| /*------------------------------------------------------------------------- |
| * |
| * extended_stats.c |
| * POSTGRES extended statistics |
| * |
| * Generic code supporting statistics objects created via CREATE STATISTICS. |
| * |
| * |
| * Portions Copyright (c) 1996-2023, PostgreSQL Global Development Group |
| * Portions Copyright (c) 1994, Regents of the University of California |
| * |
| * IDENTIFICATION |
| * src/backend/statistics/extended_stats.c |
| * |
| *------------------------------------------------------------------------- |
| */ |
| #include "postgres.h" |
| |
| #include "access/detoast.h" |
| #include "access/genam.h" |
| #include "access/htup_details.h" |
| #include "access/table.h" |
| #include "catalog/indexing.h" |
| #include "catalog/pg_collation.h" |
| #include "catalog/pg_statistic_ext.h" |
| #include "catalog/pg_statistic_ext_data.h" |
| #include "executor/executor.h" |
| #include "commands/defrem.h" |
| #include "commands/progress.h" |
| #include "miscadmin.h" |
| #include "nodes/nodeFuncs.h" |
| #include "optimizer/clauses.h" |
| #include "optimizer/optimizer.h" |
| #include "parser/parsetree.h" |
| #include "pgstat.h" |
| #include "postmaster/autovacuum.h" |
| #include "statistics/extended_stats_internal.h" |
| #include "statistics/statistics.h" |
| #include "utils/acl.h" |
| #include "utils/array.h" |
| #include "utils/attoptcache.h" |
| #include "utils/builtins.h" |
| #include "utils/datum.h" |
| #include "utils/fmgroids.h" |
| #include "utils/lsyscache.h" |
| #include "utils/memutils.h" |
| #include "utils/rel.h" |
| #include "utils/selfuncs.h" |
| #include "utils/syscache.h" |
| #include "utils/typcache.h" |
| |
| #include "cdb/cdbvars.h" |
| /* |
| * To avoid consuming too much memory during analysis and/or too much space |
| * in the resulting pg_statistic rows, we ignore varlena datums that are wider |
| * than WIDTH_THRESHOLD (after detoasting!). This is legitimate for MCV |
| * and distinct-value calculations since a wide value is unlikely to be |
| * duplicated at all, much less be a most-common value. For the same reason, |
| * ignoring wide values will not affect our estimates of histogram bin |
| * boundaries very much. |
| */ |
| #define WIDTH_THRESHOLD 1024 |
| |
| /* |
| * Used internally to refer to an individual statistics object, i.e., |
| * a pg_statistic_ext entry. |
| */ |
| typedef struct StatExtEntry |
| { |
| Oid statOid; /* OID of pg_statistic_ext entry */ |
| char *schema; /* statistics object's schema */ |
| char *name; /* statistics object's name */ |
| Bitmapset *columns; /* attribute numbers covered by the object */ |
| List *types; /* 'char' list of enabled statistics kinds */ |
| int stattarget; /* statistics target (-1 for default) */ |
| List *exprs; /* expressions */ |
| } StatExtEntry; |
| |
| |
| static List *fetch_statentries_for_relation(Relation pg_statext, Oid relid); |
| static VacAttrStats **lookup_var_attr_stats(Relation rel, Bitmapset *attrs, List *exprs, |
| int nvacatts, VacAttrStats **vacatts); |
| static void statext_store(Oid statOid, bool inh, |
| MVNDistinct *ndistinct, MVDependencies *dependencies, |
| MCVList *mcv, Datum exprs, VacAttrStats **stats); |
| static int statext_compute_stattarget(int stattarget, |
| int nattrs, VacAttrStats **stats); |
| |
| /* Information needed to analyze a single simple expression. */ |
| typedef struct AnlExprData |
| { |
| Node *expr; /* expression to analyze */ |
| VacAttrStats *vacattrstat; /* statistics attrs to analyze */ |
| } AnlExprData; |
| |
| static void compute_expr_stats(Relation onerel, double totalrows, |
| AnlExprData *exprdata, int nexprs, |
| HeapTuple *rows, int numrows); |
| static Datum serialize_expr_stats(AnlExprData *exprdata, int nexprs); |
| static Datum expr_fetch_func(VacAttrStatsP stats, int rownum, bool *isNull); |
| static AnlExprData *build_expr_data(List *exprs, int stattarget); |
| |
| static StatsBuildData *make_build_data(Relation rel, StatExtEntry *stat, |
| int numrows, HeapTuple *rows, |
| VacAttrStats **stats, int stattarget); |
| |
| |
| /* |
| * Compute requested extended stats, using the rows sampled for the plain |
| * (single-column) stats. |
| * |
| * This fetches a list of stats types from pg_statistic_ext, computes the |
| * requested stats, and serializes them back into the catalog. |
| */ |
| void |
| BuildRelationExtStatistics(Relation onerel, bool inh, double totalrows, |
| int numrows, HeapTuple *rows, |
| int natts, VacAttrStats **vacattrstats) |
| { |
| Relation pg_stext; |
| ListCell *lc; |
| List *statslist; |
| MemoryContext cxt; |
| MemoryContext oldcxt; |
| int64 ext_cnt; |
| |
| /* Do nothing if there are no columns to analyze. */ |
| if (Gp_role == GP_ROLE_EXECUTE || !natts) |
| return; |
| |
| /* the list of stats has to be allocated outside the memory context */ |
| pg_stext = table_open(StatisticExtRelationId, RowExclusiveLock); |
| statslist = fetch_statentries_for_relation(pg_stext, RelationGetRelid(onerel)); |
| |
| /* memory context for building each statistics object */ |
| cxt = AllocSetContextCreate(CurrentMemoryContext, |
| "BuildRelationExtStatistics", |
| ALLOCSET_DEFAULT_SIZES); |
| oldcxt = MemoryContextSwitchTo(cxt); |
| |
| /* report this phase */ |
| if (statslist != NIL) |
| { |
| const int index[] = { |
| PROGRESS_ANALYZE_PHASE, |
| PROGRESS_ANALYZE_EXT_STATS_TOTAL |
| }; |
| const int64 val[] = { |
| PROGRESS_ANALYZE_PHASE_COMPUTE_EXT_STATS, |
| list_length(statslist) |
| }; |
| |
| pgstat_progress_update_multi_param(2, index, val); |
| } |
| |
| ext_cnt = 0; |
| foreach(lc, statslist) |
| { |
| StatExtEntry *stat = (StatExtEntry *) lfirst(lc); |
| MVNDistinct *ndistinct = NULL; |
| MVDependencies *dependencies = NULL; |
| MCVList *mcv = NULL; |
| Datum exprstats = (Datum) 0; |
| VacAttrStats **stats; |
| ListCell *lc2; |
| int stattarget; |
| StatsBuildData *data; |
| |
| /* |
| * Check if we can build these stats based on the column analyzed. If |
| * not, report this fact (except in autovacuum) and move on. |
| */ |
| stats = lookup_var_attr_stats(onerel, stat->columns, stat->exprs, |
| natts, vacattrstats); |
| if (!stats) |
| { |
| if (!IsAutoVacuumWorkerProcess()) |
| ereport(WARNING, |
| (errcode(ERRCODE_INVALID_OBJECT_DEFINITION), |
| errmsg("statistics object \"%s.%s\" could not be computed for relation \"%s.%s\"", |
| stat->schema, stat->name, |
| get_namespace_name(onerel->rd_rel->relnamespace), |
| RelationGetRelationName(onerel)), |
| errtable(onerel))); |
| continue; |
| } |
| |
| /* compute statistics target for this statistics object */ |
| stattarget = statext_compute_stattarget(stat->stattarget, |
| bms_num_members(stat->columns), |
| stats); |
| |
| /* |
| * Don't rebuild statistics objects with statistics target set to 0 |
| * (we just leave the existing values around, just like we do for |
| * regular per-column statistics). |
| */ |
| if (stattarget == 0) |
| continue; |
| |
| /* evaluate expressions (if the statistics object has any) */ |
| data = make_build_data(onerel, stat, numrows, rows, stats, stattarget); |
| |
| /* compute statistic of each requested type */ |
| foreach(lc2, stat->types) |
| { |
| char t = (char) lfirst_int(lc2); |
| |
| if (t == STATS_EXT_NDISTINCT) |
| ndistinct = statext_ndistinct_build(totalrows, data); |
| else if (t == STATS_EXT_DEPENDENCIES) |
| dependencies = statext_dependencies_build(data); |
| else if (t == STATS_EXT_MCV) |
| mcv = statext_mcv_build(data, totalrows, stattarget); |
| else if (t == STATS_EXT_EXPRESSIONS) |
| { |
| AnlExprData *exprdata; |
| int nexprs; |
| |
| /* should not happen, thanks to checks when defining stats */ |
| if (!stat->exprs) |
| elog(ERROR, "requested expression stats, but there are no expressions"); |
| |
| exprdata = build_expr_data(stat->exprs, stattarget); |
| nexprs = list_length(stat->exprs); |
| |
| compute_expr_stats(onerel, totalrows, |
| exprdata, nexprs, |
| rows, numrows); |
| |
| exprstats = serialize_expr_stats(exprdata, nexprs); |
| } |
| } |
| |
| /* store the statistics in the catalog */ |
| statext_store(stat->statOid, inh, |
| ndistinct, dependencies, mcv, exprstats, stats); |
| |
| /* for reporting progress */ |
| pgstat_progress_update_param(PROGRESS_ANALYZE_EXT_STATS_COMPUTED, |
| ++ext_cnt); |
| |
| /* free the data used for building this statistics object */ |
| MemoryContextReset(cxt); |
| } |
| |
| MemoryContextSwitchTo(oldcxt); |
| MemoryContextDelete(cxt); |
| |
| list_free(statslist); |
| |
| table_close(pg_stext, RowExclusiveLock); |
| } |
| |
| /* |
| * ComputeExtStatisticsRows |
| * Compute number of rows required by extended statistics on a table. |
| * |
| * Computes number of rows we need to sample to build extended statistics on a |
| * table. This only looks at statistics we can actually build - for example |
| * when analyzing only some of the columns, this will skip statistics objects |
| * that would require additional columns. |
| * |
| * See statext_compute_stattarget for details about how we compute the |
| * statistics target for a statistics object (from the object target, |
| * attribute targets and default statistics target). |
| */ |
| int |
| ComputeExtStatisticsRows(Relation onerel, |
| int natts, VacAttrStats **vacattrstats) |
| { |
| Relation pg_stext; |
| ListCell *lc; |
| List *lstats; |
| MemoryContext cxt; |
| MemoryContext oldcxt; |
| int result = 0; |
| |
| /* If there are no columns to analyze, just return 0. */ |
| if (!natts) |
| return 0; |
| |
| cxt = AllocSetContextCreate(CurrentMemoryContext, |
| "ComputeExtStatisticsRows", |
| ALLOCSET_DEFAULT_SIZES); |
| oldcxt = MemoryContextSwitchTo(cxt); |
| |
| pg_stext = table_open(StatisticExtRelationId, RowExclusiveLock); |
| lstats = fetch_statentries_for_relation(pg_stext, RelationGetRelid(onerel)); |
| |
| foreach(lc, lstats) |
| { |
| StatExtEntry *stat = (StatExtEntry *) lfirst(lc); |
| int stattarget; |
| VacAttrStats **stats; |
| int nattrs = bms_num_members(stat->columns); |
| |
| /* |
| * Check if we can build this statistics object based on the columns |
