|
/* and its new index in the final rtable */
|
|
new_child_rtis = lappend_int(new_child_rtis, list_length(parse->rtable));
|
|
|
|
/* if child is itself partitioned, update parent_relids */
|
|
if (child_rte->inh)
|
|
{
|
|
Assert(child_rte->relkind == RELKIND_PARTITIONED_TABLE);
|
|
parent_relids = bms_add_member(parent_relids, appinfo->child_relid);
|
|
}
|
|
}
|
|
|
|
/*
|
|
* It's possible that the RTIs we just assigned for the child rels in the
|
|
* final rtable are different from what they were in the SELECT query.
|
|
* Adjust the AppendRelInfos so that they will correctly map RT indexes to
|
|
* the final indexes. We can do this left-to-right since no child rel's
|
|
* final RT index could be greater than what it had in the SELECT query.
|
|
*/
|
|
forboth(lc, old_child_rtis, lc2, new_child_rtis)
|
|
{
|
|
int old_child_rti = lfirst_int(lc);
|
|
int new_child_rti = lfirst_int(lc2);
|
|
|
|
if (old_child_rti == new_child_rti)
|
|
continue; /* nothing to do */
|
|
|
|
Assert(old_child_rti > new_child_rti);
|
|
|
|
ChangeVarNodes((Node *) child_appinfos,
|
|
old_child_rti, new_child_rti, 0);
|
|
}
|
|
|
|
/*
|
|
* Now set up rangetable entries for subqueries for additional children
|
|
* (the first child will just use the original ones). These all have to
|
|
* look more or less real, or EXPLAIN will get unhappy; so we just make
|
|
* them all clones of the original subqueries.
|
|
*/
|
|
next_subquery_rti = list_length(parse->rtable) + 1;
|
|
if (subqueryRTindexes != NULL)
|
|
{
|
|
int n_children = list_length(child_appinfos);
|
|
|
|
while (n_children-- > 1)
|
|
{
|
|
int oldrti = -1;
|
|
|
|
while ((oldrti = bms_next_member(subqueryRTindexes, oldrti)) >= 0)
|
|
{
|
|
RangeTblEntry *subqrte;
|
|
|
|
subqrte = rt_fetch(oldrti, parse->rtable);
|
|
parse->rtable = lappend(parse->rtable, copyObject(subqrte));
|
|
}
|
|
}
|
|
}
|
|
|
|
/*
|
|
* The query for each child is obtained by translating the query for its
|
|
* immediate parent, since the AppendRelInfo data we have shows deltas
|
|
* between parents and children. We use the parent_parses array to
|
|
* remember the appropriate query trees. This is indexed by parent relid.
|
|
* Since the maximum number of parents is limited by the number of RTEs in
|
|
* the SELECT query, we use that number to allocate the array. An extra
|
|
* entry is needed since relids start from 1.
|
|
*/
|
|
parent_parses = (Query **) palloc0((list_length(select_rtable) + 1) *
|
|
sizeof(Query *));
|
|
parent_parses[top_parentRTindex] = parse;
|
|
|
|
/*
|
|
* And now we can get on with generating a plan for each child table.
|
|
*/
|
|
foreach(lc, child_appinfos)
|
|
{
|
|
AppendRelInfo *appinfo = lfirst_node(AppendRelInfo, lc);
|
|
Index this_subquery_rti = next_subquery_rti;
|
|
Query *parent_parse;
|
|
PlannerInfo *subroot;
|
|
RangeTblEntry *child_rte;
|
|
RelOptInfo *sub_final_rel;
|
|
Path *subpath;
|
|
|
|
/*
|
|
* expand_inherited_rtentry() always processes a parent before any of
|
|
* that parent's children, so the parent query for this relation
|
|
* should already be available.
|
|
*/
|
|
parent_parse = parent_parses[appinfo->parent_relid];
|
|
Assert(parent_parse != NULL);
|
|
|
|
/*
|
|
* We need a working copy of the PlannerInfo so that we can control
|
|
* propagation of information back to the main copy.
|
|
*/
|
|
subroot = makeNode(PlannerInfo);
|
|
memcpy(subroot, root, sizeof(PlannerInfo));
|
|
|
|
/*
|
|
* Generate modified query with this rel as target. We first apply
|
|
* adjust_appendrel_attrs, which copies the Query and changes
|
|
* references to the parent RTE to refer to the current child RTE,
|
|
* then fool around with subquery RTEs.
|
|
*/
|
|
subroot->parse = (Query *)
|
|
adjust_appendrel_attrs(subroot,
|
|
(Node *) parent_parse,
|
|
1, &appinfo);
|
|
|
|
/*
|
|
* If there are securityQuals attached to the parent, move them to the
|
|
* child rel (they've already been transformed properly for that).
|
|
*/
|
|
parent_rte = rt_fetch(appinfo->parent_relid, subroot->parse->rtable);
|
|
child_rte = rt_fetch(appinfo->child_relid, subroot->parse->rtable);
|
|
child_rte->securityQuals = parent_rte->securityQuals;
|
|
parent_rte->securityQuals = NIL;
|
|
|
|
/*
|
|
* HACK: setting this to a value other than INHKIND_NONE signals to
|
|
* relation_excluded_by_constraints() to treat the result relation as
|
|
* being an appendrel member.
|
|
*/
|
|
subroot->inhTargetKind =
|
|
(rootRelation != 0) ? INHKIND_PARTITIONED : INHKIND_INHERITED;
|
|
|
|
/*
|
|
* If this child is further partitioned, remember it as a parent.
|
|
* Since a partitioned table does not have any data, we don't need to
|
|
* create a plan for it, and we can stop processing it here. We do,
|
|
* however, need to remember its modified PlannerInfo for use when
|
|
* processing its children, since we'll update their varnos based on
|
|
* the delta from immediate parent to child, not from top to child.
|
|
*
|
|
* Note: a very non-obvious point is that we have not yet added
|
|
* duplicate subquery RTEs to the subroot's rtable. We mustn't,
|
|
* because then its children would have two sets of duplicates,
|
|
* confusing matters.
|
|
*/
|
|
if (child_rte->inh)
|
|
{
|
|
Assert(child_rte->relkind == RELKIND_PARTITIONED_TABLE);
|
|
parent_parses[appinfo->child_relid] = subroot->parse;
|
|
continue;
|
|
}
|
|
|
|
/*
|
|
* Set the nominal target relation of the ModifyTable node if not
|
|
* already done. If the target is a partitioned table, we already set
|
|
* nominalRelation to refer to the partition root, above. For
|
|
* non-partitioned inheritance cases, we'll use the first child
|
|
* relation (even if it's excluded) as the nominal target relation.
|
|
* Because of the way expand_inherited_rtentry works, that should be
|
|
* the RTE representing the parent table in its role as a simple
|
|
* member of the inheritance set.
|
|
*
|
|
* It would be logically cleaner to *always* use the inheritance
|
|
* parent RTE as the nominal relation; but that RTE is not otherwise
|
|
* referenced in the plan in the non-partitioned inheritance case.
|
|
* Instead the duplicate child RTE created by expand_inherited_rtentry
|
|
* is used elsewhere in the plan, so using the original parent RTE
|
|
* would give rise to confusing use of multiple aliases in EXPLAIN
|
|
* output for what the user will think is the "same" table. OTOH,
|
|
* it's not a problem in the partitioned inheritance case, because
|
|
* there is no duplicate RTE for the parent.
|
|
*/
|
|
if (nominalRelation < 0)
|
|
nominalRelation = appinfo->child_relid;
|
|
|
|
/*
|
|
* As above, each child plan run needs its own append_rel_list and
|
|
* rowmarks, which should start out as pristine copies of the
|
|
* originals. There can't be any references to UPDATE/DELETE target
|
|
* rels in them; but there could be subquery references, which we'll
|
|
* fix up in a moment.
|
|
*/
|
|
subroot->append_rel_list = copyObject(root->append_rel_list);
|
|
subroot->rowMarks = copyObject(root->rowMarks);
|
|
|
|
/*
|
|
* If this isn't the first child Query, adjust Vars and jointree
|
|
* entries to reference the appropriate set of subquery RTEs.
|
|
*/
|
|
if (final_rtable != NIL && subqueryRTindexes != NULL)
|
|
{
|
|
int oldrti = -1;
|
|
|
|
while ((oldrti = bms_next_member(subqueryRTindexes, oldrti)) >= 0)
|
|
{
|
|
Index newrti = next_subquery_rti++;
|
|
|
|
ChangeVarNodes((Node *) subroot->parse, oldrti, newrti, 0);
|
|
ChangeVarNodes((Node *) subroot->append_rel_list,
|
|
oldrti, newrti, 0);
|
|
ChangeVarNodes((Node *) subroot->rowMarks, oldrti, newrti, 0);
|
|
}
|
|
}
|
|
|
|
/* There shouldn't be any OJ info to translate, as yet */
|
|
Assert(subroot->join_info_list == NIL);
|
|
/* and we haven't created PlaceHolderInfos, either */
|
|
Assert(subroot->placeholder_list == NIL);
|
|
|
|
/* Generate Path(s) for accessing this result relation */
|
|
grouping_planner(subroot, true, 0.0 /* retrieve all tuples */ );
|
|
|
|
/*
|
|
* Select cheapest path in case there's more than one. We always run
|
|
* modification queries to conclusion, so we care only for the
|
|
* cheapest-total path.
|
|
*/
|
|
sub_final_rel = fetch_upper_rel(subroot, UPPERREL_FINAL, NULL);
|
|
set_cheapest(sub_final_rel);
|
|
subpath = sub_final_rel->cheapest_total_path;
|
|
|
|
/*
|
|
* If this child rel was excluded by constraint exclusion, exclude it
|
|
* from the result plan.
|
|
*/
|
|
if (IS_DUMMY_REL(sub_final_rel))
|
|
continue;
|
|
|
|
/*
|
|
* If this is the first non-excluded child, its post-planning rtable
|
|
* becomes the initial contents of final_rtable; otherwise, copy its
|
|
* modified subquery RTEs into final_rtable, to ensure we have sane
|
|
* copies of those. Also save the first non-excluded child's version
|
|
* of the rowmarks list; we assume all children will end up with
|
|
* equivalent versions of that.
|
|
*/
|
|
if (final_rtable == NIL)
|
|
{
|
|
final_rtable = subroot->parse->rtable;
|
|
final_rowmarks = subroot->rowMarks;
|
|
}
|
|
else
|
|
{
|
|
Assert(list_length(final_rtable) ==
|
|
list_length(subroot->parse->rtable));
|
|
if (subqueryRTindexes != NULL)
|
|
{
|
|
int oldrti = -1;
|
|
|
|
while ((oldrti = bms_next_member(subqueryRTindexes, oldrti)) >= 0)
|
|
{
|
|
Index newrti = this_subquery_rti++;
|
|
RangeTblEntry *subqrte;
|
|
ListCell *newrticell;
|
|
|
|
subqrte = rt_fetch(newrti, subroot->parse->rtable);
|
|
newrticell = list_nth_cell(final_rtable, newrti - 1);
|
|
lfirst(newrticell) = subqrte;
|
|
}
|
|
}
|
|
}
|
|
|
|
/*
|
|
* We need to collect all the RelOptInfos from all child plans into
|
|
* the main PlannerInfo, since setrefs.c will need them. We use the
|
|
* last child's simple_rel_array, so we have to propagate forward the
|
|
* RelOptInfos that were already built in previous children.
|
|
*/
|
|
Assert(subroot->simple_rel_array_size >= save_rel_array_size);
|
|
for (rti = 1; rti < save_rel_array_size; rti++)
|
|
{
|
|
RelOptInfo *brel = save_rel_array[rti];
|
|
|
|
if (brel)
|
|
subroot->simple_rel_array[rti] = brel;
|
|
}
|
|
save_rel_array_size = subroot->simple_rel_array_size;
|
|
save_rel_array = subroot->simple_rel_array;
|
|
save_append_rel_array = subroot->append_rel_array;
|
|
|
|
/*
|
|
* Make sure any initplans from this rel get into the outer list. Note
|
|
* we're effectively assuming all children generate the same
|
|
* init_plans.
|
|
*/
|
|
root->init_plans = subroot->init_plans;
|
|
|
|
/* Build list of sub-paths */
|
|
subpaths = lappend(subpaths, subpath);
|
|
|
|
/* Build list of modified subroots, too */
|
|
subroots = lappend(subroots, subroot);
|
|
|
|
/* Build list of target-relation RT indexes */
|
|
resultRelations = lappend_int(resultRelations, appinfo->child_relid);
|
|
|
|
/* Build lists of per-relation WCO and RETURNING targetlists */
|
|
if (parse->withCheckOptions)
|
|
withCheckOptionLists = lappend(withCheckOptionLists,
|
|
subroot->parse->withCheckOptions);
|
|
if (parse->returningList)
|
|
returningLists = lappend(returningLists,
|
|
subroot->parse->returningList);
|
|
|
|
Assert(!parse->onConflict);
|
|
}
|
|
|
|
/* Result path must go into outer query's FINAL upperrel */
|
|
final_rel = fetch_upper_rel(root, UPPERREL_FINAL, NULL);
|
|
|
|
/*
|
|
* We don't currently worry about setting final_rel's consider_parallel
|
|
* flag in this case, nor about allowing FDWs or create_upper_paths_hook
|
|
* to get control here.
|
|
*/
|
|
|
|
if (subpaths == NIL)
|
|
{
|
|
/*
|
|
* We managed to exclude every child rel, so generate a dummy path
|
|
* representing the empty set. Although it's clear that no data will
|
|
* be updated or deleted, we will still need to have a ModifyTable
|
|
* node so that any statement triggers are executed. (This could be
|
|
* cleaner if we fixed nodeModifyTable.c to support zero child nodes,
|
|
* but that probably wouldn't be a net win.)
|
|
*/
|
|
Path *dummy_path;
|
|
|
|
/* tlist processing never got done, either */
|
|
root->processed_tlist = preprocess_targetlist(root);
|
|
final_rel->reltarget = create_pathtarget(root, root->processed_tlist);
|
|
|
|
/* Make a dummy path, cf set_dummy_rel_pathlist() */
|
|
dummy_path = (Path *) create_append_path(NULL, final_rel, NIL, NIL,
|
|
NIL, NULL, 0, false,
|
|
NIL, -1);
|
|
|
|
/* These lists must be nonempty to make a valid ModifyTable node */
|
|
subpaths = list_make1(dummy_path);
|
|
subroots = list_make1(root);
|
|
resultRelations = list_make1_int(parse->resultRelation);
|
|
if (parse->withCheckOptions)
|
|
withCheckOptionLists = list_make1(parse->withCheckOptions);
|
|
if (parse->returningList)
|
|
returningLists = list_make1(parse->returningList);
|
|
/* Disable tuple routing, too, just to be safe */
|
|
root->partColsUpdated = false;
|
|
}
|
|
else
|
|
{
|
|
/*
|
|
* Put back the final adjusted rtable into the master copy of the
|
|
* Query. (We mustn't do this if we found no non-excluded children,
|
|
* since we never saved an adjusted rtable at all.)
|
|
*/
|
|
parse->rtable = final_rtable;
|
|
root->simple_rel_array_size = save_rel_array_size;
|
|
root->simple_rel_array = save_rel_array;
|
|
root->append_rel_array = save_append_rel_array;
|
|
|
|
/* Must reconstruct master's simple_rte_array, too */
|
|
root->simple_rte_array = (RangeTblEntry **)
|
|
palloc0((list_length(final_rtable) + 1) * sizeof(RangeTblEntry *));
|
|
rti = 1;
|
|
foreach(lc, final_rtable)
|
|
{
|
|
RangeTblEntry *rte = lfirst_node(RangeTblEntry, lc);
|
|
|
|
root->simple_rte_array[rti++] = rte;
|
|
}
|
|
|
|
/* Put back adjusted rowmarks, too */
|
|
root->rowMarks = final_rowmarks;
|
|
}
|
|
|
|
/*
|
|
* If there was a FOR [KEY] UPDATE/SHARE clause, the LockRows node will
|
|
* have dealt with fetching non-locked marked rows, else we need to have
|
|
* ModifyTable do that.
|
|
*/
|
|
if (parse->rowMarks)
|
|
rowMarks = NIL;
|
|
else
|
|
rowMarks = root->rowMarks;
|
|
|
|
/* Create Path representing a ModifyTable to do the UPDATE/DELETE work */
|
|
add_path(final_rel, (Path *)
|
|
create_modifytable_path(root, final_rel,
|
|
parse->commandType,
|
|
parse->canSetTag,
|
|
nominalRelation,
|
|
rootRelation,
|
|
root->partColsUpdated,
|
|
resultRelations,
|
|
subpaths,
|
|
subroots,
|
|
withCheckOptionLists,
|
|
returningLists,
|
|
rowMarks,
|
|
NULL,
|
|
assign_special_exec_param(root)));
|
|
}
|
|
|
|
/*--------------------
|
|
* grouping_planner
|
|
* Perform planning steps related to grouping, aggregation, etc.
|
|
*
|
|
* This function adds all required top-level processing to the scan/join
|
|
* Path(s) produced by query_planner.
|
|
*
|
|
* If inheritance_update is true, we're being called from inheritance_planner
|
|
* and should not include a ModifyTable step in the resulting Path(s).
|
|
* (inheritance_planner will create a single ModifyTable node covering all the
|
|
* target tables.)
|
|
*
|
|
* 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 nothing; the useful output is in the Paths we attach to the
|
|
* (UPPERREL_FINAL, NULL) upperrel in *root. In addition,
|
|
* root->processed_tlist contains the final processed targetlist.
|
|
*
|
|
* Note that we have not done set_cheapest() on the final rel; it's convenient
|
|
* to leave this to the caller.
|
|
*--------------------
|
|
*/
|
|
static void
|
|
grouping_planner(PlannerInfo *root, bool inheritance_update,
|
|
double tuple_fraction)
|
|
{
|
|
Query *parse = root->parse;
|
|
int64 offset_est = 0;
|
|
int64 count_est = 0;
|
|
double limit_tuples = -1.0;
|
|
bool have_postponed_srfs = false;
|
|
PathTarget *final_target;
|
|
List *final_targets;
|
|
List *final_targets_contain_srfs;
|
|
bool final_target_parallel_safe;
|
|
RelOptInfo *current_rel;
|
|
RelOptInfo *final_rel;
|
|
FinalPathExtraData extra;
|
|
ListCell *lc;
|
|
|
|
/* 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;
|
|
}
|
|
|
|
/* Make tuple_fraction accessible to lower-level routines */
|
|
root->tuple_fraction = tuple_fraction;
|
|
|
|
if (parse->setOperations)
|
|
{
|
|
/*
|
|
* If there's a top-level ORDER BY, assume we have to fetch all the
|
|
* tuples. This might be too simplistic given all the hackery below
|
|
* to possibly avoid the sort; but the odds of accurate estimates here
|
|
* are pretty low anyway. XXX try to get rid of this in favor of
|
|
* letting plan_set_operations generate both fast-start and
|
|
* cheapest-total paths.
|
|
*/
|
|
if (parse->sortClause)
|
|
root->tuple_fraction = 0.0;
|
|
|
|
/*
|
|
* Construct Paths for set operations. The results will not need any
|
|
* work except perhaps a top-level sort and/or LIMIT. Note that any
|
|
* special work for recursive unions is the responsibility of
|
|
* plan_set_operations.
|
|
*/
|
|
current_rel = plan_set_operations(root);
|
|
|
|
/*
|
|
* We should not need to call preprocess_targetlist, since we must be
|
|
* in a SELECT query node. Instead, use the processed_tlist 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);
|
|
|
|
/* for safety, copy processed_tlist instead of modifying in-place */
|
|
root->processed_tlist =
|
|
postprocess_setop_tlist(copyObject(root->processed_tlist),
|
|
parse->targetList);
|
|
|
|
/* Also extract the PathTarget form of the setop result tlist */
|
|
final_target = current_rel->cheapest_total_path->pathtarget;
|
|
|
|
/* And check whether it's parallel safe */
|
|
final_target_parallel_safe =
|
|
is_parallel_safe(root, (Node *) final_target->exprs);
|
|
|
|
/* The setop result tlist couldn't contain any SRFs */
|
|
Assert(!parse->hasTargetSRFs);
|
|
final_targets = final_targets_contain_srfs = NIL;
|
|
|
|
/*
|
|
* Can't handle FOR [KEY] UPDATE/SHARE here (parser should have
|
|
* checked already, but let's make sure).
|
|
*/
|
|
if (parse->rowMarks)
|
|
ereport(ERROR,
|
|
(errcode(ERRCODE_FEATURE_NOT_SUPPORTED),
|
|
/*------
|
|
translator: %s is a SQL row locking clause such as FOR UPDATE */
|
|
errmsg("%s is not allowed with UNION/INTERSECT/EXCEPT",
|
|
LCS_asString(linitial_node(RowMarkClause,
|
|
parse->rowMarks)->strength))));
|
|
|
|
/*
|
|
* Calculate pathkeys that represent result ordering requirements
|
|
*/
|
|
Assert(parse->distinctClause == NIL);
|
|
root->sort_pathkeys = make_pathkeys_for_sortclauses(root,
|
|
parse->sortClause,
|
|
root->processed_tlist);
|
|
}
|
|
else
|
|
{
|
|
/* No set operations, do regular planning */
|
|
PathTarget *sort_input_target;
|
|
List *sort_input_targets;
|
|
List *sort_input_targets_contain_srfs;
|
|
bool sort_input_target_parallel_safe;
|
|
PathTarget *grouping_target;
|
|
List *grouping_targets;
|
|
List *grouping_targets_contain_srfs;
|
|
bool grouping_target_parallel_safe;
|
|
PathTarget *scanjoin_target;
|
|
List *scanjoin_targets;
|
|
List *scanjoin_targets_contain_srfs;
|
|
bool scanjoin_target_parallel_safe;
|
|
bool scanjoin_target_same_exprs;
|
|
bool have_grouping;
|
|
AggClauseCosts agg_costs;
|
|
WindowFuncLists *wflists = NULL;
|
|
List *activeWindows = NIL;
|
|
grouping_sets_data *gset_data = NULL;
|
|
standard_qp_extra qp_extra;
|
|
|
|
/* A recursive query should always have setOperations */
|
|
Assert(!root->hasRecursion);
|
|
|
|
/* Preprocess grouping sets and GROUP BY clause, if any */
|
|
if (parse->groupingSets)
|
|
{
|
|
gset_data = preprocess_grouping_sets(root);
|
|
}
|
|
else
|
|
{
|
|
/* Preprocess regular GROUP BY clause, if any */
|
|
if (parse->groupClause)
|
|
parse->groupClause = preprocess_groupclause(root, NIL);
|
|
}
|
|
|
|
/*
|
|
* Preprocess targetlist. Note that much of the remaining planning
|
|
* work will be done with the PathTarget representation of tlists, but
|
|
* we must also maintain the full representation of the final tlist so
|
|
* that we can transfer its decoration (resnames etc) to the topmost
|
|
* tlist of the finished Plan. This is kept in processed_tlist.
|
|
*/
|
|
root->processed_tlist = preprocess_targetlist(root);
|
|
|
|
/*
|
|
* Collect statistics about aggregates for estimating costs, and mark
|
|
* all the aggregates with resolved aggtranstypes. We must do this
|
|
* before slicing and dicing the tlist into various pathtargets, else
|
|
* some copies of the Aggref nodes might escape being marked with the
|
|
* correct transtypes.
|
|
*
|
|
* Note: currently, we do not detect duplicate aggregates here. This
|
|
* may result in somewhat-overestimated cost, which is fine for our
|
|
* purposes since all Paths will get charged the same. But at some
|
|
* point we might wish to do that detection in the planner, rather
|
|
* than during executor startup.
|
|
*/
|
|
MemSet(&agg_costs, 0, sizeof(AggClauseCosts));
|
|
if (parse->hasAggs)
|
|
{
|
|
get_agg_clause_costs(root, (Node *) root->processed_tlist,
|
|
AGGSPLIT_SIMPLE, &agg_costs);
|
|
get_agg_clause_costs(root, parse->havingQual, AGGSPLIT_SIMPLE,
|
|
&agg_costs);
|
|
}
|
|
|
|
/*
|
|
* Locate any window functions in the tlist. (We don't need to look
|
|
* anywhere else, since expressions used in ORDER BY will be in there
|
|
* too.) Note that they could all have been eliminated by constant
|
|
* folding, in which case we don't need to do any more work.
|
|
*/
|
|
if (parse->hasWindowFuncs)
|
|
{
|
|
wflists = find_window_functions((Node *) root->processed_tlist,
|
|
list_length(parse->windowClause));
|
|
if (wflists->numWindowFuncs > 0)
|
|
activeWindows = select_active_windows(root, wflists);
|
|
else
|
|
parse->hasWindowFuncs = false;
|
|
}
|
|
|
|
/*
|
|
* Preprocess MIN/MAX aggregates, if any. Note: be careful about
|
|
* adding logic between here and the query_planner() call. Anything
|
|
* that is needed in MIN/MAX-optimizable cases will have to be
|
|
* duplicated in planagg.c.
|
|
*/
|
|
if (parse->hasAggs)
|
|
preprocess_minmax_aggregates(root);
|
|
|
|
/*
|
|
* Figure out whether there's a hard limit on the number of rows that
|
|
* query_planner's result subplan needs to return. Even if we know a
|
|
* hard limit overall, it doesn't apply if the query has any
|
|
* grouping/aggregation operations, or SRFs in the tlist.
|
|
*/
|
|
if (parse->groupClause ||
|
|
parse->groupingSets ||
|
|
parse->distinctClause ||
|
|
parse->hasAggs ||
|
|
parse->hasWindowFuncs ||
|
|
parse->hasTargetSRFs ||
|
|
root->hasHavingQual)
|
|
root->limit_tuples = -1.0;
|
|
else
|
|
root->limit_tuples = limit_tuples;
|
|
|
|
/* Set up data needed by standard_qp_callback */
|
|
qp_extra.activeWindows = activeWindows;
|
|
qp_extra.groupClause = (gset_data
|
|
? (gset_data->rollups ? linitial_node(RollupData, gset_data->rollups)->groupClause : NIL)
|
|
: parse->groupClause);
|
|
|
|
/*
|
|
* Generate the best unsorted and presorted paths for the scan/join
|
|
* portion of this Query, ie the processing represented by the
|
|
* FROM/WHERE clauses. (Note there may not be any presorted paths.)
|
|
* We also generate (in standard_qp_callback) pathkey representations
|
|
* of the query's sort clause, distinct clause, etc.
|
|
*/
|
|
current_rel = query_planner(root, standard_qp_callback, &qp_extra);
|
|
|
|
/*
|
|
* Convert the query's result tlist into PathTarget format.
|
|
*
|
|
* Note: this cannot be done before query_planner() has performed
|
|
* appendrel expansion, because that might add resjunk entries to
|
|
* root->processed_tlist. Waiting till afterwards is also helpful
|
|
* because the target width estimates can use per-Var width numbers
|
|
* that were obtained within query_planner().
|
|
*/
|
|
final_target = create_pathtarget(root, root->processed_tlist);
|
|
final_target_parallel_safe =
|
|
is_parallel_safe(root, (Node *) final_target->exprs);
|
|
|
|
/*
|
|
* If ORDER BY was given, consider whether we should use a post-sort
|
|
* projection, and compute the adjusted target for preceding steps if
|
|
* so.
|
|
*/
|
|
if (parse->sortClause)
|
|
{
|
|
sort_input_target = make_sort_input_target(root,
|
|
final_target,
|
|
&have_postponed_srfs);
|
|
sort_input_target_parallel_safe =
|
|
is_parallel_safe(root, (Node *) sort_input_target->exprs);
|
|
}
|
|
else
|
|
{
|
|
sort_input_target = final_target;
|
|
sort_input_target_parallel_safe = final_target_parallel_safe;
|
|
}
|
|
|
|
/*
|
|
* If we have window functions to deal with, the output from any
|
|
* grouping step needs to be what the window functions want;
|
|
* otherwise, it should be sort_input_target.
|
|
*/
|
|
if (activeWindows)
|
|
{
|
|
grouping_target = make_window_input_target(root,
|
|
final_target,
|
|
activeWindows);
|
|
grouping_target_parallel_safe =
|
|
is_parallel_safe(root, (Node *) grouping_target->exprs);
|
|
}
|
|
else
|
|
{
|
|
grouping_target = sort_input_target;
|
|
grouping_target_parallel_safe = sort_input_target_parallel_safe;
|
|
}
|
|
|
|
/*
|
|
* If we have grouping or aggregation to do, the topmost scan/join
|
|
* plan node must emit what the grouping step wants; otherwise, it
|
|
* should emit grouping_target.
