diff options
Diffstat (limited to 'src/backend/commands/analyze.c')
| -rw-r--r-- | src/backend/commands/analyze.c | 1880 |
1 files changed, 1426 insertions, 454 deletions
diff --git a/src/backend/commands/analyze.c b/src/backend/commands/analyze.c index 88e56869da5..24cc7a8b254 100644 --- a/src/backend/commands/analyze.c +++ b/src/backend/commands/analyze.c @@ -8,19 +8,16 @@ * * * IDENTIFICATION - * $Header: /cvsroot/pgsql/src/backend/commands/analyze.c,v 1.16 2001/03/22 06:16:11 momjian Exp $ + * $Header: /cvsroot/pgsql/src/backend/commands/analyze.c,v 1.17 2001/05/07 00:43:17 tgl Exp $ * *------------------------------------------------------------------------- */ #include "postgres.h" -#include <sys/types.h> -#include <sys/file.h> -#include <sys/stat.h> -#include <fcntl.h> -#include <unistd.h> +#include <math.h> #include "access/heapam.h" +#include "access/tuptoaster.h" #include "catalog/catname.h" #include "catalog/indexing.h" #include "catalog/pg_operator.h" @@ -29,43 +26,139 @@ #include "commands/vacuum.h" #include "miscadmin.h" #include "parser/parse_oper.h" -#include "tcop/tcopprot.h" #include "utils/acl.h" #include "utils/builtins.h" +#include "utils/datum.h" #include "utils/fmgroids.h" -#include "utils/inval.h" #include "utils/syscache.h" +#include "utils/tuplesort.h" -#define swapLong(a,b) {long tmp; tmp=a; a=b; b=tmp;} -#define swapInt(a,b) {int tmp; tmp=a; a=b; b=tmp;} -#define swapDatum(a,b) {Datum tmp; tmp=a; a=b; b=tmp;} -#define VacAttrStatsEqValid(stats) ( stats->f_cmpeq.fn_addr != NULL ) -#define VacAttrStatsLtGtValid(stats) ( stats->f_cmplt.fn_addr != NULL && \ - stats->f_cmpgt.fn_addr != NULL && \ - RegProcedureIsValid(stats->outfunc) ) +/* + * Analysis algorithms supported + */ +typedef enum { + ALG_MINIMAL = 1, /* Compute only most-common-values */ + ALG_SCALAR /* Compute MCV, histogram, sort correlation */ +} AlgCode; + +/* + * 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 256 + +/* + * We build one of these structs for each attribute (column) that is to be + * analyzed. The struct and subsidiary data are in TransactionCommandContext, + * so they live until the end of the ANALYZE operation. + */ +typedef struct +{ + /* These fields are set up by examine_attribute */ + int attnum; /* attribute number */ + AlgCode algcode; /* Which algorithm to use for this column */ + int minrows; /* Minimum # of rows needed for stats */ + Form_pg_attribute attr; /* copy of pg_attribute row for column */ + Form_pg_type attrtype; /* copy of pg_type row for column */ + Oid eqopr; /* '=' operator for datatype, if any */ + Oid eqfunc; /* and associated function */ + Oid ltopr; /* '<' operator for datatype, if any */ + + /* These fields are filled in by the actual statistics-gathering routine */ + bool stats_valid; + float4 stanullfrac; /* fraction of entries that are NULL */ + int4 stawidth; /* average width */ + float4 stadistinct; /* # distinct values */ + int2 stakind[STATISTIC_NUM_SLOTS]; + Oid staop[STATISTIC_NUM_SLOTS]; + int numnumbers[STATISTIC_NUM_SLOTS]; + float4 *stanumbers[STATISTIC_NUM_SLOTS]; + int numvalues[STATISTIC_NUM_SLOTS]; + Datum *stavalues[STATISTIC_NUM_SLOTS]; +} VacAttrStats; + + +typedef struct +{ + Datum value; /* a data value */ + int tupno; /* position index for tuple it came from */ +} ScalarItem; + +typedef struct +{ + int count; /* # of duplicates */ + int first; /* values[] index of first occurrence */ +} ScalarMCVItem; + + +#define swapInt(a,b) {int _tmp; _tmp=a; a=b; b=_tmp;} +#define swapDatum(a,b) {Datum _tmp; _tmp=a; a=b; b=_tmp;} -static void attr_stats(Relation onerel, int attr_cnt, VacAttrStats *vacattrstats, HeapTuple tuple); -static void bucketcpy(Form_pg_attribute attr, Datum value, Datum *bucket, int *bucket_len); -static void update_attstats(Oid relid, int natts, VacAttrStats *vacattrstats); -static void del_stats(Oid relid, int attcnt, int *attnums); + +static int MESSAGE_LEVEL; + +/* context information for compare_scalars() */ +static FmgrInfo *datumCmpFn; +static SortFunctionKind datumCmpFnKind; +static int *datumCmpTupnoLink; + + +static VacAttrStats *examine_attribute(Relation onerel, int attnum); +static int acquire_sample_rows(Relation onerel, HeapTuple *rows, + int targrows, long *totalrows); +static double random_fract(void); +static double init_selection_state(int n); +static long select_next_random_record(long t, int n, double *stateptr); +static int compare_rows(const void *a, const void *b); +static int compare_scalars(const void *a, const void *b); +static int compare_mcvs(const void *a, const void *b); +static OffsetNumber get_page_max_offset(Relation relation, + BlockNumber blocknumber); +static void compute_minimal_stats(VacAttrStats *stats, + TupleDesc tupDesc, long totalrows, + HeapTuple *rows, int numrows); +static void compute_scalar_stats(VacAttrStats *stats, + TupleDesc tupDesc, long totalrows, + HeapTuple *rows, int numrows); +static void update_attstats(Oid relid, int natts, VacAttrStats **vacattrstats); /* - * analyze_rel() -- analyze relation + * analyze_rel() -- analyze one relation */ void -analyze_rel(Oid relid, List *anal_cols2, int MESSAGE_LEVEL) +analyze_rel(Oid relid, VacuumStmt *vacstmt) { - HeapTuple tuple; Relation onerel; - int32 i; - int attr_cnt, - *attnums = NULL; Form_pg_attribute *attr; - VacAttrStats *vacattrstats; - HeapScanDesc scan; + int attr_cnt, + tcnt, + i; + VacAttrStats **vacattrstats; + int targrows, + numrows; + long totalrows; + HeapTuple *rows; + HeapTuple tuple; + + if (vacstmt->verbose) + MESSAGE_LEVEL = NOTICE; + else + MESSAGE_LEVEL = DEBUG; + /* + * Begin a transaction for analyzing this relation. + * + * Note: All memory allocated during ANALYZE will live in + * TransactionCommandContext or a subcontext thereof, so it will + * all be released by transaction commit at the end of this routine. + */ StartTransactionCommand(); /* @@ -76,7 +169,7 @@ analyze_rel(Oid relid, List *anal_cols2, int MESSAGE_LEVEL) /* * Race condition -- if the pg_class tuple has gone away since the - * last time we saw it, we don't need to vacuum it. + * last time we saw it, we don't need to process it. */ tuple = SearchSysCache(RELOID, ObjectIdGetDatum(relid), @@ -88,8 +181,7 @@ analyze_rel(Oid relid, List *anal_cols2, int MESSAGE_LEVEL) } /* - * We can VACUUM ANALYZE any table except pg_statistic. see - * update_relstats + * We can ANALYZE any table except pg_statistic. See update_attstats */ if (strcmp(NameStr(((Form_pg_class) GETSTRUCT(tuple))->relname), StatisticRelationName) == 0) @@ -100,586 +192,1466 @@ analyze_rel(Oid relid, List *anal_cols2, int MESSAGE_LEVEL) } ReleaseSysCache(tuple); + /* + * Open the class, getting only a read lock on it, and check permissions + */ onerel = heap_open(relid, AccessShareLock); if (!pg_ownercheck(GetUserId(), RelationGetRelationName(onerel), RELNAME)) { - - /* - * we already did an elog during vacuum elog(NOTICE, "Skipping - * \"%s\" --- only table owner can VACUUM it", - * RelationGetRelationName(onerel)); - */ + /* No need for a notice if we already complained during VACUUM */ + if (!vacstmt->vacuum) + elog(NOTICE, "Skipping \"%s\" --- only table owner can ANALYZE it", + RelationGetRelationName(onerel)); heap_close(onerel, NoLock); CommitTransactionCommand(); return; } - elog(MESSAGE_LEVEL, "Analyzing..."); + elog(MESSAGE_LEVEL, "Analyzing %s", RelationGetRelationName(onerel)); - attr_cnt = onerel->rd_att->natts; + /* + * Determine which columns to analyze + * + * Note that system attributes are never analyzed. + */ attr = onerel->rd_att->attrs; + attr_cnt = onerel->rd_att->natts; - if (anal_cols2 != NIL) + if (vacstmt->va_cols != NIL) { - int tcnt = 0; List *le; - if (length(anal_cols2) > attr_cnt) - elog(ERROR, "vacuum: too many attributes specified for relation %s", - RelationGetRelationName(onerel)); - attnums = (int *) palloc(attr_cnt * sizeof(int)); - foreach(le, anal_cols2) + vacattrstats = (VacAttrStats **) palloc(length(vacstmt->va_cols) * + sizeof(VacAttrStats *)); + tcnt = 0; + foreach(le, vacstmt->va_cols) { - char *col = (char *) lfirst(le); + char *col = strVal(lfirst(le)); for (i = 0; i < attr_cnt; i++) { if (namestrcmp(&(attr[i]->attname), col) == 0) break; } - if (i < attr_cnt) /* found */ - attnums[tcnt++] = i; - else - { - elog(ERROR, "vacuum: there is no attribute %s in %s", + if (i >= attr_cnt) + elog(ERROR, "ANALYZE: there is no attribute %s in %s", col, RelationGetRelationName(onerel)); - } + vacattrstats[tcnt] = examine_attribute(onerel, i+1); + if (vacattrstats[tcnt] != NULL) + tcnt++; + } + attr_cnt = tcnt; + } + else + { + vacattrstats = (VacAttrStats **) palloc(attr_cnt * + sizeof(VacAttrStats *)); + tcnt = 0; + for (i = 0; i < attr_cnt; i++) + { + vacattrstats[tcnt] = examine_attribute(onerel, i+1); + if (vacattrstats[tcnt] != NULL) + tcnt++; } attr_cnt = tcnt; } - vacattrstats = (VacAttrStats *) palloc(attr_cnt * sizeof(VacAttrStats)); + /* + * Quit if no analyzable columns + */ + if (attr_cnt <= 0) + { + heap_close(onerel, NoLock); + CommitTransactionCommand(); + return; + } + /* + * Determine how many rows we need to sample, using the worst case + * from all analyzable columns. We use a lower bound of 100 rows + * to avoid possible overflow in Vitter's algorithm. + */ + targrows = 100; for (i = 0; i < attr_cnt; i++) { - Operator func_operator; - VacAttrStats *stats; - - stats = &vacattrstats[i]; - stats->attr = palloc(ATTRIBUTE_TUPLE_SIZE); - memcpy(stats->attr, attr[((attnums) ? attnums[i] : i)], - ATTRIBUTE_TUPLE_SIZE); - stats->best = stats->guess1 = stats->guess2 = 0; - stats->max = stats->min = 0; - stats->best_len = stats->guess1_len = stats->guess2_len = 0; - stats->max_len = stats->min_len = 0; - stats->initialized = false; - stats->best_cnt = stats->guess1_cnt = stats->guess1_hits = stats->guess2_hits = 0; - stats->max_cnt = stats->min_cnt = stats->null_cnt = stats->nonnull_cnt = 0; - - func_operator = compatible_oper("=", - stats->attr->atttypid, - stats->attr->atttypid, - true); - if (func_operator != NULL) - { - fmgr_info(oprfuncid(func_operator), &(stats->f_cmpeq)); - ReleaseSysCache(func_operator); - } - else - stats->f_cmpeq.fn_addr = NULL; + if (targrows < vacattrstats[i]->minrows) + targrows = vacattrstats[i]->minrows; + } + + /* + * Acquire the sample rows + */ + rows = (HeapTuple *) palloc(targrows * sizeof(HeapTuple)); + numrows = acquire_sample_rows(onerel, rows, targrows, &totalrows); - func_operator = compatible_oper("<", - stats->attr->atttypid, - stats->attr->atttypid, - true); - if (func_operator != NULL) + /* + * If we are running a standalone ANALYZE, update pages/tuples stats + * in pg_class. We have the accurate page count from heap_beginscan, + * but only an approximate number of tuples; therefore, if we are + * part of VACUUM ANALYZE do *not* overwrite the accurate count already + * inserted by VACUUM. + */ + if (!vacstmt->vacuum) + vac_update_relstats(RelationGetRelid(onerel), + onerel->rd_nblocks, + (double) totalrows, + RelationGetForm(onerel)->relhasindex); + + /* + * Compute the statistics. Temporary results during the calculations + * for each column are stored in a child context. The calc routines + * are responsible to make sure that whatever they store into the + * VacAttrStats structure is allocated in TransactionCommandContext. + */ + if (numrows > 0) + { + MemoryContext col_context, + old_context; + + col_context = AllocSetContextCreate(CurrentMemoryContext, + "Analyze Column", + ALLOCSET_DEFAULT_MINSIZE, + ALLOCSET_DEFAULT_INITSIZE, + ALLOCSET_DEFAULT_MAXSIZE); + old_context = MemoryContextSwitchTo(col_context); + for (i = 0; i < attr_cnt; i++) { - fmgr_info(oprfuncid(func_operator), &(stats->f_cmplt)); - stats->op_cmplt = oprid(func_operator); - ReleaseSysCache(func_operator); + switch (vacattrstats[i]->algcode) + { + case ALG_MINIMAL: + compute_minimal_stats(vacattrstats[i], + onerel->rd_att, totalrows, + rows, numrows); + break; + case ALG_SCALAR: + compute_scalar_stats(vacattrstats[i], + onerel->rd_att, totalrows, + rows, numrows); + break; + } + MemoryContextResetAndDeleteChildren(col_context); } - else + MemoryContextSwitchTo(old_context); + MemoryContextDelete(col_context); + + /* + * Emit the completed stats rows into pg_statistic, replacing any + * previous statistics for the target columns. (If there are stats + * in pg_statistic for columns we didn't process, we leave them alone.) + */ + update_attstats(relid, attr_cnt, vacattrstats); + } + + /* + * Close source relation now, but keep lock so that no one deletes it + * before we commit. (If someone did, they'd fail to clean up the + * entries we made in pg_statistic.) + */ + heap_close(onerel, NoLock); + + /* Commit and release working memory */ + CommitTransactionCommand(); +} + +/* + * 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(Relation onerel, int attnum) +{ + Form_pg_attribute attr = onerel->rd_att->attrs[attnum-1]; + Operator func_operator; + Oid oprrest; + HeapTuple typtuple; + Oid eqopr = InvalidOid; + Oid eqfunc = InvalidOid; + Oid ltopr = InvalidOid; + VacAttrStats *stats; + + /* Don't analyze column if user has specified not to */ + if (attr->attstattarget <= 0) + return NULL; + + /* If column has no "=" operator, we can't do much of anything */ + func_operator = compatible_oper("=", + attr->atttypid, + attr->atttypid, + true); + if (func_operator != NULL) + { + oprrest = ((Form_pg_operator) GETSTRUCT(func_operator))->oprrest; + if (oprrest == F_EQSEL) { - stats->f_cmplt.fn_addr = NULL; - stats->op_cmplt = InvalidOid; + eqopr = oprid(func_operator); + eqfunc = oprfuncid(func_operator); } + ReleaseSysCache(func_operator); + } + if (!OidIsValid(eqfunc)) + return NULL; - func_operator = compatible_oper(">", - stats->attr->atttypid, - stats->attr->atttypid, - true); - if (func_operator != NULL) + /* + * If we have "=" then we're at least able to do the minimal algorithm, + * so start filling in a VacAttrStats struct. + */ + stats = (VacAttrStats *) palloc(sizeof(VacAttrStats)); + MemSet(stats, 0, sizeof(VacAttrStats)); + stats->attnum = attnum; + stats->attr = (Form_pg_attribute) palloc(ATTRIBUTE_TUPLE_SIZE); + memcpy(stats->attr, attr, ATTRIBUTE_TUPLE_SIZE); + typtuple = SearchSysCache(TYPEOID, + ObjectIdGetDatum(attr->atttypid), + 0, 0, 0); + if (!HeapTupleIsValid(typtuple)) + elog(ERROR, "cache lookup of type %u failed", attr->atttypid); + stats->attrtype = (Form_pg_type) palloc(sizeof(FormData_pg_type)); + memcpy(stats->attrtype, GETSTRUCT(typtuple), sizeof(FormData_pg_type)); + ReleaseSysCache(typtuple); + stats->eqopr = eqopr; + stats->eqfunc = eqfunc; + + /* Is there a "<" operator with suitable semantics? */ + func_operator = compatible_oper("<", + attr->atttypid, + attr->atttypid, + true); + if (func_operator != NULL) + { + oprrest = ((Form_pg_operator) GETSTRUCT(func_operator))->oprrest; + if (oprrest == F_SCALARLTSEL) { - fmgr_info(oprfuncid(func_operator), &(stats->f_cmpgt)); - ReleaseSysCache(func_operator); + ltopr = oprid(func_operator); } - else - stats->f_cmpgt.fn_addr = NULL; + ReleaseSysCache(func_operator); + } + stats->ltopr = ltopr; + + /* + * Determine the algorithm to use (this will get more complicated later) + */ + if (OidIsValid(ltopr)) + { + /* Seems to be a scalar datatype */ + stats->algcode = ALG_SCALAR; + /*-------------------- + * The following choice of minrows is based on the paper + * "Random sampling for histogram construction: how much is enough?" + * by Surajit Chaudhuri, Rajeev Motwani and Vivek Narasayya, in + * Proceedings of ACM SIGMOD International Conference on Management + * of Data, 1998, Pages 436-447. Their Corollary 1 to Theorem 5 + * says that for table size n, histogram size k, maximum relative + * error in bin