| * analyzed. If not, ignore it (don't report anything, we'll do that |
| * during the actual build BuildRelationExtStatistics). |
| */ |
| stats = lookup_var_attr_stats(onerel, stat->columns, stat->exprs, |
| natts, vacattrstats); |
| |
| if (!stats) |
| continue; |
| |
| /* |
| * Compute statistics target, based on what's set for the statistic |
| * object itself, and for its attributes. |
| */ |
| stattarget = statext_compute_stattarget(stat->stattarget, |
| nattrs, stats); |
| |
| /* Use the largest value for all statistics objects. */ |
| if (stattarget > result) |
| result = stattarget; |
| } |
| |
| table_close(pg_stext, RowExclusiveLock); |
| |
| MemoryContextSwitchTo(oldcxt); |
| MemoryContextDelete(cxt); |
| |
| /* compute sample size based on the statistics target */ |
| return (300 * result); |
| } |
| |
| /* |
| * statext_compute_stattarget |
| * compute statistics target for an extended statistic |
| * |
| * When computing target for extended statistics objects, we consider three |
| * places where the target may be set - the statistics object itself, |
| * attributes the statistics object is defined on, and then the default |
| * statistics target. |
| * |
| * First we look at what's set for the statistics object itself, using the |
| * ALTER STATISTICS ... SET STATISTICS command. If we find a valid value |
| * there (i.e. not -1) we're done. Otherwise we look at targets set for any |
| * of the attributes the statistic is defined on, and if there are columns |
| * with defined target, we use the maximum value. We do this mostly for |
| * backwards compatibility, because this is what we did before having |
| * statistics target for extended statistics. |
| * |
| * And finally, if we still don't have a statistics target, we use the value |
| * set in default_statistics_target. |
| */ |
| static int |
| statext_compute_stattarget(int stattarget, int nattrs, VacAttrStats **stats) |
| { |
| int i; |
| |
| /* |
| * If there's statistics target set for the statistics object, use it. It |
| * may be set to 0 which disables building of that statistic. |
| */ |
| if (stattarget >= 0) |
| return stattarget; |
| |
| /* |
| * The target for the statistics object is set to -1, in which case we |
| * look at the maximum target set for any of the attributes the object is |
| * defined on. |
| */ |
| for (i = 0; i < nattrs; i++) |
| { |
| /* keep the maximum statistics target */ |
| if (stats[i]->attr->attstattarget > stattarget) |
| stattarget = stats[i]->attr->attstattarget; |
| } |
| |
| /* |
| * If the value is still negative (so neither the statistics object nor |
| * any of the columns have custom statistics target set), use the global |
| * default target. |
| */ |
| if (stattarget < 0) |
| stattarget = default_statistics_target; |
| |
| /* As this point we should have a valid statistics target. */ |
| Assert((stattarget >= 0) && (stattarget <= 10000)); |
| |
| return stattarget; |
| } |
| |
| /* |
| * statext_is_kind_built |
| * Is this stat kind built in the given pg_statistic_ext_data tuple? |
| */ |
| bool |
| statext_is_kind_built(HeapTuple htup, char type) |
| { |
| AttrNumber attnum; |
| |
| switch (type) |
| { |
| case STATS_EXT_NDISTINCT: |
| attnum = Anum_pg_statistic_ext_data_stxdndistinct; |
| break; |
| |
| case STATS_EXT_DEPENDENCIES: |
| attnum = Anum_pg_statistic_ext_data_stxddependencies; |
| break; |
| |
| case STATS_EXT_MCV: |
| attnum = Anum_pg_statistic_ext_data_stxdmcv; |
| break; |
| |
| case STATS_EXT_EXPRESSIONS: |
| attnum = Anum_pg_statistic_ext_data_stxdexpr; |
| break; |
| |
| default: |
| elog(ERROR, "unexpected statistics type requested: %d", type); |
| } |
| |
| return !heap_attisnull(htup, attnum, NULL); |
| } |
| |
| /* |
| * Return a list (of StatExtEntry) of statistics objects for the given relation. |
| */ |
| static List * |
| fetch_statentries_for_relation(Relation pg_statext, Oid relid) |
| { |
| SysScanDesc scan; |
| ScanKeyData skey; |
| HeapTuple htup; |
| List *result = NIL; |
| |
| /* |
| * Prepare to scan pg_statistic_ext for entries having stxrelid = this |
| * rel. |
| */ |
| ScanKeyInit(&skey, |
| Anum_pg_statistic_ext_stxrelid, |
| BTEqualStrategyNumber, F_OIDEQ, |
| ObjectIdGetDatum(relid)); |
| |
| scan = systable_beginscan(pg_statext, StatisticExtRelidIndexId, true, |
| NULL, 1, &skey); |
| |
| while (HeapTupleIsValid(htup = systable_getnext(scan))) |
| { |
| StatExtEntry *entry; |
| Datum datum; |
| bool isnull; |
| int i; |
| ArrayType *arr; |
| char *enabled; |
| Form_pg_statistic_ext staForm; |
| List *exprs = NIL; |
| |
| entry = palloc0(sizeof(StatExtEntry)); |
| staForm = (Form_pg_statistic_ext) GETSTRUCT(htup); |
| entry->statOid = staForm->oid; |
| entry->schema = get_namespace_name(staForm->stxnamespace); |
| entry->name = pstrdup(NameStr(staForm->stxname)); |
| entry->stattarget = staForm->stxstattarget; |
| for (i = 0; i < staForm->stxkeys.dim1; i++) |
| { |
| entry->columns = bms_add_member(entry->columns, |
| staForm->stxkeys.values[i]); |
| } |
| |
| /* decode the stxkind char array into a list of chars */ |
| datum = SysCacheGetAttrNotNull(STATEXTOID, htup, |
| Anum_pg_statistic_ext_stxkind); |
| arr = DatumGetArrayTypeP(datum); |
| if (ARR_NDIM(arr) != 1 || |
| ARR_HASNULL(arr) || |
| ARR_ELEMTYPE(arr) != CHAROID) |
| elog(ERROR, "stxkind is not a 1-D char array"); |
| enabled = (char *) ARR_DATA_PTR(arr); |
| for (i = 0; i < ARR_DIMS(arr)[0]; i++) |
| { |
| Assert((enabled[i] == STATS_EXT_NDISTINCT) || |
| (enabled[i] == STATS_EXT_DEPENDENCIES) || |
| (enabled[i] == STATS_EXT_MCV) || |
| (enabled[i] == STATS_EXT_EXPRESSIONS)); |
| entry->types = lappend_int(entry->types, (int) enabled[i]); |
| } |
| |
| /* decode expression (if any) */ |
| datum = SysCacheGetAttr(STATEXTOID, htup, |
| Anum_pg_statistic_ext_stxexprs, &isnull); |
| |
| if (!isnull) |
| { |
| char *exprsString; |
| |
| exprsString = TextDatumGetCString(datum); |
| exprs = (List *) stringToNode(exprsString); |
| |
| pfree(exprsString); |
| |
| /* |
| * Run the expressions through eval_const_expressions. This is not |
| * just an optimization, but is necessary, because the planner |
| * will be comparing them to similarly-processed qual clauses, and |
| * may fail to detect valid matches without this. We must not use |
| * canonicalize_qual, however, since these aren't qual |
| * expressions. |
| */ |
| exprs = (List *) eval_const_expressions(NULL, (Node *) exprs); |
| |
| /* May as well fix opfuncids too */ |
| fix_opfuncids((Node *) exprs); |
| } |
| |
| entry->exprs = exprs; |
| |
| result = lappend(result, entry); |
| } |
| |
| systable_endscan(scan); |
| |
| return result; |
| } |
| |
| /* |
| * examine_attribute -- pre-analysis of a single column |
| * |
| * Determine whether the column is analyzable; if so, create and initialize |
| * a VacAttrStats struct for it. If not, return NULL. |
| */ |
| static VacAttrStats * |
| examine_attribute(Node *expr) |
| { |
| HeapTuple typtuple; |
| VacAttrStats *stats; |
| int i; |
| bool ok; |
| |
| /* |
| * Create the VacAttrStats struct. Note that we only have a copy of the |
| * fixed fields of the pg_attribute tuple. |
| */ |
| stats = (VacAttrStats *) palloc0(sizeof(VacAttrStats)); |
| |
| /* fake the attribute */ |
| stats->attr = (Form_pg_attribute) palloc0(ATTRIBUTE_FIXED_PART_SIZE); |
| stats->attr->attstattarget = -1; |
| |
| /* |
| * When analyzing an expression, believe the expression tree's type not |
| * the column datatype --- the latter might be the opckeytype storage type |
| * of the opclass, which is not interesting for our purposes. (Note: if |
| * we did anything with non-expression statistics columns, we'd need to |
| * figure out where to get the correct type info from, but for now that's |
| * not a problem.) It's not clear whether anyone will care about the |
| * typmod, but we store that too just in case. |
| */ |
| stats->attrtypid = exprType(expr); |
| stats->attrtypmod = exprTypmod(expr); |
| stats->attrcollid = exprCollation(expr); |
| |
| typtuple = SearchSysCacheCopy1(TYPEOID, |
| ObjectIdGetDatum(stats->attrtypid)); |
| if (!HeapTupleIsValid(typtuple)) |
| elog(ERROR, "cache lookup failed for type %u", stats->attrtypid); |
| stats->attrtype = (Form_pg_type) GETSTRUCT(typtuple); |
| |
| /* |
| * We don't actually analyze individual attributes, so no need to set the |
| * memory context. |
| */ |
| stats->anl_context = NULL; |
| stats->tupattnum = InvalidAttrNumber; |
| |
| /* |
| * The fields describing the stats->stavalues[n] element types default to |
| * the type of the data being analyzed, but the type-specific typanalyze |
| * function can change them if it wants to store something else. |
| */ |
| for (i = 0; i < STATISTIC_NUM_SLOTS; i++) |
| { |
| stats->statypid[i] = stats->attrtypid; |
| stats->statyplen[i] = stats->attrtype->typlen; |
| stats->statypbyval[i] = stats->attrtype->typbyval; |
| stats->statypalign[i] = stats->attrtype->typalign; |
| } |
| |
| /* |
| * Call the type-specific typanalyze function. If none is specified, use |
| * std_typanalyze(). |
| */ |
| if (OidIsValid(stats->attrtype->typanalyze)) |
| ok = DatumGetBool(OidFunctionCall1(stats->attrtype->typanalyze, |
| PointerGetDatum(stats))); |
| else |
| ok = std_typanalyze(stats); |
| |
| if (!ok || stats->compute_stats == NULL || stats->minrows <= 0) |
| { |
| heap_freetuple(typtuple); |
| pfree(stats->attr); |
| pfree(stats); |
| return NULL; |
| } |
| |
| return stats; |
| } |
| |
| /* |
| * examine_expression -- pre-analysis of a single expression |
| * |
| * Determine whether the expression is analyzable; if so, create and initialize |
| * a VacAttrStats struct for it. If not, return NULL. |
| */ |
| static VacAttrStats * |
| examine_expression(Node *expr, int stattarget) |
| { |
| HeapTuple typtuple; |
| VacAttrStats *stats; |
| int i; |
| bool ok; |
| |
| Assert(expr != NULL); |
| |
| /* |
| * Create the VacAttrStats struct. |
| */ |
| stats = (VacAttrStats *) palloc0(sizeof(VacAttrStats)); |
| |
| /* |
| * When analyzing an expression, believe the expression tree's type. |
| */ |