|
|
*/
|
|
have_grouping = (parse->groupClause || parse->groupingSets ||
|
|
parse->hasAggs || root->hasHavingQual);
|
|
if (have_grouping)
|
|
{
|
|
scanjoin_target = make_group_input_target(root, final_target);
|
|
scanjoin_target_parallel_safe =
|
|
is_parallel_safe(root, (Node *) scanjoin_target->exprs);
|
|
}
|
|
else
|
|
{
|
|
scanjoin_target = grouping_target;
|
|
scanjoin_target_parallel_safe = grouping_target_parallel_safe;
|
|
}
|
|
|
|
/*
|
|
* If there are any SRFs in the targetlist, we must separate each of
|
|
* these PathTargets into SRF-computing and SRF-free targets. Replace
|
|
* each of the named targets with a SRF-free version, and remember the
|
|
* list of additional projection steps we need to add afterwards.
|
|
*/
|
|
if (parse->hasTargetSRFs)
|
|
{
|
|
/* final_target doesn't recompute any SRFs in sort_input_target */
|
|
split_pathtarget_at_srfs(root, final_target, sort_input_target,
|
|
&final_targets,
|
|
&final_targets_contain_srfs);
|
|
final_target = linitial_node(PathTarget, final_targets);
|
|
Assert(!linitial_int(final_targets_contain_srfs));
|
|
/* likewise for sort_input_target vs. grouping_target */
|
|
split_pathtarget_at_srfs(root, sort_input_target, grouping_target,
|
|
&sort_input_targets,
|
|
&sort_input_targets_contain_srfs);
|
|
sort_input_target = linitial_node(PathTarget, sort_input_targets);
|
|
Assert(!linitial_int(sort_input_targets_contain_srfs));
|
|
/* likewise for grouping_target vs. scanjoin_target */
|
|
split_pathtarget_at_srfs(root, grouping_target, scanjoin_target,
|
|
&grouping_targets,
|
|
&grouping_targets_contain_srfs);
|
|
grouping_target = linitial_node(PathTarget, grouping_targets);
|
|
Assert(!linitial_int(grouping_targets_contain_srfs));
|
|
/* scanjoin_target will not have any SRFs precomputed for it */
|
|
split_pathtarget_at_srfs(root, scanjoin_target, NULL,
|
|
&scanjoin_targets,
|
|
&scanjoin_targets_contain_srfs);
|
|
scanjoin_target = linitial_node(PathTarget, scanjoin_targets);
|
|
Assert(!linitial_int(scanjoin_targets_contain_srfs));
|
|
}
|
|
else
|
|
{
|
|
/* initialize lists; for most of these, dummy values are OK */
|
|
final_targets = final_targets_contain_srfs = NIL;
|
|
sort_input_targets = sort_input_targets_contain_srfs = NIL;
|
|
grouping_targets = grouping_targets_contain_srfs = NIL;
|
|
scanjoin_targets = list_make1(scanjoin_target);
|
|
scanjoin_targets_contain_srfs = NIL;
|
|
}
|
|
|
|
/* Apply scan/join target. */
|
|
scanjoin_target_same_exprs = list_length(scanjoin_targets) == 1
|
|
&& equal(scanjoin_target->exprs, current_rel->reltarget->exprs);
|
|
apply_scanjoin_target_to_paths(root, current_rel, scanjoin_targets,
|
|
scanjoin_targets_contain_srfs,
|
|
scanjoin_target_parallel_safe,
|
|
scanjoin_target_same_exprs);
|
|
|
|
/*
|
|
* Save the various upper-rel PathTargets we just computed into
|
|
* root->upper_targets[]. The core code doesn't use this, but it
|
|
* provides a convenient place for extensions to get at the info. For
|
|
* consistency, we save all the intermediate targets, even though some
|
|
* of the corresponding upperrels might not be needed for this query.
|
|
*/
|
|
root->upper_targets[UPPERREL_FINAL] = final_target;
|
|
root->upper_targets[UPPERREL_ORDERED] = final_target;
|
|
root->upper_targets[UPPERREL_DISTINCT] = sort_input_target;
|
|
root->upper_targets[UPPERREL_WINDOW] = sort_input_target;
|
|
root->upper_targets[UPPERREL_GROUP_AGG] = grouping_target;
|
|
|
|
/*
|
|
* If we have grouping and/or aggregation, consider ways to implement
|
|
* that. We build a new upperrel representing the output of this
|
|
* phase.
|
|
*/
|
|
if (have_grouping)
|
|
{
|
|
current_rel = create_grouping_paths(root,
|
|
current_rel,
|
|
grouping_target,
|
|
grouping_target_parallel_safe,
|
|
&agg_costs,
|
|
gset_data);
|
|
/* Fix things up if grouping_target contains SRFs */
|
|
if (parse->hasTargetSRFs)
|
|
adjust_paths_for_srfs(root, current_rel,
|
|
grouping_targets,
|
|
grouping_targets_contain_srfs);
|
|
}
|
|
|
|
/*
|
|
* If we have window functions, consider ways to implement those. We
|
|
* build a new upperrel representing the output of this phase.
|
|
*/
|
|
if (activeWindows)
|
|
{
|
|
current_rel = create_window_paths(root,
|
|
current_rel,
|
|
grouping_target,
|
|
sort_input_target,
|
|
sort_input_target_parallel_safe,
|
|
wflists,
|
|
activeWindows);
|
|
/* Fix things up if sort_input_target contains SRFs */
|
|
if (parse->hasTargetSRFs)
|
|
adjust_paths_for_srfs(root, current_rel,
|
|
sort_input_targets,
|
|
sort_input_targets_contain_srfs);
|
|
}
|
|
|
|
/*
|
|
* If there is a DISTINCT clause, consider ways to implement that. We
|
|
* build a new upperrel representing the output of this phase.
|
|
*/
|
|
if (parse->distinctClause)
|
|
{
|
|
current_rel = create_distinct_paths(root,
|
|
current_rel);
|
|
}
|
|
} /* end of if (setOperations) */
|
|
|
|
/*
|
|
* If ORDER BY was given, consider ways to implement that, and generate a
|
|
* new upperrel containing only paths that emit the correct ordering and
|
|
* project the correct final_target. We can apply the original
|
|
* limit_tuples limit in sort costing here, but only if there are no
|
|
* postponed SRFs.
|
|
*/
|
|
if (parse->sortClause)
|
|
{
|
|
current_rel = create_ordered_paths(root,
|
|
current_rel,
|
|
final_target,
|
|
final_target_parallel_safe,
|
|
have_postponed_srfs ? -1.0 :
|
|
limit_tuples);
|
|
/* Fix things up if final_target contains SRFs */
|
|
if (parse->hasTargetSRFs)
|
|
adjust_paths_for_srfs(root, current_rel,
|
|
final_targets,
|
|
final_targets_contain_srfs);
|
|
}
|
|
|
|
/*
|
|
* Now we are prepared to build the final-output upperrel.
|
|
*/
|
|
final_rel = fetch_upper_rel(root, UPPERREL_FINAL, NULL);
|
|
|
|
/*
|
|
* If the input rel is marked consider_parallel and there's nothing that's
|
|
* not parallel-safe in the LIMIT clause, then the final_rel can be marked
|
|
* consider_parallel as well. Note that if the query has rowMarks or is
|
|
* not a SELECT, consider_parallel will be false for every relation in the
|
|
* query.
|
|
*/
|
|
if (current_rel->consider_parallel &&
|
|
is_parallel_safe(root, parse->limitOffset) &&
|
|
is_parallel_safe(root, parse->limitCount))
|
|
final_rel->consider_parallel = true;
|
|
|
|
/*
|
|
* If the current_rel belongs to a single FDW, so does the final_rel.
|
|
*/
|
|
final_rel->serverid = current_rel->serverid;
|
|
final_rel->userid = current_rel->userid;
|
|
final_rel->useridiscurrent = current_rel->useridiscurrent;
|
|
final_rel->fdwroutine = current_rel->fdwroutine;
|
|
|
|
/*
|
|
* Generate paths for the final_rel. Insert all surviving paths, with
|
|
* LockRows, Limit, and/or ModifyTable steps added if needed.
|
|
*/
|
|
foreach(lc, current_rel->pathlist)
|
|
{
|
|
Path *path = (Path *) lfirst(lc);
|
|
|
|
/*
|
|
* If there is a FOR [KEY] UPDATE/SHARE clause, add the LockRows node.
|
|
* (Note: we intentionally test parse->rowMarks not root->rowMarks
|
|
* here. If there are only non-locking rowmarks, they should be
|
|
* handled by the ModifyTable node instead. However, root->rowMarks
|
|
* is what goes into the LockRows node.)
|
|
*/
|
|
if (parse->rowMarks)
|
|
{
|
|
path = (Path *) create_lockrows_path(root, final_rel, path,
|
|
root->rowMarks,
|
|
assign_special_exec_param(root));
|
|
}
|
|
|
|
/*
|
|
* If there is a LIMIT/OFFSET clause, add the LIMIT node.
|
|
*/
|
|
if (limit_needed(parse))
|
|
{
|
|
path = (Path *) create_limit_path(root, final_rel, path,
|
|
parse->limitOffset,
|
|
parse->limitCount,
|
|
offset_est, count_est);
|
|
}
|
|
|
|
/*
|
|
* If this is an INSERT/UPDATE/DELETE, and we're not being called from
|
|
* inheritance_planner, add the ModifyTable node.
|
|
*/
|
|
if (parse->commandType != CMD_SELECT && !inheritance_update)
|
|
{
|
|
Index rootRelation;
|
|
List *withCheckOptionLists;
|
|
List *returningLists;
|
|
List *rowMarks;
|
|
|
|
/*
|
|
* If target is a partition root table, we need to mark the
|
|
* ModifyTable node appropriately for that.
|
|
*/
|
|
if (rt_fetch(parse->resultRelation, parse->rtable)->relkind ==
|
|
RELKIND_PARTITIONED_TABLE)
|
|
rootRelation = parse->resultRelation;
|
|
else
|
|
rootRelation = 0;
|
|
|
|
/*
|
|
* Set up the WITH CHECK OPTION and RETURNING lists-of-lists, if
|
|
* needed.
|
|
*/
|
|
if (parse->withCheckOptions)
|
|
withCheckOptionLists = list_make1(parse->withCheckOptions);
|
|
else
|
|
withCheckOptionLists = NIL;
|
|
|
|
if (parse->returningList)
|
|
returningLists = list_make1(parse->returningList);
|
|
else
|
|
returningLists = NIL;
|
|
|
|
/*
|
|
* If there was a FOR [KEY] UPDATE/SHARE clause, the LockRows node
|
|
* will have dealt with fetching non-locked marked rows, else we
|
|
* need to have ModifyTable do that.
|
|
*/
|
|
if (parse->rowMarks)
|
|
rowMarks = NIL;
|
|
else
|
|
rowMarks = root->rowMarks;
|
|
|
|
path = (Path *)
|
|
create_modifytable_path(root, final_rel,
|
|
parse->commandType,
|
|
parse->canSetTag,
|
|
parse->resultRelation,
|
|
rootRelation,
|
|
false,
|
|
list_make1_int(parse->resultRelation),
|
|
list_make1(path),
|
|
list_make1(root),
|
|
withCheckOptionLists,
|
|
returningLists,
|
|
rowMarks,
|
|
parse->onConflict,
|
|
assign_special_exec_param(root));
|
|
}
|
|
|
|
/* And shove it into final_rel */
|
|
add_path(final_rel, path);
|
|
}
|
|
|
|
/*
|
|
* Generate partial paths for final_rel, too, if outer query levels might
|
|
* be able to make use of them.
|
|
*/
|
|
if (final_rel->consider_parallel && root->query_level > 1 &&
|
|
!limit_needed(parse))
|
|
{
|
|
Assert(!parse->rowMarks && parse->commandType == CMD_SELECT);
|
|
foreach(lc, current_rel->partial_pathlist)
|
|
{
|
|
Path *partial_path = (Path *) lfirst(lc);
|
|
|
|
add_partial_path(final_rel, partial_path);
|
|
}
|
|
}
|
|
|
|
extra.limit_needed = limit_needed(parse);
|
|
extra.limit_tuples = limit_tuples;
|
|
extra.count_est = count_est;
|
|
extra.offset_est = offset_est;
|
|
|
|
/*
|
|
* If there is an FDW that's responsible for all baserels of the query,
|
|
* let it consider adding ForeignPaths.
|
|
*/
|
|
if (final_rel->fdwroutine &&
|
|
final_rel->fdwroutine->GetForeignUpperPaths)
|
|
final_rel->fdwroutine->GetForeignUpperPaths(root, UPPERREL_FINAL,
|
|
current_rel, final_rel,
|
|
&extra);
|
|
|
|
/* Let extensions possibly add some more paths */
|
|
if (create_upper_paths_hook)
|
|
(*create_upper_paths_hook) (root, UPPERREL_FINAL,
|
|
current_rel, final_rel, &extra);
|
|
|
|
/* Note: currently, we leave it to callers to do set_cheapest() */
|
|
}
|
|
|
|
/*
|
|
* Do preprocessing for groupingSets clause and related data. This handles the
|
|
* preliminary steps of expanding the grouping sets, organizing them into lists
|
|
* of rollups, and preparing annotations which will later be filled in with
|
|
* size estimates.
|
|
*/
|
|
static grouping_sets_data *
|
|
preprocess_grouping_sets(PlannerInfo *root)
|
|
{
|
|
Query *parse = root->parse;
|
|
List *sets;
|
|
int maxref = 0;
|
|
ListCell *lc;
|
|
ListCell *lc_set;
|
|
grouping_sets_data *gd = palloc0(sizeof(grouping_sets_data));
|
|
|
|
parse->groupingSets = expand_grouping_sets(parse->groupingSets, -1);
|
|
|
|
gd->any_hashable = false;
|
|
gd->unhashable_refs = NULL;
|
|
gd->unsortable_refs = NULL;
|
|
gd->unsortable_sets = NIL;
|
|
|
|
if (parse->groupClause)
|
|
{
|
|
ListCell *lc;
|
|
|
|
foreach(lc, parse->groupClause)
|
|
{
|
|
SortGroupClause *gc = lfirst_node(SortGroupClause, lc);
|
|
Index ref = gc->tleSortGroupRef;
|
|
|
|
if (ref > maxref)
|
|
maxref = ref;
|
|
|
|
if (!gc->hashable)
|
|
gd->unhashable_refs = bms_add_member(gd->unhashable_refs, ref);
|
|
|
|
if (!OidIsValid(gc->sortop))
|
|
gd->unsortable_refs = bms_add_member(gd->unsortable_refs, ref);
|
|
}
|
|
}
|
|
|
|
/* Allocate workspace array for remapping */
|
|
gd->tleref_to_colnum_map = (int *) palloc((maxref + 1) * sizeof(int));
|
|
|
|
/*
|
|
* If we have any unsortable sets, we must extract them before trying to
|
|
* prepare rollups. Unsortable sets don't go through
|
|
* reorder_grouping_sets, so we must apply the GroupingSetData annotation
|
|
* here.
|
|
*/
|
|
if (!bms_is_empty(gd->unsortable_refs))
|
|
{
|
|
List *sortable_sets = NIL;
|
|
|
|
foreach(lc, parse->groupingSets)
|
|
{
|
|
List *gset = (List *) lfirst(lc);
|
|
|
|
if (bms_overlap_list(gd->unsortable_refs, gset))
|
|
{
|
|
GroupingSetData *gs = makeNode(GroupingSetData);
|
|
|
|
gs->set = gset;
|
|
gd->unsortable_sets = lappend(gd->unsortable_sets, gs);
|
|
|
|
/*
|
|
* We must enforce here that an unsortable set is hashable;
|
|
* later code assumes this. Parse analysis only checks that
|
|
* every individual column is either hashable or sortable.
|
|
*
|
|
* Note that passing this test doesn't guarantee we can
|
|
* generate a plan; there might be other showstoppers.
|
|
*/
|
|
if (bms_overlap_list(gd->unhashable_refs, gset))
|
|
ereport(ERROR,
|
|
(errcode(ERRCODE_FEATURE_NOT_SUPPORTED),
|
|
errmsg("could not implement GROUP BY"),
|
|
errdetail("Some of the datatypes only support hashing, while others only support sorting.")));
|
|
}
|
|
else
|
|
sortable_sets = lappend(sortable_sets, gset);
|
|
}
|
|
|
|
if (sortable_sets)
|
|
sets = extract_rollup_sets(sortable_sets);
|
|
else
|
|
sets = NIL;
|
|
}
|
|
else
|
|
sets = extract_rollup_sets(parse->groupingSets);
|
|
|
|
foreach(lc_set, sets)
|
|
{
|
|
List *current_sets = (List *) lfirst(lc_set);
|
|
RollupData *rollup = makeNode(RollupData);
|
|
GroupingSetData *gs;
|
|
|
|
/*
|
|
* Reorder the current list of grouping sets into correct prefix
|
|
* order. If only one aggregation pass is needed, try to make the
|
|
* list match the ORDER BY clause; if more than one pass is needed, we
|
|
* don't bother with that.
|
|
*
|
|
* Note that this reorders the sets from smallest-member-first to
|
|
* largest-member-first, and applies the GroupingSetData annotations,
|
|
* though the data will be filled in later.
|
|
*/
|
|
current_sets = reorder_grouping_sets(current_sets,
|
|
(list_length(sets) == 1
|
|
? parse->sortClause
|
|
: NIL));
|
|
|
|
/*
|
|
* Get the initial (and therefore largest) grouping set.
|
|
*/
|
|
gs = linitial_node(GroupingSetData, current_sets);
|
|
|
|
/*
|
|
* Order the groupClause appropriately. If the first grouping set is
|
|
* empty, then the groupClause must also be empty; otherwise we have
|
|
* to force the groupClause to match that grouping set's order.
|
|
*
|
|
* (The first grouping set can be empty even though parse->groupClause
|
|
* is not empty only if all non-empty grouping sets are unsortable.
|
|
* The groupClauses for hashed grouping sets are built later on.)
|
|
*/
|
|
if (gs->set)
|
|
rollup->groupClause = preprocess_groupclause(root, gs->set);
|
|
else
|
|
rollup->groupClause = NIL;
|
|
|
|
/*
|
|
* Is it hashable? We pretend empty sets are hashable even though we
|
|
* actually force them not to be hashed later. But don't bother if
|
|
* there's nothing but empty sets (since in that case we can't hash
|
|
* anything).
|
|
*/
|
|
if (gs->set &&
|
|
!bms_overlap_list(gd->unhashable_refs, gs->set))
|
|
{
|
|
rollup->hashable = true;
|
|
gd->any_hashable = true;
|
|
}
|
|
|
|
/*
|
|
* Now that we've pinned down an order for the groupClause for this
|
|
* list of grouping sets, we need to remap the entries in the grouping
|
|
* sets from sortgrouprefs to plain indices (0-based) into the
|
|
* groupClause for this collection of grouping sets. We keep the
|
|
* original form for later use, though.
|
|
*/
|
|
rollup->gsets = remap_to_groupclause_idx(rollup->groupClause,
|
|
current_sets,
|
|
gd->tleref_to_colnum_map);
|
|
rollup->gsets_data = current_sets;
|
|
|
|
gd->rollups = lappend(gd->rollups, rollup);
|
|
}
|
|
|
|
if (gd->unsortable_sets)
|
|
{
|
|
/*
|
|
* We have not yet pinned down a groupclause for this, but we will
|
|
* need index-based lists for estimation purposes. Construct
|
|
* hash_sets_idx based on the entire original groupclause for now.
|
|
*/
|
|
gd->hash_sets_idx = remap_to_groupclause_idx(parse->groupClause,
|
|
gd->unsortable_sets,
|
|
gd->tleref_to_colnum_map);
|
|
gd->any_hashable = true;
|
|
}
|
|
|
|
return gd;
|
|
}
|
|
|
|
/*
|
|
* Given a groupclause and a list of GroupingSetData, return equivalent sets
|
|
* (without annotation) mapped to indexes into the given groupclause.
|
|
*/
|
|
static List *
|
|
remap_to_groupclause_idx(List *groupClause,
|
|
List *gsets,
|
|
int *tleref_to_colnum_map)
|
|
{
|
|
int ref = 0;
|
|
List *result = NIL;
|
|
ListCell *lc;
|
|
|
|
foreach(lc, groupClause)
|
|
{
|
|
SortGroupClause *gc = lfirst_node(SortGroupClause, lc);
|
|
|
|
tleref_to_colnum_map[gc->tleSortGroupRef] = ref++;
|
|
}
|
|
|
|
foreach(lc, gsets)
|
|
{
|
|
List *set = NIL;
|
|
ListCell *lc2;
|
|
GroupingSetData *gs = lfirst_node(GroupingSetData, lc);
|
|
|
|
foreach(lc2, gs->set)
|
|
{
|
|
set = lappend_int(set, tleref_to_colnum_map[lfirst_int(lc2)]);
|
|
}
|
|
|
|
result = lappend(result, set);
|
|
}
|
|
|
|
return result;
|
|
}
|
|
|
|
|
|
/*
|
|
* preprocess_rowmarks - set up PlanRowMarks if needed
|
|
*/
|
|
static void
|
|
preprocess_rowmarks(PlannerInfo *root)
|
|
{
|
|
Query *parse = root->parse;
|
|
Bitmapset *rels;
|
|
List *prowmarks;
|
|
ListCell *l;
|
|
int i;
|
|
|
|
if (parse->rowMarks)
|
|
{
|
|
/*
|
|
* We've got trouble if FOR [KEY] UPDATE/SHARE appears inside
|
|
* grouping, since grouping renders a reference to individual tuple
|
|
* CTIDs invalid. This is also checked at parse time, but that's
|
|
* insufficient because of rule substitution, query pullup, etc.
|
|
*/
|
|
CheckSelectLocking(parse, linitial_node(RowMarkClause,
|
|
parse->rowMarks)->strength);
|
|
}
|
|
else
|
|
{
|
|
/*
|
|
* We only need rowmarks for UPDATE, DELETE, or FOR [KEY]
|
|
* UPDATE/SHARE.
|
|
*/
|
|
if (parse->commandType != CMD_UPDATE &&
|
|
parse->commandType != CMD_DELETE)
|
|
return;
|
|
}
|
|
|
|
/*
|
|
* We need to have rowmarks for all base relations except the target. We
|
|
* make a bitmapset of all base rels and then remove the items we don't
|
|
* need or have FOR [KEY] UPDATE/SHARE marks for.
|
|
*/
|
|
rels = get_relids_in_jointree((Node *) parse->jointree, false);
|
|
if (parse->resultRelation)
|
|
rels = bms_del_member(rels, parse->resultRelation);
|
|
|
|
/*
|
|
* Convert RowMarkClauses to PlanRowMark representation.
|
|
*/
|
|
prowmarks = NIL;
|
|
foreach(l, parse->rowMarks)
|
|
{
|
|
RowMarkClause *rc = lfirst_node(RowMarkClause, l);
|
|
RangeTblEntry *rte = rt_fetch(rc->rti, parse->rtable);
|
|
PlanRowMark *newrc;
|
|
|
|
/*
|
|
* Currently, it is syntactically impossible to have FOR UPDATE et al
|
|
* applied to an update/delete target rel. If that ever becomes
|
|
* possible, we should drop the target from the PlanRowMark list.
|
|
*/
|
|
Assert(rc->rti != parse->resultRelation);
|
|
|
|
/*
|
|
* Ignore RowMarkClauses for subqueries; they aren't real tables and
|
|
* can't support true locking. Subqueries that got flattened into the
|
|
* main query should be ignored completely. Any that didn't will get
|
|
* ROW_MARK_COPY items in the next loop.
|
|
*/
|
|
if (rte->rtekind != RTE_RELATION)
|
|
continue;
|
|
|
|
rels = bms_del_member(rels, rc->rti);
|
|
|
|
newrc = makeNode(PlanRowMark);
|
|
newrc->rti = newrc->prti = rc->rti;
|
|
newrc->rowmarkId = ++(root->glob->lastRowMarkId);
|
|
newrc->markType = select_rowmark_type(rte, rc->strength);
|
|
newrc->allMarkTypes = (1 << newrc->markType);
|
|
newrc->strength = rc->strength;
|
|
newrc->waitPolicy = rc->waitPolicy;
|
|
newrc->isParent = false;
|
|
|
|
prowmarks = lappend(prowmarks, newrc);
|
|
}
|
|
|
|
/*
|
|
* Now, add rowmarks for any non-target, non-locked base relations.
|
|
*/
|
|
i = 0;
|
|
foreach(l, parse->rtable)
|
|
{
|
|
RangeTblEntry *rte = lfirst_node(RangeTblEntry, l);
|
|
PlanRowMark *newrc;
|
|
|
|
i++;
|
|
if (!bms_is_member(i, rels))
|
|
continue;
|
|
|
|
newrc = makeNode(PlanRowMark);
|
|
newrc->rti = newrc->prti = i;
|
|
newrc->rowmarkId = ++(root->glob->lastRowMarkId);
|
|
newrc->markType = select_rowmark_type(rte, LCS_NONE);
|
|
newrc->allMarkTypes = (1 << newrc->markType);
|
|
newrc->strength = LCS_NONE;
|
|
newrc->waitPolicy = LockWaitBlock; /* doesn't matter */
|
|
newrc->isParent = false;
|
|
|
|
prowmarks = lappend(prowmarks, newrc);
|
|
}
|
|
|
|
root->rowMarks = prowmarks;
|
|
}
|
|
|
|
/*
|
|
* Select RowMarkType to use for a given table
|
|
*/
|
|
RowMarkType
|
|
select_rowmark_type(RangeTblEntry *rte, LockClauseStrength strength)
|
|
{
|
|
if (rte->rtekind != RTE_RELATION)
|
|
{
|
|
/* If it's not a table at all, use ROW_MARK_COPY */
|
|
return ROW_MARK_COPY;
|
|
}
|
|
else if (rte->relkind == RELKIND_FOREIGN_TABLE)
|
|
{
|
|
/* Let the FDW select the rowmark type, if it wants to */
|
|
FdwRoutine *fdwroutine = GetFdwRoutineByRelId(rte->relid);
|
|
|
|
if (fdwroutine->GetForeignRowMarkType != NULL)
|
|
return fdwroutine->GetForeignRowMarkType(rte, strength);
|
|
/* Otherwise, use ROW_MARK_COPY by default */
|
|
return ROW_MARK_COPY;
|
|
}
|
|
else
|
|
{
|
|
/* Regular table, apply the appropriate lock type */
|
|
switch (strength)
|
|
{
|
|
case LCS_NONE:
|
|
|
|
/*
|
|
* We don't need a tuple lock, only the ability to re-fetch
|
|
* the row.
|
|
*/
|
|
return ROW_MARK_REFERENCE;
|
|
break;
|
|
case LCS_FORKEYSHARE:
|
|
return ROW_MARK_KEYSHARE;
|
|
break;
|
|
case LCS_FORSHARE:
|
|
return ROW_MARK_SHARE;
|
|
break;
|
|
case LCS_FORNOKEYUPDATE:
|
|
return ROW_MARK_NOKEYEXCLUSIVE;
|
|
break;
|
|
case LCS_FORUPDATE:
|
|
return ROW_MARK_EXCLUSIVE;
|
|
break;
|
|
}
|
|
elog(ERROR, "unrecognized LockClauseStrength %d", (int) strength);
|
|
return ROW_MARK_EXCLUSIVE; /* keep compiler quiet */
|
|
}
|
|
}
|
|
|
|
/*
|
|
* 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 create_limit_path, 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; /* treat as not present */
|
|
}
|
|
}
|
|
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;
|
|
}
|
|
|
|
/*
|
|
* limit_needed - do we actually need a Limit plan node?
|
|
*
|
|
* If we have constant-zero OFFSET and constant-null LIMIT, we can skip adding
|
|
* a Limit node. This is worth checking for because "OFFSET 0" is a common
|
|
* locution for an optimization fence. (Because other places in the planner
|
|
* merely check whether parse->limitOffset isn't NULL, it will still work as
|
|
* an optimization fence --- we're just suppressing unnecessary run-time
|
|
* overhead.)
|
|
*
|
|
* This might look like it could be merged into preprocess_limit, but there's
|
|
* a key distinction: here we need hard constants in OFFSET/LIMIT, whereas
|
|
* in preprocess_limit it's good enough to consider estimated values.