size f, and error probability gamma, the minimum + * random sample size is + * r = 4 * k * ln(2*n/gamma) / f^2 + * Taking f = 0.5, gamma = 0.01, n = 1 million rows, we obtain + * r = 305.82 * k + * Note that because of the log function, the dependence on n is + * quite weak; even at n = 1 billion, a 300*k sample gives <= 0.59 + * bin size error with probability 0.99. So there's no real need to + * scale for n, which is a good thing because we don't necessarily + * know it at this point. + *-------------------- + */ + stats->minrows = 300 * attr->attstattarget; + } + else + { + /* Can't do much but the minimal stuff */ + stats->algcode = ALG_MINIMAL; + /* Might as well use the same minrows as above */ + stats->minrows = 300 * attr->attstattarget; + } + + return stats; +} - tuple = SearchSysCache(TYPEOID, - ObjectIdGetDatum(stats->attr->atttypid), - 0, 0, 0); - if (HeapTupleIsValid(tuple)) +/* + * acquire_sample_rows -- acquire a random sample of rows from the table + * + * Up to targrows rows are collected (if there are fewer than that many + * rows in the table, all rows are collected). When the table is larger + * than targrows, a truly random sample is collected: every row has an + * equal chance of ending up in the final sample. + * + * We also estimate the total number of rows in the table, and return that + * into *totalrows. + * + * The returned list of tuples is in order by physical position in the table. + * (We will rely on this later to derive correlation estimates.) + */ +static int +acquire_sample_rows(Relation onerel, HeapTuple *rows, int targrows, + long *totalrows) +{ + int numrows = 0; + HeapScanDesc scan; + HeapTuple tuple; + ItemPointer lasttuple; + BlockNumber lastblock, + estblock; + OffsetNumber lastoffset; + int numest; + double tuplesperpage; + long t; + double rstate; + + Assert(targrows > 1); + /* + * Do a simple linear scan until we reach the target number of rows. + */ + scan = heap_beginscan(onerel, false, SnapshotNow, 0, NULL); + while (HeapTupleIsValid(tuple = heap_getnext(scan, 0))) + { + rows[numrows++] = heap_copytuple(tuple); + if (numrows >= targrows) + break; + } + heap_endscan(scan); + /* + * If we ran out of tuples then we're done, no matter how few we + * collected. No sort is needed, since they're already in order. + */ + if (!HeapTupleIsValid(tuple)) + { + *totalrows = numrows; + return numrows; + } + /* + * Otherwise, start replacing tuples in the sample until we reach the + * end of the relation. This algorithm is from Jeff Vitter's paper + * (see full citation below). It works by repeatedly computing the number + * of the next tuple we want to fetch, which will replace a randomly + * chosen element of the reservoir (current set of tuples). At all times + * the reservoir is a true random sample of the tuples we've passed over + * so far, so when we fall off the end of the relation we're done. + * + * A slight difficulty is that since we don't want to fetch tuples or even + * pages that we skip over, it's not possible to fetch *exactly* the N'th + * tuple at each step --- we don't know how many valid tuples are on + * the skipped pages. We handle this by assuming that the average number + * of valid tuples/page on the pages already scanned over holds good for + * the rest of the relation as well; this lets us estimate which page + * the next tuple should be on and its position in the page. Then we + * fetch the first valid tuple at or after that position, being careful + * not to use the same tuple twice. This approach should still give a + * good random sample, although it's not perfect. + */ + lasttuple = &(rows[numrows-1]->t_self); + lastblock = ItemPointerGetBlockNumber(lasttuple); + lastoffset = ItemPointerGetOffsetNumber(lasttuple); + /* + * If possible, estimate tuples/page using only completely-scanned pages. + */ + for (numest = numrows; numest > 0; numest--) + { + if (ItemPointerGetBlockNumber(&(rows[numest-1]->t_self)) != lastblock) + break; + } + if (numest == 0) + { + numest = numrows; /* don't have a full page? */ + estblock = lastblock + 1; + } + else + { + estblock = lastblock; + } + tuplesperpage = (double) numest / (double) estblock; + + t = numrows; /* t is the # of records processed so far */ + rstate = init_selection_state(targrows); + for (;;) + { + double targpos; + BlockNumber targblock; + OffsetNumber targoffset, + maxoffset; + + t = select_next_random_record(t, targrows, &rstate); + /* Try to read the t'th record in the table */ + targpos = (double) t / tuplesperpage; + targblock = (BlockNumber) targpos; + targoffset = ((int) (targpos - targblock) * tuplesperpage) + + FirstOffsetNumber; + /* Make sure we are past the last selected record */ + if (targblock <= lastblock) { - stats->outfunc = ((Form_pg_type) GETSTRUCT(tuple))->typoutput; - stats->typelem = ((Form_pg_type) GETSTRUCT(tuple))->typelem; - ReleaseSysCache(tuple); + targblock = lastblock; + if (targoffset <= lastoffset) + targoffset = lastoffset + 1; } - else + /* Loop to find first valid record at or after given position */ + pageloop:; + /* + * Have we fallen off the end of the relation? (We rely on + * heap_beginscan to have updated rd_nblocks.) + */ + if (targblock >= onerel->rd_nblocks) + break; + maxoffset = get_page_max_offset(onerel, targblock); + for (;;) { - stats->outfunc = InvalidOid; - stats->typelem = InvalidOid; + HeapTupleData targtuple; + Buffer targbuffer; + + if (targoffset > maxoffset) + { + /* Fell off end of this page, try next */ + targblock++; + targoffset = FirstOffsetNumber; + goto pageloop; + } + ItemPointerSet(&targtuple.t_self, targblock, targoffset); + heap_fetch(onerel, SnapshotNow, &targtuple, &targbuffer); + if (targtuple.t_data != NULL) + { + /* + * Found a suitable tuple, so save it, replacing one old + * tuple at random + */ + int k = (int) (targrows * random_fract()); + + Assert(k >= 0 && k < targrows); + heap_freetuple(rows[k]); + rows[k] = heap_copytuple(&targtuple); + ReleaseBuffer(targbuffer); + lastblock = targblock; + lastoffset = targoffset; + break; + } + /* this tuple is dead, so advance to next one on same page */ + targoffset++; } } - /* delete existing pg_statistic rows for relation */ - del_stats(relid, ((attnums) ? attr_cnt : 0), attnums); - - /* scan relation to gather statistics */ - scan = heap_beginscan(onerel, false, SnapshotNow, 0, NULL); - while (HeapTupleIsValid(tuple = heap_getnext(scan, 0))) - attr_stats(onerel, attr_cnt, vacattrstats, tuple); + /* + * Now we need to sort the collected tuples by position (itempointer). + */ + qsort((void *) rows, numrows, sizeof(HeapTuple), compare_rows); - heap_endscan(scan); + /* + * Estimate total number of valid rows in relation. + */ + *totalrows = (long) (onerel->rd_nblocks * tuplesperpage + 0.5); - /* close rel, but keep lock so it doesn't go away before commit */ - heap_close(onerel, NoLock); + return numrows; +} - /* update statistics in pg_class */ - update_attstats(relid, attr_cnt, vacattrstats); +/* Select a random value R uniformly distributed in 0 < R < 1 */ +static double +random_fract(void) +{ + long z; - CommitTransactionCommand(); + /* random() can produce endpoint values, try again if so */ + do + { + z = random(); + } while (! (z > 0 && z < MAX_RANDOM_VALUE)); + return (double) z / (double) MAX_RANDOM_VALUE; } /* - * attr_stats() -- compute column statistics used by the planner + * These two routines embody Algorithm Z from "Random sampling with a + * reservoir" by Jeffrey S. Vitter, in ACM Trans. Math. Softw. 