| stats->attrtypid = exprType(expr); |
| stats->attrtypmod = exprTypmod(expr); |
| |
| /* |
| * We don't allow collation to be specified in CREATE STATISTICS, so we |
| * have to use the collation specified for the expression. It's possible |
| * to specify the collation in the expression "(col COLLATE "en_US")" in |
| * which case exprCollation() does the right thing. |
| */ |
| stats->attrcollid = exprCollation(expr); |
| |
| /* |
| * We don't have any pg_attribute for expressions, so let's fake something |
| * reasonable into attstattarget, which is the only thing std_typanalyze |
| * needs. |
| */ |
| stats->attr = (Form_pg_attribute) palloc(ATTRIBUTE_FIXED_PART_SIZE); |
| |
| /* |
| * We can't have statistics target specified for the expression, so we |
| * could use either the default_statistics_target, or the target computed |
| * for the extended statistics. The second option seems more reasonable. |
| */ |
| stats->attr->attstattarget = stattarget; |
| |
| /* initialize some basic fields */ |
| stats->attr->attrelid = InvalidOid; |
| stats->attr->attnum = InvalidAttrNumber; |
| stats->attr->atttypid = stats->attrtypid; |
| get_typlenbyvalalign(stats->attr->atttypid, &stats->attr->attlen, &stats->attr->attbyval, &stats->attr->attalign); |
| |
| typtuple = SearchSysCacheCopy1(TYPEOID, |
| ObjectIdGetDatum(stats->attrtypid)); |
| if (!HeapTupleIsValid(typtuple)) |
| elog(ERROR, "cache lookup failed for type %u", stats->attrtypid); |
| |
| stats->attrtype = (Form_pg_type) GETSTRUCT(typtuple); |
| stats->anl_context = CurrentMemoryContext; /* XXX should be using |
| * something else? */ |
| stats->tupattnum = InvalidAttrNumber; |
| |
| /* |
| * The fields describing the stats->stavalues[n] element types default to |
| * the type of the data being analyzed, but the type-specific typanalyze |
| * function can change them if it wants to store something else. |
| */ |
| for (i = 0; i < STATISTIC_NUM_SLOTS; i++) |
| { |
| stats->statypid[i] = stats->attrtypid; |
| stats->statyplen[i] = stats->attrtype->typlen; |
| stats->statypbyval[i] = stats->attrtype->typbyval; |
| stats->statypalign[i] = stats->attrtype->typalign; |
| } |
| |
| /* |
| * Call the type-specific typanalyze function. If none is specified, use |
| * std_typanalyze(). |
| */ |
| if (OidIsValid(stats->attrtype->typanalyze)) |
| ok = DatumGetBool(OidFunctionCall1(stats->attrtype->typanalyze, |
| PointerGetDatum(stats))); |
| else |
| ok = std_typanalyze(stats); |
| |
| if (!ok || stats->compute_stats == NULL || stats->minrows <= 0) |
| { |
| heap_freetuple(typtuple); |
| pfree(stats); |
| return NULL; |
| } |
| |
| return stats; |
| } |
| |
| /* |
| * Using 'vacatts' of size 'nvacatts' as input data, return a newly-built |
| * VacAttrStats array which includes only the items corresponding to |
| * attributes indicated by 'attrs'. If we don't have all of the per-column |
| * stats available to compute the extended stats, then we return NULL to |
| * indicate to the caller that the stats should not be built. |
| */ |
| static VacAttrStats ** |
| lookup_var_attr_stats(Relation rel, Bitmapset *attrs, List *exprs, |
| int nvacatts, VacAttrStats **vacatts) |
| { |
| int i = 0; |
| int x = -1; |
| int natts; |
| VacAttrStats **stats; |
| ListCell *lc; |
| |
| natts = bms_num_members(attrs) + list_length(exprs); |
| |
| stats = (VacAttrStats **) palloc(natts * sizeof(VacAttrStats *)); |
| |
| /* lookup VacAttrStats info for the requested columns (same attnum) */ |
| while ((x = bms_next_member(attrs, x)) >= 0) |
| { |
| int j; |
| |
| stats[i] = NULL; |
| for (j = 0; j < nvacatts; j++) |
| { |
| if (x == vacatts[j]->tupattnum) |
| { |
| stats[i] = vacatts[j]; |
| break; |
| } |
| } |
| |
| if (!stats[i]) |
| { |
| /* |
| * Looks like stats were not gathered for one of the columns |
| * required. We'll be unable to build the extended stats without |
| * this column. |
| */ |
| pfree(stats); |
| return NULL; |
| } |
| |
| /* |
| * Sanity check that the column is not dropped - stats should have |
| * been removed in this case. |
| */ |
| Assert(!stats[i]->attr->attisdropped); |
| |
| i++; |
| } |
| |
| /* also add info for expressions */ |
| foreach(lc, exprs) |
| { |
| Node *expr = (Node *) lfirst(lc); |
| |
| stats[i] = examine_attribute(expr); |
| |
| /* |
| * XXX We need tuple descriptor later, and we just grab it from |
| * stats[0]->tupDesc (see e.g. statext_mcv_build). But as coded |
| * examine_attribute does not set that, so just grab it from the first |
| * vacatts element. |
| */ |
| stats[i]->tupDesc = vacatts[0]->tupDesc; |
| |
| i++; |
| } |
| |
| return stats; |
| } |
| |
| /* |
| * statext_store |
| * Serializes the statistics and stores them into the pg_statistic_ext_data |
| * tuple. |
| */ |
| static void |
| statext_store(Oid statOid, bool inh, |
| MVNDistinct *ndistinct, MVDependencies *dependencies, |
| MCVList *mcv, Datum exprs, VacAttrStats **stats) |
| { |
| Relation pg_stextdata; |
| HeapTuple stup; |
| Datum values[Natts_pg_statistic_ext_data]; |
| bool nulls[Natts_pg_statistic_ext_data]; |
| |
| pg_stextdata = table_open(StatisticExtDataRelationId, RowExclusiveLock); |
| |
| memset(nulls, true, sizeof(nulls)); |
| memset(values, 0, sizeof(values)); |
| |
| /* basic info */ |
| values[Anum_pg_statistic_ext_data_stxoid - 1] = ObjectIdGetDatum(statOid); |
| nulls[Anum_pg_statistic_ext_data_stxoid - 1] = false; |
| |
| values[Anum_pg_statistic_ext_data_stxdinherit - 1] = BoolGetDatum(inh); |
| nulls[Anum_pg_statistic_ext_data_stxdinherit - 1] = false; |
| |
| /* |
| * Construct a new pg_statistic_ext_data tuple, replacing the calculated |
| * stats. |
| */ |
| if (ndistinct != NULL) |
| { |
| bytea *data = statext_ndistinct_serialize(ndistinct); |
| |
| nulls[Anum_pg_statistic_ext_data_stxdndistinct - 1] = (data == NULL); |
| values[Anum_pg_statistic_ext_data_stxdndistinct - 1] = PointerGetDatum(data); |
| } |
| |
| if (dependencies != NULL) |
| { |
| bytea *data = statext_dependencies_serialize(dependencies); |
| |
| nulls[Anum_pg_statistic_ext_data_stxddependencies - 1] = (data == NULL); |
| values[Anum_pg_statistic_ext_data_stxddependencies - 1] = PointerGetDatum(data); |
| } |
| if (mcv != NULL) |
| { |
| bytea *data = statext_mcv_serialize(mcv, stats); |
| |
| nulls[Anum_pg_statistic_ext_data_stxdmcv - 1] = (data == NULL); |
| values[Anum_pg_statistic_ext_data_stxdmcv - 1] = PointerGetDatum(data); |
| } |
| if (exprs != (Datum) 0) |
| { |
| nulls[Anum_pg_statistic_ext_data_stxdexpr - 1] = false; |
| values[Anum_pg_statistic_ext_data_stxdexpr - 1] = exprs; |
| } |
| |
| /* |
| * Delete the old tuple if it exists, and insert a new one. It's easier |
| * than trying to update or insert, based on various conditions. |
| */ |
| RemoveStatisticsDataById(statOid, inh); |
| |
| /* form and insert a new tuple */ |
| stup = heap_form_tuple(RelationGetDescr(pg_stextdata), values, nulls); |
| CatalogTupleInsert(pg_stextdata, stup); |
| |
| heap_freetuple(stup); |
| |
| table_close(pg_stextdata, RowExclusiveLock); |
| } |
| |
| /* initialize multi-dimensional sort */ |
| MultiSortSupport |
| multi_sort_init(int ndims) |
| { |
| MultiSortSupport mss; |
| |
| Assert(ndims >= 2); |
| |
| mss = (MultiSortSupport) palloc0(offsetof(MultiSortSupportData, ssup) |
| + sizeof(SortSupportData) * ndims); |
| |
| mss->ndims = ndims; |
| |
| return mss; |
| } |
| |
| /* |
| * Prepare sort support info using the given sort operator and collation |
| * at the position 'sortdim' |
| */ |
| void |
| multi_sort_add_dimension(MultiSortSupport mss, int sortdim, |
| Oid oper, Oid collation) |
| { |
| SortSupport ssup = &mss->ssup[sortdim]; |
| |
| ssup->ssup_cxt = CurrentMemoryContext; |
| ssup->ssup_collation = collation; |
| ssup->ssup_nulls_first = false; |
| |
| PrepareSortSupportFromOrderingOp(oper, ssup); |
| } |
| |
| /* compare all the dimensions in the selected order */ |
| int |
| multi_sort_compare(const void *a, const void *b, void *arg) |
| { |
| MultiSortSupport mss = (MultiSortSupport) arg; |
| SortItem *ia = (SortItem *) a; |
| SortItem *ib = (SortItem *) b; |
| int i; |
| |
| for (i = 0; i < mss->ndims; i++) |
| { |
| int compare; |
| |
| compare = ApplySortComparator(ia->values[i], ia->isnull[i], |
| ib->values[i], ib->isnull[i], |
| &mss->ssup[i]); |
| |
| if (compare != 0) |
| return compare; |
| } |
| |
| /* equal by default */ |
| return 0; |
| } |
| |
| /* compare selected dimension */ |
| int |
| multi_sort_compare_dim(int dim, const SortItem *a, const SortItem *b, |
| MultiSortSupport mss) |
| { |
| return ApplySortComparator(a->values[dim], a->isnull[dim], |
| b->values[dim], b->isnull[dim], |
| &mss->ssup[dim]); |
| } |
| |
| int |
| multi_sort_compare_dims(int start, int end, |
| const SortItem *a, const SortItem *b, |
| MultiSortSupport mss) |
| { |
| int dim; |
| |
| for (dim = start; dim <= end; dim++) |
| { |
| int r = ApplySortComparator(a->values[dim], a->isnull[dim], |
| b->values[dim], b->isnull[dim], |
| &mss->ssup[dim]); |
| |
| if (r != 0) |
| return r; |
| } |
| |
| return 0; |
| } |
| |
| int |
| compare_scalars_simple(const void *a, const void *b, void *arg) |
| { |
| return compare_datums_simple(*(Datum *) a, |
| *(Datum *) b, |
| (SortSupport) arg); |
| } |
| |
| int |
| compare_datums_simple(Datum a, Datum b, SortSupport ssup) |
| { |
| return ApplySortComparator(a, false, b, false, ssup); |
| } |
| |
| /* |
| * build_attnums_array |
| * Transforms a bitmap into an array of AttrNumber values. |
| * |
| * This is used for extended statistics only, so all the attributes must be |
| * user-defined. That means offsetting by FirstLowInvalidHeapAttributeNumber |
| * is not necessary here (and when querying the bitmap). |
| */ |
| AttrNumber * |
| build_attnums_array(Bitmapset *attrs, int nexprs, int *numattrs) |
| { |
| int i, |
| j; |
| AttrNumber *attnums; |
| int num = bms_num_members(attrs); |
| |
| if (numattrs) |
| *numattrs = num; |
| |
| /* build attnums from the bitmapset */ |
| attnums = (AttrNumber *) palloc(sizeof(AttrNumber) * num); |
| i = 0; |
| j = -1; |
| while ((j = bms_next_member(attrs, j)) >= 0) |