|
|
*/
|
|
bool
|
|
limit_needed(Query *parse)
|
|
{
|
|
Node *node;
|
|
|
|
node = parse->limitCount;
|
|
if (node)
|
|
{
|
|
if (IsA(node, Const))
|
|
{
|
|
/* NULL indicates LIMIT ALL, ie, no limit */
|
|
if (!((Const *) node)->constisnull)
|
|
return true; /* LIMIT with a constant value */
|
|
}
|
|
else
|
|
return true; /* non-constant LIMIT */
|
|
}
|
|
|
|
node = parse->limitOffset;
|
|
if (node)
|
|
{
|
|
if (IsA(node, Const))
|
|
{
|
|
/* Treat NULL as no offset; the executor would too */
|
|
if (!((Const *) node)->constisnull)
|
|
{
|
|
int64 offset = DatumGetInt64(((Const *) node)->constvalue);
|
|
|
|
if (offset != 0)
|
|
return true; /* OFFSET with a nonzero value */
|
|
}
|
|
}
|
|
else
|
|
return true; /* non-constant OFFSET */
|
|
}
|
|
|
|
return false; /* don't need a Limit plan node */
|
|
}
|
|
|
|
|
|
/*
|
|
* remove_useless_groupby_columns
|
|
* Remove any columns in the GROUP BY clause that are redundant due to
|
|
* being functionally dependent on other GROUP BY columns.
|
|
*
|
|
* Since some other DBMSes do not allow references to ungrouped columns, it's
|
|
* not unusual to find all columns listed in GROUP BY even though listing the
|
|
* primary-key columns would be sufficient. Deleting such excess columns
|
|
* avoids redundant sorting work, so it's worth doing. When we do this, we
|
|
* must mark the plan as dependent on the pkey constraint (compare the
|
|
* parser's check_ungrouped_columns() and check_functional_grouping()).
|
|
*
|
|
* In principle, we could treat any NOT-NULL columns appearing in a UNIQUE
|
|
* index as the determining columns. But as with check_functional_grouping(),
|
|
* there's currently no way to represent dependency on a NOT NULL constraint,
|
|
* so we consider only the pkey for now.
|
|
*/
|
|
static void
|
|
remove_useless_groupby_columns(PlannerInfo *root)
|
|
{
|
|
Query *parse = root->parse;
|
|
Bitmapset **groupbyattnos;
|
|
Bitmapset **surplusvars;
|
|
ListCell *lc;
|
|
int relid;
|
|
|
|
/* No chance to do anything if there are less than two GROUP BY items */
|
|
if (list_length(parse->groupClause) < 2)
|
|
return;
|
|
|
|
/* Don't fiddle with the GROUP BY clause if the query has grouping sets */
|
|
if (parse->groupingSets)
|
|
return;
|
|
|
|
/*
|
|
* Scan the GROUP BY clause to find GROUP BY items that are simple Vars.
|
|
* Fill groupbyattnos[k] with a bitmapset of the column attnos of RTE k
|
|
* that are GROUP BY items.
|
|
*/
|
|
groupbyattnos = (Bitmapset **) palloc0(sizeof(Bitmapset *) *
|
|
(list_length(parse->rtable) + 1));
|
|
foreach(lc, parse->groupClause)
|
|
{
|
|
SortGroupClause *sgc = lfirst_node(SortGroupClause, lc);
|
|
TargetEntry *tle = get_sortgroupclause_tle(sgc, parse->targetList);
|
|
Var *var = (Var *) tle->expr;
|
|
|
|
/*
|
|
* Ignore non-Vars and Vars from other query levels.
|
|
*
|
|
* XXX in principle, stable expressions containing Vars could also be
|
|
* removed, if all the Vars are functionally dependent on other GROUP
|
|
* BY items. But it's not clear that such cases occur often enough to
|
|
* be worth troubling over.
|
|
*/
|
|
if (!IsA(var, Var) ||
|
|
var->varlevelsup > 0)
|
|
continue;
|
|
|
|
/* OK, remember we have this Var */
|
|
relid = var->varno;
|
|
Assert(relid <= list_length(parse->rtable));
|
|
groupbyattnos[relid] = bms_add_member(groupbyattnos[relid],
|
|
var->varattno - FirstLowInvalidHeapAttributeNumber);
|
|
}
|
|
|
|
/*
|
|
* Consider each relation and see if it is possible to remove some of its
|
|
* Vars from GROUP BY. For simplicity and speed, we do the actual removal
|
|
* in a separate pass. Here, we just fill surplusvars[k] with a bitmapset
|
|
* of the column attnos of RTE k that are removable GROUP BY items.
|
|
*/
|
|
surplusvars = NULL; /* don't allocate array unless required */
|
|
relid = 0;
|
|
foreach(lc, parse->rtable)
|
|
{
|
|
RangeTblEntry *rte = lfirst_node(RangeTblEntry, lc);
|
|
Bitmapset *relattnos;
|
|
Bitmapset *pkattnos;
|
|
Oid constraintOid;
|
|
|
|
relid++;
|
|
|
|
/* Only plain relations could have primary-key constraints */
|
|
if (rte->rtekind != RTE_RELATION)
|
|
continue;
|
|
|
|
/*
|
|
* We must skip inheritance parent tables as some of the child rels
|
|
* may cause duplicate rows. This cannot happen with partitioned
|
|
* tables, however.
|
|
*/
|
|
if (rte->inh && rte->relkind != RELKIND_PARTITIONED_TABLE)
|
|
continue;
|
|
|
|
/* Nothing to do unless this rel has multiple Vars in GROUP BY */
|
|
relattnos = groupbyattnos[relid];
|
|
if (bms_membership(relattnos) != BMS_MULTIPLE)
|
|
continue;
|
|
|
|
/*
|
|
* Can't remove any columns for this rel if there is no suitable
|
|
* (i.e., nondeferrable) primary key constraint.
|
|
*/
|
|
pkattnos = get_primary_key_attnos(rte->relid, false, &constraintOid);
|
|
if (pkattnos == NULL)
|
|
continue;
|
|
|
|
/*
|
|
* If the primary key is a proper subset of relattnos then we have
|
|
* some items in the GROUP BY that can be removed.
|
|
*/
|
|
if (bms_subset_compare(pkattnos, relattnos) == BMS_SUBSET1)
|
|
{
|
|
/*
|
|
* To easily remember whether we've found anything to do, we don't
|
|
* allocate the surplusvars[] array until we find something.
|
|
*/
|
|
if (surplusvars == NULL)
|
|
surplusvars = (Bitmapset **) palloc0(sizeof(Bitmapset *) *
|
|
(list_length(parse->rtable) + 1));
|
|
|
|
/* Remember the attnos of the removable columns */
|
|
surplusvars[relid] = bms_difference(relattnos, pkattnos);
|
|
|
|
/* Also, mark the resulting plan as dependent on this constraint */
|
|
parse->constraintDeps = lappend_oid(parse->constraintDeps,
|
|
constraintOid);
|
|
}
|
|
}
|
|
|
|
/*
|
|
* If we found any surplus Vars, build a new GROUP BY clause without them.
|
|
* (Note: this may leave some TLEs with unreferenced ressortgroupref
|
|
* markings, but that's harmless.)
|
|
*/
|
|
if (surplusvars != NULL)
|
|
{
|
|
List *new_groupby = NIL;
|
|
|
|
foreach(lc, parse->groupClause)
|
|
{
|
|
SortGroupClause *sgc = lfirst_node(SortGroupClause, lc);
|
|
TargetEntry *tle = get_sortgroupclause_tle(sgc, parse->targetList);
|
|
Var *var = (Var *) tle->expr;
|
|
|
|
/*
|
|
* New list must include non-Vars, outer Vars, and anything not
|
|
* marked as surplus.
|
|
*/
|
|
if (!IsA(var, Var) ||
|
|
var->varlevelsup > 0 ||
|
|
!bms_is_member(var->varattno - FirstLowInvalidHeapAttributeNumber,
|
|
surplusvars[var->varno]))
|
|
new_groupby = lappend(new_groupby, sgc);
|
|
}
|
|
|
|
parse->groupClause = new_groupby;
|
|
}
|
|
}
|
|
|
|
/*
|
|
* preprocess_groupclause - do preparatory work on GROUP BY clause
|
|
*
|
|
* The idea here is to adjust the ordering of the GROUP BY elements
|
|
* (which in itself is semantically insignificant) to match ORDER BY,
|
|
* thereby allowing a single sort operation to both implement the ORDER BY
|
|
* requirement and set up for a Unique step that implements GROUP BY.
|
|
*
|
|
* In principle it might be interesting to consider other orderings of the
|
|
* GROUP BY elements, which could match the sort ordering of other
|
|
* possible plans (eg an indexscan) and thereby reduce cost. We don't
|
|
* bother with that, though. Hashed grouping will frequently win anyway.
|
|
*
|
|
* Note: we need no comparable processing of the distinctClause because
|
|
* the parser already enforced that that matches ORDER BY.
|
|
*
|
|
* For grouping sets, the order of items is instead forced to agree with that
|
|
* of the grouping set (and items not in the grouping set are skipped). The
|
|
* work of sorting the order of grouping set elements to match the ORDER BY if
|
|
* possible is done elsewhere.
|
|
*/
|
|
static List *
|
|
preprocess_groupclause(PlannerInfo *root, List *force)
|
|
{
|
|
Query *parse = root->parse;
|
|
List *new_groupclause = NIL;
|
|
bool partial_match;
|
|
ListCell *sl;
|
|
ListCell *gl;
|
|
|
|
/* For grouping sets, we need to force the ordering */
|
|
if (force)
|
|
{
|
|
foreach(sl, force)
|
|
{
|
|
Index ref = lfirst_int(sl);
|
|
SortGroupClause *cl = get_sortgroupref_clause(ref, parse->groupClause);
|
|
|
|
new_groupclause = lappend(new_groupclause, cl);
|
|
}
|
|
|
|
return new_groupclause;
|
|
}
|
|
|
|
/* If no ORDER BY, nothing useful to do here */
|
|
if (parse->sortClause == NIL)
|
|
return parse->groupClause;
|
|
|
|
/*
|
|
* Scan the ORDER BY clause and construct a list of matching GROUP BY
|
|
* items, but only as far as we can make a matching prefix.
|
|
*
|
|
* This code assumes that the sortClause contains no duplicate items.
|
|
*/
|
|
foreach(sl, parse->sortClause)
|
|
{
|
|
SortGroupClause *sc = lfirst_node(SortGroupClause, sl);
|
|
|
|
foreach(gl, parse->groupClause)
|
|
{
|
|
SortGroupClause *gc = lfirst_node(SortGroupClause, gl);
|
|
|
|
if (equal(gc, sc))
|
|
{
|
|
new_groupclause = lappend(new_groupclause, gc);
|
|
break;
|
|
}
|
|
}
|
|
if (gl == NULL)
|
|
break; /* no match, so stop scanning */
|
|
}
|
|
|
|
/* Did we match all of the ORDER BY list, or just some of it? */
|
|
partial_match = (sl != NULL);
|
|
|
|
/* If no match at all, no point in reordering GROUP BY */
|
|
if (new_groupclause == NIL)
|
|
return parse->groupClause;
|
|
|
|
/*
|
|
* Add any remaining GROUP BY items to the new list, but only if we were
|
|
* able to make a complete match. In other words, we only rearrange the
|
|
* GROUP BY list if the result is that one list is a prefix of the other
|
|
* --- otherwise there's no possibility of a common sort. Also, give up
|
|
* if there are any non-sortable GROUP BY items, since then there's no
|
|
* hope anyway.
|
|
*/
|
|
foreach(gl, parse->groupClause)
|
|
{
|
|
SortGroupClause *gc = lfirst_node(SortGroupClause, gl);
|
|
|
|
if (list_member_ptr(new_groupclause, gc))
|
|
continue; /* it matched an ORDER BY item */
|
|
if (partial_match)
|
|
return parse->groupClause; /* give up, no common sort possible */
|
|
if (!OidIsValid(gc->sortop))
|
|
return parse->groupClause; /* give up, GROUP BY can't be sorted */
|
|
new_groupclause = lappend(new_groupclause, gc);
|
|
}
|
|
|
|
/* Success --- install the rearranged GROUP BY list */
|
|
Assert(list_length(parse->groupClause) == list_length(new_groupclause));
|
|
return new_groupclause;
|
|
}
|
|
|
|
/*
|
|
* Extract lists of grouping sets that can be implemented using a single
|
|
* rollup-type aggregate pass each. Returns a list of lists of grouping sets.
|
|
*
|
|
* Input must be sorted with smallest sets first. Result has each sublist
|
|
* sorted with smallest sets first.
|
|
*
|
|
* We want to produce the absolute minimum possible number of lists here to
|
|
* avoid excess sorts. Fortunately, there is an algorithm for this; the problem
|
|
* of finding the minimal partition of a partially-ordered set into chains
|
|
* (which is what we need, taking the list of grouping sets as a poset ordered
|
|
* by set inclusion) can be mapped to the problem of finding the maximum
|
|
* cardinality matching on a bipartite graph, which is solvable in polynomial
|
|
* time with a worst case of no worse than O(n^2.5) and usually much
|
|
* better. Since our N is at most 4096, we don't need to consider fallbacks to
|
|
* heuristic or approximate methods. (Planning time for a 12-d cube is under
|
|
* half a second on my modest system even with optimization off and assertions
|
|
* on.)
|
|
*/
|
|
static List *
|
|
extract_rollup_sets(List *groupingSets)
|
|
{
|
|
int num_sets_raw = list_length(groupingSets);
|
|
int num_empty = 0;
|
|
int num_sets = 0; /* distinct sets */
|
|
int num_chains = 0;
|
|
List *result = NIL;
|
|
List **results;
|
|
List **orig_sets;
|
|
Bitmapset **set_masks;
|
|
int *chains;
|
|
short **adjacency;
|
|
short *adjacency_buf;
|
|
BipartiteMatchState *state;
|
|
int i;
|
|
int j;
|
|
int j_size;
|
|
ListCell *lc1 = list_head(groupingSets);
|
|
ListCell *lc;
|
|
|
|
/*
|
|
* Start by stripping out empty sets. The algorithm doesn't require this,
|
|
* but the planner currently needs all empty sets to be returned in the
|
|
* first list, so we strip them here and add them back after.
|
|
*/
|
|
while (lc1 && lfirst(lc1) == NIL)
|
|
{
|
|
++num_empty;
|
|
lc1 = lnext(groupingSets, lc1);
|
|
}
|
|
|
|
/* bail out now if it turns out that all we had were empty sets. */
|
|
if (!lc1)
|
|
return list_make1(groupingSets);
|
|
|
|
/*----------
|
|
* We don't strictly need to remove duplicate sets here, but if we don't,
|
|
* they tend to become scattered through the result, which is a bit
|
|
* confusing (and irritating if we ever decide to optimize them out).
|
|
* So we remove them here and add them back after.
|
|
*
|
|
* For each non-duplicate set, we fill in the following:
|
|
*
|
|
* orig_sets[i] = list of the original set lists
|
|
* set_masks[i] = bitmapset for testing inclusion
|
|
* adjacency[i] = array [n, v1, v2, ... vn] of adjacency indices
|
|
*
|
|
* chains[i] will be the result group this set is assigned to.
|
|
*
|
|
* We index all of these from 1 rather than 0 because it is convenient
|
|
* to leave 0 free for the NIL node in the graph algorithm.
|
|
*----------
|
|
*/
|
|
orig_sets = palloc0((num_sets_raw + 1) * sizeof(List *));
|
|
set_masks = palloc0((num_sets_raw + 1) * sizeof(Bitmapset *));
|
|
adjacency = palloc0((num_sets_raw + 1) * sizeof(short *));
|
|
adjacency_buf = palloc((num_sets_raw + 1) * sizeof(short));
|
|
|
|
j_size = 0;
|
|
j = 0;
|
|
i = 1;
|
|
|
|
for_each_cell(lc, groupingSets, lc1)
|
|
{
|
|
List *candidate = (List *) lfirst(lc);
|
|
Bitmapset *candidate_set = NULL;
|
|
ListCell *lc2;
|
|
int dup_of = 0;
|
|
|
|
foreach(lc2, candidate)
|
|
{
|
|
candidate_set = bms_add_member(candidate_set, lfirst_int(lc2));
|
|
}
|
|
|
|
/* we can only be a dup if we're the same length as a previous set */
|
|
if (j_size == list_length(candidate))
|
|
{
|
|
int k;
|
|
|
|
for (k = j; k < i; ++k)
|
|
{
|
|
if (bms_equal(set_masks[k], candidate_set))
|
|
{
|
|
dup_of = k;
|
|
break;
|
|
}
|
|
}
|
|
}
|
|
else if (j_size < list_length(candidate))
|
|
{
|
|
j_size = list_length(candidate);
|
|
j = i;
|
|
}
|
|
|
|
if (dup_of > 0)
|
|
{
|
|
orig_sets[dup_of] = lappend(orig_sets[dup_of], candidate);
|
|
bms_free(candidate_set);
|
|
}
|
|
else
|
|
{
|
|
int k;
|
|
int n_adj = 0;
|
|
|
|
orig_sets[i] = list_make1(candidate);
|
|
set_masks[i] = candidate_set;
|
|
|
|
/* fill in adjacency list; no need to compare equal-size sets */
|
|
|
|
for (k = j - 1; k > 0; --k)
|
|
{
|
|
if (bms_is_subset(set_masks[k], candidate_set))
|
|
adjacency_buf[++n_adj] = k;
|
|
}
|
|
|
|
if (n_adj > 0)
|
|
{
|
|
adjacency_buf[0] = n_adj;
|
|
adjacency[i] = palloc((n_adj + 1) * sizeof(short));
|
|
memcpy(adjacency[i], adjacency_buf, (n_adj + 1) * sizeof(short));
|
|
}
|
|
else
|
|
adjacency[i] = NULL;
|
|
|
|
++i;
|
|
}
|
|
}
|
|
|
|
num_sets = i - 1;
|
|
|
|
/*
|
|
* Apply the graph matching algorithm to do the work.
|
|
*/
|
|
state = BipartiteMatch(num_sets, num_sets, adjacency);
|
|
|
|
/*
|
|
* Now, the state->pair* fields have the info we need to assign sets to
|
|
* chains. Two sets (u,v) belong to the same chain if pair_uv[u] = v or
|
|
* pair_vu[v] = u (both will be true, but we check both so that we can do
|
|
* it in one pass)
|
|
*/
|
|
chains = palloc0((num_sets + 1) * sizeof(int));
|
|
|
|
for (i = 1; i <= num_sets; ++i)
|
|
{
|
|
int u = state->pair_vu[i];
|
|
int v = state->pair_uv[i];
|
|
|
|
if (u > 0 && u < i)
|
|
chains[i] = chains[u];
|
|
else if (v > 0 && v < i)
|
|
chains[i] = chains[v];
|
|
else
|
|
chains[i] = ++num_chains;
|
|
}
|
|
|
|
/* build result lists. */
|
|
results = palloc0((num_chains + 1) * sizeof(List *));
|
|
|
|
for (i = 1; i <= num_sets; ++i)
|
|
{
|
|
int c = chains[i];
|
|
|
|
Assert(c > 0);
|
|
|
|
results[c] = list_concat(results[c], orig_sets[i]);
|
|
}
|
|
|
|
/* push any empty sets back on the first list. */
|
|
while (num_empty-- > 0)
|
|
results[1] = lcons(NIL, results[1]);
|
|
|
|
/* make result list */
|
|
for (i = 1; i <= num_chains; ++i)
|
|
result = lappend(result, results[i]);
|
|
|
|
/*
|
|
* Free all the things.
|
|
*
|
|
* (This is over-fussy for small sets but for large sets we could have
|
|
* tied up a nontrivial amount of memory.)
|
|
*/
|
|
BipartiteMatchFree(state);
|
|
pfree(results);
|
|
pfree(chains);
|
|
for (i = 1; i <= num_sets; ++i)
|
|
if (adjacency[i])
|
|
pfree(adjacency[i]);
|
|
pfree(adjacency);
|
|
pfree(adjacency_buf);
|
|
pfree(orig_sets);
|
|
for (i = 1; i <= num_sets; ++i)
|
|
bms_free(set_masks[i]);
|
|
pfree(set_masks);
|
|
|
|
return result;
|
|
}
|
|
|
|
/*
|
|
* Reorder the elements of a list of grouping sets such that they have correct
|
|
* prefix relationships. Also inserts the GroupingSetData annotations.
|
|
*
|
|
* The input must be ordered with smallest sets first; the result is returned
|
|
* with largest sets first. Note that the result shares no list substructure
|
|
* with the input, so it's safe for the caller to modify it later.
|
|
*
|
|
* If we're passed in a sortclause, we follow its order of columns to the
|
|
* extent possible, to minimize the chance that we add unnecessary sorts.
|
|
* (We're trying here to ensure that GROUPING SETS ((a,b,c),(c)) ORDER BY c,b,a
|
|
* gets implemented in one pass.)
|
|
*/
|
|
static List *
|
|
reorder_grouping_sets(List *groupingsets, List *sortclause)
|
|
{
|
|
ListCell *lc;
|
|
List *previous = NIL;
|
|
List *result = NIL;
|
|
|
|
foreach(lc, groupingsets)
|
|
{
|
|
List *candidate = (List *) lfirst(lc);
|
|
List *new_elems = list_difference_int(candidate, previous);
|
|
GroupingSetData *gs = makeNode(GroupingSetData);
|
|
|
|
while (list_length(sortclause) > list_length(previous) &&
|
|
list_length(new_elems) > 0)
|
|
{
|
|
SortGroupClause *sc = list_nth(sortclause, list_length(previous));
|
|
int ref = sc->tleSortGroupRef;
|
|
|
|
if (list_member_int(new_elems, ref))
|
|
{
|
|
previous = lappend_int(previous, ref);
|
|
new_elems = list_delete_int(new_elems, ref);
|
|
}
|
|
else
|
|
{
|
|
/* diverged from the sortclause; give up on it */
|
|
sortclause = NIL;
|
|
break;
|
|
}
|
|
}
|
|
|
|
previous = list_concat(previous, new_elems);
|
|
|
|
gs->set = list_copy(previous);
|
|
result = lcons(gs, result);
|
|
}
|
|
|
|
list_free(previous);
|
|
|
|
return result;
|
|
}
|
|
|
|
/*
|
|
* Compute query_pathkeys and other pathkeys during plan generation
|
|
*/
|
|
static void
|
|
standard_qp_callback(PlannerInfo *root, void *extra)
|
|
{
|
|
Query *parse = root->parse;
|
|
standard_qp_extra *qp_extra = (standard_qp_extra *) extra;
|
|
List *tlist = root->processed_tlist;
|
|
List *activeWindows = qp_extra->activeWindows;
|
|
|
|
/*
|
|
* Calculate pathkeys that represent grouping/ordering requirements. The
|
|
* sortClause is certainly sort-able, but GROUP BY and DISTINCT might not
|
|
* be, in which case we just leave their pathkeys empty.
|
|
*/
|
|
if (qp_extra->groupClause &&
|
|
grouping_is_sortable(qp_extra->groupClause))
|
|
root->group_pathkeys =
|
|
make_pathkeys_for_sortclauses(root,
|
|
qp_extra->groupClause,
|
|
tlist);
|
|
else
|
|
root->group_pathkeys = NIL;
|
|
|
|
/* We consider only the first (bottom) window in pathkeys logic */
|
|
if (activeWindows != NIL)
|
|
{
|
|
WindowClause *wc = linitial_node(WindowClause, activeWindows);
|
|
|
|
root->window_pathkeys = make_pathkeys_for_window(root,
|
|
wc,
|
|
tlist);
|
|
}
|
|
else
|
|
root->window_pathkeys = NIL;
|
|
|
|
if (parse->distinctClause &&
|
|
grouping_is_sortable(parse->distinctClause))
|
|
root->distinct_pathkeys =
|
|
make_pathkeys_for_sortclauses(root,
|
|
parse->distinctClause,
|
|
tlist);
|
|
else
|
|
root->distinct_pathkeys = NIL;
|
|
|
|
root->sort_pathkeys =
|
|
make_pathkeys_for_sortclauses(root,
|
|
parse->sortClause,
|
|
tlist);
|
|
|
|
/*
|
|
* Figure out whether we want a sorted result from query_planner.
|
|
*
|
|
* If we have a sortable GROUP BY clause, then we want a result sorted
|
|
* properly for grouping. Otherwise, if we have window functions to
|
|
* evaluate, we try to sort for the first window. Otherwise, if there's a
|
|
* sortable DISTINCT clause that's more rigorous than the ORDER BY clause,
|
|
* we try to produce output that's sufficiently well sorted for the
|
|
* DISTINCT. Otherwise, if there is an ORDER BY clause, we want to sort
|
|
* by the ORDER BY clause.
|
|
*
|
|
* Note: if we have both ORDER BY and GROUP BY, 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. The choice for DISTINCT versus ORDER BY is
|
|
* much easier, since we know that the parser ensured that one is a
|
|
* superset of the other.
|
|
*/
|
|
if (root->group_pathkeys)
|
|
root->query_pathkeys = root->group_pathkeys;
|
|
else if (root->window_pathkeys)
|
|
root->query_pathkeys = root->window_pathkeys;
|
|
else if (list_length(root->distinct_pathkeys) >
|
|
list_length(root->sort_pathkeys))
|
|
root->query_pathkeys = root->distinct_pathkeys;
|
|
else if (root->sort_pathkeys)
|
|
root->query_pathkeys = root->sort_pathkeys;
|
|
else
|
|
root->query_pathkeys = NIL;
|
|
}
|
|
|
|
/*
|
|
* Estimate number of groups produced by grouping clauses (1 if not grouping)
|
|
*
|
|
* path_rows: number of output rows from scan/join step
|
|
* gd: grouping sets data including list of grouping sets and their clauses
|
|
* target_list: target list containing group clause references
|
|
*
|
|
* If doing grouping sets, we also annotate the gsets data with the estimates
|
|
* for each set and each individual rollup list, with a view to later
|
|
* determining whether some combination of them could be hashed instead.
|
|
*/
|
|
static double
|
|
get_number_of_groups(PlannerInfo *root,
|
|
double path_rows,
|
|
grouping_sets_data *gd,
|
|
List *target_list)
|
|
{
|
|
Query *parse = root->parse;
|
|
double dNumGroups;
|
|
|
|
if (parse->groupClause)
|
|
{
|
|
List *groupExprs;
|
|
|
|
if (parse->groupingSets)
|
|
{
|
|
/* Add up the estimates for each grouping set */
|
|
ListCell *lc;
|
|
ListCell *lc2;
|
|
|
|
Assert(gd); /* keep Coverity happy */
|
|
|
|
dNumGroups = 0;
|
|
|
|
foreach(lc, gd->rollups)
|
|
{
|
|
RollupData *rollup = lfirst_node(RollupData, lc);
|
|
ListCell *lc;
|
|
|
|
groupExprs = get_sortgrouplist_exprs(rollup->groupClause,
|
|
target_list);
|
|
|
|
rollup->numGroups = 0.0;
|
|
|
|
forboth(lc, rollup->gsets, lc2, rollup->gsets_data)
|
|
{
|
|
List *gset = (List *) lfirst(lc);
|
|
GroupingSetData *gs = lfirst_node(GroupingSetData, lc2);
|
|
double numGroups = estimate_num_groups(root,
|
|
groupExprs,
|
|
path_rows,
|
|
&gset);
|
|
|
|
gs->numGroups = numGroups;
|
|
rollup->numGroups += numGroups;
|
|
}
|
|
|
|
dNumGroups += rollup->numGroups;
|
|
}
|
|
|
|
if (gd->hash_sets_idx)
|
|
{
|
|
ListCell *lc;
|
|
|
|
gd->dNumHashGroups = 0;
|
|
|
|
groupExprs = get_sortgrouplist_exprs(parse->groupClause,
|
|
target_list);
|
|
|
|
forboth(lc, gd->hash_sets_idx, lc2, gd->unsortable_sets)
|
|
{
|
|
List *gset = (List *) lfirst(lc);
|
|
GroupingSetData *gs = lfirst_node(GroupingSetData, lc2);
|
|
double numGroups = estimate_num_groups(root,
|
|
groupExprs,
|
|
path_rows,
|
|
&gset);
|
|
|
|
gs->numGroups = numGroups;
|
|
gd->dNumHashGroups += numGroups;
|
|
}
|
|
|
|
dNumGroups += gd->dNumHashGroups;
|
|
}
|
|
}
|
|
else
|
|
{
|
|
/* Plain GROUP BY */
|
|
groupExprs = get_sortgrouplist_exprs(parse->groupClause,
|
|
target_list);
|
|
|
|
dNumGroups = estimate_num_groups(root, groupExprs, path_rows,
|
|
NULL);
|
|
}
|
|
}
|
|
else if (parse->groupingSets)
|
|
{
|
|
/* Empty grouping sets ... one result row for each one */
|
|
dNumGroups = list_length(parse->groupingSets);
|
|
}
|
|
else if (parse->hasAggs || root->hasHavingQual)
|
|
{
|
|
/* Plain aggregation, one result row */
|
|
dNumGroups = 1;
|
|
}
|
|
else
|
|
{
|
|
/* Not grouping */
|
|
dNumGroups = 1;
|
|
}
|
|
|
|
return dNumGroups;
|
|
}
|
|
|
|
/*
|
|
* create_grouping_paths
|
|
*
|
|
* Build a new upperrel containing Paths for grouping and/or aggregation.
