Create a type-specific typanalyze routine for tsvector, which collects stats
on the most common individual lexemes in place of the mostly-useless default behavior of counting duplicate tsvectors. Future work: create selectivity estimation functions that actually do something with these stats. (Some other things we ought to look at doing: using the Lossy Counting algorithm in compute_minimal_stats, and using the element-counting idea for stats on regular arrays.) Jan Urbanski
This commit is contained in:
parent
6816577a78
commit
6f6d863258
@ -1,4 +1,4 @@
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<!-- $PostgreSQL: pgsql/doc/src/sgml/catalogs.sgml,v 2.167 2008/07/11 07:02:43 petere Exp $ -->
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<!-- $PostgreSQL: pgsql/doc/src/sgml/catalogs.sgml,v 2.168 2008/07/14 00:51:45 tgl Exp $ -->
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<!--
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Documentation of the system catalogs, directed toward PostgreSQL developers
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-->
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@ -6516,6 +6516,8 @@
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<entry>
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A list of the most common values in the column. (NULL if
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no values seem to be more common than any others.)
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For some datatypes such as <type>tsvector</>, this is a list of
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the most common element values rather than values of the type itself.
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</entry>
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</row>
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@ -6524,10 +6526,10 @@
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<entry><type>real[]</type></entry>
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<entry></entry>
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<entry>
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A list of the frequencies of the most common values,
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A list of the frequencies of the most common values or elements,
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i.e., number of occurrences of each divided by total number of rows.
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(NULL when <structfield>most_common_vals</structfield> is.)
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</entry>
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</entry>
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</row>
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<row>
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@ -3,7 +3,7 @@
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*
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* Copyright (c) 1996-2008, PostgreSQL Global Development Group
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*
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* $PostgreSQL: pgsql/src/backend/catalog/system_views.sql,v 1.52 2008/05/15 00:17:39 tgl Exp $
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* $PostgreSQL: pgsql/src/backend/catalog/system_views.sql,v 1.53 2008/07/14 00:51:45 tgl Exp $
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*/
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CREATE VIEW pg_roles AS
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@ -110,30 +110,30 @@ CREATE VIEW pg_stats AS
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stanullfrac AS null_frac,
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stawidth AS avg_width,
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stadistinct AS n_distinct,
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CASE 1
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WHEN stakind1 THEN stavalues1
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WHEN stakind2 THEN stavalues2
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WHEN stakind3 THEN stavalues3
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WHEN stakind4 THEN stavalues4
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END AS most_common_vals,
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CASE 1
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WHEN stakind1 THEN stanumbers1
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WHEN stakind2 THEN stanumbers2
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WHEN stakind3 THEN stanumbers3
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WHEN stakind4 THEN stanumbers4
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END AS most_common_freqs,
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CASE 2
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WHEN stakind1 THEN stavalues1
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WHEN stakind2 THEN stavalues2
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WHEN stakind3 THEN stavalues3
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WHEN stakind4 THEN stavalues4
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END AS histogram_bounds,
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CASE 3
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WHEN stakind1 THEN stanumbers1[1]
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WHEN stakind2 THEN stanumbers2[1]
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WHEN stakind3 THEN stanumbers3[1]
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WHEN stakind4 THEN stanumbers4[1]
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END AS correlation
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CASE
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WHEN stakind1 IN (1, 4) THEN stavalues1
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WHEN stakind2 IN (1, 4) THEN stavalues2
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WHEN stakind3 IN (1, 4) THEN stavalues3
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WHEN stakind4 IN (1, 4) THEN stavalues4
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END AS most_common_vals,
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CASE
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WHEN stakind1 IN (1, 4) THEN stanumbers1
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WHEN stakind2 IN (1, 4) THEN stanumbers2
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WHEN stakind3 IN (1, 4) THEN stanumbers3
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WHEN stakind4 IN (1, 4) THEN stanumbers4
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END AS most_common_freqs,
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CASE
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WHEN stakind1 = 2 THEN stavalues1
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WHEN stakind2 = 2 THEN stavalues2
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WHEN stakind3 = 2 THEN stavalues3
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WHEN stakind4 = 2 THEN stavalues4
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END AS histogram_bounds,
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CASE
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WHEN stakind1 = 3 THEN stanumbers1[1]
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WHEN stakind2 = 3 THEN stanumbers2[1]
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WHEN stakind3 = 3 THEN stanumbers3[1]
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WHEN stakind4 = 3 THEN stanumbers4[1]
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END AS correlation
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FROM pg_statistic s JOIN pg_class c ON (c.oid = s.starelid)
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JOIN pg_attribute a ON (c.oid = attrelid AND attnum = s.staattnum)
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LEFT JOIN pg_namespace n ON (n.oid = c.relnamespace)
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@ -4,7 +4,7 @@
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#
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# Copyright (c) 2006-2008, PostgreSQL Global Development Group
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#
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# $PostgreSQL: pgsql/src/backend/tsearch/Makefile,v 1.6 2008/02/19 10:30:08 petere Exp $
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# $PostgreSQL: pgsql/src/backend/tsearch/Makefile,v 1.7 2008/07/14 00:51:45 tgl Exp $
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#
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#-------------------------------------------------------------------------
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subdir = src/backend/tsearch
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@ -19,7 +19,7 @@ DICTFILES=synonym_sample.syn thesaurus_sample.ths hunspell_sample.affix \
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OBJS = ts_locale.o ts_parse.o wparser.o wparser_def.o dict.o \
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dict_simple.o dict_synonym.o dict_thesaurus.o \