| { |
| int attnum = (j - nexprs); |
| |
| /* |
| * Make sure the bitmap contains only user-defined attributes. As |
| * bitmaps can't contain negative values, this can be violated in two |
| * ways. Firstly, the bitmap might contain 0 as a member, and secondly |
| * the integer value might be larger than MaxAttrNumber. |
| */ |
| Assert(AttributeNumberIsValid(attnum)); |
| Assert(attnum <= MaxAttrNumber); |
| Assert(attnum >= (-nexprs)); |
| |
| attnums[i++] = (AttrNumber) attnum; |
| |
| /* protect against overflows */ |
| Assert(i <= num); |
| } |
| |
| return attnums; |
| } |
| |
| /* |
| * build_sorted_items |
| * build a sorted array of SortItem with values from rows |
| * |
| * Note: All the memory is allocated in a single chunk, so that the caller |
| * can simply pfree the return value to release all of it. |
| */ |
| SortItem * |
| build_sorted_items(StatsBuildData *data, int *nitems, |
| MultiSortSupport mss, |
| int numattrs, AttrNumber *attnums) |
| { |
| int i, |
| j, |
| len, |
| nrows; |
| int nvalues = data->numrows * numattrs; |
| |
| SortItem *items; |
| Datum *values; |
| bool *isnull; |
| char *ptr; |
| int *typlen; |
| |
| /* Compute the total amount of memory we need (both items and values). */ |
| len = data->numrows * sizeof(SortItem) + nvalues * (sizeof(Datum) + sizeof(bool)); |
| |
| /* Allocate the memory and split it into the pieces. */ |
| ptr = palloc0(len); |
| |
| /* items to sort */ |
| items = (SortItem *) ptr; |
| ptr += data->numrows * sizeof(SortItem); |
| |
| /* values and null flags */ |
| values = (Datum *) ptr; |
| ptr += nvalues * sizeof(Datum); |
| |
| isnull = (bool *) ptr; |
| ptr += nvalues * sizeof(bool); |
| |
| /* make sure we consumed the whole buffer exactly */ |
| Assert((ptr - (char *) items) == len); |
| |
| /* fix the pointers to Datum and bool arrays */ |
| nrows = 0; |
| for (i = 0; i < data->numrows; i++) |
| { |
| items[nrows].values = &values[nrows * numattrs]; |
| items[nrows].isnull = &isnull[nrows * numattrs]; |
| |
| nrows++; |
| } |
| |
| /* build a local cache of typlen for all attributes */ |
| typlen = (int *) palloc(sizeof(int) * data->nattnums); |
| for (i = 0; i < data->nattnums; i++) |
| typlen[i] = get_typlen(data->stats[i]->attrtypid); |
| |
| nrows = 0; |
| for (i = 0; i < data->numrows; i++) |
| { |
| bool toowide = false; |
| |
| /* load the values/null flags from sample rows */ |
| for (j = 0; j < numattrs; j++) |
| { |
| Datum value; |
| bool isnull; |
| int attlen; |
| AttrNumber attnum = attnums[j]; |
| |
| int idx; |
| |
| /* match attnum to the pre-calculated data */ |
| for (idx = 0; idx < data->nattnums; idx++) |
| { |
| if (attnum == data->attnums[idx]) |
| break; |
| } |
| |
| Assert(idx < data->nattnums); |
| |
| value = data->values[idx][i]; |
| isnull = data->nulls[idx][i]; |
| attlen = typlen[idx]; |
| |
| /* |
| * If this is a varlena value, check if it's too wide and if yes |
| * then skip the whole item. Otherwise detoast the value. |
| * |
| * XXX It may happen that we've already detoasted some preceding |
| * values for the current item. We don't bother to cleanup those |
| * on the assumption that those are small (below WIDTH_THRESHOLD) |
| * and will be discarded at the end of analyze. |
| */ |
| if ((!isnull) && (attlen == -1)) |
| { |
| if (toast_raw_datum_size(value) > WIDTH_THRESHOLD) |
| { |
| toowide = true; |
| break; |
| } |
| |
| value = PointerGetDatum(PG_DETOAST_DATUM(value)); |
| } |
| |
| items[nrows].values[j] = value; |
| items[nrows].isnull[j] = isnull; |
| } |
| |
| if (toowide) |
| continue; |
| |
| nrows++; |
| } |
| |
| /* store the actual number of items (ignoring the too-wide ones) */ |
| *nitems = nrows; |
| |
| /* all items were too wide */ |
| if (nrows == 0) |
| { |
| /* everything is allocated as a single chunk */ |
| pfree(items); |
| return NULL; |
| } |
| |
| /* do the sort, using the multi-sort */ |
| qsort_interruptible(items, nrows, sizeof(SortItem), |
| multi_sort_compare, mss); |
| |
| return items; |
| } |
| |
| /* |
| * has_stats_of_kind |
| * Check whether the list contains statistic of a given kind |
| */ |
| bool |
| has_stats_of_kind(List *stats, char requiredkind) |
| { |
| ListCell *l; |
| |
| foreach(l, stats) |
| { |
| StatisticExtInfo *stat = (StatisticExtInfo *) lfirst(l); |
| |
| if (stat->kind == requiredkind) |
| return true; |
| } |
| |
| return false; |
| } |
| |
| /* |
| * stat_find_expression |
| * Search for an expression in statistics object's list of expressions. |
| * |
| * Returns the index of the expression in the statistics object's list of |
| * expressions, or -1 if not found. |
| */ |
| static int |
| stat_find_expression(StatisticExtInfo *stat, Node *expr) |
| { |
| ListCell *lc; |
| int idx; |
| |
| idx = 0; |
| foreach(lc, stat->exprs) |
| { |
| Node *stat_expr = (Node *) lfirst(lc); |
| |
| if (equal(stat_expr, expr)) |
| return idx; |
| idx++; |
| } |
| |
| /* Expression not found */ |
| return -1; |
| } |
| |
| /* |
| * stat_covers_expressions |
| * Test whether a statistics object covers all expressions in a list. |
| * |
| * Returns true if all expressions are covered. If expr_idxs is non-NULL, it |
| * is populated with the indexes of the expressions found. |
| */ |
| static bool |
| stat_covers_expressions(StatisticExtInfo *stat, List *exprs, |
| Bitmapset **expr_idxs) |
| { |
| ListCell *lc; |
| |
| foreach(lc, exprs) |
| { |
| Node *expr = (Node *) lfirst(lc); |
| int expr_idx; |
| |
| expr_idx = stat_find_expression(stat, expr); |
| if (expr_idx == -1) |
| return false; |
| |
| if (expr_idxs != NULL) |
| *expr_idxs = bms_add_member(*expr_idxs, expr_idx); |
| } |
| |
| /* If we reach here, all expressions are covered */ |
| return true; |
| } |
| |
| /* |
| * choose_best_statistics |
| * Look for and return statistics with the specified 'requiredkind' which |
| * have keys that match at least two of the given attnums. Return NULL if |
| * there's no match. |
| * |
| * The current selection criteria is very simple - we choose the statistics |
| * object referencing the most attributes in covered (and still unestimated |
| * clauses), breaking ties in favor of objects with fewer keys overall. |
| * |
| * The clause_attnums is an array of bitmaps, storing attnums for individual |
| * clauses. A NULL element means the clause is either incompatible or already |
| * estimated. |
| * |
| * XXX If multiple statistics objects tie on both criteria, then which object |
| * is chosen depends on the order that they appear in the stats list. Perhaps |
| * further tiebreakers are needed. |
| */ |
| StatisticExtInfo * |
| choose_best_statistics(List *stats, char requiredkind, bool inh, |
| Bitmapset **clause_attnums, List **clause_exprs, |
| int nclauses) |
| { |
| ListCell *lc; |
| StatisticExtInfo *best_match = NULL; |
| int best_num_matched = 2; /* goal #1: maximize */ |
| int best_match_keys = (STATS_MAX_DIMENSIONS + 1); /* goal #2: minimize */ |
| |
| foreach(lc, stats) |
| { |
| int i; |
| StatisticExtInfo *info = (StatisticExtInfo *) lfirst(lc); |
| Bitmapset *matched_attnums = NULL; |
| Bitmapset *matched_exprs = NULL; |
| int num_matched; |
| int numkeys; |
| |
| /* skip statistics that are not of the correct type */ |
| if (info->kind != requiredkind) |
| continue; |
| |
| /* skip statistics with mismatching inheritance flag */ |
| if (info->inherit != inh) |
| continue; |
| |
| /* |
| * Collect attributes and expressions in remaining (unestimated) |
| * clauses fully covered by this statistic object. |
| * |
| * We know already estimated clauses have both clause_attnums and |
| * clause_exprs set to NULL. We leave the pointers NULL if already |
| * estimated, or we reset them to NULL after estimating the clause. |
| */ |
| for (i = 0; i < nclauses; i++) |
| { |
| Bitmapset *expr_idxs = NULL; |
| |
| /* ignore incompatible/estimated clauses */ |
| if (!clause_attnums[i] && !clause_exprs[i]) |
| continue; |
| |
| /* ignore clauses that are not covered by this object */ |
| if (!bms_is_subset(clause_attnums[i], info->keys) || |
| !stat_covers_expressions(info, clause_exprs[i], &expr_idxs)) |
| continue; |
| |
| /* record attnums and indexes of expressions covered */ |
| matched_attnums = bms_add_members(matched_attnums, clause_attnums[i]); |
| matched_exprs = bms_add_members(matched_exprs, expr_idxs); |
| } |
| |
| num_matched = bms_num_members(matched_attnums) + bms_num_members(matched_exprs); |
| |
| bms_free(matched_attnums); |
| bms_free(matched_exprs); |
| |
| /* |
| * save the actual number of keys in the stats so that we can choose |
| * the narrowest stats with the most matching keys. |
| */ |
| numkeys = bms_num_members(info->keys) + list_length(info->exprs); |
| |
| /* |
| * Use this object when it increases the number of matched attributes |
| * and expressions or when it matches the same number of attributes |
| * and expressions but these stats have fewer keys than any previous |
| * match. |
| */ |
| if (num_matched > best_num_matched || |
| (num_matched == best_num_matched && numkeys < best_match_keys)) |
| { |
| best_match = info; |
| best_num_matched = num_matched; |
| best_match_keys = numkeys; |
| } |
| } |
| |
| return best_match; |
| } |
| |
| /* |
| * statext_is_compatible_clause_internal |
| * Determines if the clause is compatible with MCV lists. |
| * |
| * To be compatible, the given clause must be a combination of supported |
| * clauses built from Vars or sub-expressions (where a sub-expression is |
| * something that exactly matches an expression found in statistics objects). |
| * This function recursively examines the clause and extracts any |
| * sub-expressions that will need to be matched against statistics. |
| * |
| * Currently, we only support the following types of clauses: |
| * |
| * (a) OpExprs of the form (Var/Expr op Const), or (Const op Var/Expr), where |
| * the op is one of ("=", "<", ">", ">=", "<=") |
| * |
| * (b) (Var/Expr IS [NOT] NULL) |
| * |
| * (c) combinations using AND/OR/NOT |
| * |
| * (d) ScalarArrayOpExprs of the form (Var/Expr op ANY (Const)) or |