|
|
* Along the way, we also build an upperrel for Paths which are partially
|
|
* grouped and/or aggregated. A partially grouped and/or aggregated path
|
|
* needs a FinalizeAggregate node to complete the aggregation. Currently,
|
|
* the only partially grouped paths we build are also partial paths; that
|
|
* is, they need a Gather and then a FinalizeAggregate.
|
|
*
|
|
* input_rel: contains the source-data Paths
|
|
* target: the pathtarget for the result Paths to compute
|
|
* agg_costs: cost info about all aggregates in query (in AGGSPLIT_SIMPLE mode)
|
|
* gd: grouping sets data including list of grouping sets and their clauses
|
|
*
|
|
* Note: all Paths in input_rel are expected to return the target computed
|
|
* by make_group_input_target.
|
|
*/
|
|
static RelOptInfo *
|
|
create_grouping_paths(PlannerInfo *root,
|
|
RelOptInfo *input_rel,
|
|
PathTarget *target,
|
|
bool target_parallel_safe,
|
|
const AggClauseCosts *agg_costs,
|
|
grouping_sets_data *gd)
|
|
{
|
|
Query *parse = root->parse;
|
|
RelOptInfo *grouped_rel;
|
|
RelOptInfo *partially_grouped_rel;
|
|
|
|
/*
|
|
* Create grouping relation to hold fully aggregated grouping and/or
|
|
* aggregation paths.
|
|
*/
|
|
grouped_rel = make_grouping_rel(root, input_rel, target,
|
|
target_parallel_safe, parse->havingQual);
|
|
|
|
/*
|
|
* Create either paths for a degenerate grouping or paths for ordinary
|
|
* grouping, as appropriate.
|
|
*/
|
|
if (is_degenerate_grouping(root))
|
|
create_degenerate_grouping_paths(root, input_rel, grouped_rel);
|
|
else
|
|
{
|
|
int flags = 0;
|
|
GroupPathExtraData extra;
|
|
|
|
/*
|
|
* Determine whether it's possible to perform sort-based
|
|
* implementations of grouping. (Note that if groupClause is empty,
|
|
* grouping_is_sortable() is trivially true, and all the
|
|
* pathkeys_contained_in() tests will succeed too, so that we'll
|
|
* consider every surviving input path.)
|
|
*
|
|
* If we have grouping sets, we might be able to sort some but not all
|
|
* of them; in this case, we need can_sort to be true as long as we
|
|
* must consider any sorted-input plan.
|
|
*/
|
|
if ((gd && gd->rollups != NIL)
|
|
|| grouping_is_sortable(parse->groupClause))
|
|
flags |= GROUPING_CAN_USE_SORT;
|
|
|
|
/*
|
|
* Determine whether we should consider hash-based implementations of
|
|
* grouping.
|
|
*
|
|
* Hashed aggregation only applies if we're grouping. If we have
|
|
* grouping sets, some groups might be hashable but others not; in
|
|
* this case we set can_hash true as long as there is nothing globally
|
|
* preventing us from hashing (and we should therefore consider plans
|
|
* with hashes).
|
|
*
|
|
* Executor doesn't support hashed aggregation with DISTINCT or ORDER
|
|
* BY aggregates. (Doing so would imply storing *all* the input
|
|
* values in the hash table, and/or running many sorts in parallel,
|
|
* either of which seems like a certain loser.) We similarly don't
|
|
* support ordered-set aggregates in hashed aggregation, but that case
|
|
* is also included in the numOrderedAggs count.
|
|
*
|
|
* Note: grouping_is_hashable() is much more expensive to check than
|
|
* the other gating conditions, so we want to do it last.
|
|
*/
|
|
if ((parse->groupClause != NIL &&
|
|
agg_costs->numOrderedAggs == 0 &&
|
|
(gd ? gd->any_hashable : grouping_is_hashable(parse->groupClause))))
|
|
flags |= GROUPING_CAN_USE_HASH;
|
|
|
|
/*
|
|
* Determine whether partial aggregation is possible.
|
|
*/
|
|
if (can_partial_agg(root, agg_costs))
|
|
flags |= GROUPING_CAN_PARTIAL_AGG;
|
|
|
|
extra.flags = flags;
|
|
extra.target_parallel_safe = target_parallel_safe;
|
|
extra.havingQual = parse->havingQual;
|
|
extra.targetList = parse->targetList;
|
|
extra.partial_costs_set = false;
|
|
|
|
/*
|
|
* Determine whether partitionwise aggregation is in theory possible.
|
|
* It can be disabled by the user, and for now, we don't try to
|
|
* support grouping sets. create_ordinary_grouping_paths() will check
|
|
* additional conditions, such as whether input_rel is partitioned.
|
|
*/
|
|
if (enable_partitionwise_aggregate && !parse->groupingSets)
|
|
extra.patype = PARTITIONWISE_AGGREGATE_FULL;
|
|
else
|
|
extra.patype = PARTITIONWISE_AGGREGATE_NONE;
|
|
|
|
create_ordinary_grouping_paths(root, input_rel, grouped_rel,
|
|
agg_costs, gd, &extra,
|
|
&partially_grouped_rel);
|
|
}
|
|
|
|
set_cheapest(grouped_rel);
|
|
return grouped_rel;
|
|
}
|
|
|
|
/*
|
|
* make_grouping_rel
|
|
*
|
|
* Create a new grouping rel and set basic properties.
|
|
*
|
|
* input_rel represents the underlying scan/join relation.
|
|
* target is the output expected from the grouping relation.
|
|
*/
|
|
static RelOptInfo *
|
|
make_grouping_rel(PlannerInfo *root, RelOptInfo *input_rel,
|
|
PathTarget *target, bool target_parallel_safe,
|
|
Node *havingQual)
|
|
{
|
|
RelOptInfo *grouped_rel;
|
|
|
|
if (IS_OTHER_REL(input_rel))
|
|
{
|
|
grouped_rel = fetch_upper_rel(root, UPPERREL_GROUP_AGG,
|
|
input_rel->relids);
|
|
grouped_rel->reloptkind = RELOPT_OTHER_UPPER_REL;
|
|
}
|
|
else
|
|
{
|
|
/*
|
|
* By tradition, the relids set for the main grouping relation is
|
|
* NULL. (This could be changed, but might require adjustments
|
|
* elsewhere.)
|
|
*/
|
|
grouped_rel = fetch_upper_rel(root, UPPERREL_GROUP_AGG, NULL);
|
|
}
|
|
|
|
/* Set target. */
|
|
grouped_rel->reltarget = target;
|
|
|
|
/*
|
|
* If the input relation is not parallel-safe, then the grouped relation
|
|
* can't be parallel-safe, either. Otherwise, it's parallel-safe if the
|
|
* target list and HAVING quals are parallel-safe.
|
|
*/
|
|
if (input_rel->consider_parallel && target_parallel_safe &&
|
|
is_parallel_safe(root, (Node *) havingQual))
|
|
grouped_rel->consider_parallel = true;
|
|
|
|
/*
|
|
* If the input rel belongs to a single FDW, so does the grouped rel.
|
|
*/
|
|
grouped_rel->serverid = input_rel->serverid;
|
|
grouped_rel->userid = input_rel->userid;
|
|
grouped_rel->useridiscurrent = input_rel->useridiscurrent;
|
|
grouped_rel->fdwroutine = input_rel->fdwroutine;
|
|
|
|
return grouped_rel;
|
|
}
|
|
|
|
/*
|
|
* is_degenerate_grouping
|
|
*
|
|
* A degenerate grouping is one in which the query has a HAVING qual and/or
|
|
* grouping sets, but no aggregates and no GROUP BY (which implies that the
|
|
* grouping sets are all empty).
|
|
*/
|
|
static bool
|
|
is_degenerate_grouping(PlannerInfo *root)
|
|
{
|
|
Query *parse = root->parse;
|
|
|
|
return (root->hasHavingQual || parse->groupingSets) &&
|
|
!parse->hasAggs && parse->groupClause == NIL;
|
|
}
|
|
|
|
/*
|
|
* create_degenerate_grouping_paths
|
|
*
|
|
* When the grouping is degenerate (see is_degenerate_grouping), we are
|
|
* supposed to emit either zero or one row for each grouping set 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 module to avoid having to generate the earlier paths
|
|
* in the first place.
|
|
*/
|
|
static void
|
|
create_degenerate_grouping_paths(PlannerInfo *root, RelOptInfo *input_rel,
|
|
RelOptInfo *grouped_rel)
|
|
{
|
|
Query *parse = root->parse;
|
|
int nrows;
|
|
Path *path;
|
|
|
|
nrows = list_length(parse->groupingSets);
|
|
if (nrows > 1)
|
|
{
|
|
/*
|
|
* Doesn't seem worthwhile writing code to cons up a generate_series
|
|
* or a values scan to emit multiple rows. Instead just make N clones
|
|
* and append them. (With a volatile HAVING clause, this means you
|
|
* might get between 0 and N output rows. Offhand I think that's
|
|
* desired.)
|
|
*/
|
|
List *paths = NIL;
|
|
|
|
while (--nrows >= 0)
|
|
{
|
|
path = (Path *)
|
|
create_group_result_path(root, grouped_rel,
|
|
grouped_rel->reltarget,
|
|
(List *) parse->havingQual);
|
|
paths = lappend(paths, path);
|
|
}
|
|
path = (Path *)
|
|
create_append_path(root,
|
|
grouped_rel,
|
|
paths,
|
|
NIL,
|
|
NIL,
|
|
NULL,
|
|
0,
|
|
false,
|
|
NIL,
|
|
-1);
|
|
}
|
|
else
|
|
{
|
|
/* No grouping sets, or just one, so one output row */
|
|
path = (Path *)
|
|
create_group_result_path(root, grouped_rel,
|
|
grouped_rel->reltarget,
|
|
(List *) parse->havingQual);
|
|
}
|
|
|
|
add_path(grouped_rel, path);
|
|
}
|
|
|
|
/*
|
|
* create_ordinary_grouping_paths
|
|
*
|
|
* Create grouping paths for the ordinary (that is, non-degenerate) case.
|
|
*
|
|
* We need to consider sorted and hashed aggregation in the same function,
|
|
* because otherwise (1) it would be harder to throw an appropriate error
|
|
* message if neither way works, and (2) we should not allow hashtable size
|
|
* considerations to dissuade us from using hashing if sorting is not possible.
|
|
*
|
|
* *partially_grouped_rel_p will be set to the partially grouped rel which this
|
|
* function creates, or to NULL if it doesn't create one.
|
|
*/
|
|
static void
|
|
create_ordinary_grouping_paths(PlannerInfo *root, RelOptInfo *input_rel,
|
|
RelOptInfo *grouped_rel,
|
|
const AggClauseCosts *agg_costs,
|
|
grouping_sets_data *gd,
|
|
GroupPathExtraData *extra,
|
|
RelOptInfo **partially_grouped_rel_p)
|
|
{
|
|
Path *cheapest_path = input_rel->cheapest_total_path;
|
|
RelOptInfo *partially_grouped_rel = NULL;
|
|
double dNumGroups;
|
|
PartitionwiseAggregateType patype = PARTITIONWISE_AGGREGATE_NONE;
|
|
|
|
/*
|
|
* If this is the topmost grouping relation or if the parent relation is
|
|
* doing some form of partitionwise aggregation, then we may be able to do
|
|
* it at this level also. However, if the input relation is not
|
|
* partitioned, partitionwise aggregate is impossible.
|
|
*/
|
|
if (extra->patype != PARTITIONWISE_AGGREGATE_NONE &&
|
|
IS_PARTITIONED_REL(input_rel))
|
|
{
|
|
/*
|
|
* If this is the topmost relation or if the parent relation is doing
|
|
* full partitionwise aggregation, then we can do full partitionwise
|
|
* aggregation provided that the GROUP BY clause contains all of the
|
|
* partitioning columns at this level. Otherwise, we can do at most
|
|
* partial partitionwise aggregation. But if partial aggregation is
|
|
* not supported in general then we can't use it for partitionwise
|
|
* aggregation either.
|
|
*/
|
|
if (extra->patype == PARTITIONWISE_AGGREGATE_FULL &&
|
|
group_by_has_partkey(input_rel, extra->targetList,
|
|
root->parse->groupClause))
|
|
patype = PARTITIONWISE_AGGREGATE_FULL;
|
|
else if ((extra->flags & GROUPING_CAN_PARTIAL_AGG) != 0)
|
|
patype = PARTITIONWISE_AGGREGATE_PARTIAL;
|
|
else
|
|
patype = PARTITIONWISE_AGGREGATE_NONE;
|
|
}
|
|
|
|
/*
|
|
* Before generating paths for grouped_rel, we first generate any possible
|
|
* partially grouped paths; that way, later code can easily consider both
|
|
* parallel and non-parallel approaches to grouping.
|
|
*/
|
|
if ((extra->flags & GROUPING_CAN_PARTIAL_AGG) != 0)
|
|
{
|
|
bool force_rel_creation;
|
|
|
|
/*
|
|
* If we're doing partitionwise aggregation at this level, force
|
|
* creation of a partially_grouped_rel so we can add partitionwise
|
|
* paths to it.
|
|
*/
|
|
force_rel_creation = (patype == PARTITIONWISE_AGGREGATE_PARTIAL);
|
|
|
|
partially_grouped_rel =
|
|
create_partial_grouping_paths(root,
|
|
grouped_rel,
|
|
input_rel,
|
|
gd,
|
|
extra,
|
|
force_rel_creation);
|
|
}
|
|
|
|
/* Set out parameter. */
|
|
*partially_grouped_rel_p = partially_grouped_rel;
|
|
|
|
/* Apply partitionwise aggregation technique, if possible. */
|
|
if (patype != PARTITIONWISE_AGGREGATE_NONE)
|
|
create_partitionwise_grouping_paths(root, input_rel, grouped_rel,
|
|
partially_grouped_rel, agg_costs,
|
|
gd, patype, extra);
|
|
|
|
/* If we are doing partial aggregation only, return. */
|
|
if (extra->patype == PARTITIONWISE_AGGREGATE_PARTIAL)
|
|
{
|
|
Assert(partially_grouped_rel);
|
|
|
|
if (partially_grouped_rel->pathlist)
|
|
set_cheapest(partially_grouped_rel);
|
|
|
|
return;
|
|
}
|
|
|
|
/* Gather any partially grouped partial paths. */
|
|
if (partially_grouped_rel && partially_grouped_rel->partial_pathlist)
|
|
{
|
|
gather_grouping_paths(root, partially_grouped_rel);
|
|
set_cheapest(partially_grouped_rel);
|
|
}
|
|
|
|
/*
|
|
* Estimate number of groups.
|
|
*/
|
|
dNumGroups = get_number_of_groups(root,
|
|
cheapest_path->rows,
|
|
gd,
|
|
extra->targetList);
|
|
|
|
/* Build final grouping paths */
|
|
add_paths_to_grouping_rel(root, input_rel, grouped_rel,
|
|
partially_grouped_rel, agg_costs, gd,
|
|
dNumGroups, extra);
|
|
|
|
/* Give a helpful error if we failed to find any implementation */
|
|
if (grouped_rel->pathlist == NIL)
|
|
ereport(ERROR,
|
|
(errcode(ERRCODE_FEATURE_NOT_SUPPORTED),
|
|
errmsg("could not implement GROUP BY"),
|
|
errdetail("Some of the datatypes only support hashing, while others only support sorting.")));
|
|
|
|
/*
|
|
* If there is an FDW that's responsible for all baserels of the query,
|
|
* let it consider adding ForeignPaths.
|
|
*/
|
|
if (grouped_rel->fdwroutine &&
|
|
grouped_rel->fdwroutine->GetForeignUpperPaths)
|
|
grouped_rel->fdwroutine->GetForeignUpperPaths(root, UPPERREL_GROUP_AGG,
|
|
input_rel, grouped_rel,
|
|
extra);
|
|
|
|
/* Let extensions possibly add some more paths */
|
|
if (create_upper_paths_hook)
|
|
(*create_upper_paths_hook) (root, UPPERREL_GROUP_AGG,
|
|
input_rel, grouped_rel,
|
|
extra);
|
|
}
|
|
|
|
/*
|
|
* For a given input path, consider the possible ways of doing grouping sets on
|
|
* it, by combinations of hashing and sorting. This can be called multiple
|
|
* times, so it's important that it not scribble on input. No result is
|
|
* returned, but any generated paths are added to grouped_rel.
|
|
*/
|
|
static void
|
|
consider_groupingsets_paths(PlannerInfo *root,
|
|
RelOptInfo *grouped_rel,
|
|
Path *path,
|
|
bool is_sorted,
|
|
bool can_hash,
|
|
grouping_sets_data *gd,
|
|
const AggClauseCosts *agg_costs,
|
|
double dNumGroups)
|
|
{
|
|
Query *parse = root->parse;
|
|
|
|
/*
|
|
* If we're not being offered sorted input, then only consider plans that
|
|
* can be done entirely by hashing.
|
|
*
|
|
* We can hash everything if it looks like it'll fit in work_mem. But if
|
|
* the input is actually sorted despite not being advertised as such, we
|
|
* prefer to make use of that in order to use less memory.
|
|
*
|
|
* If none of the grouping sets are sortable, then ignore the work_mem
|
|
* limit and generate a path anyway, since otherwise we'll just fail.
|
|
*/
|
|
if (!is_sorted)
|
|
{
|
|
List *new_rollups = NIL;
|
|
RollupData *unhashed_rollup = NULL;
|
|
List *sets_data;
|
|
List *empty_sets_data = NIL;
|
|
List *empty_sets = NIL;
|
|
ListCell *lc;
|
|
ListCell *l_start = list_head(gd->rollups);
|
|
AggStrategy strat = AGG_HASHED;
|
|
double hashsize;
|
|
double exclude_groups = 0.0;
|
|
|
|
Assert(can_hash);
|
|
|
|
/*
|
|
* If the input is coincidentally sorted usefully (which can happen
|
|
* even if is_sorted is false, since that only means that our caller
|
|
* has set up the sorting for us), then save some hashtable space by
|
|
* making use of that. But we need to watch out for degenerate cases:
|
|
*
|
|
* 1) If there are any empty grouping sets, then group_pathkeys might
|
|
* be NIL if all non-empty grouping sets are unsortable. In this case,
|
|
* there will be a rollup containing only empty groups, and the
|
|
* pathkeys_contained_in test is vacuously true; this is ok.
|
|
*
|
|
* XXX: the above relies on the fact that group_pathkeys is generated
|
|
* from the first rollup. If we add the ability to consider multiple
|
|
* sort orders for grouping input, this assumption might fail.
|
|
*
|
|
* 2) If there are no empty sets and only unsortable sets, then the
|
|
* rollups list will be empty (and thus l_start == NULL), and
|
|
* group_pathkeys will be NIL; we must ensure that the vacuously-true
|
|
* pathkeys_contained_in test doesn't cause us to crash.
|
|
*/
|
|
if (l_start != NULL &&
|
|
pathkeys_contained_in(root->group_pathkeys, path->pathkeys))
|
|
{
|
|
unhashed_rollup = lfirst_node(RollupData, l_start);
|
|
exclude_groups = unhashed_rollup->numGroups;
|
|
l_start = lnext(gd->rollups, l_start);
|
|
}
|
|
|
|
hashsize = estimate_hashagg_tablesize(path,
|
|
agg_costs,
|
|
dNumGroups - exclude_groups);
|
|
|
|
/*
|
|
* gd->rollups is empty if we have only unsortable columns to work
|
|
* with. Override work_mem in that case; otherwise, we'll rely on the
|
|
* sorted-input case to generate usable mixed paths.
|
|
*/
|
|
if (hashsize > work_mem * 1024L && gd->rollups)
|
|
return; /* nope, won't fit */
|
|
|
|
/*
|
|
* We need to burst the existing rollups list into individual grouping
|
|
* sets and recompute a groupClause for each set.
|
|
*/
|
|
sets_data = list_copy(gd->unsortable_sets);
|
|
|
|
for_each_cell(lc, gd->rollups, l_start)
|
|
{
|
|
RollupData *rollup = lfirst_node(RollupData, lc);
|
|
|
|
/*
|
|
* If we find an unhashable rollup that's not been skipped by the
|
|
* "actually sorted" check above, we can't cope; we'd need sorted
|
|
* input (with a different sort order) but we can't get that here.
|
|
* So bail out; we'll get a valid path from the is_sorted case
|
|
* instead.
|
|
*
|
|
* The mere presence of empty grouping sets doesn't make a rollup
|
|
* unhashable (see preprocess_grouping_sets), we handle those
|
|
* specially below.
|
|
*/
|
|
if (!rollup->hashable)
|
|
return;
|
|
|
|
sets_data = list_concat(sets_data, rollup->gsets_data);
|
|
}
|
|
foreach(lc, sets_data)
|
|
{
|
|
GroupingSetData *gs = lfirst_node(GroupingSetData, lc);
|
|
List *gset = gs->set;
|
|
RollupData *rollup;
|
|
|
|
if (gset == NIL)
|
|
{
|
|
/* Empty grouping sets can't be hashed. */
|
|
empty_sets_data = lappend(empty_sets_data, gs);
|
|
empty_sets = lappend(empty_sets, NIL);
|
|
}
|
|
else
|
|
{
|
|
rollup = makeNode(RollupData);
|
|
|
|
rollup->groupClause = preprocess_groupclause(root, gset);
|
|
rollup->gsets_data = list_make1(gs);
|
|
rollup->gsets = remap_to_groupclause_idx(rollup->groupClause,
|
|
rollup->gsets_data,
|
|
gd->tleref_to_colnum_map);
|
|
rollup->numGroups = gs->numGroups;
|
|
rollup->hashable = true;
|
|
rollup->is_hashed = true;
|
|
new_rollups = lappend(new_rollups, rollup);
|
|
}
|
|
}
|
|
|
|
/*
|
|
* If we didn't find anything nonempty to hash, then bail. We'll
|
|
* generate a path from the is_sorted case.
|
|
*/
|
|
if (new_rollups == NIL)
|
|
return;
|
|
|
|
/*
|
|
* If there were empty grouping sets they should have been in the
|
|
* first rollup.
|
|
*/
|
|
Assert(!unhashed_rollup || !empty_sets);
|
|
|
|
if (unhashed_rollup)
|
|
{
|
|
new_rollups = lappend(new_rollups, unhashed_rollup);
|
|
strat = AGG_MIXED;
|
|
}
|
|
else if (empty_sets)
|
|
{
|
|
RollupData *rollup = makeNode(RollupData);
|
|
|
|
rollup->groupClause = NIL;
|
|
rollup->gsets_data = empty_sets_data;
|
|
rollup->gsets = empty_sets;
|
|
rollup->numGroups = list_length(empty_sets);
|
|
rollup->hashable = false;
|
|
rollup->is_hashed = false;
|
|
new_rollups = lappend(new_rollups, rollup);
|
|
strat = AGG_MIXED;
|
|
}
|
|
|
|
add_path(grouped_rel, (Path *)
|
|
create_groupingsets_path(root,
|
|
grouped_rel,
|
|
path,
|
|
(List *) parse->havingQual,
|
|
strat,
|
|
new_rollups,
|
|
agg_costs,
|
|
dNumGroups));
|
|
return;
|
|
}
|
|
|
|
/*
|
|
* If we have sorted input but nothing we can do with it, bail.
|
|
*/
|
|
if (list_length(gd->rollups) == 0)
|
|
return;
|
|
|
|
/*
|
|
* Given sorted input, we try and make two paths: one sorted and one mixed
|
|
* sort/hash. (We need to try both because hashagg might be disabled, or
|
|
* some columns might not be sortable.)
|
|
*
|
|
* can_hash is passed in as false if some obstacle elsewhere (such as
|
|
* ordered aggs) means that we shouldn't consider hashing at all.
|
|
*/
|
|
if (can_hash && gd->any_hashable)
|
|
{
|
|
List *rollups = NIL;
|
|
List *hash_sets = list_copy(gd->unsortable_sets);
|
|
double availspace = (work_mem * 1024.0);
|
|
ListCell *lc;
|
|
|
|
/*
|
|
* Account first for space needed for groups we can't sort at all.
|
|
*/
|
|
availspace -= estimate_hashagg_tablesize(path,
|
|
agg_costs,
|
|
gd->dNumHashGroups);
|
|
|
|
if (availspace > 0 && list_length(gd->rollups) > 1)
|
|
{
|
|
double scale;
|
|
int num_rollups = list_length(gd->rollups);
|
|
int k_capacity;
|
|
int *k_weights = palloc(num_rollups * sizeof(int));
|
|
Bitmapset *hash_items = NULL;
|
|
int i;
|
|
|
|
/*
|
|
* We treat this as a knapsack problem: the knapsack capacity
|
|
* represents work_mem, the item weights are the estimated memory
|
|
* usage of the hashtables needed to implement a single rollup,
|
|
* and we really ought to use the cost saving as the item value;
|
|
* however, currently the costs assigned to sort nodes don't
|
|
* reflect the comparison costs well, and so we treat all items as
|
|
* of equal value (each rollup we hash instead saves us one sort).
|
|
*
|
|
* To use the discrete knapsack, we need to scale the values to a
|
|
* reasonably small bounded range. We choose to allow a 5% error
|
|
* margin; we have no more than 4096 rollups in the worst possible
|
|
* case, which with a 5% error margin will require a bit over 42MB
|
|
* of workspace. (Anyone wanting to plan queries that complex had
|
|
* better have the memory for it. In more reasonable cases, with
|
|
* no more than a couple of dozen rollups, the memory usage will
|
|
* be negligible.)
|
|
*
|
|
* k_capacity is naturally bounded, but we clamp the values for
|
|
* scale and weight (below) to avoid overflows or underflows (or
|
|
* uselessly trying to use a scale factor less than 1 byte).
|
|
*/
|
|
scale = Max(availspace / (20.0 * num_rollups), 1.0);
|
|
k_capacity = (int) floor(availspace / scale);
|
|
|
|
/*
|
|
* We leave the first rollup out of consideration since it's the
|
|
* one that matches the input sort order. We assign indexes "i"
|
|
* to only those entries considered for hashing; the second loop,
|
|
* below, must use the same condition.
|
|
*/
|
|
i = 0;
|
|
for_each_cell(lc, gd->rollups, list_second_cell(gd->rollups))
|
|
{
|
|
RollupData *rollup = lfirst_node(RollupData, lc);
|
|
|
|
if (rollup->hashable)
|
|
{
|
|
double sz = estimate_hashagg_tablesize(path,
|
|
agg_costs,
|
|
rollup->numGroups);
|
|
|
|
/*
|
|
* If sz is enormous, but work_mem (and hence scale) is
|
|
* small, avoid integer overflow here.
|
|
*/
|
|
k_weights[i] = (int) Min(floor(sz / scale),
|
|
k_capacity + 1.0);
|
|
++i;
|
|
}
|
|
}
|
|
|
|
/*
|
|
* Apply knapsack algorithm; compute the set of items which
|
|
* maximizes the value stored (in this case the number of sorts
|
|
* saved) while keeping the total size (approximately) within
|
|
* capacity.
|
|
*/
|
|
if (i > 0)
|
|
hash_items = DiscreteKnapsack(k_capacity, i, k_weights, NULL);
|
|
|
|
if (!bms_is_empty(hash_items))
|
|
{
|
|
rollups = list_make1(linitial(gd->rollups));
|
|
|
|
i = 0;
|
|
for_each_cell(lc, gd->rollups, list_second_cell(gd->rollups))
|
|
{
|
|
RollupData *rollup = lfirst_node(RollupData, lc);
|
|
|
|
if (rollup->hashable)
|
|
{
|
|
if (bms_is_member(i, hash_items))
|
|
hash_sets = list_concat(hash_sets,
|
|
rollup->gsets_data);
|
|
else
|
|
rollups = lappend(rollups, rollup);
|
|
++i;
|
|
}
|
|
else
|
|
rollups = lappend(rollups, rollup);
|
|
}
|
|
}
|
|
}
|
|
|
|
if (!rollups && hash_sets)
|
|
rollups = list_copy(gd->rollups);
|
|
|
|
foreach(lc, hash_sets)
|
|
{
|
|
GroupingSetData *gs = lfirst_node(GroupingSetData, lc);
|
|
RollupData *rollup = makeNode(RollupData);
|
|
|
|
Assert(gs->set != NIL);
|
|
|
|
rollup->groupClause = preprocess_groupclause(root, gs->set);
|
|
rollup->gsets_data = list_make1(gs);
|
|
rollup->gsets = remap_to_groupclause_idx(rollup->groupClause,
|
|
rollup->gsets_data,
|
|
gd->tleref_to_colnum_map);
|
|
rollup->numGroups = gs->numGroups;
|
|
rollup->hashable = true;
|
|
rollup->is_hashed = true;
|
|
rollups = lcons(rollup, rollups);
|
|
}
|
|
|
|
if (rollups)
|
|
{
|
|
add_path(grouped_rel, (Path *)
|
|
create_groupingsets_path(root,
|
|
grouped_rel,
|
|
path,
|
|
(List *) parse->havingQual,
|
|
AGG_MIXED,
|
|
rollups,
|
|
agg_costs,
|
|
dNumGroups));
|
|
}
|
|
}
|
|
|
|
/*
|
|
* Now try the simple sorted case.