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dict_ispell.o regis.o spell.o \
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to_tsany.o ts_utils.o
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to_tsany.o ts_typanalyze.o ts_utils.o
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include $(top_srcdir)/src/backend/common.mk
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src/backend/tsearch/ts_typanalyze.c
Normal file
403
src/backend/tsearch/ts_typanalyze.c
Normal file
@ -0,0 +1,403 @@
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/*-------------------------------------------------------------------------
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*
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* ts_typanalyze.c
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* functions for gathering statistics from tsvector columns
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*
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* Portions Copyright (c) 1996-2008, PostgreSQL Global Development Group
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*
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*
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* IDENTIFICATION
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* $PostgreSQL: pgsql/src/backend/tsearch/ts_typanalyze.c,v 1.1 2008/07/14 00:51:45 tgl Exp $
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*
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*-------------------------------------------------------------------------
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*/
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#include "postgres.h"
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#include "access/hash.h"
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#include "catalog/pg_operator.h"
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#include "commands/vacuum.h"
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#include "tsearch/ts_type.h"
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#include "utils/builtins.h"
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#include "utils/hsearch.h"
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/* A hash key for lexemes */
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typedef struct
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{
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char *lexeme; /* lexeme (not NULL terminated!) */
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int length; /* its length in bytes */
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} LexemeHashKey;
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/* A hash table entry for the Lossy Counting algorithm */
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typedef struct
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{
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LexemeHashKey key; /* This is 'e' from the LC algorithm. */
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int frequency; /* This is 'f'. */
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int delta; /* And this is 'delta'. */
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} TrackItem;
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static void compute_tsvector_stats(VacAttrStats *stats,
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AnalyzeAttrFetchFunc fetchfunc,
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int samplerows,
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double totalrows);
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static void prune_lexemes_hashtable(HTAB *lexemes_tab, int b_current);
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static uint32 lexeme_hash(const void *key, Size keysize);
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static int lexeme_match(const void *key1, const void *key2, Size keysize);
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static int trackitem_compare_desc(const void *e1, const void *e2);
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/*
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* ts_typanalyze -- a custom typanalyze function for tsvector columns
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*/
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Datum
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ts_typanalyze(PG_FUNCTION_ARGS)
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{
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VacAttrStats *stats = (VacAttrStats *) PG_GETARG_POINTER(0);
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Form_pg_attribute attr = stats->attr;
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/* If the attstattarget column is negative, use the default value */
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/* NB: it is okay to scribble on stats->attr since it's a copy */
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if (attr->attstattarget < 0)
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attr->attstattarget = default_statistics_target;
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stats->compute_stats = compute_tsvector_stats;
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/* see comment about the choice of minrows from analyze.c */
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stats->minrows = 300 * attr->attstattarget;
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PG_RETURN_BOOL(true);
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}
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/*
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* compute_tsvector_stats() -- compute statistics for a tsvector column
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*
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* This functions computes statistics that are useful for determining @@
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* operations' selectivity, along with the fraction of non-null rows and
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* average width.
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*
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* Instead of finding the most common values, as we do for most datatypes,
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* we're looking for the most common lexemes. This is more useful, because
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* there most probably won't be any two rows with the same tsvector and thus
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* the notion of a MCV is a bit bogus with this datatype. With a list of the
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* most common lexemes we can do a better job at figuring out @@ selectivity.
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*
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* For the same reasons we assume that tsvector columns are unique when
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* determining the number of distinct values.
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*
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* The algorithm used is Lossy Counting, as proposed in the paper "Approximate
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* frequency counts over data streams" by G. S. Manku and R. Motwani, in
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* Proceedings of the 28th International Conference on Very Large Data Bases,
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* Hong Kong, China, August 2002, section 4.2. The paper is available at
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* http://www.vldb.org/conf/2002/S10P03.pdf
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*
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* The Lossy Counting (aka LC) algorithm goes like this:
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* Let D be a set of triples (e, f, d), where e is an element value, f is
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* that element's frequency (occurrence count) and d is the maximum error in
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* f. We start with D empty and process the elements in batches of size
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* w. (The batch size is also known as "bucket size".) Let the current batch
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* number be b_current, starting with 1. For each element e we either
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* increment its f count, if it's already in D, or insert a new triple into D
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* with values (e, 1, b_current - 1). After processing each batch we prune D,
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* by removing from it all elements with f + d <= b_current. Finally, we
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* gather elements with largest f. The LC paper proves error bounds on f
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* dependent on the batch size w, and shows that the required table size
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* is no more than a few times w.