| * (Var/Expr op ALL (Const)) |
| * |
| * In the future, the range of supported clauses may be expanded to more |
| * complex cases, for example (Var op Var). |
| * |
| * Arguments: |
| * clause: (sub)clause to be inspected (bare clause, not a RestrictInfo) |
| * relid: rel that all Vars in clause must belong to |
| * *attnums: input/output parameter collecting attribute numbers of all |
| * mentioned Vars. Note that we do not offset the attribute numbers, |
| * so we can't cope with system columns. |
| * *exprs: input/output parameter collecting primitive subclauses within |
| * the clause tree |
| * |
| * Returns false if there is something we definitively can't handle. |
| * On true return, we can proceed to match the *exprs against statistics. |
| */ |
| static bool |
| statext_is_compatible_clause_internal(PlannerInfo *root, Node *clause, |
| Index relid, Bitmapset **attnums, |
| List **exprs) |
| { |
| /* Look inside any binary-compatible relabeling (as in examine_variable) */ |
| if (IsA(clause, RelabelType)) |
| clause = (Node *) ((RelabelType *) clause)->arg; |
| |
| /* plain Var references (boolean Vars or recursive checks) */ |
| if (IsA(clause, Var)) |
| { |
| Var *var = (Var *) clause; |
| |
| /* Ensure var is from the correct relation */ |
| if (var->varno != relid) |
| return false; |
| |
| /* we also better ensure the Var is from the current level */ |
| if (var->varlevelsup > 0) |
| return false; |
| |
| /* |
| * Also reject system attributes and whole-row Vars (we don't allow |
| * stats on those). |
| */ |
| if (!AttrNumberIsForUserDefinedAttr(var->varattno)) |
| return false; |
| |
| /* OK, record the attnum for later permissions checks. */ |
| *attnums = bms_add_member(*attnums, var->varattno); |
| |
| return true; |
| } |
| |
| /* (Var/Expr op Const) or (Const op Var/Expr) */ |
| if (is_opclause(clause)) |
| { |
| RangeTblEntry *rte = root->simple_rte_array[relid]; |
| OpExpr *expr = (OpExpr *) clause; |
| Node *clause_expr; |
| |
| /* Only expressions with two arguments are considered compatible. */ |
| if (list_length(expr->args) != 2) |
| return false; |
| |
| /* Check if the expression has the right shape */ |
| if (!examine_opclause_args(expr->args, &clause_expr, NULL, NULL)) |
| return false; |
| |
| /* |
| * If it's not one of the supported operators ("=", "<", ">", etc.), |
| * just ignore the clause, as it's not compatible with MCV lists. |
| * |
| * This uses the function for estimating selectivity, not the operator |
| * directly (a bit awkward, but well ...). |
| */ |
| switch (get_oprrest(expr->opno)) |
| { |
| case F_EQSEL: |
| case F_NEQSEL: |
| case F_SCALARLTSEL: |
| case F_SCALARLESEL: |
| case F_SCALARGTSEL: |
| case F_SCALARGESEL: |
| /* supported, will continue with inspection of the Var/Expr */ |
| break; |
| |
| default: |
| /* other estimators are considered unknown/unsupported */ |
| return false; |
| } |
| |
| /* |
| * If there are any securityQuals on the RTE from security barrier |
| * views or RLS policies, then the user may not have access to all the |
| * table's data, and we must check that the operator is leak-proof. |
| * |
| * If the operator is leaky, then we must ignore this clause for the |
| * purposes of estimating with MCV lists, otherwise the operator might |
| * reveal values from the MCV list that the user doesn't have |
| * permission to see. |
| */ |
| if (rte->securityQuals != NIL && |
| !get_func_leakproof(get_opcode(expr->opno))) |
| return false; |
| |
| /* Check (Var op Const) or (Const op Var) clauses by recursing. */ |
| if (IsA(clause_expr, Var)) |
| return statext_is_compatible_clause_internal(root, clause_expr, |
| relid, attnums, exprs); |
| |
| /* Otherwise we have (Expr op Const) or (Const op Expr). */ |
| *exprs = lappend(*exprs, clause_expr); |
| return true; |
| } |
| |
| /* Var/Expr IN Array */ |
| if (IsA(clause, ScalarArrayOpExpr)) |
| { |
| RangeTblEntry *rte = root->simple_rte_array[relid]; |
| ScalarArrayOpExpr *expr = (ScalarArrayOpExpr *) clause; |
| Node *clause_expr; |
| bool expronleft; |
| |
| /* Only expressions with two arguments are considered compatible. */ |
| if (list_length(expr->args) != 2) |
| return false; |
| |
| /* Check if the expression has the right shape (one Var, one Const) */ |
| if (!examine_opclause_args(expr->args, &clause_expr, NULL, &expronleft)) |
| return false; |
| |
| /* We only support Var on left, Const on right */ |
| if (!expronleft) |
| return false; |
| |
| /* |
| * If it's not one of the supported operators ("=", "<", ">", etc.), |
| * just ignore the clause, as it's not compatible with MCV lists. |
| * |
| * This uses the function for estimating selectivity, not the operator |
| * directly (a bit awkward, but well ...). |
| */ |
| switch (get_oprrest(expr->opno)) |
| { |
| case F_EQSEL: |
| case F_NEQSEL: |
| case F_SCALARLTSEL: |
| case F_SCALARLESEL: |
| case F_SCALARGTSEL: |
| case F_SCALARGESEL: |
| /* supported, will continue with inspection of the Var/Expr */ |
| break; |
| |
| default: |
| /* other estimators are considered unknown/unsupported */ |
| return false; |
| } |
| |
| /* |
| * If there are any securityQuals on the RTE from security barrier |
| * views or RLS policies, then the user may not have access to all the |
| * table's data, and we must check that the operator is leak-proof. |
| * |
| * If the operator is leaky, then we must ignore this clause for the |
| * purposes of estimating with MCV lists, otherwise the operator might |
| * reveal values from the MCV list that the user doesn't have |
| * permission to see. |
| */ |
| if (rte->securityQuals != NIL && |
| !get_func_leakproof(get_opcode(expr->opno))) |
| return false; |
| |
| /* Check Var IN Array clauses by recursing. */ |
| if (IsA(clause_expr, Var)) |
| return statext_is_compatible_clause_internal(root, clause_expr, |
| relid, attnums, exprs); |
| |
| /* Otherwise we have Expr IN Array. */ |
| *exprs = lappend(*exprs, clause_expr); |
| return true; |
| } |
| |
| /* AND/OR/NOT clause */ |
| if (is_andclause(clause) || |
| is_orclause(clause) || |
| is_notclause(clause)) |
| { |
| /* |
| * AND/OR/NOT-clauses are supported if all sub-clauses are supported |
| * |
| * Perhaps we could improve this by handling mixed cases, when some of |
| * the clauses are supported and some are not. Selectivity for the |
| * supported subclauses would be computed using extended statistics, |
| * and the remaining clauses would be estimated using the traditional |
| * algorithm (product of selectivities). |
| * |
| * It however seems overly complex, and in a way we already do that |
| * because if we reject the whole clause as unsupported here, it will |
| * be eventually passed to clauselist_selectivity() which does exactly |
| * this (split into supported/unsupported clauses etc). |
| */ |
| BoolExpr *expr = (BoolExpr *) clause; |
| ListCell *lc; |
| |
| foreach(lc, expr->args) |
| { |
| /* |
| * If we find an incompatible clause in the arguments, treat the |
| * whole clause as incompatible. |
| */ |
| if (!statext_is_compatible_clause_internal(root, |
| (Node *) lfirst(lc), |
| relid, attnums, exprs)) |
| return false; |
| } |
| |
| return true; |
| } |
| |
| /* Var/Expr IS NULL */ |
| if (IsA(clause, NullTest)) |
| { |
| NullTest *nt = (NullTest *) clause; |
| |
| /* Check Var IS NULL clauses by recursing. */ |
| if (IsA(nt->arg, Var)) |
| return statext_is_compatible_clause_internal(root, (Node *) (nt->arg), |
| relid, attnums, exprs); |
| |
| /* Otherwise we have Expr IS NULL. */ |
| *exprs = lappend(*exprs, nt->arg); |
| return true; |
| } |
| |
| /* |
| * Treat any other expressions as bare expressions to be matched against |
| * expressions in statistics objects. |
| */ |
| *exprs = lappend(*exprs, clause); |
| return true; |
| } |
| |
| /* |
| * statext_is_compatible_clause |
| * Determines if the clause is compatible with MCV lists. |
| * |
| * See statext_is_compatible_clause_internal, above, for the basic rules. |
| * This layer deals with RestrictInfo superstructure and applies permissions |
| * checks to verify that it's okay to examine all mentioned Vars. |
| * |
| * Arguments: |
| * clause: clause to be inspected (in RestrictInfo form) |
| * relid: rel that all Vars in clause must belong to |
| * *attnums: input/output parameter collecting attribute numbers of all |
| * mentioned Vars. Note that we do not offset the attribute numbers, |
| * so we can't cope with system columns. |
| * *exprs: input/output parameter collecting primitive subclauses within |
| * the clause tree |
| * |
| * Returns false if there is something we definitively can't handle. |
| * On true return, we can proceed to match the *exprs against statistics. |
| */ |
| static bool |
| statext_is_compatible_clause(PlannerInfo *root, Node *clause, Index relid, |
| Bitmapset **attnums, List **exprs) |
| { |
| RangeTblEntry *rte = root->simple_rte_array[relid]; |
| RelOptInfo *rel = root->simple_rel_array[relid]; |
| RestrictInfo *rinfo; |
| int clause_relid; |
| Oid userid; |
| |
| /* |
| * Special-case handling for bare BoolExpr AND clauses, because the |
| * restrictinfo machinery doesn't build RestrictInfos on top of AND |
| * clauses. |
| */ |
| if (is_andclause(clause)) |
| { |
| BoolExpr *expr = (BoolExpr *) clause; |
| ListCell *lc; |
| |
| /* |
| * Check that each sub-clause is compatible. We expect these to be |
| * RestrictInfos. |
| */ |
| foreach(lc, expr->args) |
| { |
| if (!statext_is_compatible_clause(root, (Node *) lfirst(lc), |
| relid, attnums, exprs)) |
| return false; |
| } |
| |
| return true; |
| } |
| |
| /* Otherwise it must be a RestrictInfo. */ |
| if (!IsA(clause, RestrictInfo)) |
| return false; |
| rinfo = (RestrictInfo *) clause; |
| |
| /* Pseudoconstants are not really interesting here. */ |
| if (rinfo->pseudoconstant) |
| return false; |
| |
| /* Clauses referencing other varnos are incompatible. */ |
| if (!bms_get_singleton_member(rinfo->clause_relids, &clause_relid) || |
| clause_relid != relid) |
| return false; |
| |