|
|
*/
|
|
if (!gd->unsortable_sets)
|
|
add_path(grouped_rel, (Path *)
|
|
create_groupingsets_path(root,
|
|
grouped_rel,
|
|
path,
|
|
(List *) parse->havingQual,
|
|
AGG_SORTED,
|
|
gd->rollups,
|
|
agg_costs,
|
|
dNumGroups));
|
|
}
|
|
|
|
/*
|
|
* create_window_paths
|
|
*
|
|
* Build a new upperrel containing Paths for window-function evaluation.
|
|
*
|
|
* input_rel: contains the source-data Paths
|
|
* input_target: result of make_window_input_target
|
|
* output_target: what the topmost WindowAggPath should return
|
|
* wflists: result of find_window_functions
|
|
* activeWindows: result of select_active_windows
|
|
*
|
|
* Note: all Paths in input_rel are expected to return input_target.
|
|
*/
|
|
static RelOptInfo *
|
|
create_window_paths(PlannerInfo *root,
|
|
RelOptInfo *input_rel,
|
|
PathTarget *input_target,
|
|
PathTarget *output_target,
|
|
bool output_target_parallel_safe,
|
|
WindowFuncLists *wflists,
|
|
List *activeWindows)
|
|
{
|
|
RelOptInfo *window_rel;
|
|
ListCell *lc;
|
|
|
|
/* For now, do all work in the (WINDOW, NULL) upperrel */
|
|
window_rel = fetch_upper_rel(root, UPPERREL_WINDOW, NULL);
|
|
|
|
/*
|
|
* If the input relation is not parallel-safe, then the window relation
|
|
* can't be parallel-safe, either. Otherwise, we need to examine the
|
|
* target list and active windows for non-parallel-safe constructs.
|
|
*/
|
|
if (input_rel->consider_parallel && output_target_parallel_safe &&
|
|
is_parallel_safe(root, (Node *) activeWindows))
|
|
window_rel->consider_parallel = true;
|
|
|
|
/*
|
|
* If the input rel belongs to a single FDW, so does the window rel.
|
|
*/
|
|
window_rel->serverid = input_rel->serverid;
|
|
window_rel->userid = input_rel->userid;
|
|
window_rel->useridiscurrent = input_rel->useridiscurrent;
|
|
window_rel->fdwroutine = input_rel->fdwroutine;
|
|
|
|
/*
|
|
* Consider computing window functions starting from the existing
|
|
* cheapest-total path (which will likely require a sort) as well as any
|
|
* existing paths that satisfy root->window_pathkeys (which won't).
|
|
*/
|
|
foreach(lc, input_rel->pathlist)
|
|
{
|
|
Path *path = (Path *) lfirst(lc);
|
|
|
|
if (path == input_rel->cheapest_total_path ||
|
|
pathkeys_contained_in(root->window_pathkeys, path->pathkeys))
|
|
create_one_window_path(root,
|
|
window_rel,
|
|
path,
|
|
input_target,
|
|
output_target,
|
|
wflists,
|
|
activeWindows);
|
|
}
|
|
|
|
/*
|
|
* If there is an FDW that's responsible for all baserels of the query,
|
|
* let it consider adding ForeignPaths.
|
|
*/
|
|
if (window_rel->fdwroutine &&
|
|
window_rel->fdwroutine->GetForeignUpperPaths)
|
|
window_rel->fdwroutine->GetForeignUpperPaths(root, UPPERREL_WINDOW,
|
|
input_rel, window_rel,
|
|
NULL);
|
|
|
|
/* Let extensions possibly add some more paths */
|
|
if (create_upper_paths_hook)
|
|
(*create_upper_paths_hook) (root, UPPERREL_WINDOW,
|
|
input_rel, window_rel, NULL);
|
|
|
|
/* Now choose the best path(s) */
|
|
set_cheapest(window_rel);
|
|
|
|
return window_rel;
|
|
}
|
|
|
|
/*
|
|
* Stack window-function implementation steps atop the given Path, and
|
|
* add the result to window_rel.
|
|
*
|
|
* window_rel: upperrel to contain result
|
|
* path: input Path to use (must return input_target)
|
|
* input_target: result of make_window_input_target
|
|
* output_target: what the topmost WindowAggPath should return
|
|
* wflists: result of find_window_functions
|
|
* activeWindows: result of select_active_windows
|
|
*/
|
|
static void
|
|
create_one_window_path(PlannerInfo *root,
|
|
RelOptInfo *window_rel,
|
|
Path *path,
|
|
PathTarget *input_target,
|
|
PathTarget *output_target,
|
|
WindowFuncLists *wflists,
|
|
List *activeWindows)
|
|
{
|
|
PathTarget *window_target;
|
|
ListCell *l;
|
|
|
|
/*
|
|
* Since each window clause could require a different sort order, we stack
|
|
* up a WindowAgg node for each clause, with sort steps between them as
|
|
* needed. (We assume that select_active_windows chose a good order for
|
|
* executing the clauses in.)
|
|
*
|
|
* input_target should contain all Vars and Aggs needed for the result.
|
|
* (In some cases we wouldn't need to propagate all of these all the way
|
|
* to the top, since they might only be needed as inputs to WindowFuncs.
|
|
* It's probably not worth trying to optimize that though.) It must also
|
|
* contain all window partitioning and sorting expressions, to ensure
|
|
* they're computed only once at the bottom of the stack (that's critical
|
|
* for volatile functions). As we climb up the stack, we'll add outputs
|
|
* for the WindowFuncs computed at each level.
|
|
*/
|
|
window_target = input_target;
|
|
|
|
foreach(l, activeWindows)
|
|
{
|
|
WindowClause *wc = lfirst_node(WindowClause, l);
|
|
List *window_pathkeys;
|
|
|
|
window_pathkeys = make_pathkeys_for_window(root,
|
|
wc,
|
|
root->processed_tlist);
|
|
|
|
/* Sort if necessary */
|
|
if (!pathkeys_contained_in(window_pathkeys, path->pathkeys))
|
|
{
|
|
path = (Path *) create_sort_path(root, window_rel,
|
|
path,
|
|
window_pathkeys,
|
|
-1.0);
|
|
}
|
|
|
|
if (lnext(activeWindows, l))
|
|
{
|
|
/*
|
|
* Add the current WindowFuncs to the output target for this
|
|
* intermediate WindowAggPath. We must copy window_target to
|
|
* avoid changing the previous path's target.
|
|
*
|
|
* Note: a WindowFunc adds nothing to the target's eval costs; but
|
|
* we do need to account for the increase in tlist width.
|
|
*/
|
|
ListCell *lc2;
|
|
|
|
window_target = copy_pathtarget(window_target);
|
|
foreach(lc2, wflists->windowFuncs[wc->winref])
|
|
{
|
|
WindowFunc *wfunc = lfirst_node(WindowFunc, lc2);
|
|
|
|
add_column_to_pathtarget(window_target, (Expr *) wfunc, 0);
|
|
window_target->width += get_typavgwidth(wfunc->wintype, -1);
|
|
}
|
|
}
|
|
else
|
|
{
|
|
/* Install the goal target in the topmost WindowAgg */
|
|
window_target = output_target;
|
|
}
|
|
|
|
path = (Path *)
|
|
create_windowagg_path(root, window_rel, path, window_target,
|
|
wflists->windowFuncs[wc->winref],
|
|
wc);
|
|
}
|
|
|
|
add_path(window_rel, path);
|
|
}
|
|
|
|
/*
|
|
* create_distinct_paths
|
|
*
|
|
* Build a new upperrel containing Paths for SELECT DISTINCT evaluation.
|
|
*
|
|
* input_rel: contains the source-data Paths
|
|
*
|
|
* Note: input paths should already compute the desired pathtarget, since
|
|
* Sort/Unique won't project anything.
|
|
*/
|
|
static RelOptInfo *
|
|
create_distinct_paths(PlannerInfo *root,
|
|
RelOptInfo *input_rel)
|
|
{
|
|
Query *parse = root->parse;
|
|
Path *cheapest_input_path = input_rel->cheapest_total_path;
|
|
RelOptInfo *distinct_rel;
|
|
double numDistinctRows;
|
|
bool allow_hash;
|
|
Path *path;
|
|
ListCell *lc;
|
|
|
|
/* For now, do all work in the (DISTINCT, NULL) upperrel */
|
|
distinct_rel = fetch_upper_rel(root, UPPERREL_DISTINCT, NULL);
|
|
|
|
/*
|
|
* We don't compute anything at this level, so distinct_rel will be
|
|
* parallel-safe if the input rel is parallel-safe. In particular, if
|
|
* there is a DISTINCT ON (...) clause, any path for the input_rel will
|
|
* output those expressions, and will not be parallel-safe unless those
|
|
* expressions are parallel-safe.
|
|
*/
|
|
distinct_rel->consider_parallel = input_rel->consider_parallel;
|
|
|
|
/*
|
|
* If the input rel belongs to a single FDW, so does the distinct_rel.
|
|
*/
|
|
distinct_rel->serverid = input_rel->serverid;
|
|
distinct_rel->userid = input_rel->userid;
|
|
distinct_rel->useridiscurrent = input_rel->useridiscurrent;
|
|
distinct_rel->fdwroutine = input_rel->fdwroutine;
|
|
|
|
/* Estimate number of distinct rows there will be */
|
|
if (parse->groupClause || parse->groupingSets || parse->hasAggs ||
|
|
root->hasHavingQual)
|
|
{
|
|
/*
|
|
* If there was grouping or aggregation, use the number of input rows
|
|
* as the estimated number of DISTINCT rows (ie, assume the input is
|
|
* already mostly unique).
|
|
*/
|
|
numDistinctRows = cheapest_input_path->rows;
|
|
}
|
|
else
|
|
{
|
|
/*
|
|
* Otherwise, the UNIQUE filter has effects comparable to GROUP BY.
|
|
*/
|
|
List *distinctExprs;
|
|
|
|
distinctExprs = get_sortgrouplist_exprs(parse->distinctClause,
|
|
parse->targetList);
|
|
numDistinctRows = estimate_num_groups(root, distinctExprs,
|
|
cheapest_input_path->rows,
|
|
NULL);
|
|
}
|
|
|
|
/*
|
|
* Consider sort-based implementations of DISTINCT, if possible.
|
|
*/
|
|
if (grouping_is_sortable(parse->distinctClause))
|
|
{
|
|
/*
|
|
* First, if we have any adequately-presorted paths, just stick a
|
|
* Unique node on those. Then consider doing an explicit sort of the
|
|
* cheapest input path and Unique'ing that.
|
|
*
|
|
* When we have DISTINCT ON, we must sort by the more rigorous of
|
|
* DISTINCT and ORDER BY, else it won't have the desired behavior.
|
|
* Also, if we do have to do an explicit sort, we might as well use
|
|
* the more rigorous ordering to avoid a second sort later. (Note
|
|
* that the parser will have ensured that one clause is a prefix of
|
|
* the other.)
|
|
*/
|
|
List *needed_pathkeys;
|
|
|
|
if (parse->hasDistinctOn &&
|
|
list_length(root->distinct_pathkeys) <
|
|
list_length(root->sort_pathkeys))
|
|
needed_pathkeys = root->sort_pathkeys;
|
|
else
|
|
needed_pathkeys = root->distinct_pathkeys;
|
|
|
|
foreach(lc, input_rel->pathlist)
|
|
{
|
|
Path *path = (Path *) lfirst(lc);
|
|
|
|
if (pathkeys_contained_in(needed_pathkeys, path->pathkeys))
|
|
{
|
|
add_path(distinct_rel, (Path *)
|
|
create_upper_unique_path(root, distinct_rel,
|
|
path,
|
|
list_length(root->distinct_pathkeys),
|
|
numDistinctRows));
|
|
}
|
|
}
|
|
|
|
/* For explicit-sort case, always use the more rigorous clause */
|
|
if (list_length(root->distinct_pathkeys) <
|
|
list_length(root->sort_pathkeys))
|
|
{
|
|
needed_pathkeys = root->sort_pathkeys;
|
|
/* Assert checks that parser didn't mess up... */
|
|
Assert(pathkeys_contained_in(root->distinct_pathkeys,
|
|
needed_pathkeys));
|
|
}
|
|
else
|
|
needed_pathkeys = root->distinct_pathkeys;
|
|
|
|
path = cheapest_input_path;
|
|
if (!pathkeys_contained_in(needed_pathkeys, path->pathkeys))
|
|
path = (Path *) create_sort_path(root, distinct_rel,
|
|
path,
|
|
needed_pathkeys,
|
|
-1.0);
|
|
|
|
add_path(distinct_rel, (Path *)
|
|
create_upper_unique_path(root, distinct_rel,
|
|
path,
|
|
list_length(root->distinct_pathkeys),
|
|
numDistinctRows));
|
|
}
|
|
|
|
/*
|
|
* Consider hash-based implementations of DISTINCT, if possible.
|
|
*
|
|
* If we were not able to make any other types of path, we *must* hash or
|
|
* die trying. If we do have other choices, there are several things that
|
|
* should prevent selection of hashing: if the query uses DISTINCT ON
|
|
* (because it won't really have the expected behavior if we hash), or if
|
|
* enable_hashagg is off, or if it looks like the hashtable will exceed
|
|
* work_mem.
|
|
*
|
|
* Note: grouping_is_hashable() is much more expensive to check than the
|
|
* other gating conditions, so we want to do it last.
|
|
*/
|
|
if (distinct_rel->pathlist == NIL)
|
|
allow_hash = true; /* we have no alternatives */
|
|
else if (parse->hasDistinctOn || !enable_hashagg)
|
|
allow_hash = false; /* policy-based decision not to hash */
|
|
else
|
|
{
|
|
Size hashentrysize;
|
|
|
|
/* Estimate per-hash-entry space at tuple width... */
|
|
hashentrysize = MAXALIGN(cheapest_input_path->pathtarget->width) +
|
|
MAXALIGN(SizeofMinimalTupleHeader);
|
|
/* plus the per-hash-entry overhead */
|
|
hashentrysize += hash_agg_entry_size(0);
|
|
|
|
/* Allow hashing only if hashtable is predicted to fit in work_mem */
|
|
allow_hash = (hashentrysize * numDistinctRows <= work_mem * 1024L);
|
|
}
|
|
|
|
if (allow_hash && grouping_is_hashable(parse->distinctClause))
|
|
{
|
|
/* Generate hashed aggregate path --- no sort needed */
|
|
add_path(distinct_rel, (Path *)
|
|
create_agg_path(root,
|
|
distinct_rel,
|
|
cheapest_input_path,
|
|
cheapest_input_path->pathtarget,
|
|
AGG_HASHED,
|
|
AGGSPLIT_SIMPLE,
|
|
parse->distinctClause,
|
|
NIL,
|
|
NULL,
|
|
numDistinctRows));
|
|
}
|
|
|
|
/* Give a helpful error if we failed to find any implementation */
|
|
if (distinct_rel->pathlist == NIL)
|
|
ereport(ERROR,
|
|
(errcode(ERRCODE_FEATURE_NOT_SUPPORTED),
|
|
errmsg("could not implement DISTINCT"),
|
|
errdetail("Some of the datatypes only support hashing, while others only support sorting.")));
|
|
|
|
/*
|
|
* If there is an FDW that's responsible for all baserels of the query,
|
|
* let it consider adding ForeignPaths.
|
|
*/
|
|
if (distinct_rel->fdwroutine &&
|
|
distinct_rel->fdwroutine->GetForeignUpperPaths)
|
|
distinct_rel->fdwroutine->GetForeignUpperPaths(root, UPPERREL_DISTINCT,
|
|
input_rel, distinct_rel,
|
|
NULL);
|
|
|
|
/* Let extensions possibly add some more paths */
|
|
if (create_upper_paths_hook)
|
|
(*create_upper_paths_hook) (root, UPPERREL_DISTINCT,
|
|
input_rel, distinct_rel, NULL);
|
|
|
|
/* Now choose the best path(s) */
|
|
set_cheapest(distinct_rel);
|
|
|
|
return distinct_rel;
|
|
}
|
|
|
|
/*
|
|
* create_ordered_paths
|
|
*
|
|
* Build a new upperrel containing Paths for ORDER BY evaluation.
|
|
*
|
|
* All paths in the result must satisfy the ORDER BY ordering.
|
|
* The only new path we need consider is an explicit sort on the
|
|
* cheapest-total existing path.
|
|
*
|
|
* input_rel: contains the source-data Paths
|
|
* target: the output tlist the result Paths must emit
|
|
* limit_tuples: estimated bound on the number of output tuples,
|
|
* or -1 if no LIMIT or couldn't estimate
|
|
*/
|
|
static RelOptInfo *
|
|
create_ordered_paths(PlannerInfo *root,
|
|
RelOptInfo *input_rel,
|
|
PathTarget *target,
|
|
bool target_parallel_safe,
|
|
double limit_tuples)
|
|
{
|
|
Path *cheapest_input_path = input_rel->cheapest_total_path;
|
|
RelOptInfo *ordered_rel;
|
|
ListCell *lc;
|
|
|
|
/* For now, do all work in the (ORDERED, NULL) upperrel */
|
|
ordered_rel = fetch_upper_rel(root, UPPERREL_ORDERED, NULL);
|
|
|
|
/*
|
|
* If the input relation is not parallel-safe, then the ordered relation
|
|
* can't be parallel-safe, either. Otherwise, it's parallel-safe if the
|
|
* target list is parallel-safe.
|
|
*/
|
|
if (input_rel->consider_parallel && target_parallel_safe)
|
|
ordered_rel->consider_parallel = true;
|
|
|
|
/*
|
|
* If the input rel belongs to a single FDW, so does the ordered_rel.
|
|
*/
|
|
ordered_rel->serverid = input_rel->serverid;
|
|
ordered_rel->userid = input_rel->userid;
|
|
ordered_rel->useridiscurrent = input_rel->useridiscurrent;
|
|
ordered_rel->fdwroutine = input_rel->fdwroutine;
|
|
|
|
foreach(lc, input_rel->pathlist)
|
|
{
|
|
Path *path = (Path *) lfirst(lc);
|
|
bool is_sorted;
|
|
|
|
is_sorted = pathkeys_contained_in(root->sort_pathkeys,
|
|
path->pathkeys);
|
|
if (path == cheapest_input_path || is_sorted)
|
|
{
|
|
if (!is_sorted)
|
|
{
|
|
/* An explicit sort here can take advantage of LIMIT */
|
|
path = (Path *) create_sort_path(root,
|
|
ordered_rel,
|
|
path,
|
|
root->sort_pathkeys,
|
|
limit_tuples);
|
|
}
|
|
|
|
/* Add projection step if needed */
|
|
if (path->pathtarget != target)
|
|
path = apply_projection_to_path(root, ordered_rel,
|
|
path, target);
|
|
|
|
add_path(ordered_rel, path);
|
|
}
|
|
}
|
|
|
|
/*
|
|
* generate_gather_paths() will have already generated a simple Gather
|
|
* path for the best parallel path, if any, and the loop above will have
|
|
* considered sorting it. Similarly, generate_gather_paths() will also
|
|
* have generated order-preserving Gather Merge plans which can be used
|
|
* without sorting if they happen to match the sort_pathkeys, and the loop
|
|
* above will have handled those as well. However, there's one more
|
|
* possibility: it may make sense to sort the cheapest partial path
|
|
* according to the required output order and then use Gather Merge.
|
|
*/
|
|
if (ordered_rel->consider_parallel && root->sort_pathkeys != NIL &&
|
|
input_rel->partial_pathlist != NIL)
|
|
{
|
|
Path *cheapest_partial_path;
|
|
|
|
cheapest_partial_path = linitial(input_rel->partial_pathlist);
|
|
|
|
/*
|
|
* If cheapest partial path doesn't need a sort, this is redundant
|
|
* with what's already been tried.
|
|
*/
|
|
if (!pathkeys_contained_in(root->sort_pathkeys,
|
|
cheapest_partial_path->pathkeys))
|
|
{
|
|
Path *path;
|
|
double total_groups;
|
|
|
|
path = (Path *) create_sort_path(root,
|
|
ordered_rel,
|
|
cheapest_partial_path,
|
|
root->sort_pathkeys,
|
|
limit_tuples);
|
|
|
|
total_groups = cheapest_partial_path->rows *
|
|
cheapest_partial_path->parallel_workers;
|
|
path = (Path *)
|
|
create_gather_merge_path(root, ordered_rel,
|
|
path,
|
|
path->pathtarget,
|
|
root->sort_pathkeys, NULL,
|
|
&total_groups);
|
|
|
|
/* Add projection step if needed */
|
|
if (path->pathtarget != target)
|
|
path = apply_projection_to_path(root, ordered_rel,
|
|
path, target);
|
|
|
|
add_path(ordered_rel, path);
|
|
}
|
|
}
|
|
|
|
/*
|
|
* If there is an FDW that's responsible for all baserels of the query,
|
|
* let it consider adding ForeignPaths.
|
|
*/
|
|
if (ordered_rel->fdwroutine &&
|
|
ordered_rel->fdwroutine->GetForeignUpperPaths)
|
|
ordered_rel->fdwroutine->GetForeignUpperPaths(root, UPPERREL_ORDERED,
|
|
input_rel, ordered_rel,
|
|
NULL);
|
|
|
|
/* Let extensions possibly add some more paths */
|
|
if (create_upper_paths_hook)
|
|
(*create_upper_paths_hook) (root, UPPERREL_ORDERED,
|
|
input_rel, ordered_rel, NULL);
|
|
|
|
/*
|
|
* No need to bother with set_cheapest here; grouping_planner does not
|
|
* need us to do it.
|
|
*/
|
|
Assert(ordered_rel->pathlist != NIL);
|
|
|
|
return ordered_rel;
|
|
}
|
|
|
|
|
|
/*
|
|
* make_group_input_target
|
|
* Generate appropriate PathTarget for initial input to grouping nodes.
|
|
*
|
|
* If there is grouping or aggregation, the scan/join subplan cannot emit
|
|
* the query's final targetlist; for example, it certainly can't emit any
|
|
* aggregate function calls. This routine generates the correct target
|
|
* for the scan/join subplan.
|
|
*
|
|
* The query 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; other expressions
|
|
* will be computed by the upper plan 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
|
|
* 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.
|
|
*
|
|
* 'final_target' is the query's final target list (in PathTarget form)
|
|
*
|
|
* The result is the PathTarget to be computed by the Paths returned from
|
|
* query_planner().
|
|
*/
|
|
static PathTarget *
|
|
make_group_input_target(PlannerInfo *root, PathTarget *final_target)
|
|
{
|
|
Query *parse = root->parse;
|
|
PathTarget *input_target;
|
|
List *non_group_cols;
|
|
List *non_group_vars;
|
|
int i;
|
|
ListCell *lc;
|
|
|
|
/*
|
|
* We must build a target containing all grouping columns, plus any other
|
|
* Vars mentioned in the query's targetlist and HAVING qual.
|
|
*/
|
|
input_target = create_empty_pathtarget();
|
|
non_group_cols = NIL;
|
|
|
|
i = 0;
|
|
foreach(lc, final_target->exprs)
|
|
{
|
|
Expr *expr = (Expr *) lfirst(lc);
|
|
Index sgref = get_pathtarget_sortgroupref(final_target, i);
|
|
|
|
if (sgref && parse->groupClause &&
|
|
get_sortgroupref_clause_noerr(sgref, parse->groupClause) != NULL)
|
|
{
|
|
/*
|
|
* It's a grouping column, so add it to the input target as-is.
|
|
*/
|
|
add_column_to_pathtarget(input_target, expr, sgref);
|
|
}
|
|
else
|
|
{
|
|
/*
|
|
* Non-grouping column, so just remember the expression for later
|
|
* call to pull_var_clause.
|
|
*/
|
|
non_group_cols = lappend(non_group_cols, expr);
|
|
}
|
|
|
|
i++;
|
|
}
|
|
|
|
/*
|
|
* If there's a HAVING clause, we'll need the Vars it uses, too.
|
|
*/
|
|
if (parse->havingQual)
|
|
non_group_cols = lappend(non_group_cols, parse->havingQual);
|
|
|
|
/*
|
|
* Pull out all the Vars mentioned in non-group cols (plus HAVING), and
|
|
* add them to the input target if not already present. (A Var used
|
|
* directly as a GROUP BY item will be present already.) Note this
|
|
* includes Vars used in resjunk items, so we are covering the needs of
|
|
* ORDER BY and window specifications. Vars used within Aggrefs and
|
|
* WindowFuncs will be pulled out here, too.
|
|
*/
|
|
non_group_vars = pull_var_clause((Node *) non_group_cols,
|
|
PVC_RECURSE_AGGREGATES |
|
|
PVC_RECURSE_WINDOWFUNCS |
|
|
PVC_INCLUDE_PLACEHOLDERS);
|
|
add_new_columns_to_pathtarget(input_target, non_group_vars);
|
|
|
|
/* clean up cruft */
|
|
list_free(non_group_vars);
|
|
list_free(non_group_cols);
|
|
|
|
/* XXX this causes some redundant cost calculation ... */
|
|
return set_pathtarget_cost_width(root, input_target);
|
|
}
|
|
|
|
/*
|
|
* make_partial_grouping_target
|
|
* Generate appropriate PathTarget for output of partial aggregate
|
|
* (or partial grouping, if there are no aggregates) nodes.
|
|
*
|
|
* A partial aggregation node needs to emit all the same aggregates that
|
|
* a regular aggregation node would, plus any aggregates used in HAVING;
|
|
* except that the Aggref nodes should be marked as partial aggregates.
|
|
*
|
|
* In addition, we'd better emit any Vars and PlaceHolderVars that are
|
|
* used outside of Aggrefs in the aggregation tlist and HAVING. (Presumably,
|
|
* these would be Vars that are grouped by or used in grouping expressions.)
|
|
*
|
|
* grouping_target is the tlist to be emitted by the topmost aggregation step.
|
|
* havingQual represents the HAVING clause.
|
|
*/
|
|
static PathTarget *
|
|
make_partial_grouping_target(PlannerInfo *root,
|
|
PathTarget *grouping_target,
|
|
Node *havingQual)
|
|
{
|
|
Query *parse = root->parse;
|
|
PathTarget *partial_target;
|
|
List *non_group_cols;
|
|
List *non_group_exprs;
|
|
int i;
|
|
ListCell *lc;
|
|
|
|
partial_target = create_empty_pathtarget();
|
|
non_group_cols = NIL;
|
|
|
|
i = 0;
|
|
foreach(lc, grouping_target->exprs)
|
|
{
|
|
Expr *expr = (Expr *) lfirst(lc);
|
|
Index sgref = get_pathtarget_sortgroupref(grouping_target, i);
|
|
|
|
if (sgref && parse->groupClause &&
|
|
get_sortgroupref_clause_noerr(sgref, parse->groupClause) != NULL)
|
|
{
|
|
/*
|
|
* It's a grouping column, so add it to the partial_target as-is.
|
|
* (This allows the upper agg step to repeat the grouping calcs.)
|
|
*/
|
|
add_column_to_pathtarget(partial_target, expr, sgref);
|
|
}
|
|
else
|
|
{
|
|
/*
|
|
* Non-grouping column, so just remember the expression for later
|
|
* call to pull_var_clause.
|
|
*/
|
|
non_group_cols = lappend(non_group_cols, expr);
|
|
}
|
|
|
|
i++;
|
|
}
|
|
|
|
/*
|
|
* If there's a HAVING clause, we'll need the Vars/Aggrefs it uses, too.