11, 1 + * (Mar. 1985), Pages 37-57. While Vitter describes his algorithm in terms + * of the count S of records to skip before processing another record, + * it is convenient to work primarily with t, the index (counting from 1) + * of the last record processed and next record to process. The only extra + * state needed between calls is W, a random state variable. * - * We compute the column min, max, null and non-null counts. - * Plus we attempt to find the count of the value that occurs most - * frequently in each column. These figures are used to compute - * the selectivity of the column. + * init_selection_state computes the initial W value. * - * We use a three-bucket cache to get the most frequent item. - * The 'guess' buckets count hits. A cache miss causes guess1 - * to get the most hit 'guess' item in the most recent cycle, and - * the new item goes into guess2. Whenever the total count of hits - * of a 'guess' entry is larger than 'best', 'guess' becomes 'best'. + * Given that we've already processed t records (t >= n), + * select_next_random_record determines the number of the next record to + * process. + */ +static double +init_selection_state(int n) +{ + /* Initial value of W (for use when Algorithm Z is first applied) */ + return exp(- log(random_fract())/n); +} + +static long +select_next_random_record(long t, int n, double *stateptr) +{ + /* The magic constant here is T from Vitter's paper */ + if (t <= (22 * n)) + { + /* Process records using Algorithm X until t is large enough */ + double V, + quot; + + V = random_fract(); /* Generate V */ + t++; + quot = (double) (t - n) / (double) t; + /* Find min S satisfying (4.1) */ + while (quot > V) + { + t++; + quot *= (double) (t - n) / (double) t; + } + } + else + { + /* Now apply Algorithm Z */ + double W = *stateptr; + long term = t - n + 1; + int S; + + for (;;) + { + long numer, + numer_lim, + denom; + double U, + X, + lhs, + rhs, + y, + tmp; + + /* Generate U and X */ + U = random_fract(); + X = t * (W - 1.0); + S = X; /* S is tentatively set to floor(X) */ + /* Test if U <= h(S)/cg(X) in the manner of (6.3) */ + tmp = (double) (t + 1) / (double) term; + lhs = exp(log(((U * tmp * tmp) * (term + S))/(t + X))/n); + rhs = (((t + X)/(term + S)) * term)/t; + if (lhs <= rhs) + { + W = rhs/lhs; + break; + } + /* Test if U <= f(S)/cg(X) */ + y = (((U * (t + 1))/term) * (t + S + 1))/(t + X); + if (n < S) + { + denom = t; + numer_lim = term + S; + } + else + { + denom = t - n + S; + numer_lim = t + 1; + } + for (numer = t + S; numer >= numer_lim; numer--) + { + y *= (double) numer / (double) denom; + denom--; + } + W = exp(- log(random_fract())/n); /* Generate W in advance */ + if (exp(log(y)/n) <= (t + X)/t) + break; + } + t += S + 1; + *stateptr = W; + } + return t; +} + +/* + * qsort comparator for sorting rows[] array + */ +static int +compare_rows(const void *a, const void *b) +{ + HeapTuple ha = * (HeapTuple *) a; + HeapTuple hb = * (HeapTuple *) b; + BlockNumber ba = ItemPointerGetBlockNumber(&ha->t_self); + OffsetNumber oa = ItemPointerGetOffsetNumber(&ha->t_self); + BlockNumber bb = ItemPointerGetBlockNumber(&hb->t_self); + OffsetNumber ob = ItemPointerGetOffsetNumber(&hb->t_self); + + if (ba < bb) + return -1; + if (ba > bb) + return 1; + if (oa < ob) + return -1; + if (oa > ob) + return 1; + return 0; +} + +/* + * Discover the largest valid tuple offset number on the given page + * + * This code probably ought to live in some other module. + */ +static OffsetNumber +get_page_max_offset(Relation relation, BlockNumber blocknumber) +{ + Buffer buffer; + Page p; + OffsetNumber offnum; + + buffer = ReadBuffer(relation, blocknumber); + if (!BufferIsValid(buffer)) + elog(ERROR, "get_page_max_offset: %s relation: ReadBuffer(%ld) failed", + RelationGetRelationName(relation), (long) blocknumber); + LockBuffer(buffer, BUFFER_LOCK_SHARE); + p = BufferGetPage(buffer); + offnum = PageGetMaxOffsetNumber(p); + LockBuffer(buffer, BUFFER_LOCK_UNLOCK); + ReleaseBuffer(buffer); + return offnum; +} + + +/* + * compute_minimal_stats() -- compute minimal column statistics * - * This method works perfectly for columns with unique values, and columns - * with only two unique values, plus nulls. + * We use this when we can find only an "=" operator for the datatype. * - * It becomes less perfect as the number of unique values increases and - * their distribution in the table becomes more random. + * We determine the fraction of non-null rows, the average width, the + * most common values, and the (estimated) number of distinct values. * + * The most common values are determined by brute force: we keep a list + * of previously seen values, ordered by number of times seen, as we scan + * the samples. A newly seen value is inserted just after the last + * multiply-seen value, causing the bottommost (oldest) singly-seen value + * to drop off the list. The accuracy of this method, and also its cost, + * depend mainly on the length of the list we are willing to keep. */ static void -attr_stats(Relation onerel, int attr_cnt, VacAttrStats *vacattrstats, HeapTuple tuple) +compute_minimal_stats(VacAttrStats *stats, + TupleDesc tupDesc, long totalrows, + HeapTuple *rows, int numrows) { int i; - TupleDesc tupDesc = onerel->rd_att; - - for (i = 0; i < attr_cnt; i++) + int null_cnt = 0; + int nonnull_cnt = 0; + int toowide_cnt = 0; + double total_width = 0; + bool is_varlena = (!stats->attr->attbyval && + stats->attr->attlen == -1); + FmgrInfo f_cmpeq; + typedef struct + { + Datum value; + int count; + } TrackItem; + TrackItem *track; + int track_cnt, + track_max; + int num_mcv = stats->attr->attstattarget; + + /* We track up to 2*n values for an n-element MCV list; but at least 10 */ + track_max = 2 * num_mcv; + if (track_max < 10) + track_max = 10; + track = (TrackItem *) palloc(track_max * sizeof(TrackItem)); + track_cnt = 0; + + fmgr_info(stats->eqfunc, &f_cmpeq); + + for (i = 0; i < numrows; i++) { - VacAttrStats *stats = &vacattrstats[i]; - Datum origvalue; + HeapTuple tuple = rows[i]; Datum value; bool isnull; - bool value_hit; - - if (!VacAttrStatsEqValid(stats)) - continue; - -#ifdef _DROP_COLUMN_HACK__ - if (COLUMN_IS_DROPPED(stats->attr)) - continue; -#endif /* _DROP_COLUMN_HACK__ */ + bool match; + int firstcount1, + j; - origvalue = heap_getattr(tuple, stats->attr->attnum, - tupDesc, &isnull); + value = heap_getattr(tuple, stats->attnum, tupDesc, &isnull); + /* Check for null/nonnull */ if (isnull) { - stats->null_cnt++; + null_cnt++; continue; } - stats->nonnull_cnt++; + nonnull_cnt++; /* - * If the value is toasted, detoast it to avoid repeated - * detoastings and resultant memory leakage inside the comparison - * routines. + * If it's a varlena field, add up widths for average width + * calculation. Note that if the value is toasted, we + * use the toasted width. We don't bother with this calculation + * if it's a fixed-width type. */ - if (!stats->attr->attbyval && stats->attr->attlen == -1) - value = PointerGetDatum(PG_DETOAST_DATUM(origvalue)); - else - value = origvalue; - - if (!stats->initialized) + if (is_varlena) { - bucketcpy(stats->attr, value, &stats->best, &stats->best_len); - /* best_cnt gets incremented below */ - bucketcpy(stats->attr, value, &stats->guess1, &stats->guess1_len); - stats->guess1_cnt = stats->guess1_hits = 1; - bucketcpy(stats->attr, value, &stats->guess2, &stats->guess2_len); - stats->guess2_hits = 1; - if (VacAttrStatsLtGtValid(stats)) + total_width += VARSIZE(DatumGetPointer(value)); + /* + * If the value is toasted, we want to detoast it just once to + * avoid repeated detoastings and resultant excess memory usage + * during the comparisons. Also, check to see if the value is + * excessively wide, and if so don't detoast at all --- just + * ignore the value. + */ + if (toast_raw_datum_size(value) > WIDTH_THRESHOLD) { - bucketcpy(stats->attr, value, &stats->max, &stats->max_len); - bucketcpy(stats->attr, value, &stats->min, &stats->min_len); - /* min_cnt, max_cnt get incremented below */ + toowide_cnt++; + continue; } - stats->initialized = true; + value = PointerGetDatum(PG_DETOAST_DATUM(value)); } - if (VacAttrStatsLtGtValid(stats)) + /* + * See