| /* Check the clause and determine what attributes it references. */ |
| if (!statext_is_compatible_clause_internal(root, (Node *) rinfo->clause, |
| relid, attnums, exprs)) |
| return false; |
| |
| /* |
| * Check that the user has permission to read all required attributes. |
| */ |
| userid = OidIsValid(rel->userid) ? rel->userid : GetUserId(); |
| |
| /* Table-level SELECT privilege is sufficient for all columns */ |
| if (pg_class_aclcheck(rte->relid, userid, ACL_SELECT) != ACLCHECK_OK) |
| { |
| Bitmapset *clause_attnums = NULL; |
| int attnum = -1; |
| |
| /* |
| * We have to check per-column privileges. *attnums has the attnums |
| * for individual Vars we saw, but there may also be Vars within |
| * subexpressions in *exprs. We can use pull_varattnos() to extract |
| * those, but there's an impedance mismatch: attnums returned by |
| * pull_varattnos() are offset by FirstLowInvalidHeapAttributeNumber, |
| * while attnums within *attnums aren't. Convert *attnums to the |
| * offset style so we can combine the results. |
| */ |
| while ((attnum = bms_next_member(*attnums, attnum)) >= 0) |
| { |
| clause_attnums = |
| bms_add_member(clause_attnums, |
| attnum - FirstLowInvalidHeapAttributeNumber); |
| } |
| |
| /* Now merge attnums from *exprs into clause_attnums */ |
| if (*exprs != NIL) |
| pull_varattnos((Node *) *exprs, relid, &clause_attnums); |
| |
| attnum = -1; |
| while ((attnum = bms_next_member(clause_attnums, attnum)) >= 0) |
| { |
| /* Undo the offset */ |
| AttrNumber attno = attnum + FirstLowInvalidHeapAttributeNumber; |
| |
| if (attno == InvalidAttrNumber) |
| { |
| /* Whole-row reference, so must have access to all columns */ |
| if (pg_attribute_aclcheck_all(rte->relid, userid, ACL_SELECT, |
| ACLMASK_ALL) != ACLCHECK_OK) |
| return false; |
| } |
| else |
| { |
| if (pg_attribute_aclcheck(rte->relid, attno, userid, |
| ACL_SELECT) != ACLCHECK_OK) |
| return false; |
| } |
| } |
| } |
| |
| /* If we reach here, the clause is OK */ |
| return true; |
| } |
| |
| /* |
| * statext_mcv_clauselist_selectivity |
| * Estimate clauses using the best multi-column statistics. |
| * |
| * Applies available extended (multi-column) statistics on a table. There may |
| * be multiple applicable statistics (with respect to the clauses), in which |
| * case we use greedy approach. In each round we select the best statistic on |
| * a table (measured by the number of attributes extracted from the clauses |
| * and covered by it), and compute the selectivity for the supplied clauses. |
| * We repeat this process with the remaining clauses (if any), until none of |
| * the available statistics can be used. |
| * |
| * One of the main challenges with using MCV lists is how to extrapolate the |
| * estimate to the data not covered by the MCV list. To do that, we compute |
| * not only the "MCV selectivity" (selectivities for MCV items matching the |
| * supplied clauses), but also the following related selectivities: |
| * |
| * - simple selectivity: Computed without extended statistics, i.e. as if the |
| * columns/clauses were independent. |
| * |
| * - base selectivity: Similar to simple selectivity, but is computed using |
| * the extended statistic by adding up the base frequencies (that we compute |
| * and store for each MCV item) of matching MCV items. |
| * |
| * - total selectivity: Selectivity covered by the whole MCV list. |
| * |
| * These are passed to mcv_combine_selectivities() which combines them to |
| * produce a selectivity estimate that makes use of both per-column statistics |
| * and the multi-column MCV statistics. |
| * |
| * 'estimatedclauses' is an input/output parameter. We set bits for the |
| * 0-based 'clauses' indexes we estimate for and also skip clause items that |
| * already have a bit set. |
| */ |
| static Selectivity |
| statext_mcv_clauselist_selectivity(PlannerInfo *root, List *clauses, int varRelid, |
| JoinType jointype, SpecialJoinInfo *sjinfo, |
| RelOptInfo *rel, Bitmapset **estimatedclauses, |
| bool is_or) |
| { |
| ListCell *l; |
| Bitmapset **list_attnums; /* attnums extracted from the clause */ |
| List **list_exprs; /* expressions matched to any statistic */ |
| int listidx; |
| Selectivity sel = (is_or) ? 0.0 : 1.0; |
| RangeTblEntry *rte = planner_rt_fetch(rel->relid, root); |
| |
| /* check if there's any stats that might be useful for us. */ |
| if (!has_stats_of_kind(rel->statlist, STATS_EXT_MCV)) |
| return sel; |
| |
| list_attnums = (Bitmapset **) palloc(sizeof(Bitmapset *) * |
| list_length(clauses)); |
| |
| /* expressions extracted from complex expressions */ |
| list_exprs = (List **) palloc(sizeof(Node *) * list_length(clauses)); |
| |
| /* |
| * Pre-process the clauses list to extract the attnums and expressions |
| * seen in each item. We need to determine if there are any clauses which |
| * will be useful for selectivity estimations with extended stats. Along |
| * the way we'll record all of the attnums and expressions for each clause |
| * in lists which we'll reference later so we don't need to repeat the |
| * same work again. |
| * |
| * We also skip clauses that we already estimated using different types of |
| * statistics (we treat them as incompatible). |
| */ |
| listidx = 0; |
| foreach(l, clauses) |
| { |
| Node *clause = (Node *) lfirst(l); |
| Bitmapset *attnums = NULL; |
| List *exprs = NIL; |
| |
| if (!bms_is_member(listidx, *estimatedclauses) && |
| statext_is_compatible_clause(root, clause, rel->relid, &attnums, &exprs)) |
| { |
| list_attnums[listidx] = attnums; |
| list_exprs[listidx] = exprs; |
| } |
| else |
| { |
| list_attnums[listidx] = NULL; |
| list_exprs[listidx] = NIL; |
| } |
| |
| listidx++; |
| } |
| |
| /* apply as many extended statistics as possible */ |
| while (true) |
| { |
| StatisticExtInfo *stat; |
| List *stat_clauses; |
| Bitmapset *simple_clauses; |
| |
| /* find the best suited statistics object for these attnums */ |
| stat = choose_best_statistics(rel->statlist, STATS_EXT_MCV, rte->inh, |
| list_attnums, list_exprs, |
| list_length(clauses)); |
| |
| /* |
| * if no (additional) matching stats could be found then we've nothing |
| * to do |
| */ |
| if (!stat) |
| break; |
| |
| /* Ensure choose_best_statistics produced an expected stats type. */ |
| Assert(stat->kind == STATS_EXT_MCV); |
| |
| /* now filter the clauses to be estimated using the selected MCV */ |
| stat_clauses = NIL; |
| |
| /* record which clauses are simple (single column or expression) */ |
| simple_clauses = NULL; |
| |
| listidx = -1; |
| foreach(l, clauses) |
| { |
| /* Increment the index before we decide if to skip the clause. */ |
| listidx++; |
| |
| /* |
| * Ignore clauses from which we did not extract any attnums or |
| * expressions (this needs to be consistent with what we do in |
| * choose_best_statistics). |
| * |
| * This also eliminates already estimated clauses - both those |
| * estimated before and during applying extended statistics. |
| * |
| * XXX This check is needed because both bms_is_subset and |
| * stat_covers_expressions return true for empty attnums and |
| * expressions. |
| */ |
| if (!list_attnums[listidx] && !list_exprs[listidx]) |
| continue; |
| |
| /* |
| * The clause was not estimated yet, and we've extracted either |
| * attnums or expressions from it. Ignore it if it's not fully |
| * covered by the chosen statistics object. |
| * |
| * We need to check both attributes and expressions, and reject if |
| * either is not covered. |
| */ |
| if (!bms_is_subset(list_attnums[listidx], stat->keys) || |
| !stat_covers_expressions(stat, list_exprs[listidx], NULL)) |
| continue; |
| |
| /* |
| * Now we know the clause is compatible (we have either attnums or |
| * expressions extracted from it), and was not estimated yet. |
| */ |
| |
| /* record simple clauses (single column or expression) */ |
| if ((list_attnums[listidx] == NULL && |
| list_length(list_exprs[listidx]) == 1) || |
| (list_exprs[listidx] == NIL && |
| bms_membership(list_attnums[listidx]) == BMS_SINGLETON)) |
| simple_clauses = bms_add_member(simple_clauses, |
| list_length(stat_clauses)); |
| |
| /* add clause to list and mark it as estimated */ |
| stat_clauses = lappend(stat_clauses, (Node *) lfirst(l)); |
| *estimatedclauses = bms_add_member(*estimatedclauses, listidx); |
| |
| /* |
| * Reset the pointers, so that choose_best_statistics knows this |
| * clause was estimated and does not consider it again. |
| */ |
| bms_free(list_attnums[listidx]); |
| list_attnums[listidx] = NULL; |
| |
| list_free(list_exprs[listidx]); |
| list_exprs[listidx] = NULL; |
| } |
| |
| if (is_or) |
| { |
| bool *or_matches = NULL; |
| Selectivity simple_or_sel = 0.0, |
| stat_sel = 0.0; |
| MCVList *mcv_list; |
| |
| /* Load the MCV list stored in the statistics object */ |
| mcv_list = statext_mcv_load(stat->statOid, rte->inh); |
| |
| /* |
| * Compute the selectivity of the ORed list of clauses covered by |
| * this statistics object by estimating each in turn and combining |
| * them using the formula P(A OR B) = P(A) + P(B) - P(A AND B). |
| * This allows us to use the multivariate MCV stats to better |
| * estimate the individual terms and their overlap. |
| * |
| * Each time we iterate this formula, the clause "A" above is |
| * equal to all the clauses processed so far, combined with "OR". |
| */ |
| listidx = 0; |
| foreach(l, stat_clauses) |
| { |
| Node *clause = (Node *) lfirst(l); |
| Selectivity simple_sel, |
| overlap_simple_sel, |
| mcv_sel, |
| mcv_basesel, |
| overlap_mcvsel, |
| overlap_basesel, |
| mcv_totalsel, |
| clause_sel, |
| overlap_sel; |
| |
| /* |
| * "Simple" selectivity of the next clause and its overlap |
| * with any of the previous clauses. These are our initial |
| * estimates of P(B) and P(A AND B), assuming independence of |
| * columns/clauses. |
| */ |
| simple_sel = clause_selectivity_ext(root, clause, varRelid, |
| jointype, sjinfo, false, false); |
| |
| overlap_simple_sel = simple_or_sel * simple_sel; |
| |
| /* |
| * New "simple" selectivity of all clauses seen so far, |