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*
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* We use a hashtable for the D structure and a bucket width of
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* statistic_target * 100, where 100 is an arbitrarily chosen constant, meant
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* to approximate the number of lexemes in a single tsvector.
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*/
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static void
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compute_tsvector_stats(VacAttrStats *stats,
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AnalyzeAttrFetchFunc fetchfunc,
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int samplerows,
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double totalrows)
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{
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int num_mcelem;
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int null_cnt = 0;
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double total_width = 0;
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/* This is D from the LC algorithm. */
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HTAB *lexemes_tab;
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HASHCTL hash_ctl;
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HASH_SEQ_STATUS scan_status;
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/* This is the current bucket number from the LC algorithm */
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int b_current;
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/* This is 'w' from the LC algorithm */
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int bucket_width;
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int vector_no,
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lexeme_no;
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LexemeHashKey hash_key;
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TrackItem *item;
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/* We want statistic_target * 100 lexemes in the MCELEM array */
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num_mcelem = stats->attr->attstattarget * 100;
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/*
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* We set bucket width equal to the target number of result lexemes.
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* This is probably about right but perhaps might need to be scaled
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* up or down a bit?
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*/
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bucket_width = num_mcelem;
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/*
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* Create the hashtable. It will be in local memory, so we don't need to
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* worry about initial size too much. Also we don't need to pay any
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* attention to locking and memory management.
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*/
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MemSet(&hash_ctl, 0, sizeof(hash_ctl));
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hash_ctl.keysize = sizeof(LexemeHashKey);
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hash_ctl.entrysize = sizeof(TrackItem);
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hash_ctl.hash = lexeme_hash;
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hash_ctl.match = lexeme_match;
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hash_ctl.hcxt = CurrentMemoryContext;
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lexemes_tab = hash_create("Analyzed lexemes table",
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bucket_width * 4,
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&hash_ctl,
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HASH_ELEM | HASH_FUNCTION | HASH_COMPARE | HASH_CONTEXT);
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/* Initialize counters. */
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b_current = 1;
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lexeme_no = 1;
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/* Loop over the tsvectors. */
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for (vector_no = 0; vector_no < samplerows; vector_no++)
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{
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Datum value;
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bool isnull;
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TSVector vector;
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WordEntry *curentryptr;
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char *lexemesptr;
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int j;
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vacuum_delay_point();
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value = fetchfunc(stats, vector_no, &isnull);
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/*
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* Check for null/nonnull.
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*/
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if (isnull)
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{
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null_cnt++;
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continue;
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}
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/*
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* Add up widths for average-width calculation. Since it's a
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* tsvector, we know it's varlena. As in the regular
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* compute_minimal_stats function, we use the toasted width for this
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* calculation.
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*/
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total_width += VARSIZE_ANY(DatumGetPointer(value));
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/*
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* Now detoast the tsvector if needed.
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*/
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vector = DatumGetTSVector(value);
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/*
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* We loop through the lexemes in the tsvector and add them to our
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* tracking hashtable. Note: the hashtable entries will point into
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* the (detoasted) tsvector value, therefore we cannot free that
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* storage until we're done.