if the value matches anything we're already tracking. + */ + match = false; + firstcount1 = track_cnt; + for (j = 0; j < track_cnt; j++) { - if (DatumGetBool(FunctionCall2(&stats->f_cmplt, - value, stats->min))) + if (DatumGetBool(FunctionCall2(&f_cmpeq, value, track[j].value))) { - bucketcpy(stats->attr, value, &stats->min, &stats->min_len); - stats->min_cnt = 1; + match = true; + break; } - else if (DatumGetBool(FunctionCall2(&stats->f_cmpeq, - value, stats->min))) - stats->min_cnt++; + if (j < firstcount1 && track[j].count == 1) + firstcount1 = j; + } - if (DatumGetBool(FunctionCall2(&stats->f_cmpgt, - value, stats->max))) + if (match) + { + /* Found a match */ + track[j].count++; + /* This value may now need to "bubble up" in the track list */ + while (j > 0 && track[j].count > track[j-1].count) { - bucketcpy(stats->attr, value, &stats->max, &stats->max_len); - stats->max_cnt = 1; + swapDatum(track[j].value, track[j-1].value); + swapInt(track[j].count, track[j-1].count); + j--; } - else if (DatumGetBool(FunctionCall2(&stats->f_cmpeq, - value, stats->max))) - stats->max_cnt++; } - - value_hit = true; - if (DatumGetBool(FunctionCall2(&stats->f_cmpeq, - value, stats->best))) - stats->best_cnt++; - else if (DatumGetBool(FunctionCall2(&stats->f_cmpeq, - value, stats->guess1))) + else { - stats->guess1_cnt++; - stats->guess1_hits++; + /* No match. Insert at head of count-1 list */ + if (track_cnt < track_max) + track_cnt++; + for (j = track_cnt-1; j > firstcount1; j--) + { + track[j].value = track[j-1].value; + track[j].count = track[j-1].count; + } + if (firstcount1 < track_cnt) + { + track[firstcount1].value = value; + track[firstcount1].count = 1; + } } - else if (DatumGetBool(FunctionCall2(&stats->f_cmpeq, - value, stats->guess2))) - stats->guess2_hits++; + } + + /* We can only compute valid stats if we found some non-null values. */ + if (nonnull_cnt > 0) + { + int nmultiple, + summultiple; + + stats->stats_valid = true; + /* Do the simple null-frac and width stats */ + stats->stanullfrac = (double) null_cnt / (double) numrows; + if (is_varlena) + stats->stawidth = total_width / (double) nonnull_cnt; else - value_hit = false; + stats->stawidth = stats->attrtype->typlen; - if (stats->guess2_hits > stats->guess1_hits) + /* Count the number of values we found multiple times */ + summultiple = 0; + for (nmultiple = 0; nmultiple < track_cnt; nmultiple++) { - swapDatum(stats->guess1, stats->guess2); - swapInt(stats->guess1_len, stats->guess2_len); - swapLong(stats->guess1_hits, stats->guess2_hits); - stats->guess1_cnt = stats->guess1_hits; + if (track[nmultiple].count == 1) + break; + summultiple += track[nmultiple].count; } - if (stats->guess1_cnt > stats->best_cnt) + + if (nmultiple == 0) { - swapDatum(stats->best, stats->guess1); - swapInt(stats->best_len, stats->guess1_len); - swapLong(stats->best_cnt, stats->guess1_cnt); - stats->guess1_hits = 1; - stats->guess2_hits = 1; + /* If we found no repeated values, assume it's a unique column */ + stats->stadistinct = -1.0; } - if (!value_hit) + else if (track_cnt < track_max && toowide_cnt == 0 && + nmultiple == track_cnt) { - bucketcpy(stats->attr, value, &stats->guess2, &stats->guess2_len); - stats->guess1_hits = 1; - stats->guess2_hits = 1; + /* + * Our track list includes every value in the sample, and every + * value appeared more than once. Assume the column has just + * these values. + */ + stats->stadistinct = track_cnt; } + else + { + /*---------- + * Estimate the number of distinct values using the estimator + * proposed by Chaudhuri et al (see citation above). This is + * sqrt(n/r) * max(f1,1) + f2 + f3 + ... + * where fk is the number of distinct values that occurred + * exactly k times in our sample of r rows (from a total of n). + * We assume (not very reliably!) that all the multiply-occurring + * values are reflected in the final track[] list, and the other + * nonnull values all appeared but once. + *---------- + */ + int f1 = nonnull_cnt - summultiple; + double term1; - /* Clean up detoasted copy, if any */ - if (value != origvalue) - pfree(DatumGetPointer(value)); - } -} + if (f1 < 1) + f1 = 1; + term1 = sqrt((double) totalrows / (double) numrows) * f1; + stats->stadistinct = floor(term1 + nmultiple + 0.5); + } -/* - * bucketcpy() -- copy a new value into one of the statistics buckets - */ -static void -bucketcpy(Form_pg_attribute attr, Datum value, Datum *bucket, int *bucket_len) -{ - if (attr->attbyval) - *bucket = value; - else - { - int len = (attr->attlen != -1 ? attr->attlen : VARSIZE(value)); + /* + * If we estimated the number of distinct values at more than 10% + * of the total row count (a very arbitrary limit), then assume + * that stadistinct should scale with the row count rather than be + * a fixed value. + */ + if (stats->stadistinct > 0.1 * totalrows) + stats->stadistinct = - (stats->stadistinct / totalrows); - /* Avoid unnecessary palloc() traffic... */ - if (len > *bucket_len) + /* Generate an MCV slot entry, only if we found multiples */ + if (nmultiple < num_mcv) + num_mcv = nmultiple; + if (num_mcv > 0) { - if (*bucket_len != 0) - pfree(DatumGetPointer(*bucket)); - *bucket = PointerGetDatum(palloc(len)); - *bucket_len = len; + MemoryContext old_context; + Datum *mcv_values; + float4 *mcv_freqs; + + /* Must copy the target values into TransactionCommandContext */ + old_context = MemoryContextSwitchTo(TransactionCommandContext); + mcv_values = (Datum *) palloc(num_mcv * sizeof(Datum)); + mcv_freqs = (float4 *) palloc(num_mcv * sizeof(float4)); + for (i = 0; i < num_mcv; i++) + { + mcv_values[i] = datumCopy(track[i].value, + stats->attr->attbyval, + stats->attr->attlen); + mcv_freqs[i] = (double) track[i].count / (double) numrows; + } + MemoryContextSwitchTo(old_context); + + stats->stakind[0] = STATISTIC_KIND_MCV; + stats->staop[0] = stats->eqopr; + stats->stanumbers[0] = mcv_freqs; + stats->numnumbers[0] = num_mcv; + stats->stavalues[0] = mcv_values; + stats->numvalues[0] = num_mcv; } - memcpy(DatumGetPointer(*bucket), DatumGetPointer(value), len); } + + /* We don't need to bother cleaning up any of our temporary palloc's */ } /* - * update_attstats() -- update attribute statistics for one relation + * compute_scalar_stats() -- compute column statistics * - * Statistics are stored in several places: the pg_class row for the - * relation has stats about the whole relation, the pg_attribute rows - * for each attribute store "dispersion", and there is a pg_statistic - * row for each (non-system) attribute. (Dispersion probably ought to - * be moved to pg_statistic, but it's not worth doing unless there's - * another reason to have to change pg_attribute.) The pg_class values - * are updated by VACUUM, not here. - * - * We violate no-overwrite semantics here by storing new values for - * the dispersion column directly into the pg_attribute tuple that's - * already on the page. The reason for this is that if we updated - * these tuples in the usual way, vacuuming pg_attribute itself - * wouldn't work very well --- by the time we got done with a vacuum - * cycle, most of the tuples in pg_attribute would've been obsoleted. - * Updating pg_attribute's own statistics would be especially tricky. - * Of course, this only works for fixed-size never-null columns, but - * dispersion is. + * We use this when we can find "=" and "<" operators for the datatype. * - * pg_statistic rows are just added normally. This means that - * pg_statistic will probably contain some deleted rows at the - * completion of a vacuum cycle, unless it happens to get vacuumed last. + * We determine the fraction of non-null rows, the average width, the + * most common values, the (estimated) number of distinct values, the + * distribution histogram, and the correlation of physical to logical order. * - * To keep things