| * assuming independence. |
| */ |
| simple_or_sel += simple_sel - overlap_simple_sel; |
| CLAMP_PROBABILITY(simple_or_sel); |
| |
| /* |
| * Multi-column estimate of this clause using MCV statistics, |
| * along with base and total selectivities, and corresponding |
| * selectivities for the overlap term P(A AND B). |
| */ |
| mcv_sel = mcv_clause_selectivity_or(root, stat, mcv_list, |
| clause, &or_matches, |
| &mcv_basesel, |
| &overlap_mcvsel, |
| &overlap_basesel, |
| &mcv_totalsel); |
| |
| /* |
| * Combine the simple and multi-column estimates. |
| * |
| * If this clause is a simple single-column clause, then we |
| * just use the simple selectivity estimate for it, since the |
| * multi-column statistics are unlikely to improve on that |
| * (and in fact could make it worse). For the overlap, we |
| * always make use of the multi-column statistics. |
| */ |
| if (bms_is_member(listidx, simple_clauses)) |
| clause_sel = simple_sel; |
| else |
| clause_sel = mcv_combine_selectivities(simple_sel, |
| mcv_sel, |
| mcv_basesel, |
| mcv_totalsel); |
| |
| overlap_sel = mcv_combine_selectivities(overlap_simple_sel, |
| overlap_mcvsel, |
| overlap_basesel, |
| mcv_totalsel); |
| |
| /* Factor these into the result for this statistics object */ |
| stat_sel += clause_sel - overlap_sel; |
| CLAMP_PROBABILITY(stat_sel); |
| |
| listidx++; |
| } |
| |
| /* |
| * Factor the result for this statistics object into the overall |
| * result. We treat the results from each separate statistics |
| * object as independent of one another. |
| */ |
| sel = sel + stat_sel - sel * stat_sel; |
| } |
| else /* Implicitly-ANDed list of clauses */ |
| { |
| Selectivity simple_sel, |
| mcv_sel, |
| mcv_basesel, |
| mcv_totalsel, |
| stat_sel; |
| |
| /* |
| * "Simple" selectivity, i.e. without any extended statistics, |
| * essentially assuming independence of the columns/clauses. |
| */ |
| simple_sel = clauselist_selectivity_ext(root, stat_clauses, |
| varRelid, jointype, |
| sjinfo, false, false); |
| |
| /* |
| * Multi-column estimate using MCV statistics, along with base and |
| * total selectivities. |
| */ |
| mcv_sel = mcv_clauselist_selectivity(root, stat, stat_clauses, |
| varRelid, jointype, sjinfo, |
| rel, &mcv_basesel, |
| &mcv_totalsel); |
| |
| /* Combine the simple and multi-column estimates. */ |
| stat_sel = mcv_combine_selectivities(simple_sel, |
| mcv_sel, |
| mcv_basesel, |
| mcv_totalsel); |
| |
| /* Factor this into the overall result */ |
| sel *= stat_sel; |
| } |
| } |
| |
| return sel; |
| } |
| |
| /* |
| * statext_clauselist_selectivity |
| * Estimate clauses using the best multi-column statistics. |
| */ |
| Selectivity |
| statext_clauselist_selectivity(PlannerInfo *root, List *clauses, int varRelid, |
| JoinType jointype, SpecialJoinInfo *sjinfo, |
| RelOptInfo *rel, Bitmapset **estimatedclauses, |
| bool is_or) |
| { |
| Selectivity sel; |
| |
| /* First, try estimating clauses using a multivariate MCV list. */ |
| sel = statext_mcv_clauselist_selectivity(root, clauses, varRelid, jointype, |
| sjinfo, rel, estimatedclauses, is_or); |
| |
| /* |
| * Functional dependencies only work for clauses connected by AND, so for |
| * OR clauses we're done. |
| */ |
| if (is_or) |
| return sel; |
| |
| /* |
| * Then, apply functional dependencies on the remaining clauses by calling |
| * dependencies_clauselist_selectivity. Pass 'estimatedclauses' so the |
| * function can properly skip clauses already estimated above. |
| * |
| * The reasoning for applying dependencies last is that the more complex |
| * stats can track more complex correlations between the attributes, and |
| * so may be considered more reliable. |
| * |
| * For example, MCV list can give us an exact selectivity for values in |
| * two columns, while functional dependencies can only provide information |
| * about the overall strength of the dependency. |
| */ |
| sel *= dependencies_clauselist_selectivity(root, clauses, varRelid, |
| jointype, sjinfo, rel, |
| estimatedclauses); |
| |
| return sel; |
| } |
| |
| /* |
| * examine_opclause_args |
| * Split an operator expression's arguments into Expr and Const parts. |
| * |
| * Attempts to match the arguments to either (Expr op Const) or (Const op |
| * Expr), possibly with a RelabelType on top. When the expression matches this |
| * form, returns true, otherwise returns false. |
| * |
| * Optionally returns pointers to the extracted Expr/Const nodes, when passed |
| * non-null pointers (exprp, cstp and expronleftp). The expronleftp flag |
| * specifies on which side of the operator we found the expression node. |
| */ |
| bool |
| examine_opclause_args(List *args, Node **exprp, Const **cstp, |
| bool *expronleftp) |
| { |
| Node *expr; |
| Const *cst; |
| bool expronleft; |
| Node *leftop, |
| *rightop; |
| |
| /* enforced by statext_is_compatible_clause_internal */ |
| Assert(list_length(args) == 2); |
| |
| leftop = linitial(args); |
| rightop = lsecond(args); |
| |
| /* strip RelabelType from either side of the expression */ |
| if (IsA(leftop, RelabelType)) |
| leftop = (Node *) ((RelabelType *) leftop)->arg; |
| |
| if (IsA(rightop, RelabelType)) |
| rightop = (Node *) ((RelabelType *) rightop)->arg; |
| |
| if (IsA(rightop, Const)) |
| { |
| expr = (Node *) leftop; |
| cst = (Const *) rightop; |
| expronleft = true; |
| } |
| else if (IsA(leftop, Const)) |
| { |
| expr = (Node *) rightop; |
| cst = (Const *) leftop; |
| expronleft = false; |
| } |
| else |
| return false; |
| |
| /* return pointers to the extracted parts if requested */ |
| if (exprp) |
| *exprp = expr; |
| |
| if (cstp) |
| *cstp = cst; |
| |
| if (expronleftp) |
| *expronleftp = expronleft; |
| |
| return true; |
| } |
| |
| |
| /* |
| * Compute statistics about expressions of a relation. |
| */ |
| static void |
| compute_expr_stats(Relation onerel, double totalrows, |
| AnlExprData *exprdata, int nexprs, |
| HeapTuple *rows, int numrows) |
| { |
| MemoryContext expr_context, |
| old_context; |
| int ind, |
| i; |
| |
| expr_context = AllocSetContextCreate(CurrentMemoryContext, |
| "Analyze Expression", |
| ALLOCSET_DEFAULT_SIZES); |
| old_context = MemoryContextSwitchTo(expr_context); |
| |
| for (ind = 0; ind < nexprs; ind++) |
| { |
| AnlExprData *thisdata = &exprdata[ind]; |
| VacAttrStats *stats = thisdata->vacattrstat; |
| Node *expr = thisdata->expr; |
| TupleTableSlot *slot; |
| EState *estate; |
| ExprContext *econtext; |
| Datum *exprvals; |
| bool *exprnulls; |
| ExprState *exprstate; |
| int tcnt; |
| |
| /* Are we still in the main context? */ |
| Assert(CurrentMemoryContext == expr_context); |
| |
| /* |
| * Need an EState for evaluation of expressions. Create it in the |
| * per-expression context to be sure it gets cleaned up at the bottom |
| * of the loop. |
| */ |
| estate = CreateExecutorState(); |
| econtext = GetPerTupleExprContext(estate); |
| |
| /* Set up expression evaluation state */ |
| exprstate = ExecPrepareExpr((Expr *) expr, estate); |
| |
| /* Need a slot to hold the current heap tuple, too */ |
| slot = MakeSingleTupleTableSlot(RelationGetDescr(onerel), |
| &TTSOpsHeapTuple); |
| |
| /* Arrange for econtext's scan tuple to be the tuple under test */ |
| econtext->ecxt_scantuple = slot; |
| |
| /* Compute and save expression values */ |
| exprvals = (Datum *) palloc(numrows * sizeof(Datum)); |
| exprnulls = (bool *) palloc(numrows * sizeof(bool)); |
| |
| tcnt = 0; |
| for (i = 0; i < numrows; i++) |
| { |
| Datum datum; |
| bool isnull; |
| |
| /* |
| * Reset the per-tuple context each time, to reclaim any cruft |
| * left behind by evaluating the statistics expressions. |
| */ |
| ResetExprContext(econtext); |
| |
| /* Set up for expression evaluation */ |
| ExecStoreHeapTuple(rows[i], slot, false); |
| |
| /* |
| * Evaluate the expression. We do this in the per-tuple context so |
| * as not to leak memory, and then copy the result into the |
| * context created at the beginning of this function. |
| */ |
| datum = ExecEvalExprSwitchContext(exprstate, |
| GetPerTupleExprContext(estate), |
| &isnull); |
| if (isnull) |
| { |
| exprvals[tcnt] = (Datum) 0; |
| exprnulls[tcnt] = true; |
| } |
| else |
| { |
| /* Make sure we copy the data into the context. */ |
| Assert(CurrentMemoryContext == expr_context); |
| |
| exprvals[tcnt] = datumCopy(datum, |
| stats->attrtype->typbyval, |
| stats->attrtype->typlen); |
| exprnulls[tcnt] = false; |
| } |
| |
| tcnt++; |
| } |
| |
| /* |
| * Now we can compute the statistics for the expression columns. |
| * |
| * XXX Unlike compute_index_stats we don't need to switch and reset |
| * memory contexts here, because we're only computing stats for a |
| * single expression (and not iterating over many indexes), so we just |
| * do it in expr_context. Note that compute_stats copies the result |
| * into stats->anl_context, so it does not disappear. |
| */ |
| if (tcnt > 0) |
| { |
| AttributeOpts *aopt = |
| get_attribute_options(stats->attr->attrelid, |
| stats->attr->attnum); |
| |
| stats->exprvals = exprvals; |
| stats->exprnulls = exprnulls; |
| stats->rowstride = 1; |
| stats->compute_stats(stats, |
| expr_fetch_func, |
| tcnt, |
| tcnt); |
| |
| /* |
| * If the n_distinct option is specified, it overrides the above |
| * computation. |
| */ |
| if (aopt != NULL && aopt->n_distinct != 0.0) |
| stats->stadistinct = aopt->n_distinct; |
| } |
| |
| /* And clean up */ |
| MemoryContextSwitchTo(expr_context); |
| |
| ExecDropSingleTupleTableSlot(slot); |
| FreeExecutorState(estate); |
| MemoryContextResetAndDeleteChildren(expr_context); |
| } |
| |
| MemoryContextSwitchTo(old_context); |
| MemoryContextDelete(expr_context); |
| } |
| |
| |
| /* |
| * Fetch function for analyzing statistics object expressions. |
| * |
| * We have not bothered to construct tuples from the data, instead the data |
| * is just in Datum arrays. |
| */ |
| static Datum |
| expr_fetch_func(VacAttrStatsP stats, int rownum, bool *isNull) |
| { |
| int i; |
| |
| /* exprvals and exprnulls are already offset for proper column */ |