|
|
*/
|
|
if (havingQual)
|
|
non_group_cols = lappend(non_group_cols, havingQual);
|
|
|
|
/*
|
|
* Pull out all the Vars, PlaceHolderVars, and Aggrefs mentioned in
|
|
* non-group cols (plus HAVING), and add them to the partial_target if not
|
|
* already present. (An expression used directly as a GROUP BY item will
|
|
* be present already.) Note this includes Vars used in resjunk items, so
|
|
* we are covering the needs of ORDER BY and window specifications.
|
|
*/
|
|
non_group_exprs = pull_var_clause((Node *) non_group_cols,
|
|
PVC_INCLUDE_AGGREGATES |
|
|
PVC_RECURSE_WINDOWFUNCS |
|
|
PVC_INCLUDE_PLACEHOLDERS);
|
|
|
|
add_new_columns_to_pathtarget(partial_target, non_group_exprs);
|
|
|
|
/*
|
|
* Adjust Aggrefs to put them in partial mode. At this point all Aggrefs
|
|
* are at the top level of the target list, so we can just scan the list
|
|
* rather than recursing through the expression trees.
|
|
*/
|
|
foreach(lc, partial_target->exprs)
|
|
{
|
|
Aggref *aggref = (Aggref *) lfirst(lc);
|
|
|
|
if (IsA(aggref, Aggref))
|
|
{
|
|
Aggref *newaggref;
|
|
|
|
/*
|
|
* We shouldn't need to copy the substructure of the Aggref node,
|
|
* but flat-copy the node itself to avoid damaging other trees.
|
|
*/
|
|
newaggref = makeNode(Aggref);
|
|
memcpy(newaggref, aggref, sizeof(Aggref));
|
|
|
|
/* For now, assume serialization is required */
|
|
mark_partial_aggref(newaggref, AGGSPLIT_INITIAL_SERIAL);
|
|
|
|
lfirst(lc) = newaggref;
|
|
}
|
|
}
|
|
|
|
/* clean up cruft */
|
|
list_free(non_group_exprs);
|
|
list_free(non_group_cols);
|
|
|
|
/* XXX this causes some redundant cost calculation ... */
|
|
return set_pathtarget_cost_width(root, partial_target);
|
|
}
|
|
|
|
/*
|
|
* mark_partial_aggref
|
|
* Adjust an Aggref to make it represent a partial-aggregation step.
|
|
*
|
|
* The Aggref node is modified in-place; caller must do any copying required.
|
|
*/
|
|
void
|
|
mark_partial_aggref(Aggref *agg, AggSplit aggsplit)
|
|
{
|
|
/* aggtranstype should be computed by this point */
|
|
Assert(OidIsValid(agg->aggtranstype));
|
|
/* ... but aggsplit should still be as the parser left it */
|
|
Assert(agg->aggsplit == AGGSPLIT_SIMPLE);
|
|
|
|
/* Mark the Aggref with the intended partial-aggregation mode */
|
|
agg->aggsplit = aggsplit;
|
|
|
|
/*
|
|
* Adjust result type if needed. Normally, a partial aggregate returns
|
|
* the aggregate's transition type; but if that's INTERNAL and we're
|
|
* serializing, it returns BYTEA instead.
|
|
*/
|
|
if (DO_AGGSPLIT_SKIPFINAL(aggsplit))
|
|
{
|
|
if (agg->aggtranstype == INTERNALOID && DO_AGGSPLIT_SERIALIZE(aggsplit))
|
|
agg->aggtype = BYTEAOID;
|
|
else
|
|
agg->aggtype = agg->aggtranstype;
|
|
}
|
|
}
|
|
|
|
/*
|
|
* 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 = lfirst_node(TargetEntry, l);
|
|
TargetEntry *orig_tle;
|
|
|
|
/* ignore resjunk columns in setop result */
|
|
if (new_tle->resjunk)
|
|
continue;
|
|
|
|
Assert(orig_tlist_item != NULL);
|
|
orig_tle = lfirst_node(TargetEntry, orig_tlist_item);
|
|
orig_tlist_item = lnext(orig_tlist, 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;
|
|
}
|
|
|
|
/*
|
|
* select_active_windows
|
|
* Create a list of the "active" window clauses (ie, those referenced
|
|
* by non-deleted WindowFuncs) in the order they are to be executed.
|
|
*/
|
|
static List *
|
|
select_active_windows(PlannerInfo *root, WindowFuncLists *wflists)
|
|
{
|
|
List *windowClause = root->parse->windowClause;
|
|
List *result = NIL;
|
|
ListCell *lc;
|
|
int nActive = 0;
|
|
WindowClauseSortData *actives = palloc(sizeof(WindowClauseSortData)
|
|
* list_length(windowClause));
|
|
|
|
/* First, construct an array of the active windows */
|
|
foreach(lc, windowClause)
|
|
{
|
|
WindowClause *wc = lfirst_node(WindowClause, lc);
|
|
|
|
/* It's only active if wflists shows some related WindowFuncs */
|
|
Assert(wc->winref <= wflists->maxWinRef);
|
|
if (wflists->windowFuncs[wc->winref] == NIL)
|
|
continue;
|
|
|
|
actives[nActive].wc = wc; /* original clause */
|
|
|
|
/*
|
|
* For sorting, we want the list of partition keys followed by the
|
|
* list of sort keys. But pathkeys construction will remove duplicates
|
|
* between the two, so we can as well (even though we can't detect all
|
|
* of the duplicates, since some may come from ECs - that might mean
|
|
* we miss optimization chances here). We must, however, ensure that
|
|
* the order of entries is preserved with respect to the ones we do
|
|
* keep.
|
|
*
|
|
* partitionClause and orderClause had their own duplicates removed in
|
|
* parse analysis, so we're only concerned here with removing
|
|
* orderClause entries that also appear in partitionClause.
|
|
*/
|
|
actives[nActive].uniqueOrder =
|
|
list_concat_unique(list_copy(wc->partitionClause),
|
|
wc->orderClause);
|
|
nActive++;
|
|
}
|
|
|
|
/*
|
|
* Sort active windows by their partitioning/ordering clauses, ignoring
|
|
* any framing clauses, so that the windows that need the same sorting are
|
|
* adjacent in the list. When we come to generate paths, this will avoid
|
|
* inserting additional Sort nodes.
|
|
*
|
|
* This is how we implement a specific requirement from the SQL standard,
|
|
* which says that when two or more windows are order-equivalent (i.e.
|
|
* have matching partition and order clauses, even if their names or
|
|
* framing clauses differ), then all peer rows must be presented in the
|
|
* same order in all of them. If we allowed multiple sort nodes for such
|
|
* cases, we'd risk having the peer rows end up in different orders in
|
|
* equivalent windows due to sort instability. (See General Rule 4 of
|
|
* <window clause> in SQL2008 - SQL2016.)
|
|
*
|
|
* Additionally, if the entire list of clauses of one window is a prefix
|
|
* of another, put first the window with stronger sorting requirements.
|
|
* This way we will first sort for stronger window, and won't have to sort
|
|
* again for the weaker one.
|
|
*/
|
|
qsort(actives, nActive, sizeof(WindowClauseSortData), common_prefix_cmp);
|
|
|
|
/* build ordered list of the original WindowClause nodes */
|
|
for (int i = 0; i < nActive; i++)
|
|
result = lappend(result, actives[i].wc);
|
|
|
|
pfree(actives);
|
|
|
|
return result;
|
|
}
|
|
|
|
/*
|
|
* common_prefix_cmp
|
|
* QSort comparison function for WindowClauseSortData
|
|
*
|
|
* Sort the windows by the required sorting clauses. First, compare the sort
|
|
* clauses themselves. Second, if one window's clauses are a prefix of another
|
|
* one's clauses, put the window with more sort clauses first.
|
|
*/
|
|
static int
|
|
common_prefix_cmp(const void *a, const void *b)
|
|
{
|
|
const WindowClauseSortData *wcsa = a;
|
|
const WindowClauseSortData *wcsb = b;
|
|
ListCell *item_a;
|
|
ListCell *item_b;
|
|
|
|
forboth(item_a, wcsa->uniqueOrder, item_b, wcsb->uniqueOrder)
|
|
{
|
|
SortGroupClause *sca = lfirst_node(SortGroupClause, item_a);
|
|
SortGroupClause *scb = lfirst_node(SortGroupClause, item_b);
|
|
|
|
if (sca->tleSortGroupRef > scb->tleSortGroupRef)
|
|
return -1;
|
|
else if (sca->tleSortGroupRef < scb->tleSortGroupRef)
|
|
return 1;
|
|
else if (sca->sortop > scb->sortop)
|
|
return -1;
|
|
else if (sca->sortop < scb->sortop)
|
|
return 1;
|
|
else if (sca->nulls_first && !scb->nulls_first)
|
|
return -1;
|
|
else if (!sca->nulls_first && scb->nulls_first)
|
|
return 1;
|
|
/* no need to compare eqop, since it is fully determined by sortop */
|
|
}
|
|
|
|
if (list_length(wcsa->uniqueOrder) > list_length(wcsb->uniqueOrder))
|
|
return -1;
|
|
else if (list_length(wcsa->uniqueOrder) < list_length(wcsb->uniqueOrder))
|
|
return 1;
|
|
|
|
return 0;
|
|
}
|
|
|
|
/*
|
|
* make_window_input_target
|
|
* Generate appropriate PathTarget for initial input to WindowAgg nodes.
|
|
*
|
|
* When the query has window functions, this function computes the desired
|
|
* target to be computed by the node just below the first WindowAgg.
|
|
* This tlist must contain all values needed to evaluate the window functions,
|
|
* compute the final target list, and perform any required final sort step.
|
|
* If multiple WindowAggs are needed, each intermediate one adds its window
|
|
* function results onto this base tlist; only the topmost WindowAgg computes
|
|
* the actual desired target list.
|
|
*
|
|
* This function is much like make_group_input_target, though not quite enough
|
|
* like it to share code. As in that function, we flatten most expressions
|
|
* into their component variables. But we do not want to flatten window
|
|
* PARTITION BY/ORDER BY clauses, since that might result in multiple
|
|
* evaluations of them, which would be bad (possibly even resulting in
|
|
* inconsistent answers, if they contain volatile functions).
|
|
* Also, we must not flatten GROUP BY clauses that were left unflattened by
|
|
* make_group_input_target, because we may no longer have access to the
|
|
* individual Vars in them.
|
|
*
|
|
* Another key difference from make_group_input_target is that we don't
|
|
* flatten Aggref expressions, since those are to be computed below the
|
|
* window functions and just referenced like Vars above that.
|
|
*
|
|
* 'final_target' is the query's final target list (in PathTarget form)
|
|
* 'activeWindows' is the list of active windows previously identified by
|
|
* select_active_windows.
|
|
*
|
|
* The result is the PathTarget to be computed by the plan node immediately
|
|
* below the first WindowAgg node.
|
|
*/
|
|
static PathTarget *
|
|
make_window_input_target(PlannerInfo *root,
|
|
PathTarget *final_target,
|
|
List *activeWindows)
|
|
{
|
|
Query *parse = root->parse;
|
|
PathTarget *input_target;
|
|
Bitmapset *sgrefs;
|
|
List *flattenable_cols;
|
|
List *flattenable_vars;
|
|
int i;
|
|
ListCell *lc;
|
|
|
|
Assert(parse->hasWindowFuncs);
|
|
|
|
/*
|
|
* Collect the sortgroupref numbers of window PARTITION/ORDER BY clauses
|
|
* into a bitmapset for convenient reference below.
|
|
*/
|
|
sgrefs = NULL;
|
|
foreach(lc, activeWindows)
|
|
{
|
|
WindowClause *wc = lfirst_node(WindowClause, lc);
|
|
ListCell *lc2;
|
|
|
|
foreach(lc2, wc->partitionClause)
|
|
{
|
|
SortGroupClause *sortcl = lfirst_node(SortGroupClause, lc2);
|
|
|
|
sgrefs = bms_add_member(sgrefs, sortcl->tleSortGroupRef);
|
|
}
|
|
foreach(lc2, wc->orderClause)
|
|
{
|
|
SortGroupClause *sortcl = lfirst_node(SortGroupClause, lc2);
|
|
|
|
sgrefs = bms_add_member(sgrefs, sortcl->tleSortGroupRef);
|
|
}
|
|
}
|
|
|
|
/* Add in sortgroupref numbers of GROUP BY clauses, too */
|
|
foreach(lc, parse->groupClause)
|
|
{
|
|
SortGroupClause *grpcl = lfirst_node(SortGroupClause, lc);
|
|
|
|
sgrefs = bms_add_member(sgrefs, grpcl->tleSortGroupRef);
|
|
}
|
|
|
|
/*
|
|
* Construct a target containing all the non-flattenable targetlist items,
|
|
* and save aside the others for a moment.
|
|
*/
|
|
input_target = create_empty_pathtarget();
|
|
flattenable_cols = NIL;
|
|
|
|
i = 0;
|
|
foreach(lc, final_target->exprs)
|
|
{
|
|
Expr *expr = (Expr *) lfirst(lc);
|
|
Index sgref = get_pathtarget_sortgroupref(final_target, i);
|
|
|
|
/*
|
|
* Don't want to deconstruct window clauses or GROUP BY items. (Note
|
|
* that such items can't contain window functions, so it's okay to
|
|
* compute them below the WindowAgg nodes.)
|
|
*/
|
|
if (sgref != 0 && bms_is_member(sgref, sgrefs))
|
|
{
|
|
/*
|
|
* Don't want to deconstruct this value, so add it to the input
|
|
* target as-is.
|
|
*/
|
|
add_column_to_pathtarget(input_target, expr, sgref);
|
|
}
|
|
else
|
|
{
|
|
/*
|
|
* Column is to be flattened, so just remember the expression for
|
|
* later call to pull_var_clause.
|
|
*/
|
|
flattenable_cols = lappend(flattenable_cols, expr);
|
|
}
|
|
|
|
i++;
|
|
}
|
|
|
|
/*
|
|
* Pull out all the Vars and Aggrefs mentioned in flattenable columns, and
|
|
* add them to the input target if not already present. (Some might be
|
|
* there already because they're used directly as window/group clauses.)
|
|
*
|
|
* Note: it's essential to use PVC_INCLUDE_AGGREGATES here, so that any
|
|
* Aggrefs are placed in the Agg node's tlist and not left to be computed
|
|
* at higher levels. On the other hand, we should recurse into
|
|
* WindowFuncs to make sure their input expressions are available.
|
|
*/
|
|
flattenable_vars = pull_var_clause((Node *) flattenable_cols,
|
|
PVC_INCLUDE_AGGREGATES |
|
|
PVC_RECURSE_WINDOWFUNCS |
|
|
PVC_INCLUDE_PLACEHOLDERS);
|
|
add_new_columns_to_pathtarget(input_target, flattenable_vars);
|
|
|
|
/* clean up cruft */
|
|
list_free(flattenable_vars);
|
|
list_free(flattenable_cols);
|
|
|
|
/* XXX this causes some redundant cost calculation ... */
|
|
return set_pathtarget_cost_width(root, input_target);
|
|
}
|
|
|
|
/*
|
|
* make_pathkeys_for_window
|
|
* Create a pathkeys list describing the required input ordering
|
|
* for the given WindowClause.
|
|
*
|
|
* The required ordering is first the PARTITION keys, then the ORDER keys.
|
|
* In the future we might try to implement windowing using hashing, in which
|
|
* case the ordering could be relaxed, but for now we always sort.
|
|
*/
|
|
static List *
|
|
make_pathkeys_for_window(PlannerInfo *root, WindowClause *wc,
|
|
List *tlist)
|
|
{
|
|
List *window_pathkeys;
|
|
List *window_sortclauses;
|
|
|
|
/* Throw error if can't sort */
|
|
if (!grouping_is_sortable(wc->partitionClause))
|
|
ereport(ERROR,
|
|
(errcode(ERRCODE_FEATURE_NOT_SUPPORTED),
|
|
errmsg("could not implement window PARTITION BY"),
|
|
errdetail("Window partitioning columns must be of sortable datatypes.")));
|
|
if (!grouping_is_sortable(wc->orderClause))
|
|
ereport(ERROR,
|
|
(errcode(ERRCODE_FEATURE_NOT_SUPPORTED),
|
|
errmsg("could not implement window ORDER BY"),
|
|
errdetail("Window ordering columns must be of sortable datatypes.")));
|
|
|
|
/* Okay, make the combined pathkeys */
|
|
window_sortclauses = list_concat_copy(wc->partitionClause, wc->orderClause);
|
|
window_pathkeys = make_pathkeys_for_sortclauses(root,
|
|
window_sortclauses,
|
|
tlist);
|
|
list_free(window_sortclauses);
|
|
return window_pathkeys;
|
|
}
|
|
|
|
/*
|
|
* make_sort_input_target
|
|
* Generate appropriate PathTarget for initial input to Sort step.
|
|
*
|
|
* If the query has ORDER BY, this function chooses the target to be computed
|
|
* by the node just below the Sort (and DISTINCT, if any, since Unique can't
|
|
* project) steps. This might or might not be identical to the query's final
|
|
* output target.
|
|
*
|
|
* The main argument for keeping the sort-input tlist the same as the final
|
|
* is that we avoid a separate projection node (which will be needed if
|
|
* they're different, because Sort can't project). However, there are also
|
|
* advantages to postponing tlist evaluation till after the Sort: it ensures
|
|
* a consistent order of evaluation for any volatile functions in the tlist,
|
|
* and if there's also a LIMIT, we can stop the query without ever computing
|
|
* tlist functions for later rows, which is beneficial for both volatile and
|
|
* expensive functions.
|
|
*
|
|
* Our current policy is to postpone volatile expressions till after the sort
|
|
* unconditionally (assuming that that's possible, ie they are in plain tlist
|
|
* columns and not ORDER BY/GROUP BY/DISTINCT columns). We also prefer to
|
|
* postpone set-returning expressions, because running them beforehand would
|
|
* bloat the sort dataset, and because it might cause unexpected output order
|
|
* if the sort isn't stable. However there's a constraint on that: all SRFs
|
|
* in the tlist should be evaluated at the same plan step, so that they can
|
|
* run in sync in nodeProjectSet. So if any SRFs are in sort columns, we
|
|
* mustn't postpone any SRFs. (Note that in principle that policy should
|
|
* probably get applied to the group/window input targetlists too, but we
|
|
* have not done that historically.) Lastly, expensive expressions are
|
|
* postponed if there is a LIMIT, or if root->tuple_fraction shows that
|
|
* partial evaluation of the query is possible (if neither is true, we expect
|
|
* to have to evaluate the expressions for every row anyway), or if there are
|
|
* any volatile or set-returning expressions (since once we've put in a
|
|
* projection at all, it won't cost any more to postpone more stuff).
|
|
*
|
|
* Another issue that could potentially be considered here is that
|
|
* evaluating tlist expressions could result in data that's either wider
|
|
* or narrower than the input Vars, thus changing the volume of data that
|
|
* has to go through the Sort. However, we usually have only a very bad
|
|
* idea of the output width of any expression more complex than a Var,
|
|
* so for now it seems too risky to try to optimize on that basis.
|
|
*
|
|
* Note that if we do produce a modified sort-input target, and then the
|
|
* query ends up not using an explicit Sort, no particular harm is done:
|
|
* we'll initially use the modified target for the preceding path nodes,
|
|
* but then change them to the final target with apply_projection_to_path.
|
|
* Moreover, in such a case the guarantees about evaluation order of
|
|
* volatile functions still hold, since the rows are sorted already.
|
|
*
|
|
* This function has some things in common with make_group_input_target and
|
|
* make_window_input_target, though the detailed rules for what to do are
|
|
* different. We never flatten/postpone any grouping or ordering columns;
|
|
* those are needed before the sort. If we do flatten a particular
|
|
* expression, we leave Aggref and WindowFunc nodes alone, since those were
|
|
* computed earlier.
|
|
*
|
|
* 'final_target' is the query's final target list (in PathTarget form)
|
|
* 'have_postponed_srfs' is an output argument, see below
|
|
*
|
|
* The result is the PathTarget to be computed by the plan node immediately
|
|
* below the Sort step (and the Distinct step, if any). This will be
|
|
* exactly final_target if we decide a projection step wouldn't be helpful.
|
|
*
|
|
* In addition, *have_postponed_srfs is set to true if we choose to postpone
|
|
* any set-returning functions to after the Sort.
|
|
*/
|
|
static PathTarget *
|
|
make_sort_input_target(PlannerInfo *root,
|
|
PathTarget *final_target,
|
|
bool *have_postponed_srfs)
|
|
{
|
|
Query *parse = root->parse;
|
|
PathTarget *input_target;
|
|
int ncols;
|
|
bool *col_is_srf;
|
|
bool *postpone_col;
|
|
bool have_srf;
|
|
bool have_volatile;
|
|
bool have_expensive;
|
|
bool have_srf_sortcols;
|
|
bool postpone_srfs;
|
|
List *postponable_cols;
|
|
List *postponable_vars;
|
|
int i;
|
|
ListCell *lc;
|
|
|
|
/* Shouldn't get here unless query has ORDER BY */
|
|
Assert(parse->sortClause);
|
|
|
|
*have_postponed_srfs = false; /* default result */
|
|
|
|
/* Inspect tlist and collect per-column information */
|
|
ncols = list_length(final_target->exprs);
|
|
col_is_srf = (bool *) palloc0(ncols * sizeof(bool));
|
|
postpone_col = (bool *) palloc0(ncols * sizeof(bool));
|
|
have_srf = have_volatile = have_expensive = have_srf_sortcols = false;
|
|
|
|
i = 0;
|
|
foreach(lc, final_target->exprs)
|
|
{
|
|
Expr *expr = (Expr *) lfirst(lc);
|
|
|
|
/*
|
|
* If the column has a sortgroupref, assume it has to be evaluated
|
|
* before sorting. Generally such columns would be ORDER BY, GROUP
|
|
* BY, etc targets. One exception is columns that were removed from
|
|
* GROUP BY by remove_useless_groupby_columns() ... but those would
|
|
* only be Vars anyway. There don't seem to be any cases where it
|
|
* would be worth the trouble to double-check.
|
|
*/
|
|
if (get_pathtarget_sortgroupref(final_target, i) == 0)
|
|
{
|
|
/*
|
|
* Check for SRF or volatile functions. Check the SRF case first
|
|
* because we must know whether we have any postponed SRFs.
|
|
*/
|
|
if (parse->hasTargetSRFs &&
|
|
expression_returns_set((Node *) expr))
|
|
{
|
|
/* We'll decide below whether these are postponable */
|
|
col_is_srf[i] = true;
|
|
have_srf = true;
|
|
}
|
|
else if (contain_volatile_functions((Node *) expr))
|
|
{
|
|
/* Unconditionally postpone */
|
|
postpone_col[i] = true;
|
|
have_volatile = true;
|
|
}
|
|
else
|
|
{
|
|
/*
|
|
* Else check the cost. XXX it's annoying to have to do this
|
|
* when set_pathtarget_cost_width() just did it. Refactor to
|
|
* allow sharing the work?
|
|
*/
|
|
QualCost cost;
|
|
|
|
cost_qual_eval_node(&cost, (Node *) expr, root);
|
|
|
|
/*
|
|
* We arbitrarily define "expensive" as "more than 10X
|
|
* cpu_operator_cost". Note this will take in any PL function
|
|
* with default cost.
|
|
*/
|
|
if (cost.per_tuple > 10 * cpu_operator_cost)
|
|
{
|
|
postpone_col[i] = true;
|
|
have_expensive = true;
|
|
}
|
|
}
|
|
}
|
|
else
|
|
{
|
|
/* For sortgroupref cols, just check if any contain SRFs */
|
|
if (!have_srf_sortcols &&
|
|
parse->hasTargetSRFs &&
|
|
expression_returns_set((Node *) expr))
|
|
have_srf_sortcols = true;
|
|
}
|
|
|
|
i++;
|
|
}
|
|
|
|
/*
|
|
* We can postpone SRFs if we have some but none are in sortgroupref cols.
|
|
*/
|
|
postpone_srfs = (have_srf && !have_srf_sortcols);
|
|
|
|
/*
|
|
* If we don't need a post-sort projection, just return final_target.
|
|
*/
|
|
if (!(postpone_srfs || have_volatile ||
|
|
(have_expensive &&
|
|
(parse->limitCount || root->tuple_fraction > 0))))
|
|
return final_target;
|
|
|
|
/*
|
|
* Report whether the post-sort projection will contain set-returning
|
|
* functions. This is important because it affects whether the Sort can
|
|
* rely on the query's LIMIT (if any) to bound the number of rows it needs
|
|
* to return.
|
|
*/
|
|
*have_postponed_srfs = postpone_srfs;
|
|
|
|
/*
|
|
* Construct the sort-input target, taking all non-postponable columns and
|
|
* then adding Vars, PlaceHolderVars, Aggrefs, and WindowFuncs found in
|
|
* the postponable ones.
|
|
*/
|
|
input_target = create_empty_pathtarget();
|
|
postponable_cols = NIL;
|
|
|
|
i = 0;
|
|
foreach(lc, final_target->exprs)
|
|
{
|
|
Expr *expr = (Expr *) lfirst(lc);
|
|
|
|
if (postpone_col[i] || (postpone_srfs && col_is_srf[i]))
|
|
postponable_cols = lappend(postponable_cols, expr);
|
|
else
|
|
add_column_to_pathtarget(input_target, expr,
|
|
get_pathtarget_sortgroupref(final_target, i));
|
|
|
|
i++;
|
|
}
|
|
|
|
/*
|
|
* Pull out all the Vars, Aggrefs, and WindowFuncs mentioned in
|
|
* postponable columns, and add them to the sort-input target if not
|
|
* already present. (Some might be there already.) We mustn't
|
|
* deconstruct Aggrefs or WindowFuncs here, since the projection node
|
|
* would be unable to recompute them.
|
|
*/
|
|
postponable_vars = pull_var_clause((Node *) postponable_cols,
|
|
PVC_INCLUDE_AGGREGATES |
|
|
PVC_INCLUDE_WINDOWFUNCS |
|
|
PVC_INCLUDE_PLACEHOLDERS);
|
|
add_new_columns_to_pathtarget(input_target, postponable_vars);
|
|
|
|
/* clean up cruft */
|
|
list_free(postponable_vars);
|
|
list_free(postponable_cols);
|
|
|
|
/* XXX this represents even more redundant cost calculation ... */
|
|
return set_pathtarget_cost_width(root, input_target);
|
|
}
|
|
|
|
/*
|
|
* get_cheapest_fractional_path
|
|
* Find the cheapest path for retrieving a specified fraction of all
|
|
* the tuples expected to be returned by the given relation.
|
|
*
|
|
* We interpret tuple_fraction the same way as grouping_planner.
|
|
*
|
|
* We assume set_cheapest() has been run on the given rel.
|
|
*/
|
|
Path *
|
|
get_cheapest_fractional_path(RelOptInfo *rel, double tuple_fraction)
|
|
{
|
|
Path *best_path = rel->cheapest_total_path;
|
|
ListCell *l;
|
|
|
|
/* If all tuples will be retrieved, just return the cheapest-total path */
|
|
if (tuple_fraction <= 0.0)
|
|
return best_path;
|
|
|
|
/* Convert absolute # of tuples to a fraction; no need to clamp to 0..1 */
|
|
if (tuple_fraction >= 1.0 && best_path->rows > 0)
|
|
tuple_fraction /= best_path->rows;
|
|
|
|
foreach(l, rel->pathlist)
|
|
{
|
|
Path *path = (Path *) lfirst(l);
|
|
|
|
if (path == rel->cheapest_total_path ||
|
|
compare_fractional_path_costs(best_path, path, tuple_fraction) <= 0)
|
|
continue;
|
|
|
|
best_path = path;
|
|
}
|
|
|
|
return best_path;
|
|
}
|
|
|
|
/*
|
|
* adjust_paths_for_srfs
|
|
* Fix up the Paths of the given upperrel to handle tSRFs properly.
|
|
*
|
|
* The executor can only handle set-returning functions that appear at the
|
|
* top level of the targetlist of a ProjectSet plan node. If we have any SRFs
|
|
* that are not at top level, we need to split up the evaluation into multiple
|
|
* plan levels in which each level satisfies this constraint. This function
|
|
* modifies each Path of an upperrel that (might) compute any SRFs in its
|
|
* output tlist to insert appropriate projection steps.
|
|
*
|
|
* The given targets and targets_contain_srfs lists are from
|
|
* split_pathtarget_at_srfs(). We assume the existing Paths emit the first
|
|
* target in targets.