simple, we punt for pg_statistic, and don't try - * to compute or store rows for pg_statistic itself in pg_statistic. - * This could possibly be made to work, but it's not worth the trouble. + * The desired stats can be determined fairly easily after sorting the + * data values into order. */ static void -update_attstats(Oid relid, int natts, VacAttrStats *vacattrstats) +compute_scalar_stats(VacAttrStats *stats, + TupleDesc tupDesc, long totalrows, + HeapTuple *rows, int numrows) { - Relation ad, - sd; - HeapScanDesc scan; - HeapTuple atup, - stup; - ScanKeyData askey; - Form_pg_attribute attp; - - ad = heap_openr(AttributeRelationName, RowExclusiveLock); - sd = heap_openr(StatisticRelationName, RowExclusiveLock); - - /* Find pg_attribute rows for this relation */ - ScanKeyEntryInitialize(&askey, 0, Anum_pg_attribute_attrelid, - F_INT4EQ, relid); - - scan = heap_beginscan(ad, false, SnapshotNow, 1, &askey); - - while (HeapTupleIsValid(atup = heap_getnext(scan, 0))) + int i; + int null_cnt = 0; + int nonnull_cnt = 0; + int toowide_cnt = 0; + double total_width = 0; + bool is_varlena = (!stats->attr->attbyval && + stats->attr->attlen == -1); + double corr_xysum; + RegProcedure cmpFn; + SortFunctionKind cmpFnKind; + FmgrInfo f_cmpfn; + ScalarItem *values; + int values_cnt = 0; + int *tupnoLink; + ScalarMCVItem *track; + int track_cnt = 0; + int num_mcv = stats->attr->attstattarget; + + values = (ScalarItem *) palloc(numrows * sizeof(ScalarItem)); + tupnoLink = (int *) palloc(numrows * sizeof(int)); + track = (ScalarMCVItem *) palloc(num_mcv * sizeof(ScalarMCVItem)); + + SelectSortFunction(stats->ltopr, &cmpFn, &cmpFnKind); + fmgr_info(cmpFn, &f_cmpfn); + + /* Initial scan to find sortable values */ + for (i = 0; i < numrows; i++) { - int i; - VacAttrStats *stats; + HeapTuple tuple = rows[i]; + Datum value; + bool isnull; - attp = (Form_pg_attribute) GETSTRUCT(atup); - if (attp->attnum <= 0) /* skip system attributes for now */ - continue; + value = heap_getattr(tuple, stats->attnum, tupDesc, &isnull); - for (i = 0; i < natts; i++) + /* Check for null/nonnull */ + if (isnull) { - if (attp->attnum == vacattrstats[i].attr->attnum) - break; + null_cnt++; + continue; } - if (i >= natts) - continue; /* skip attr if no stats collected */ - stats = &(vacattrstats[i]); + nonnull_cnt++; - if (VacAttrStatsEqValid(stats)) + /* + * If it's a varlena field, add up widths for average width + * calculation. Note that if the value is toasted, we + * use the toasted width. We don't bother with this calculation + * if it's a fixed-width type. + */ + if (is_varlena) { - float4 selratio; /* average ratio of rows selected - * for a random constant */ - - /* Compute dispersion */ - if (stats->nonnull_cnt == 0 && stats->null_cnt == 0) + total_width += VARSIZE(DatumGetPointer(value)); + /* + * If the value is toasted, we want to detoast it just once to + * avoid repeated detoastings and resultant excess memory usage + * during the comparisons. Also, check to see if the value is + * excessively wide, and if so don't detoast at all --- just + * ignore the value. + */ + if (toast_raw_datum_size(value) > WIDTH_THRESHOLD) { - - /* - * empty relation, so put a dummy value in attdispersion - */ - selratio = 0; + toowide_cnt++; + continue; } - else if (stats->null_cnt <= 1 && stats->best_cnt == 1) - { + value = PointerGetDatum(PG_DETOAST_DATUM(value)); + } - /* - * looks like we have a unique-key attribute --- flag this - * with special -1.0 flag value. - * - * The correct dispersion is 1.0/numberOfRows, but since the - * relation row count can get updated without recomputing - * dispersion, we want to store a "symbolic" value and - * figure 1.0/numberOfRows on the fly. - */ - selratio = -1; - } - else + /* Add it to the list to be sorted */ + values[values_cnt].value = value; + values[values_cnt].tupno = values_cnt; + tupnoLink[values_cnt] = values_cnt; + values_cnt++; + } + + /* We can only compute valid stats if we found some sortable values. */ + if (values_cnt > 0) + { + int ndistinct, /* # distinct values in sample */ + nmultiple, /* # that appear multiple times */ + num_hist, + dups_cnt; + int slot_idx = 0; + + /* Sort the collected values */ + datumCmpFn = &f_cmpfn; + datumCmpFnKind = cmpFnKind; + datumCmpTupnoLink = tupnoLink; + qsort((void *) values, values_cnt, + sizeof(ScalarItem), compare_scalars); + + /* + * Now scan the values in order, find the most common ones, + * and also accumulate ordering-correlation statistics. + * + * To determine which are most common, we first have to count the + * number of duplicates of each value. The duplicates are adjacent + * in the sorted list, so a brute-force approach is to compare + * successive datum values until we find two that are not equal. + * However, that requires N-1 invocations of the datum comparison + * routine, which are completely redundant with work that was done + * during the sort. (The sort algorithm must at some point have + * compared each pair of items that are adjacent in the sorted order; + * otherwise it could not know that it's ordered the pair correctly.) + * We exploit this by having compare_scalars remember the highest + * tupno index that each ScalarItem has been found equal to. At the + * end of the sort, a ScalarItem's tupnoLink will still point to + * itself if and only if it is the last item of its group of + * duplicates (since the group will be ordered by tupno). + */ + corr_xysum = 0; + ndistinct = 0; + nmultiple = 0; + dups_cnt = 0; + for (i = 0; i < values_cnt; i++) + { + int tupno = values[i].tupno; + + corr_xysum += (double) i * (double) tupno; + dups_cnt++; + if (tupnoLink[tupno] == tupno) { - if (VacAttrStatsLtGtValid(stats) && - stats->min_cnt + stats->max_cnt == stats->nonnull_cnt) + /* Reached end of duplicates of this value */ + ndistinct++; + if (dups_cnt > 1) { + nmultiple++; + if (track_cnt < num_mcv || + dups_cnt > track[track_cnt-1].count) + { + /* + * Found a new item for the mcv list; find its + * position, bubbling down old items if needed. + * Loop invariant is that j points at an empty/ + * replaceable slot. + */ + int j; + + if (track_cnt < num_mcv) + track_cnt++; + for (j = track_cnt-1; j > 0; j--) + { + if (dups_cnt <= track[j-1].count) + break; + track[j].count = track[j-1].count; + track[j].first = track[j-1].first; + } + track[j].count = dups_cnt; + track[j].first = i + 1 - dups_cnt; + } + } + dups_cnt = 0; + } + } - /* - * exact result when there are just 1 or 2 values... - */ - double min_cnt_d = stats->min_cnt, - max_cnt_d = stats->max_cnt, - null_cnt_d = stats->null_cnt; - double total = ((double) stats->nonnull_cnt) + null_cnt_d; + stats->stats_valid = true; + /* Do the simple null-frac and width stats */ + stats->stanullfrac = (double) null_cnt / (double) numrows; + if (is_varlena) + stats->stawidth = total_width / (double) nonnull_cnt; + else + stats->stawidth = stats->attrtype->typlen; - selratio = (min_cnt_d * min_cnt_d + max_cnt_d * max_cnt_d + null_cnt_d * null_cnt_d) / (total * total); - } - else - { - double most = (double) (stats->best_cnt > stats->null_cnt ? stats->best_cnt : stats->null_cnt); - double total = ((double) stats->nonnull_cnt) + ((double) stats->null_cnt); + if (nmultiple == 0) + { + /* If we found no repeated values, assume it's a unique column */ + stats->stadistinct = -1.0; + } + else if (toowide_cnt == 0 && nmultiple == ndistinct) + { + /* + * Every value in the sample appeared more than once. Assume the + * column has just these values. + */ + stats->stadistinct = ndistinct; + } + else + { + /*---------- + * Estimate the number of distinct values using the estimator + * proposed by Chaudhuri et al (see citation above). This is + * sqrt(n/r) * max(f1,1) + f2 + f3 + ... + * where fk is the number of distinct values that occurred + * exactly k times in our sample of r rows (from a total of n). + * Overwidth values are assumed to have been distinct. + *---------- + */ + int f1 = ndistinct - nmultiple + toowide_cnt; + double term1; - /* - * we assume count of other values are 20% of best - * count in table - */ - selratio = (most * most + 0.20 * most * (total - most)) / (total * total); - } - /* Make sure calculated values are in-range */ - if (selratio < 0.0) - selratio = 0.0; - else if (selratio > 1.0) - selratio = 1.0; + if (f1 < 1) + f1 = 1; + term1 = sqrt((double) totalrows / (double) numrows) * f1; + stats->stadistinct = floor(term1 + nmultiple + 0.5); + } + + /* + * If we estimated the number of distinct values at more than 10% + * of the total row count (a very arbitrary limit), then assume + * that stadistinct should scale with the row count rather than be + * a fixed value. + */ + if (stats->stadistinct > 0.1 * totalrows) + stats->stadistinct = - (stats->stadistinct / totalrows); + + /* Generate an MCV slot entry, only if we found multiples */ + if (nmultiple < num_mcv) + num_mcv = nmultiple; + Assert(track_cnt >= num_mcv); + if (num_mcv > 0) + { + MemoryContext old_context; + Datum *mcv_values; + float4 *mcv_freqs; + + /* Must copy the target values into TransactionCommandContext */ + old_context = MemoryContextSwitchTo(TransactionCommandContext); + mcv_values = (Datum *) palloc(num_mcv * sizeof(Datum)); + mcv_freqs = (float4 *) palloc(num_mcv * sizeof(float4)); + for (i = 0; i < num_mcv; i++) + { + mcv_values[i] = datumCopy(values[track[i].first].value, + stats->attr->attbyval, + stats->attr->attlen); + mcv_freqs[i] = (double) track[i].count / (double) numrows; } + MemoryContextSwitchTo(old_context); + + stats->stakind[slot_idx] = STATISTIC_KIND_MCV; + stats->staop[slot_idx] = stats->eqopr; + stats->stanumbers[slot_idx] = mcv_freqs; + stats->numnumbers[slot_idx] = num_mcv; + stats->stavalues[slot_idx] = mcv_values; + stats->numvalues[slot_idx] = num_mcv; + slot_idx++; + } - /* overwrite the existing statistics in the tuple */ - attp->attdispersion = selratio; + /* + * Generate a histogram slot entry if there are at least two + * distinct values not accounted for in the MCV list. (This + * ensures the histogram won't collapse to empty or a singleton.) + */ + num_hist = ndistinct - num_mcv; + if (num_hist > stats->attr->attstattarget) + num_hist = stats->attr->attstattarget + 1; + if (num_hist >= 2) + { + MemoryContext old_context; + Datum *hist_values; + int nvals; - /* invalidate the tuple in the cache and write the buffer */ - RelationInvalidateHeapTuple(ad, atup); - WriteNoReleaseBuffer(scan->rs_cbuf); + /* Sort the MCV items into position order to speed next loop */ + qsort((void *) track, num_mcv, + sizeof(ScalarMCVItem), compare_mcvs); /* - * Create pg_statistic tuples for the relation, if we have - * gathered the right data. del_stats() previously deleted - * all the pg_statistic tuples for the rel, so we just have to - * insert new ones here. + * Collapse out the MCV items from the values[] array. * - * Note analyze_rel() has seen to it that we won't come here when - * vacuuming pg_statistic itself. + * Note we destroy the values[] array here... but we don't need + * it for anything more. We do, however, still need values_cnt. */ - if (VacAttrStatsLtGtValid(stats) && stats->initialized) + if (num_mcv > 0) { - float4 nullratio; - float4 bestratio; - FmgrInfo out_function; - char *out_string; - double best_cnt_d = stats->best_cnt, - null_cnt_d = stats->null_cnt, - nonnull_cnt_d = stats->nonnull_cnt; /* prevent overflow */ - Datum values[Natts_pg_statistic]; - char nulls[Natts_pg_statistic]; - Relation irelations[Num_pg_statistic_indices]; + int src, + dest; + int j; - nullratio = null_cnt_d / (nonnull_cnt_d + null_cnt_d); - bestratio = best_cnt_d / (nonnull_cnt_d + null_cnt_d); - - fmgr_info(stats->outfunc, &out_function); + src = dest = 0; + j = 0; /* index of next interesting MCV item */ + while (src < values_cnt) + { + int ncopy; + + if (j < num_mcv) + { + int first = track[j].first; + + if (src >= first) + { + /* advance past this MCV item */ + src = first + track[j].count; + j++; + continue; + } + ncopy = first - src; + } + else + { + ncopy = values_cnt - src; + } + memmove(&values[dest], &values[src], + ncopy * sizeof(ScalarItem)); + src += ncopy; + dest += ncopy; + } + nvals = dest; + } + else + nvals = values_cnt; + Assert(nvals >= num_hist); - for (i = 0; i < Natts_pg_statistic; ++i) - nulls[i] = ' '; + /* Must copy the target values into TransactionCommandContext */ + old_context = MemoryContextSwitchTo(TransactionCommandContext); + hist_values = (Datum *) palloc(num_hist * sizeof(Datum)); + for (i = 0; i < num_hist; i++) + { + int pos; - /* - * initialize values[] - */ - i = 0; - values[i++] = ObjectIdGetDatum(relid); /* starelid */ - values[i++] = Int16GetDatum(attp->attnum); /* staattnum */ - values[i++] = ObjectIdGetDatum(stats->op_cmplt); /* staop */ - values[i++] = Float4GetDatum(nullratio); /* stanullfrac */ - values[i++] = Float4GetDatum(bestratio); /* stacommonfrac */ - out_string = DatumGetCString(FunctionCall3(&out_function, - stats->best, - ObjectIdGetDatum(stats->typelem), - Int32GetDatum(stats->attr->atttypmod))); - values[i++] = DirectFunctionCall1(textin, /* stacommonval */ - CStringGetDatum(out_string)); - pfree(out_string); - out_string = DatumGetCString(FunctionCall3(&out_function, - stats->min, - ObjectIdGetDatum(stats->typelem), - Int32GetDatum(stats->attr->atttypmod))); - values[i++] = DirectFunctionCall1(textin, /* staloval */ - CStringGetDatum(out_string)); - pfree(out_string); - out_string = DatumGetCString(FunctionCall3(&out_function, - stats->max, - ObjectIdGetDatum(stats->typelem), - Int32GetDatum(stats->attr->atttypmod))); - values[i++] = DirectFunctionCall1(textin, /* stahival */ - CStringGetDatum(out_string)); - pfree(out_string); - - stup = heap_formtuple(sd->rd_att, values, nulls); - - /* store tuple and update indexes too */ - heap_insert(sd, stup); - - CatalogOpenIndices(Num_pg_statistic_indices, Name_pg_statistic_indices, irelations); - CatalogIndexInsert(irelations, Num_pg_statistic_indices, sd, stup); - CatalogCloseIndices(Num_pg_statistic_indices, irelations); - - /* release allocated space */ - pfree(DatumGetPointer(values[Anum_pg_statistic_stacommonval - 1])); - pfree(DatumGetPointer(values[Anum_pg_statistic_staloval - 1])); - pfree(DatumGetPointer(values[Anum_pg_statistic_stahival - 1])); - heap_freetuple(stup); + pos = (i * (nvals - 1)) / (num_hist - 1); + hist_values[i] = datumCopy(values[pos].value, + stats->attr->attbyval, + stats->attr->attlen); } + MemoryContextSwitchTo(old_context); + + stats->stakind[slot_idx] = STATISTIC_KIND_HISTOGRAM; + stats->staop[slot_idx] = stats->ltopr; + stats->stavalues[slot_idx] = hist_values; + stats->numvalues[slot_idx] = num_hist; + slot_idx++; + } + + /* Generate a correlation entry if there are multiple values */ + if (values_cnt > 1) + { + MemoryContext old_context; + float4 *corrs; + double corr_xsum, + corr_x2sum; + + /* Must copy the target values into TransactionCommandContext */ + old_context = MemoryContextSwitchTo(TransactionCommandContext); + corrs = (float4 *) palloc(sizeof(float4)); + MemoryContextSwitchTo(old_context); + + /*---------- + * Since we know the x and y value sets are both + * 0, 1, ..., values_cnt-1 + * we have sum(x) = sum(y) = + * (values_cnt-1)*values_cnt / 2 + * and sum(x^2) = sum(y^2) = + * (values_cnt-1)*values_cnt*(2*values_cnt-1) / 6. + *---------- + */ + corr_xsum = (double) (values_cnt-1) * (double) values_cnt / 2.0; + corr_x2sum = (double) (values_cnt-1) * (double) values_cnt * + (double) (2*values_cnt-1) / 6.0; + /* And the correlation coefficient reduces to */ + corrs[0] = (values_cnt * corr_xysum - corr_xsum * corr_xsum) / + (values_cnt * corr_x2sum - corr_xsum * corr_xsum); + + stats->stakind[slot_idx] = STATISTIC_KIND_CORRELATION; + stats->staop[slot_idx] = stats->ltopr; + stats->stanumbers[slot_idx] = corrs; + stats->numnumbers[slot_idx] = 1; + slot_idx++; } } - heap_endscan(scan); - /* close rels, but hold locks till upcoming commit */ - heap_close(ad, NoLock); - heap_close(sd, NoLock); + + /* We don't need to bother cleaning up any of our temporary palloc's */ } /* - * del_stats() -- delete pg_statistic rows for a relation + * qsort comparator for sorting ScalarItems * - * If a list of attribute numbers is given, only zap stats for those attrs. + * Aside from sorting the items, we update the datumCmpTupnoLink[] array + * whenever two ScalarItems are found to contain equal datums. The array + * is indexed by tupno; for each ScalarItem, it contains the highest + * tupno that that item's datum has been found to be equal to. This allows + * us to avoid additional comparisons in compute_scalar_stats(). */ -static void -del_stats(Oid relid, int attcnt, int *attnums) +static int +compare_scalars(const void *a, const void *b) { - Relation pgstatistic; - HeapScanDesc scan; - HeapTuple tuple; - ScanKeyData key; + Datum da = ((ScalarItem *) a)->value; + int ta = ((ScalarItem *) a)->tupno; + Datum db = ((ScalarItem *) b)->value; + int tb = ((ScalarItem *) b)->tupno; - pgstatistic = heap_openr(StatisticRelationName, RowExclusiveLock); + if (datumCmpFnKind == SORTFUNC_LT) + { + if (DatumGetBool(FunctionCall2(datumCmpFn, da, db))) + return -1; /* a < b */ + if (DatumGetBool(FunctionCall2(datumCmpFn, db, da))) + return 1; /* a > b */ + } + else + { + /* sort function is CMP or REVCMP */ + int32 compare; - ScanKeyEntryInitialize(&key, 0x0, Anum_pg_statistic_starelid, - F_OIDEQ, ObjectIdGetDatum(relid)); - scan = heap_beginscan(pgstatistic, false, SnapshotNow, 1, &key); + compare = DatumGetInt32(FunctionCall2(datumCmpFn, da, db)); + if (compare != 0) + { + if (datumCmpFnKind == SORTFUNC_REVCMP) + compare = -compare; + return compare; + } + } - while (HeapTupleIsValid(tuple = heap_getnext(scan, 0))) + /* + * The two datums are equal, so update datumCmpTupnoLink[]. + */ + if (datumCmpTupnoLink[ta] < tb) + datumCmpTupnoLink[ta] = tb; + if (datumCmpTupnoLink[tb] < ta) + datumCmpTupnoLink[tb] = ta; + + /* + * For equal datums, sort by tupno + */ + return ta - tb; +} + +/* + * qsort comparator for sorting ScalarMCVItems by position + */ +static int +compare_mcvs(const void *a, const void *b) +{ + int da = ((ScalarMCVItem *) a)->first; + int db = ((ScalarMCVItem *) b)->first; + + return da - db; +} + + +/* + * update_attstats() -- update attribute statistics for one relation + * + * Statistics are stored in several places: the pg_class row for the + * relation has stats about the whole relation, and there is a + * pg_statistic row for each (non-system) attribute that has ever + * been analyzed. The pg_class values are updated by VACUUM, not here. + * + * pg_statistic rows are just added or updated normally. This means + * that pg_statistic will probably contain some deleted rows at the + * completion of a vacuum cycle, unless it happens to get vacuumed last. + * + * To keep things simple, we punt for pg_statistic, and don't try + * to compute or store rows for pg_statistic itself in pg_statistic. + * This could possibly be made to work, but it's not worth the trouble. + * Note analyze_rel() has seen to it that we won't come here when + * vacuuming pg_statistic itself. + */ +static void +update_attstats(Oid relid, int natts, VacAttrStats **vacattrstats) +{ + Relation sd; + int attno; + + /* + * We use an ExclusiveLock on pg_statistic to ensure that only one + * backend is writing it at a time --- without that, we might have to + * deal with concurrent updates here, and it's not worth the trouble. + */ + sd = heap_openr(StatisticRelationName, ExclusiveLock); + + for (attno = 0; attno < natts; attno++) { - if (attcnt > 0) + VacAttrStats *stats = vacattrstats[attno]; + FmgrInfo out_function; + HeapTuple stup, + oldtup; + int i, k, n; + Datum values[Natts_pg_statistic]; + char nulls[Natts_pg_statistic]; + char replaces[Natts_pg_statistic]; + Relation irelations[Num_pg_statistic_indices]; + + /* Ignore attr if we weren't able to collect stats */ + if (!stats->stats_valid) + continue; + + fmgr_info(stats->attrtype->typoutput, &out_function); + + /* + * Construct a new pg_statistic tuple + */ + for (i = 0; i < Natts_pg_statistic; ++i) { - Form_pg_statistic pgs = (Form_pg_statistic) GETSTRUCT(tuple); - int i; + nulls[i] = ' '; + replaces[i] = 'r'; + } - for (i = 0; i < attcnt; i++) + i = 0; + values[i++] = ObjectIdGetDatum(relid); /* starelid */ + values[i++] = Int16GetDatum(stats->attnum); /* staattnum */ + values[i++] = Float4GetDatum(stats->stanullfrac); /* stanullfrac */ + values[i++] = Int32GetDatum(stats->stawidth); /* stawidth */ + values[i++] = Float4GetDatum(stats->stadistinct); /* stadistinct */ + for (k = 0; k < STATISTIC_NUM_SLOTS; k++) + { + values[i++] = Int16GetDatum(stats->stakind[k]); /* stakindN */ + } + for (k = 0; k < STATISTIC_NUM_SLOTS; k++) + { + values[i++] = ObjectIdGetDatum(stats->staop[k]); /* staopN */ + } + for (k = 0; k < STATISTIC_NUM_SLOTS; k++) + { + int nnum = stats->numnumbers[k]; + + if (nnum > 0) { - if (pgs->staattnum == attnums[i] + 1) - break; + Datum *numdatums = (Datum *) palloc(nnum * sizeof(Datum)); + ArrayType *arry; + + for (n = 0; n < nnum; n++) + numdatums[n] = Float4GetDatum(stats->stanumbers[k][n]); + /* XXX knows more than it should about type float4: */ + arry = construct_array(numdatums, nnum, + false, sizeof(float4), 'i'); + values[i++] = PointerGetDatum(arry); /* stanumbersN */ + } + else + { + nulls[i] = 'n'; + values[i++] = (Datum) 0; } - if (i >= attcnt) - continue; /* don't delete it */ } - simple_heap_delete(pgstatistic, &tuple->t_self); - } + for (k = 0; k < STATISTIC_NUM_SLOTS; k++) + { + int ntxt = stats->numvalues[k]; - heap_endscan(scan); + if (ntxt > 0) + { + Datum *txtdatums = (Datum *) palloc(ntxt * sizeof(Datum)); + ArrayType *arry; - /* - * Close rel, but *keep* lock; we will need to reacquire it later, so - * there's a possibility of deadlock against another VACUUM process if - * we let go now. Keeping the lock shouldn't delay any common - * operation other than an attempted VACUUM of pg_statistic itself. - */ - heap_close(pgstatistic, NoLock); + for (n = 0; n < ntxt; n++) + { + /* + * Convert data values to a text string to be inserted + * into the text array. + */ + Datum stringdatum; + + stringdatum = + FunctionCall3(&out_function, + stats->stavalues[k][n], + ObjectIdGetDatum(stats->attrtype->typelem), + Int32GetDatum(stats->attr->atttypmod)); + txtdatums[n] = DirectFunctionCall1(textin, stringdatum); + pfree(DatumGetPointer(stringdatum)); + } + /* XXX knows more than it should about type text: */ + arry = construct_array(txtdatums, ntxt, + false, -1, 'i'); + values[i++] = PointerGetDatum(arry); /* stavaluesN */ + } + else + { + nulls[i] = 'n'; + values[i++] = (Datum) 0; + } + } + + /* Is there already a pg_statistic tuple for this attribute? */ + oldtup = SearchSysCache(STATRELATT, + ObjectIdGetDatum(relid), + Int16GetDatum(stats->attnum), + 0, 0); + + if (HeapTupleIsValid(oldtup)) + { + /* Yes, replace it */ + stup = heap_modifytuple(oldtup, + sd, + values, + nulls, + replaces); + ReleaseSysCache(oldtup); + simple_heap_update(sd, &stup->t_self, stup); + } + else + { + /* No, insert new tuple */ + stup = heap_formtuple(sd->rd_att, values, nulls); + heap_insert(sd, stup); + } + + /* update indices too */ + CatalogOpenIndices(Num_pg_statistic_indices, Name_pg_statistic_indices, + irelations); + CatalogIndexInsert(irelations, Num_pg_statistic_indices, sd, stup); + CatalogCloseIndices(Num_pg_statistic_indices, irelations); + + heap_freetuple(stup); + } + + /* close rel, but hold lock till upcoming commit */ + heap_close(sd, NoLock); } |