| i = rownum * stats->rowstride; |
| *isNull = stats->exprnulls[i]; |
| return stats->exprvals[i]; |
| } |
| |
| /* |
| * Build analyze data for a list of expressions. As this is not tied |
| * directly to a relation (table or index), we have to fake some of |
| * the fields in examine_expression(). |
| */ |
| static AnlExprData * |
| build_expr_data(List *exprs, int stattarget) |
| { |
| int idx; |
| int nexprs = list_length(exprs); |
| AnlExprData *exprdata; |
| ListCell *lc; |
| |
| exprdata = (AnlExprData *) palloc0(nexprs * sizeof(AnlExprData)); |
| |
| idx = 0; |
| foreach(lc, exprs) |
| { |
| Node *expr = (Node *) lfirst(lc); |
| AnlExprData *thisdata = &exprdata[idx]; |
| |
| thisdata->expr = expr; |
| thisdata->vacattrstat = examine_expression(expr, stattarget); |
| idx++; |
| } |
| |
| return exprdata; |
| } |
| |
| /* form an array of pg_statistic rows (per update_attstats) */ |
| static Datum |
| serialize_expr_stats(AnlExprData *exprdata, int nexprs) |
| { |
| int exprno; |
| Oid typOid; |
| Relation sd; |
| |
| ArrayBuildState *astate = NULL; |
| |
| sd = table_open(StatisticRelationId, RowExclusiveLock); |
| |
| /* lookup OID of composite type for pg_statistic */ |
| typOid = get_rel_type_id(StatisticRelationId); |
| if (!OidIsValid(typOid)) |
| ereport(ERROR, |
| (errcode(ERRCODE_WRONG_OBJECT_TYPE), |
| errmsg("relation \"%s\" does not have a composite type", |
| "pg_statistic"))); |
| |
| for (exprno = 0; exprno < nexprs; exprno++) |
| { |
| int i, |
| k; |
| VacAttrStats *stats = exprdata[exprno].vacattrstat; |
| |
| Datum values[Natts_pg_statistic]; |
| bool nulls[Natts_pg_statistic]; |
| HeapTuple stup; |
| |
| if (!stats->stats_valid) |
| { |
| astate = accumArrayResult(astate, |
| (Datum) 0, |
| true, |
| typOid, |
| CurrentMemoryContext); |
| continue; |
| } |
| |
| /* |
| * Construct a new pg_statistic tuple |
| */ |
| for (i = 0; i < Natts_pg_statistic; ++i) |
| { |
| nulls[i] = false; |
| } |
| |
| values[Anum_pg_statistic_starelid - 1] = ObjectIdGetDatum(InvalidOid); |
| values[Anum_pg_statistic_staattnum - 1] = Int16GetDatum(InvalidAttrNumber); |
| values[Anum_pg_statistic_stainherit - 1] = BoolGetDatum(false); |
| values[Anum_pg_statistic_stanullfrac - 1] = Float4GetDatum(stats->stanullfrac); |
| values[Anum_pg_statistic_stawidth - 1] = Int32GetDatum(stats->stawidth); |
| values[Anum_pg_statistic_stadistinct - 1] = Float4GetDatum(stats->stadistinct); |
| i = Anum_pg_statistic_stakind1 - 1; |
| for (k = 0; k < STATISTIC_NUM_SLOTS; k++) |
| { |
| values[i++] = Int16GetDatum(stats->stakind[k]); /* stakindN */ |
| } |
| i = Anum_pg_statistic_staop1 - 1; |
| for (k = 0; k < STATISTIC_NUM_SLOTS; k++) |
| { |
| values[i++] = ObjectIdGetDatum(stats->staop[k]); /* staopN */ |
| } |
| i = Anum_pg_statistic_stacoll1 - 1; |
| for (k = 0; k < STATISTIC_NUM_SLOTS; k++) |
| { |
| values[i++] = ObjectIdGetDatum(stats->stacoll[k]); /* stacollN */ |
| } |
| i = Anum_pg_statistic_stanumbers1 - 1; |
| for (k = 0; k < STATISTIC_NUM_SLOTS; k++) |
| { |
| int nnum = stats->numnumbers[k]; |
| |
| if (nnum > 0) |
| { |
| int n; |
| Datum *numdatums = (Datum *) palloc(nnum * sizeof(Datum)); |
| ArrayType *arry; |
| |
| for (n = 0; n < nnum; n++) |
| numdatums[n] = Float4GetDatum(stats->stanumbers[k][n]); |
| arry = construct_array_builtin(numdatums, nnum, FLOAT4OID); |
| values[i++] = PointerGetDatum(arry); /* stanumbersN */ |
| } |
| else |
| { |
| nulls[i] = true; |
| values[i++] = (Datum) 0; |
| } |
| } |
| i = Anum_pg_statistic_stavalues1 - 1; |
| for (k = 0; k < STATISTIC_NUM_SLOTS; k++) |
| { |
| if (stats->numvalues[k] > 0) |
| { |
| ArrayType *arry; |
| |
| arry = construct_array(stats->stavalues[k], |
| stats->numvalues[k], |
| stats->statypid[k], |
| stats->statyplen[k], |
| stats->statypbyval[k], |
| stats->statypalign[k]); |
| values[i++] = PointerGetDatum(arry); /* stavaluesN */ |
| } |
| else |
| { |
| nulls[i] = true; |
| values[i++] = (Datum) 0; |
| } |
| } |
| |
| stup = heap_form_tuple(RelationGetDescr(sd), values, nulls); |
| |
| astate = accumArrayResult(astate, |
| heap_copy_tuple_as_datum(stup, RelationGetDescr(sd)), |
| false, |
| typOid, |
| CurrentMemoryContext); |
| } |
| |
| table_close(sd, RowExclusiveLock); |
| |
| return makeArrayResult(astate, CurrentMemoryContext); |
| } |
| |
| /* |
| * Loads pg_statistic record from expression statistics for expression |
| * identified by the supplied index. |
| */ |
| HeapTuple |
| statext_expressions_load(Oid stxoid, bool inh, int idx) |
| { |
| bool isnull; |
| Datum value; |
| HeapTuple htup; |
| ExpandedArrayHeader *eah; |
| HeapTupleHeader td; |
| HeapTupleData tmptup; |
| HeapTuple tup; |
| |
| htup = SearchSysCache2(STATEXTDATASTXOID, |
| ObjectIdGetDatum(stxoid), BoolGetDatum(inh)); |
| if (!HeapTupleIsValid(htup)) |
| elog(ERROR, "cache lookup failed for statistics object %u", stxoid); |
| |
| value = SysCacheGetAttr(STATEXTDATASTXOID, htup, |
| Anum_pg_statistic_ext_data_stxdexpr, &isnull); |
| if (isnull) |
| elog(ERROR, |
| "requested statistics kind \"%c\" is not yet built for statistics object %u", |
| STATS_EXT_EXPRESSIONS, stxoid); |
| |
| eah = DatumGetExpandedArray(value); |
| |
| deconstruct_expanded_array(eah); |
| |
| td = DatumGetHeapTupleHeader(eah->dvalues[idx]); |
| |
| /* Build a temporary HeapTuple control structure */ |
| tmptup.t_len = HeapTupleHeaderGetDatumLength(td); |
| ItemPointerSetInvalid(&(tmptup.t_self)); |
| tmptup.t_tableOid = InvalidOid; |
| tmptup.t_data = td; |
| |
| tup = heap_copytuple(&tmptup); |
| |
| ReleaseSysCache(htup); |
| |
| return tup; |
| } |
| |
| /* |
| * Evaluate the expressions, so that we can use the results to build |
| * all the requested statistics types. This matters especially for |
| * expensive expressions, of course. |
| */ |
| static StatsBuildData * |
| make_build_data(Relation rel, StatExtEntry *stat, int numrows, HeapTuple *rows, |
| VacAttrStats **stats, int stattarget) |
| { |
| /* evaluated expressions */ |
| StatsBuildData *result; |
| char *ptr; |
| Size len; |
| |
| int i; |
| int k; |
| int idx; |
| TupleTableSlot *slot; |
| EState *estate; |
| ExprContext *econtext; |
| List *exprstates = NIL; |
| int nkeys = bms_num_members(stat->columns) + list_length(stat->exprs); |
| ListCell *lc; |
| |
| /* allocate everything as a single chunk, so we can free it easily */ |
| len = MAXALIGN(sizeof(StatsBuildData)); |
| len += MAXALIGN(sizeof(AttrNumber) * nkeys); /* attnums */ |
| len += MAXALIGN(sizeof(VacAttrStats *) * nkeys); /* stats */ |
| |
| /* values */ |
| len += MAXALIGN(sizeof(Datum *) * nkeys); |
| len += nkeys * MAXALIGN(sizeof(Datum) * numrows); |
| |
| /* nulls */ |
| len += MAXALIGN(sizeof(bool *) * nkeys); |
| len += nkeys * MAXALIGN(sizeof(bool) * numrows); |
| |
| ptr = palloc(len); |
| |
| /* set the pointers */ |
| result = (StatsBuildData *) ptr; |
| ptr += MAXALIGN(sizeof(StatsBuildData)); |
| |
| /* attnums */ |
| result->attnums = (AttrNumber *) ptr; |
| ptr += MAXALIGN(sizeof(AttrNumber) * nkeys); |
| |
| /* stats */ |
| result->stats = (VacAttrStats **) ptr; |
| ptr += MAXALIGN(sizeof(VacAttrStats *) * nkeys); |
| |
| /* values */ |
| result->values = (Datum **) ptr; |
| ptr += MAXALIGN(sizeof(Datum *) * nkeys); |
| |
| /* nulls */ |
| result->nulls = (bool **) ptr; |
| ptr += MAXALIGN(sizeof(bool *) * nkeys); |
| |
| for (i = 0; i < nkeys; i++) |
| { |
| result->values[i] = (Datum *) ptr; |
| ptr += MAXALIGN(sizeof(Datum) * numrows); |
| |
| result->nulls[i] = (bool *) ptr; |
| ptr += MAXALIGN(sizeof(bool) * numrows); |
| } |
| |
| Assert((ptr - (char *) result) == len); |
| |
| /* we have it allocated, so let's fill the values */ |
| result->nattnums = nkeys; |
| result->numrows = numrows; |
| |
| /* fill the attribute info - first attributes, then expressions */ |
| idx = 0; |
| k = -1; |
| while ((k = bms_next_member(stat->columns, k)) >= 0) |
| { |
| result->attnums[idx] = k; |
| result->stats[idx] = stats[idx]; |
| |
| idx++; |
| } |
| |
| k = -1; |
| foreach(lc, stat->exprs) |
| { |
| Node *expr = (Node *) lfirst(lc); |
| |
| result->attnums[idx] = k; |
| result->stats[idx] = examine_expression(expr, stattarget); |
| |
| idx++; |
| k--; |
| } |
| |
| /* first extract values for all the regular attributes */ |
| for (i = 0; i < numrows; i++) |
| { |
| idx = 0; |
| k = -1; |
| while ((k = bms_next_member(stat->columns, k)) >= 0) |
| { |
| result->values[idx][i] = heap_getattr(rows[i], k, |
| result->stats[idx]->tupDesc, |
| &result->nulls[idx][i]); |
| |
| idx++; |
| } |
| } |
| |
| /* Need an EState for evaluation expressions. */ |
| estate = CreateExecutorState(); |
| econtext = GetPerTupleExprContext(estate); |
| |
| /* Need a slot to hold the current heap tuple, too */ |
| slot = MakeSingleTupleTableSlot(RelationGetDescr(rel), |
| &TTSOpsHeapTuple); |
| |
| /* Arrange for econtext's scan tuple to be the tuple under test */ |
| econtext->ecxt_scantuple = slot; |
| |
| /* Set up expression evaluation state */ |
| exprstates = ExecPrepareExprList(stat->exprs, estate); |
| |
| for (i = 0; i < numrows; i++) |
| { |
| /* |
| * Reset the per-tuple context each time, to reclaim any cruft left |
| * behind by evaluating the statistics object expressions. |
| */ |
| ResetExprContext(econtext); |
| |
| /* Set up for expression evaluation */ |
| ExecStoreHeapTuple(rows[i], slot, false); |
| |
| idx = bms_num_members(stat->columns); |
| foreach(lc, exprstates) |
| { |
| Datum datum; |
| bool isnull; |
| ExprState *exprstate = (ExprState *) lfirst(lc); |
| |
| /* |
| * XXX This probably leaks memory. Maybe we should use |
| * ExecEvalExprSwitchContext but then we need to copy the result |
| * somewhere else. |
| */ |
| datum = ExecEvalExpr(exprstate, |
| GetPerTupleExprContext(estate), |
| &isnull); |
| if (isnull) |
| { |
| result->values[idx][i] = (Datum) 0; |
| result->nulls[idx][i] = true; |
| } |
| else |
| { |
| result->values[idx][i] = (Datum) datum; |
| result->nulls[idx][i] = false; |
| } |
| |
| idx++; |
| } |
| } |
| |
| ExecDropSingleTupleTableSlot(slot); |
| FreeExecutorState(estate); |
| |
| return result; |
| } |