|
|
*/
|
|
static void
|
|
adjust_paths_for_srfs(PlannerInfo *root, RelOptInfo *rel,
|
|
List *targets, List *targets_contain_srfs)
|
|
{
|
|
ListCell *lc;
|
|
|
|
Assert(list_length(targets) == list_length(targets_contain_srfs));
|
|
Assert(!linitial_int(targets_contain_srfs));
|
|
|
|
/* If no SRFs appear at this plan level, nothing to do */
|
|
if (list_length(targets) == 1)
|
|
return;
|
|
|
|
/*
|
|
* Stack SRF-evaluation nodes atop each path for the rel.
|
|
*
|
|
* In principle we should re-run set_cheapest() here to identify the
|
|
* cheapest path, but it seems unlikely that adding the same tlist eval
|
|
* costs to all the paths would change that, so we don't bother. Instead,
|
|
* just assume that the cheapest-startup and cheapest-total paths remain
|
|
* so. (There should be no parameterized paths anymore, so we needn't
|
|
* worry about updating cheapest_parameterized_paths.)
|
|
*/
|
|
foreach(lc, rel->pathlist)
|
|
{
|
|
Path *subpath = (Path *) lfirst(lc);
|
|
Path *newpath = subpath;
|
|
ListCell *lc1,
|
|
*lc2;
|
|
|
|
Assert(subpath->param_info == NULL);
|
|
forboth(lc1, targets, lc2, targets_contain_srfs)
|
|
{
|
|
PathTarget *thistarget = lfirst_node(PathTarget, lc1);
|
|
bool contains_srfs = (bool) lfirst_int(lc2);
|
|
|
|
/* If this level doesn't contain SRFs, do regular projection */
|
|
if (contains_srfs)
|
|
newpath = (Path *) create_set_projection_path(root,
|
|
rel,
|
|
newpath,
|
|
thistarget);
|
|
else
|
|
newpath = (Path *) apply_projection_to_path(root,
|
|
rel,
|
|
newpath,
|
|
thistarget);
|
|
}
|
|
lfirst(lc) = newpath;
|
|
if (subpath == rel->cheapest_startup_path)
|
|
rel->cheapest_startup_path = newpath;
|
|
if (subpath == rel->cheapest_total_path)
|
|
rel->cheapest_total_path = newpath;
|
|
}
|
|
|
|
/* Likewise for partial paths, if any */
|
|
foreach(lc, rel->partial_pathlist)
|
|
{
|
|
Path *subpath = (Path *) lfirst(lc);
|
|
Path *newpath = subpath;
|
|
ListCell *lc1,
|
|
*lc2;
|
|
|
|
Assert(subpath->param_info == NULL);
|
|
forboth(lc1, targets, lc2, targets_contain_srfs)
|
|
{
|
|
PathTarget *thistarget = lfirst_node(PathTarget, lc1);
|
|
bool contains_srfs = (bool) lfirst_int(lc2);
|
|
|
|
/* If this level doesn't contain SRFs, do regular projection */
|
|
if (contains_srfs)
|
|
newpath = (Path *) create_set_projection_path(root,
|
|
rel,
|
|
newpath,
|
|
thistarget);
|
|
else
|
|
{
|
|
/* avoid apply_projection_to_path, in case of multiple refs */
|
|
newpath = (Path *) create_projection_path(root,
|
|
rel,
|
|
newpath,
|
|
thistarget);
|
|
}
|
|
}
|
|
lfirst(lc) = newpath;
|
|
}
|
|
}
|
|
|
|
/*
|
|
* expression_planner
|
|
* Perform planner's transformations on a standalone expression.
|
|
*
|
|
* Various utility commands need to evaluate expressions that are not part
|
|
* of a plannable query. They can do so using the executor's regular
|
|
* expression-execution machinery, but first the expression has to be fed
|
|
* through here to transform it from parser output to something executable.
|
|
*
|
|
* Currently, we disallow sublinks in standalone expressions, so there's no
|
|
* real "planning" involved here. (That might not always be true though.)
|
|
* What we must do is run eval_const_expressions to ensure that any function
|
|
* calls are converted to positional notation and function default arguments
|
|
* get inserted. The fact that constant subexpressions get simplified is a
|
|
* side-effect that is useful when the expression will get evaluated more than
|
|
* once. Also, we must fix operator function IDs.
|
|
*
|
|
* This does not return any information about dependencies of the expression.
|
|
* Hence callers should use the results only for the duration of the current
|
|
* query. Callers that would like to cache the results for longer should use
|
|
* expression_planner_with_deps, probably via the plancache.
|
|
*
|
|
* Note: this must not make any damaging changes to the passed-in expression
|
|
* tree. (It would actually be okay to apply fix_opfuncids to it, but since
|
|
* we first do an expression_tree_mutator-based walk, what is returned will
|
|
* be a new node tree.) The result is constructed in the current memory
|
|
* context; beware that this can leak a lot of additional stuff there, too.
|
|
*/
|
|
Expr *
|
|
expression_planner(Expr *expr)
|
|
{
|
|
Node *result;
|
|
|
|
/*
|
|
* Convert named-argument function calls, insert default arguments and
|
|
* simplify constant subexprs
|
|
*/
|
|
result = eval_const_expressions(NULL, (Node *) expr);
|
|
|
|
/* Fill in opfuncid values if missing */
|
|
fix_opfuncids(result);
|
|
|
|
return (Expr *) result;
|
|
}
|
|
|
|
/*
|
|
* expression_planner_with_deps
|
|
* Perform planner's transformations on a standalone expression,
|
|
* returning expression dependency information along with the result.
|
|
*
|
|
* This is identical to expression_planner() except that it also returns
|
|
* information about possible dependencies of the expression, ie identities of
|
|
* objects whose definitions affect the result. As in a PlannedStmt, these
|
|
* are expressed as a list of relation Oids and a list of PlanInvalItems.
|
|
*/
|
|
Expr *
|
|
expression_planner_with_deps(Expr *expr,
|
|
List **relationOids,
|
|
List **invalItems)
|
|
{
|
|
Node *result;
|
|
PlannerGlobal glob;
|
|
PlannerInfo root;
|
|
|
|
/* Make up dummy planner state so we can use setrefs machinery */
|
|
MemSet(&glob, 0, sizeof(glob));
|
|
glob.type = T_PlannerGlobal;
|
|
glob.relationOids = NIL;
|
|
glob.invalItems = NIL;
|
|
|
|
MemSet(&root, 0, sizeof(root));
|
|
root.type = T_PlannerInfo;
|
|
root.glob = &glob;
|
|
|
|
/*
|
|
* Convert named-argument function calls, insert default arguments and
|
|
* simplify constant subexprs. Collect identities of inlined functions
|
|
* and elided domains, too.
|
|
*/
|
|
result = eval_const_expressions(&root, (Node *) expr);
|
|
|
|
/* Fill in opfuncid values if missing */
|
|
fix_opfuncids(result);
|
|
|
|
/*
|
|
* Now walk the finished expression to find anything else we ought to
|
|
* record as an expression dependency.
|
|
*/
|
|
(void) extract_query_dependencies_walker(result, &root);
|
|
|
|
*relationOids = glob.relationOids;
|
|
*invalItems = glob.invalItems;
|
|
|
|
return (Expr *) result;
|
|
}
|
|
|
|
|
|
/*
|
|
* plan_cluster_use_sort
|
|
* Use the planner to decide how CLUSTER should implement sorting
|
|
*
|
|
* tableOid is the OID of a table to be clustered on its index indexOid
|
|
* (which is already known to be a btree index). Decide whether it's
|
|
* cheaper to do an indexscan or a seqscan-plus-sort to execute the CLUSTER.
|
|
* Return true to use sorting, false to use an indexscan.
|
|
*
|
|
* Note: caller had better already hold some type of lock on the table.
|
|
*/
|
|
bool
|
|
plan_cluster_use_sort(Oid tableOid, Oid indexOid)
|
|
{
|
|
PlannerInfo *root;
|
|
Query *query;
|
|
PlannerGlobal *glob;
|
|
RangeTblEntry *rte;
|
|
RelOptInfo *rel;
|
|
IndexOptInfo *indexInfo;
|
|
QualCost indexExprCost;
|
|
Cost comparisonCost;
|
|
Path *seqScanPath;
|
|
Path seqScanAndSortPath;
|
|
IndexPath *indexScanPath;
|
|
ListCell *lc;
|
|
|
|
/* We can short-circuit the cost comparison if indexscans are disabled */
|
|
if (!enable_indexscan)
|
|
return true; /* use sort */
|
|
|
|
/* Set up mostly-dummy planner state */
|
|
query = makeNode(Query);
|
|
query->commandType = CMD_SELECT;
|
|
|
|
glob = makeNode(PlannerGlobal);
|
|
|
|
root = makeNode(PlannerInfo);
|
|
root->parse = query;
|
|
root->glob = glob;
|
|
root->query_level = 1;
|
|
root->planner_cxt = CurrentMemoryContext;
|
|
root->wt_param_id = -1;
|
|
|
|
/* Build a minimal RTE for the rel */
|
|
rte = makeNode(RangeTblEntry);
|
|
rte->rtekind = RTE_RELATION;
|
|
rte->relid = tableOid;
|
|
rte->relkind = RELKIND_RELATION; /* Don't be too picky. */
|
|
rte->rellockmode = AccessShareLock;
|
|
rte->lateral = false;
|
|
rte->inh = false;
|
|
rte->inFromCl = true;
|
|
query->rtable = list_make1(rte);
|
|
|
|
/* Set up RTE/RelOptInfo arrays */
|
|
setup_simple_rel_arrays(root);
|
|
|
|
/* Build RelOptInfo */
|
|
rel = build_simple_rel(root, 1, NULL);
|
|
|
|
/* Locate IndexOptInfo for the target index */
|
|
indexInfo = NULL;
|
|
foreach(lc, rel->indexlist)
|
|
{
|
|
indexInfo = lfirst_node(IndexOptInfo, lc);
|
|
if (indexInfo->indexoid == indexOid)
|
|
break;
|
|
}
|
|
|
|
/*
|
|
* It's possible that get_relation_info did not generate an IndexOptInfo
|
|
* for the desired index; this could happen if it's not yet reached its
|
|
* indcheckxmin usability horizon, or if it's a system index and we're
|
|
* ignoring system indexes. In such cases we should tell CLUSTER to not
|
|
* trust the index contents but use seqscan-and-sort.
|
|
*/
|
|
if (lc == NULL) /* not in the list? */
|
|
return true; /* use sort */
|
|
|
|
/*
|
|
* Rather than doing all the pushups that would be needed to use
|
|
* set_baserel_size_estimates, just do a quick hack for rows and width.
|
|
*/
|
|
rel->rows = rel->tuples;
|
|
rel->reltarget->width = get_relation_data_width(tableOid, NULL);
|
|
|
|
root->total_table_pages = rel->pages;
|
|
|
|
/*
|
|
* Determine eval cost of the index expressions, if any. We need to
|
|
* charge twice that amount for each tuple comparison that happens during
|
|
* the sort, since tuplesort.c will have to re-evaluate the index
|
|
* expressions each time. (XXX that's pretty inefficient...)
|
|
*/
|
|
cost_qual_eval(&indexExprCost, indexInfo->indexprs, root);
|
|
comparisonCost = 2.0 * (indexExprCost.startup + indexExprCost.per_tuple);
|
|
|
|
/* Estimate the cost of seq scan + sort */
|
|
seqScanPath = create_seqscan_path(root, rel, NULL, 0);
|
|
cost_sort(&seqScanAndSortPath, root, NIL,
|
|
seqScanPath->total_cost, rel->tuples, rel->reltarget->width,
|
|
comparisonCost, maintenance_work_mem, -1.0);
|
|
|
|
/* Estimate the cost of index scan */
|
|
indexScanPath = create_index_path(root, indexInfo,
|
|
NIL, NIL, NIL, NIL,
|
|
ForwardScanDirection, false,
|
|
NULL, 1.0, false);
|
|
|
|
return (seqScanAndSortPath.total_cost < indexScanPath->path.total_cost);
|
|
}
|
|
|
|
/*
|
|
* plan_create_index_workers
|
|
* Use the planner to decide how many parallel worker processes
|
|
* CREATE INDEX should request for use
|
|
*
|
|
* tableOid is the table on which the index is to be built. indexOid is the
|
|
* OID of an index to be created or reindexed (which must be a btree index).
|
|
*
|
|
* Return value is the number of parallel worker processes to request. It
|
|
* may be unsafe to proceed if this is 0. Note that this does not include the
|
|
* leader participating as a worker (value is always a number of parallel
|
|
* worker processes).
|
|
*
|
|
* Note: caller had better already hold some type of lock on the table and
|
|
* index.
|
|
*/
|
|
int
|
|
plan_create_index_workers(Oid tableOid, Oid indexOid)
|
|
{
|
|
PlannerInfo *root;
|
|
Query *query;
|
|
PlannerGlobal *glob;
|
|
RangeTblEntry *rte;
|
|
Relation heap;
|
|
Relation index;
|
|
RelOptInfo *rel;
|
|
int parallel_workers;
|
|
BlockNumber heap_blocks;
|
|
double reltuples;
|
|
double allvisfrac;
|
|
|
|
/* Return immediately when parallelism disabled */
|
|
if (max_parallel_maintenance_workers == 0)
|
|
return 0;
|
|
|
|
/* Set up largely-dummy planner state */
|
|
query = makeNode(Query);
|
|
query->commandType = CMD_SELECT;
|
|
|
|
glob = makeNode(PlannerGlobal);
|
|
|
|
root = makeNode(PlannerInfo);
|
|
root->parse = query;
|
|
root->glob = glob;
|
|
root->query_level = 1;
|
|
root->planner_cxt = CurrentMemoryContext;
|
|
root->wt_param_id = -1;
|
|
|
|
/*
|
|
* Build a minimal RTE.
|
|
*
|
|
* Mark the RTE with inh = true. This is a kludge to prevent
|
|
* get_relation_info() from fetching index info, which is necessary
|
|
* because it does not expect that any IndexOptInfo is currently
|
|
* undergoing REINDEX.
|
|
*/
|
|
rte = makeNode(RangeTblEntry);
|
|
rte->rtekind = RTE_RELATION;
|
|
rte->relid = tableOid;
|
|
rte->relkind = RELKIND_RELATION; /* Don't be too picky. */
|
|
rte->rellockmode = AccessShareLock;
|
|
rte->lateral = false;
|
|
rte->inh = true;
|
|
rte->inFromCl = true;
|
|
query->rtable = list_make1(rte);
|
|
|
|
/* Set up RTE/RelOptInfo arrays */
|
|
setup_simple_rel_arrays(root);
|
|
|
|
/* Build RelOptInfo */
|
|
rel = build_simple_rel(root, 1, NULL);
|
|
|
|
/* Rels are assumed already locked by the caller */
|
|
heap = table_open(tableOid, NoLock);
|
|
index = index_open(indexOid, NoLock);
|
|
|
|
/*
|
|
* Determine if it's safe to proceed.
|
|
*
|
|
* Currently, parallel workers can't access the leader's temporary tables.
|
|
* Furthermore, any index predicate or index expressions must be parallel
|
|
* safe.
|
|
*/
|
|
if (heap->rd_rel->relpersistence == RELPERSISTENCE_TEMP ||
|
|
!is_parallel_safe(root, (Node *) RelationGetIndexExpressions(index)) ||
|
|
!is_parallel_safe(root, (Node *) RelationGetIndexPredicate(index)))
|
|
{
|
|
parallel_workers = 0;
|
|
goto done;
|
|
}
|
|
|
|
/*
|
|
* If parallel_workers storage parameter is set for the table, accept that
|
|
* as the number of parallel worker processes to launch (though still cap
|
|
* at max_parallel_maintenance_workers). Note that we deliberately do not
|
|
* consider any other factor when parallel_workers is set. (e.g., memory
|
|
* use by workers.)
|
|
*/
|
|
if (rel->rel_parallel_workers != -1)
|
|
{
|
|
parallel_workers = Min(rel->rel_parallel_workers,
|
|
max_parallel_maintenance_workers);
|
|
goto done;
|
|
}
|
|
|
|
/*
|
|
* Estimate heap relation size ourselves, since rel->pages cannot be
|
|
* trusted (heap RTE was marked as inheritance parent)
|
|
*/
|
|
estimate_rel_size(heap, NULL, &heap_blocks, &reltuples, &allvisfrac);
|
|
|
|
/*
|
|
* Determine number of workers to scan the heap relation using generic
|
|
* model
|
|
*/
|
|
parallel_workers = compute_parallel_worker(rel, heap_blocks, -1,
|
|
max_parallel_maintenance_workers);
|
|
|
|
/*
|
|
* Cap workers based on available maintenance_work_mem as needed.
|
|
*
|
|
* Note that each tuplesort participant receives an even share of the
|
|
* total maintenance_work_mem budget. Aim to leave participants
|
|
* (including the leader as a participant) with no less than 32MB of
|
|
* memory. This leaves cases where maintenance_work_mem is set to 64MB
|
|
* immediately past the threshold of being capable of launching a single
|
|
* parallel worker to sort.
|
|
*/
|
|
while (parallel_workers > 0 &&
|
|
maintenance_work_mem / (parallel_workers + 1) < 32768L)
|
|
parallel_workers--;
|
|
|
|
done:
|
|
index_close(index, NoLock);
|
|
table_close(heap, NoLock);
|
|
|
|
return parallel_workers;
|
|
}
|
|
|
|
/*
|
|
* add_paths_to_grouping_rel
|
|
*
|
|
* Add non-partial paths to grouping relation.
|
|
*/
|
|
static void
|
|
add_paths_to_grouping_rel(PlannerInfo *root, RelOptInfo *input_rel,
|
|
RelOptInfo *grouped_rel,
|
|
RelOptInfo *partially_grouped_rel,
|
|
const AggClauseCosts *agg_costs,
|
|
grouping_sets_data *gd, double dNumGroups,
|
|
GroupPathExtraData *extra)
|
|
{
|
|
Query *parse = root->parse;
|
|
Path *cheapest_path = input_rel->cheapest_total_path;
|
|
ListCell *lc;
|
|
bool can_hash = (extra->flags & GROUPING_CAN_USE_HASH) != 0;
|
|
bool can_sort = (extra->flags & GROUPING_CAN_USE_SORT) != 0;
|
|
List *havingQual = (List *) extra->havingQual;
|
|
AggClauseCosts *agg_final_costs = &extra->agg_final_costs;
|
|
|
|
if (can_sort)
|
|
{
|
|
/*
|
|
* Use any available suitably-sorted path as input, and also consider
|
|
* sorting the cheapest-total path.
|
|
*/
|
|
foreach(lc, input_rel->pathlist)
|
|
{
|
|
Path *path = (Path *) lfirst(lc);
|
|
bool is_sorted;
|
|
|
|
is_sorted = pathkeys_contained_in(root->group_pathkeys,
|
|
path->pathkeys);
|
|
if (path == cheapest_path || is_sorted)
|
|
{
|
|
/* Sort the cheapest-total path if it isn't already sorted */
|
|
if (!is_sorted)
|
|
path = (Path *) create_sort_path(root,
|
|
grouped_rel,
|
|
path,
|
|
root->group_pathkeys,
|
|
-1.0);
|
|
|
|
/* Now decide what to stick atop it */
|
|
if (parse->groupingSets)
|
|
{
|
|
consider_groupingsets_paths(root, grouped_rel,
|
|
path, true, can_hash,
|
|
gd, agg_costs, dNumGroups);
|
|
}
|
|
else if (parse->hasAggs)
|
|
{
|
|
/*
|
|
* We have aggregation, possibly with plain GROUP BY. Make
|
|
* an AggPath.
|
|
*/
|
|
add_path(grouped_rel, (Path *)
|
|
create_agg_path(root,
|
|
grouped_rel,
|
|
path,
|
|
grouped_rel->reltarget,
|
|
parse->groupClause ? AGG_SORTED : AGG_PLAIN,
|
|
AGGSPLIT_SIMPLE,
|
|
parse->groupClause,
|
|
havingQual,
|
|
agg_costs,
|
|
dNumGroups));
|
|
}
|
|
else if (parse->groupClause)
|
|
{
|
|
/*
|
|
* We have GROUP BY without aggregation or grouping sets.
|
|
* Make a GroupPath.
|
|
*/
|
|
add_path(grouped_rel, (Path *)
|
|
create_group_path(root,
|
|
grouped_rel,
|
|
path,
|
|
parse->groupClause,
|
|
havingQual,
|
|
dNumGroups));
|
|
}
|
|
else
|
|
{
|
|
/* Other cases should have been handled above */
|
|
Assert(false);
|
|
}
|
|
}
|
|
}
|
|
|
|
/*
|
|
* Instead of operating directly on the input relation, we can
|
|
* consider finalizing a partially aggregated path.
|
|
*/
|
|
if (partially_grouped_rel != NULL)
|
|
{
|
|
foreach(lc, partially_grouped_rel->pathlist)
|
|
{
|
|
Path *path = (Path *) lfirst(lc);
|
|
|
|
/*
|
|
* Insert a Sort node, if required. But there's no point in
|
|
* sorting anything but the cheapest path.
|
|
*/
|
|
if (!pathkeys_contained_in(root->group_pathkeys, path->pathkeys))
|
|
{
|
|
if (path != partially_grouped_rel->cheapest_total_path)
|
|
continue;
|
|
path = (Path *) create_sort_path(root,
|
|
grouped_rel,
|
|
path,
|
|
root->group_pathkeys,
|
|
-1.0);
|
|
}
|
|
|
|
if (parse->hasAggs)
|
|
add_path(grouped_rel, (Path *)
|
|
create_agg_path(root,
|
|
grouped_rel,
|
|
path,
|
|
grouped_rel->reltarget,
|
|
parse->groupClause ? AGG_SORTED : AGG_PLAIN,
|
|
AGGSPLIT_FINAL_DESERIAL,
|
|
parse->groupClause,
|
|
havingQual,
|
|
agg_final_costs,
|
|
dNumGroups));
|
|
else
|
|
add_path(grouped_rel, (Path *)
|
|
create_group_path(root,
|
|
grouped_rel,
|
|
path,
|
|
parse->groupClause,
|
|
havingQual,
|
|
dNumGroups));
|
|
}
|
|
}
|
|
}
|
|
|
|
if (can_hash)
|
|
{
|
|
double hashaggtablesize;
|
|
|
|
if (parse->groupingSets)
|
|
{
|
|
/*
|
|
* Try for a hash-only groupingsets path over unsorted input.
|
|
*/
|
|
consider_groupingsets_paths(root, grouped_rel,
|
|
cheapest_path, false, true,
|
|
gd, agg_costs, dNumGroups);
|
|
}
|
|
else
|
|
{
|
|
hashaggtablesize = estimate_hashagg_tablesize(cheapest_path,
|
|
agg_costs,
|
|
dNumGroups);
|
|
|
|
/*
|
|
* Provided that the estimated size of the hashtable does not
|
|
* exceed work_mem, we'll generate a HashAgg Path, although if we
|
|
* were unable to sort above, then we'd better generate a Path, so
|
|
* that we at least have one.
|
|
*/
|
|
if (hashaggtablesize < work_mem * 1024L ||
|
|
grouped_rel->pathlist == NIL)
|
|
{
|
|
/*
|
|
* We just need an Agg over the cheapest-total input path,
|
|
* since input order won't matter.
|
|
*/
|
|
add_path(grouped_rel, (Path *)
|
|
create_agg_path(root, grouped_rel,
|
|
cheapest_path,
|
|
grouped_rel->reltarget,
|
|
AGG_HASHED,
|
|
AGGSPLIT_SIMPLE,
|
|
parse->groupClause,
|
|
havingQual,
|
|
agg_costs,
|
|
dNumGroups));
|
|
}
|
|
}
|
|
|
|
/*
|
|
* Generate a Finalize HashAgg Path atop of the cheapest partially
|
|
* grouped path, assuming there is one. Once again, we'll only do this
|
|
* if it looks as though the hash table won't exceed work_mem.
|
|
*/
|
|
if (partially_grouped_rel && partially_grouped_rel->pathlist)
|
|
{
|
|
Path *path = partially_grouped_rel->cheapest_total_path;
|
|
|
|
hashaggtablesize = estimate_hashagg_tablesize(path,
|
|
agg_final_costs,
|
|
dNumGroups);
|
|
|
|
if (hashaggtablesize < work_mem * 1024L)
|
|
add_path(grouped_rel, (Path *)
|
|
create_agg_path(root,
|
|
grouped_rel,
|
|
path,
|
|
grouped_rel->reltarget,
|
|
AGG_HASHED,
|
|
AGGSPLIT_FINAL_DESERIAL,
|
|
parse->groupClause,
|
|
havingQual,
|
|
agg_final_costs,
|
|
dNumGroups));
|
|
}
|
|
}
|
|
|
|
/*
|
|
* When partitionwise aggregate is used, we might have fully aggregated
|
|
* paths in the partial pathlist, because add_paths_to_append_rel() will
|
|
* consider a path for grouped_rel consisting of a Parallel Append of
|
|
* non-partial paths from each child.
|
|
*/
|
|
if (grouped_rel->partial_pathlist != NIL)
|
|
gather_grouping_paths(root, grouped_rel);
|
|
}
|
|
|
|
/*
|
|
* create_partial_grouping_paths
|
|
*
|
|
* Create a new upper relation representing the result of partial aggregation
|
|
* and populate it with appropriate paths. Note that we don't finalize the
|
|
* lists of paths here, so the caller can add additional partial or non-partial
|
|
* paths and must afterward call gather_grouping_paths and set_cheapest on
|
|
* the returned upper relation.
|
|
*
|
|
* All paths for this new upper relation -- both partial and non-partial --
|
|
* have been partially aggregated but require a subsequent FinalizeAggregate
|
|
* step.
|
|
*
|
|
* NB: This function is allowed to return NULL if it determines that there is
|
|
* no real need to create a new RelOptInfo.
|
|
*/
|
|
static RelOptInfo *
|
|
create_partial_grouping_paths(PlannerInfo *root,
|
|
RelOptInfo *grouped_rel,
|
|
RelOptInfo *input_rel,
|
|
grouping_sets_data *gd,
|
|
GroupPathExtraData *extra,
|
|
bool force_rel_creation)
|
|
{
|
|
Query *parse = root->parse;
|
|
RelOptInfo *partially_grouped_rel;
|
|
AggClauseCosts *agg_partial_costs = &extra->agg_partial_costs;
|
|
AggClauseCosts *agg_final_costs = &extra->agg_final_costs;
|
|
Path *cheapest_partial_path = NULL;
|
|
Path *cheapest_total_path = NULL;
|
|
double dNumPartialGroups = 0;
|
|
double dNumPartialPartialGroups = 0;
|
|
ListCell *lc;
|
|
bool can_hash = (extra->flags & GROUPING_CAN_USE_HASH) != 0;
|
|
bool can_sort = (extra->flags & GROUPING_CAN_USE_SORT) != 0;
|
|
|
|
/*
|
|
* Consider whether we should generate partially aggregated non-partial
|
|
* paths. We can only do this if we have a non-partial path, and only if
|
|
* the parent of the input rel is performing partial partitionwise
|
|
* aggregation. (Note that extra->patype is the type of partitionwise
|
|
* aggregation being used at the parent level, not this level.)
|
|
*/
|
|
if (input_rel->pathlist != NIL &&
|
|
extra->patype == PARTITIONWISE_AGGREGATE_PARTIAL)
|
|
cheapest_total_path = input_rel->cheapest_total_path;
|
|
|
|
/*
|
|
* If parallelism is possible for grouped_rel, then we should consider
|
|
* generating partially-grouped partial paths. However, if the input rel
|
|
* has no partial paths, then we can't.
|
|
*/
|
|
if (grouped_rel->consider_parallel && input_rel->partial_pathlist != NIL)
|
|
cheapest_partial_path = linitial(input_rel->partial_pathlist);
|
|
|
|
/*
|
|
* If we can't partially aggregate partial paths, and we can't partially
|
|
* aggregate non-partial paths, then don't bother creating the new
|
|
* RelOptInfo at all, unless the caller specified force_rel_creation.
|
|
*/
|
|
if (cheapest_total_path == NULL &&
|
|
cheapest_partial_path == NULL &&
|
|
!force_rel_creation)
|
|
return NULL;
|
|
|
|
/*
|
|
* Build a new upper relation to represent the result of partially
|
|
* aggregating the rows from the input relation.
|
|
*/
|
|
partially_grouped_rel = fetch_upper_rel(root,
|
|
UPPERREL_PARTIAL_GROUP_AGG,
|
|
grouped_rel->relids);
|
|
partially_grouped_rel->consider_parallel =
|
|
grouped_rel->consider_parallel;
|
|
partially_grouped_rel->reloptkind = grouped_rel->reloptkind;
|
|
partially_grouped_rel->serverid = grouped_rel->serverid;
|
|
partially_grouped_rel->userid = grouped_rel->userid;
|
|
partially_grouped_rel->useridiscurrent = grouped_rel->useridiscurrent;
|
|
partially_grouped_rel->fdwroutine = grouped_rel->fdwroutine;
|
|
|
|
/*
|
|
* Build target list for partial aggregate paths. These paths cannot just
|
|
* emit the same tlist as regular aggregate paths, because (1) we must
|
|
* include Vars and Aggrefs needed in HAVING, which might not appear in
|
|
* the result tlist, and (2) the Aggrefs must be set in partial mode.
|
|
*/
|
|
partially_grouped_rel->reltarget =
|
|
make_partial_grouping_target(root, grouped_rel->reltarget,
|
|
extra->havingQual);
|
|
|
|
if (!extra->partial_costs_set)
|
|
{
|
|
/*
|
|
* Collect statistics about aggregates for estimating costs of
|
|
* performing aggregation in parallel.
|
|
*/
|
|
MemSet(agg_partial_costs, 0, sizeof(AggClauseCosts));
|
|
MemSet(agg_final_costs, 0, sizeof(AggClauseCosts));
|
|
if (parse->hasAggs)
|
|
{
|
|
List *partial_target_exprs;
|
|
|
|
/* partial phase */
|
|
partial_target_exprs = partially_grouped_rel->reltarget->exprs;
|
|
get_agg_clause_costs(root, (Node *) partial_target_exprs,
|
|
AGGSPLIT_INITIAL_SERIAL,
|
|
agg_partial_costs);
|
|
|
|
/* final phase */
|
|
get_agg_clause_costs(root, (Node *) grouped_rel->reltarget->exprs,
|
|
AGGSPLIT_FINAL_DESERIAL,
|
|
agg_final_costs);
|
|
get_agg_clause_costs(root, extra->havingQual,
|
|
AGGSPLIT_FINAL_DESERIAL,
|
|
agg_final_costs);
|
|
}
|
|
|
|
extra->partial_costs_set = true;
|
|
}
|
|
|
|
/* Estimate number of partial groups. */
|
|
if (cheapest_total_path != NULL)
|
|
dNumPartialGroups =
|
|
get_number_of_groups(root,
|
|
cheapest_total_path->rows,
|
|
gd,
|
|
extra->targetList);
|
|
if (cheapest_partial_path != NULL)
|
|
dNumPartialPartialGroups =
|
|
get_number_of_groups(root,
|
|
cheapest_partial_path->rows,
|
|
gd,
|
|
extra->targetList);
|
|
|
|
if (can_sort && cheapest_total_path != NULL)
|
|
{
|
|
/* This should have been checked previously */
|
|
Assert(parse->hasAggs || parse->groupClause);
|
|
|
|
/*
|
|
* Use any available suitably-sorted path as input, and also consider
|
|
* sorting the cheapest partial path.
|
|
*/
|
|
foreach(lc, input_rel->pathlist)
|
|
{
|
|
Path *path = (Path *) lfirst(lc);
|
|
bool is_sorted;
|
|
|
|
is_sorted = pathkeys_contained_in(root->group_pathkeys,
|
|
path->pathkeys);
|
|
if (path == cheapest_total_path || is_sorted)
|
|
{
|
|
/* Sort the cheapest partial path, if it isn't already */
|
|
if (!is_sorted)
|
|
path = (Path *) create_sort_path(root,
|
|
partially_grouped_rel,
|
|
path,
|
|
root->group_pathkeys,
|
|
-1.0);
|
|
|
|
if (parse->hasAggs)
|
|
add_path(partially_grouped_rel, (Path *)
|
|
create_agg_path(root,
|
|
partially_grouped_rel,
|
|
path,
|
|
partially_grouped_rel->reltarget,
|
|
parse->groupClause ? AGG_SORTED : AGG_PLAIN,
|
|
AGGSPLIT_INITIAL_SERIAL,
|
|
parse->groupClause,
|
|
NIL,
|
|
agg_partial_costs,
|
|
dNumPartialGroups));
|
|
else
|
|
add_path(partially_grouped_rel, (Path *)
|
|
create_group_path(root,
|
|
partially_grouped_rel,
|
|
path,
|
|
parse->groupClause,
|
|
NIL,
|
|
dNumPartialGroups));
|
|
}
|
|
}
|
|
}
|
|
|
|
if (can_sort && cheapest_partial_path != NULL)
|
|
{
|
|
/* Similar to above logic, but for partial paths. */
|
|
foreach(lc, input_rel->partial_pathlist)
|
|
{
|
|
Path *path = (Path *) lfirst(lc);
|
|
bool is_sorted;
|
|
|
|
is_sorted = pathkeys_contained_in(root->group_pathkeys,
|
|
path->pathkeys);
|
|
if (path == cheapest_partial_path || is_sorted)
|
|
{
|
|
/* Sort the cheapest partial path, if it isn't already */
|
|
if (!is_sorted)
|
|
path = (Path *) create_sort_path(root,
|
|
partially_grouped_rel,
|
|
path,
|
|
root->group_pathkeys,
|
|
-1.0);
|
|
|
|
if (parse->hasAggs)
|
|
add_partial_path(partially_grouped_rel, (Path *)
|
|
create_agg_path(root,
|
|
partially_grouped_rel,
|
|
path,
|
|
partially_grouped_rel->reltarget,
|
|
parse->groupClause ? AGG_SORTED : AGG_PLAIN,
|
|
AGGSPLIT_INITIAL_SERIAL,
|
|
parse->groupClause,
|
|
NIL,
|
|
agg_partial_costs,
|
|
dNumPartialPartialGroups));
|
|
else
|
|
add_partial_path(partially_grouped_rel, (Path *)
|
|
create_group_path(root,
|
|
partially_grouped_rel,
|
|
path,
|
|
parse->groupClause,
|
|
NIL,
|
|
dNumPartialPartialGroups));
|
|
}
|
|
}
|
|
}
|
|
|
|
if (can_hash && cheapest_total_path != NULL)
|
|
{
|
|
double hashaggtablesize;
|
|
|
|
/* Checked above */
|
|
Assert(parse->hasAggs || parse->groupClause);
|
|
|
|
hashaggtablesize =
|
|
estimate_hashagg_tablesize(cheapest_total_path,
|
|
agg_partial_costs,
|
|
dNumPartialGroups);
|
|
|
|
/*
|
|
* Tentatively produce a partial HashAgg Path, depending on if it
|
|
* looks as if the hash table will fit in work_mem.
|
|
*/
|
|
if (hashaggtablesize < work_mem * 1024L &&
|
|
cheapest_total_path != NULL)
|
|
{
|
|
add_path(partially_grouped_rel, (Path *)
|
|
create_agg_path(root,
|
|
partially_grouped_rel,
|
|
cheapest_total_path,
|
|
partially_grouped_rel->reltarget,
|
|
AGG_HASHED,
|
|
AGGSPLIT_INITIAL_SERIAL,
|
|
parse->groupClause,
|
|
NIL,
|
|
agg_partial_costs,
|
|
dNumPartialGroups));
|
|
}
|
|
}
|
|
|
|
if (can_hash && cheapest_partial_path != NULL)
|
|
{
|
|
double hashaggtablesize;
|
|
|
|
hashaggtablesize =
|
|
estimate_hashagg_tablesize(cheapest_partial_path,
|
|
agg_partial_costs,
|
|
dNumPartialPartialGroups);
|
|
|
|
/* Do the same for partial paths. */
|
|
if (hashaggtablesize < work_mem * 1024L &&
|
|
cheapest_partial_path != NULL)
|
|
{
|
|
add_partial_path(partially_grouped_rel, (Path *)
|
|
create_agg_path(root,
|
|
partially_grouped_rel,
|
|
cheapest_partial_path,
|
|
partially_grouped_rel->reltarget,
|
|
AGG_HASHED,
|
|
AGGSPLIT_INITIAL_SERIAL,
|
|
parse->groupClause,
|
|
NIL,
|
|
agg_partial_costs,
|
|
dNumPartialPartialGroups));
|
|
}
|
|
}
|
|
|
|
/*
|
|
* If there is an FDW that's responsible for all baserels of the query,
|
|
* let it consider adding partially grouped ForeignPaths.
|
|
*/
|
|
if (partially_grouped_rel->fdwroutine &&
|
|
partially_grouped_rel->fdwroutine->GetForeignUpperPaths)
|
|
{
|
|
FdwRoutine *fdwroutine = partially_grouped_rel->fdwroutine;
|
|
|
|
fdwroutine->GetForeignUpperPaths(root,
|
|
UPPERREL_PARTIAL_GROUP_AGG,
|
|
input_rel, partially_grouped_rel,
|
|
extra);
|
|
}
|
|
|
|
return partially_grouped_rel;
|
|
}
|
|
|
|
/*
|
|
* Generate Gather and Gather Merge paths for a grouping relation or partial
|
|
* grouping relation.
|
|
*
|
|
* generate_gather_paths does most of the work, but we also consider a special
|
|
* case: we could try sorting the data by the group_pathkeys and then applying
|
|
* Gather Merge.
|
|
*
|
|
* NB: This function shouldn't be used for anything other than a grouped or
|
|
* partially grouped relation not only because of the fact that it explicitly
|
|
* references group_pathkeys but we pass "true" as the third argument to
|
|
* generate_gather_paths().
|
|
*/
|
|
static void
|
|
gather_grouping_paths(PlannerInfo *root, RelOptInfo *rel)
|
|
{
|
|
Path *cheapest_partial_path;
|
|
|
|
/* Try Gather for unordered paths and Gather Merge for ordered ones. */
|
|
generate_gather_paths(root, rel, true);
|
|
|
|
/* Try cheapest partial path + explicit Sort + Gather Merge. */
|
|
cheapest_partial_path = linitial(rel->partial_pathlist);
|
|
if (!pathkeys_contained_in(root->group_pathkeys,
|
|
cheapest_partial_path->pathkeys))
|
|
{
|
|
Path *path;
|
|
double total_groups;
|
|
|
|
total_groups =
|
|
cheapest_partial_path->rows * cheapest_partial_path->parallel_workers;
|
|
path = (Path *) create_sort_path(root, rel, cheapest_partial_path,
|
|
root->group_pathkeys,
|
|
-1.0);
|
|
path = (Path *)
|
|
create_gather_merge_path(root,
|
|
rel,
|
|
path,
|
|
rel->reltarget,
|
|
root->group_pathkeys,
|
|
NULL,
|
|
&total_groups);
|
|
|
|
add_path(rel, path);
|
|
}
|
|
}
|
|
|
|
/*
|
|
* can_partial_agg
|
|
*
|
|
* Determines whether or not partial grouping and/or aggregation is possible.
|
|
* Returns true when possible, false otherwise.
|
|
*/
|
|
static bool
|
|
can_partial_agg(PlannerInfo *root, const AggClauseCosts *agg_costs)
|
|
{
|
|
Query *parse = root->parse;
|
|
|
|
if (!parse->hasAggs && parse->groupClause == NIL)
|
|
{
|
|
/*
|
|
* We don't know how to do parallel aggregation unless we have either
|
|
* some aggregates or a grouping clause.
|
|
*/
|
|
return false;
|
|
}
|
|
else if (parse->groupingSets)
|
|
{
|
|
/* We don't know how to do grouping sets in parallel. */
|
|
return false;
|
|
}
|
|
else if (agg_costs->hasNonPartial || agg_costs->hasNonSerial)
|
|
{
|
|
/* Insufficient support for partial mode. */
|
|
return false;
|
|
}
|
|
|
|
/* Everything looks good. */
|
|
return true;
|
|
}
|
|
|
|
/*
|
|
* apply_scanjoin_target_to_paths
|
|
*
|
|
* Adjust the final scan/join relation, and recursively all of its children,
|
|
* to generate the final scan/join target. It would be more correct to model
|
|
* this as a separate planning step with a new RelOptInfo at the toplevel and
|
|
* for each child relation, but doing it this way is noticeably cheaper.
|
|
* Maybe that problem can be solved at some point, but for now we do this.
|
|
*
|
|
* If tlist_same_exprs is true, then the scan/join target to be applied has
|
|
* the same expressions as the existing reltarget, so we need only insert the
|
|
* appropriate sortgroupref information. By avoiding the creation of
|
|
* projection paths we save effort both immediately and at plan creation time.
|
|
*/
|
|
static void
|
|
apply_scanjoin_target_to_paths(PlannerInfo *root,
|
|
RelOptInfo *rel,
|
|
List *scanjoin_targets,
|
|
List *scanjoin_targets_contain_srfs,
|
|
bool scanjoin_target_parallel_safe,
|
|
bool tlist_same_exprs)
|
|
{
|
|
bool rel_is_partitioned = IS_PARTITIONED_REL(rel);
|
|
PathTarget *scanjoin_target;
|
|
ListCell *lc;
|
|
|
|
/* This recurses, so be paranoid. */
|
|
check_stack_depth();
|
|
|
|
/*
|
|
* If the rel is partitioned, we want to drop its existing paths and
|
|
* generate new ones. This function would still be correct if we kept the
|
|
* existing paths: we'd modify them to generate the correct target above
|
|
* the partitioning Append, and then they'd compete on cost with paths
|
|
* generating the target below the Append. However, in our current cost
|
|
* model the latter way is always the same or cheaper cost, so modifying
|
|
* the existing paths would just be useless work. Moreover, when the cost
|
|
* is the same, varying roundoff errors might sometimes allow an existing
|
|
* path to be picked, resulting in undesirable cross-platform plan
|
|
* variations. So we drop old paths and thereby force the work to be done
|
|
* below the Append, except in the case of a non-parallel-safe target.
|
|
*
|
|
* Some care is needed, because we have to allow generate_gather_paths to
|
|
* see the old partial paths in the next stanza. Hence, zap the main
|
|
* pathlist here, then allow generate_gather_paths to add path(s) to the
|
|
* main list, and finally zap the partial pathlist.
|
|
*/
|
|
if (rel_is_partitioned)
|
|
rel->pathlist = NIL;
|
|
|
|
/*
|
|
* If the scan/join target is not parallel-safe, partial paths cannot
|
|
* generate it.
|
|
*/
|
|
if (!scanjoin_target_parallel_safe)
|
|
{
|
|
/*
|
|
* Since we can't generate the final scan/join target in parallel
|
|
* workers, this is our last opportunity to use any partial paths that
|
|
* exist; so build Gather path(s) that use them and emit whatever the
|
|
* current reltarget is. We don't do this in the case where the
|
|
* target is parallel-safe, since we will be able to generate superior
|
|
* paths by doing it after the final scan/join target has been
|
|
* applied.
|
|
*/
|
|
generate_gather_paths(root, rel, false);
|
|
|
|
/* Can't use parallel query above this level. */
|
|
rel->partial_pathlist = NIL;
|
|
rel->consider_parallel = false;
|
|
}
|
|
|
|
/* Finish dropping old paths for a partitioned rel, per comment above */
|
|
if (rel_is_partitioned)
|
|
rel->partial_pathlist = NIL;
|
|
|
|
/* Extract SRF-free scan/join target. */
|
|
scanjoin_target = linitial_node(PathTarget, scanjoin_targets);
|
|
|
|
/*
|
|
* Apply the SRF-free scan/join target to each existing path.
|
|
*
|
|
* If the tlist exprs are the same, we can just inject the sortgroupref
|
|
* information into the existing pathtargets. Otherwise, replace each
|
|
* path with a projection path that generates the SRF-free scan/join
|
|
* target. This can't change the ordering of paths within rel->pathlist,
|
|
* so we just modify the list in place.
|
|
*/
|
|
foreach(lc, rel->pathlist)
|
|
{
|
|
Path *subpath = (Path *) lfirst(lc);
|
|
|
|
/* Shouldn't have any parameterized paths anymore */
|
|
Assert(subpath->param_info == NULL);
|
|
|
|
if (tlist_same_exprs)
|
|
subpath->pathtarget->sortgrouprefs =
|
|
scanjoin_target->sortgrouprefs;
|
|
else
|
|
{
|
|
Path *newpath;
|
|
|
|
newpath = (Path *) create_projection_path(root, rel, subpath,
|
|
scanjoin_target);
|
|
lfirst(lc) = newpath;
|
|
}
|
|
}
|
|
|
|
/* Likewise adjust the targets for any partial paths. */
|
|
foreach(lc, rel->partial_pathlist)
|
|
{
|
|
Path *subpath = (Path *) lfirst(lc);
|
|
|
|
/* Shouldn't have any parameterized paths anymore */
|
|
Assert(subpath->param_info == NULL);
|
|
|
|
if (tlist_same_exprs)
|
|
subpath->pathtarget->sortgrouprefs =
|
|
scanjoin_target->sortgrouprefs;
|
|
else
|
|
{
|
|
Path *newpath;
|
|
|
|
newpath = (Path *) create_projection_path(root, rel, subpath,
|
|
scanjoin_target);
|
|
lfirst(lc) = newpath;
|
|
}
|
|
}
|
|
|
|
/*
|
|
* Now, if final scan/join target contains SRFs, insert ProjectSetPath(s)
|
|
* atop each existing path. (Note that this function doesn't look at the
|
|
* cheapest-path fields, which is a good thing because they're bogus right
|
|
* now.)
|
|
*/
|
|
if (root->parse->hasTargetSRFs)
|
|
adjust_paths_for_srfs(root, rel,
|
|
scanjoin_targets,
|
|
scanjoin_targets_contain_srfs);
|
|
|
|
/*
|
|
* Update the rel's target to be the final (with SRFs) scan/join target.
|
|
* This now matches the actual output of all the paths, and we might get
|
|
* confused in createplan.c if they don't agree. We must do this now so
|
|
* that any append paths made in the next part will use the correct
|
|
* pathtarget (cf. create_append_path).
|
|
*
|
|
* Note that this is also necessary if GetForeignUpperPaths() gets called
|
|
* on the final scan/join relation or on any of its children, since the
|
|
* FDW might look at the rel's target to create ForeignPaths.
|
|
*/
|
|
rel->reltarget = llast_node(PathTarget, scanjoin_targets);
|
|
|
|
/*
|
|
* If the relation is partitioned, recursively apply the scan/join target
|
|
* to all partitions, and generate brand-new Append paths in which the
|
|
* scan/join target is computed below the Append rather than above it.
|
|
* Since Append is not projection-capable, that might save a separate
|
|
* Result node, and it also is important for partitionwise aggregate.
|
|
*/
|
|
if (rel_is_partitioned)
|
|
{
|
|
List *live_children = NIL;
|
|
int partition_idx;
|
|
|
|
/* Adjust each partition. */
|
|
for (partition_idx = 0; partition_idx < rel->nparts; partition_idx++)
|
|
{
|
|
RelOptInfo *child_rel = rel->part_rels[partition_idx];
|
|
AppendRelInfo **appinfos;
|
|
int nappinfos;
|
|
List *child_scanjoin_targets = NIL;
|
|
ListCell *lc;
|
|
|
|
/* Pruned or dummy children can be ignored. */
|
|
if (child_rel == NULL || IS_DUMMY_REL(child_rel))
|
|
continue;
|
|
|
|
/* Translate scan/join targets for this child. */
|
|
appinfos = find_appinfos_by_relids(root, child_rel->relids,
|
|
&nappinfos);
|
|
foreach(lc, scanjoin_targets)
|
|
{
|
|
PathTarget *target = lfirst_node(PathTarget, lc);
|
|
|
|
target = copy_pathtarget(target);
|
|
target->exprs = (List *)
|
|
adjust_appendrel_attrs(root,
|
|
(Node *) target->exprs,
|
|
nappinfos, appinfos);
|
|
child_scanjoin_targets = lappend(child_scanjoin_targets,
|
|
target);
|
|
}
|
|
pfree(appinfos);
|
|
|
|
/* Recursion does the real work. */
|
|
apply_scanjoin_target_to_paths(root, child_rel,
|
|
child_scanjoin_targets,
|
|
scanjoin_targets_contain_srfs,
|
|
scanjoin_target_parallel_safe,
|
|
tlist_same_exprs);
|
|
|
|
/* Save non-dummy children for Append paths. */
|
|
if (!IS_DUMMY_REL(child_rel))
|
|
live_children = lappend(live_children, child_rel);
|
|
}
|
|
|
|
/* Build new paths for this relation by appending child paths. */
|
|
add_paths_to_append_rel(root, rel, live_children);
|
|
}
|
|
|
|
/*
|
|
* Consider generating Gather or Gather Merge paths. We must only do this
|
|
* if the relation is parallel safe, and we don't do it for child rels to
|
|
* avoid creating multiple Gather nodes within the same plan. We must do
|
|
* this after all paths have been generated and before set_cheapest, since
|
|
* one of the generated paths may turn out to be the cheapest one.
|
|
*/
|
|
if (rel->consider_parallel && !IS_OTHER_REL(rel))
|
|
generate_gather_paths(root, rel, false);
|
|
|
|
/*
|
|
* Reassess which paths are the cheapest, now that we've potentially added
|
|
* new Gather (or Gather Merge) and/or Append (or MergeAppend) paths to
|
|
* this relation.
|
|
*/
|
|
set_cheapest(rel);
|
|
}
|
|
|
|
/*
|
|
* create_partitionwise_grouping_paths
|
|
*
|
|
* If the partition keys of input relation are part of the GROUP BY clause, all
|
|
* the rows belonging to a given group come from a single partition. This
|
|
* allows aggregation/grouping over a partitioned relation to be broken down
|
|
* into aggregation/grouping on each partition. This should be no worse, and
|
|
* often better, than the normal approach.
|
|
*
|
|
* However, if the GROUP BY clause does not contain all the partition keys,
|
|
* rows from a given group may be spread across multiple partitions. In that
|
|
* case, we perform partial aggregation for each group, append the results,
|
|
* and then finalize aggregation. This is less certain to win than the
|
|
* previous case. It may win if the PartialAggregate stage greatly reduces
|
|
* the number of groups, because fewer rows will pass through the Append node.
|
|
* It may lose if we have lots of small groups.
|
|
*/
|
|
static void
|
|
create_partitionwise_grouping_paths(PlannerInfo *root,
|
|
RelOptInfo *input_rel,
|
|
RelOptInfo *grouped_rel,
|
|
RelOptInfo *partially_grouped_rel,
|
|
const AggClauseCosts *agg_costs,
|
|
grouping_sets_data *gd,
|
|
PartitionwiseAggregateType patype,
|
|
GroupPathExtraData *extra)
|
|
{
|
|
int nparts = input_rel->nparts;
|
|
int cnt_parts;
|
|
List *grouped_live_children = NIL;
|
|
List *partially_grouped_live_children = NIL;
|
|
PathTarget *target = grouped_rel->reltarget;
|
|
bool partial_grouping_valid = true;
|
|
|
|
Assert(patype != PARTITIONWISE_AGGREGATE_NONE);
|
|
Assert(patype != PARTITIONWISE_AGGREGATE_PARTIAL ||
|
|
partially_grouped_rel != NULL);
|
|
|
|
/* Add paths for partitionwise aggregation/grouping. */
|
|
for (cnt_parts = 0; cnt_parts < nparts; cnt_parts++)
|
|
{
|
|
RelOptInfo *child_input_rel = input_rel->part_rels[cnt_parts];
|
|
PathTarget *child_target = copy_pathtarget(target);
|
|
AppendRelInfo **appinfos;
|
|
int nappinfos;
|
|
GroupPathExtraData child_extra;
|
|
RelOptInfo *child_grouped_rel;
|
|
RelOptInfo *child_partially_grouped_rel;
|
|
|
|
/* Pruned or dummy children can be ignored. */
|
|
if (child_input_rel == NULL || IS_DUMMY_REL(child_input_rel))
|
|
continue;
|
|
|
|
/*
|
|
* Copy the given "extra" structure as is and then override the
|
|
* members specific to this child.
|
|
*/
|
|
memcpy(&child_extra, extra, sizeof(child_extra));
|
|
|
|
appinfos = find_appinfos_by_relids(root, child_input_rel->relids,
|
|
&nappinfos);
|
|
|
|
child_target->exprs = (List *)
|
|
adjust_appendrel_attrs(root,
|
|
(Node *) target->exprs,
|
|
nappinfos, appinfos);
|
|
|
|
/* Translate havingQual and targetList. */
|
|
child_extra.havingQual = (Node *)
|
|
adjust_appendrel_attrs(root,
|
|
extra->havingQual,
|
|
nappinfos, appinfos);
|
|
child_extra.targetList = (List *)
|
|
adjust_appendrel_attrs(root,
|
|
(Node *) extra->targetList,
|
|
nappinfos, appinfos);
|
|
|
|
/*
|
|
* extra->patype was the value computed for our parent rel; patype is
|
|
* the value for this relation. For the child, our value is its
|
|
* parent rel's value.
|
|
*/
|
|
child_extra.patype = patype;
|
|
|
|
/*
|
|
* Create grouping relation to hold fully aggregated grouping and/or
|
|
* aggregation paths for the child.
|
|
*/
|
|
child_grouped_rel = make_grouping_rel(root, child_input_rel,
|
|
child_target,
|
|
extra->target_parallel_safe,
|
|
child_extra.havingQual);
|
|
|
|
/* Create grouping paths for this child relation. */
|
|
create_ordinary_grouping_paths(root, child_input_rel,
|
|
child_grouped_rel,
|
|
agg_costs, gd, &child_extra,
|
|
&child_partially_grouped_rel);
|
|
|
|
if (child_partially_grouped_rel)
|
|
{
|
|
partially_grouped_live_children =
|
|
lappend(partially_grouped_live_children,
|
|
child_partially_grouped_rel);
|
|
}
|
|
else
|
|
partial_grouping_valid = false;
|
|
|
|
if (patype == PARTITIONWISE_AGGREGATE_FULL)
|
|
{
|
|
set_cheapest(child_grouped_rel);
|
|
grouped_live_children = lappend(grouped_live_children,
|
|
child_grouped_rel);
|
|
}
|
|
|
|
pfree(appinfos);
|
|
}
|
|
|
|
/*
|
|
* Try to create append paths for partially grouped children. For full
|
|
* partitionwise aggregation, we might have paths in the partial_pathlist
|
|
* if parallel aggregation is possible. For partial partitionwise
|
|
* aggregation, we may have paths in both pathlist and partial_pathlist.
|
|
*
|
|
* NB: We must have a partially grouped path for every child in order to
|
|
* generate a partially grouped path for this relation.
|
|
*/
|
|
if (partially_grouped_rel && partial_grouping_valid)
|
|
{
|
|
Assert(partially_grouped_live_children != NIL);
|
|
|
|
add_paths_to_append_rel(root, partially_grouped_rel,
|
|
partially_grouped_live_children);
|
|
|
|
/*
|
|
* We need call set_cheapest, since the finalization step will use the
|
|
* cheapest path from the rel.
|
|
*/
|
|
if (partially_grouped_rel->pathlist)
|
|
set_cheapest(partially_grouped_rel);
|
|
}
|
|
|
|
/* If possible, create append paths for fully grouped children. */
|
|
if (patype == PARTITIONWISE_AGGREGATE_FULL)
|
|
{
|
|
Assert(grouped_live_children != NIL);
|
|
|
|
add_paths_to_append_rel(root, grouped_rel, grouped_live_children);
|
|
}
|
|
}
|
|
|
|
/*
|
|
* group_by_has_partkey
|
|
*
|
|
* Returns true, if all the partition keys of the given relation are part of
|
|
* the GROUP BY clauses, false otherwise.
|
|
*/
|
|
static bool
|
|
group_by_has_partkey(RelOptInfo *input_rel,
|
|
List *targetList,
|
|
List *groupClause)
|
|
{
|
|
List *groupexprs = get_sortgrouplist_exprs(groupClause, targetList);
|
|
int cnt = 0;
|
|
int partnatts;
|
|
|
|
/* Input relation should be partitioned. */
|
|
Assert(input_rel->part_scheme);
|
|
|
|
/* Rule out early, if there are no partition keys present. */
|
|
if (!input_rel->partexprs)
|
|
return false;
|
|
|
|
partnatts = input_rel->part_scheme->partnatts;
|
|
|
|
for (cnt = 0; cnt < partnatts; cnt++)
|
|
{
|
|
List *partexprs = input_rel->partexprs[cnt];
|
|
ListCell *lc;
|
|
bool found = false;
|
|
|
|
foreach(lc, partexprs)
|
|
{
|
|
Expr *partexpr = lfirst(lc);
|
|
|
|
if (list_member(groupexprs, partexpr))
|
|
{
|
|
found = true;
|
|
break;
|
|
}
|
|
}
|
|
|
|
/*
|
|
* If none of the partition key expressions match with any of the
|
|
* GROUP BY expression, return false.
|
|
*/
|
|
if (!found)
|
|
return false;
|
|
}
|
|
|
|
return true;
|
|
}
|