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*/
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lexemesptr = STRPTR(vector);
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curentryptr = ARRPTR(vector);
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for (j = 0; j < vector->size; j++)
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{
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bool found;
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/* Construct a hash key */
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hash_key.lexeme = lexemesptr + curentryptr->pos;
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hash_key.length = curentryptr->len;
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/* Lookup current lexeme in hashtable, adding it if new */
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item = (TrackItem *) hash_search(lexemes_tab,
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(const void *) &hash_key,
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HASH_ENTER, &found);
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if (found)
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{
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/* The lexeme is already on the tracking list */
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item->frequency++;
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}
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else
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{
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/* Initialize new tracking list element */
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item->frequency = 1;
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item->delta = b_current - 1;
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}
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/* We prune the D structure after processing each bucket */
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if (lexeme_no % bucket_width == 0)
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{
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prune_lexemes_hashtable(lexemes_tab, b_current);
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b_current++;
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}
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/* Advance to the next WordEntry in the tsvector */
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lexeme_no++;
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curentryptr++;
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}
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}
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/* We can only compute real stats if we found some non-null values. */
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if (null_cnt < samplerows)
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{
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int nonnull_cnt = samplerows - null_cnt;
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int i;
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TrackItem **sort_table;
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||||
int track_len;
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stats->stats_valid = true;
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/* Do the simple null-frac and average width stats */
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stats->stanullfrac = (double) null_cnt / (double) samplerows;
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stats->stawidth = total_width / (double) nonnull_cnt;
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||||
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||||
/* Assume it's a unique column (see notes above) */
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stats->stadistinct = -1.0;
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||||
/*
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* Determine the top-N lexemes by simply copying pointers from the
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* hashtable into an array and applying qsort()
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||||
*/
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||||
track_len = hash_get_num_entries(lexemes_tab);
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sort_table = (TrackItem **) palloc(sizeof(TrackItem *) * track_len);
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||||
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||||
hash_seq_init(&scan_status, lexemes_tab);
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||||
i = 0;
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||||
while ((item = (TrackItem *) hash_seq_search(&scan_status)) != NULL)
|
||||
{
|
||||
sort_table[i++] = item;
|
||||
}
|
||||
Assert(i == track_len);
|
||||
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||||
qsort(sort_table, track_len, sizeof(TrackItem *),
|
||||
trackitem_compare_desc);
|
||||
|
||||
/* Suppress any single-occurrence items */
|
||||
while (track_len > 0)
|
||||
{
|
||||
if (sort_table[track_len-1]->frequency > 1)
|
||||
break;
|
||||
track_len--;
|
||||
}
|
||||
|
||||
/* Determine the number of most common lexemes to be stored */
|
||||
if (num_mcelem > track_len)
|
||||
num_mcelem = track_len;
|
||||
|
||||
/* Generate MCELEM slot entry */
|
||||
if (num_mcelem > 0)
|
||||
{
|
||||
MemoryContext old_context;
|
||||
Datum *mcelem_values;
|
||||
float4 *mcelem_freqs;
|
||||
|
||||
/* Must copy the target values into anl_context */
|
||||
old_context = MemoryContextSwitchTo(stats->anl_context);
|
||||
mcelem_values = (Datum *) palloc(num_mcelem * sizeof(Datum));
|
||||
mcelem_freqs = (float4 *) palloc(num_mcelem * sizeof(float4));
|
||||
|
||||
for (i = 0; i < num_mcelem; i++)
|
||||
{
|
||||
TrackItem *item = sort_table[i];
|
||||
|
||||
mcelem_values[i] =
|
||||
PointerGetDatum(cstring_to_text_with_len(item->key.lexeme,
|
||||
item->key.length));
|
||||
mcelem_freqs[i] = (double) item->frequency / (double) nonnull_cnt;
|
||||
}
|
||||
MemoryContextSwitchTo(old_context);
|
||||
|
||||
stats->stakind[0] = STATISTIC_KIND_MCELEM;
|
||||
stats->staop[0] = TextEqualOperator;
|
||||
stats->stanumbers[0] = mcelem_freqs;
|
||||
stats->numnumbers[0] = num_mcelem;
|
||||
stats->stavalues[0] = mcelem_values;
|
||||
stats->numvalues[0] = num_mcelem;
|
||||
/* We are storing text values */
|
||||
stats->statypid[0] = TEXTOID;
|
||||
stats->statyplen[0] = -1; /* typlen, -1 for varlena */
|
||||
stats->statypbyval[0] = false;
|
||||
stats->statypalign[0] = 'i';
|
||||
}
|
||||
}
|
||||
else
|
||||
{
|
||||
/* We found only nulls; assume the column is entirely null */
|
||||
stats->stats_valid = true;
|
||||
stats->stanullfrac = 1.0;
|
||||
stats->stawidth = 0; /* "unknown" */
|
||||
stats->stadistinct = 0.0; /* "unknown" */
|
||||
}
|
||||
|
||||
/*
|
||||
* We don't need to bother cleaning up any of our temporary palloc's.
|
||||
* The hashtable should also go away, as it used a child memory context.
|
||||
*/
|
||||
}
|
||||
|
||||
/*
|
||||
* A function to prune the D structure from the Lossy Counting algorithm.
|
||||
* Consult compute_tsvector_stats() for wider explanation.
|
||||
*/
|
||||
static void
|
||||
prune_lexemes_hashtable(HTAB *lexemes_tab, int b_current)
|
||||
{
|
||||
HASH_SEQ_STATUS scan_status;
|
||||
TrackItem *item;
|
||||
|
||||
hash_seq_init(&scan_status, lexemes_tab);
|
||||
while ((item = (TrackItem *) hash_seq_search(&scan_status)) != NULL)
|
||||
{
|
||||
if (item->frequency + item->delta <= b_current)
|
||||
{
|
||||
if (hash_search(lexemes_tab, (const void *) &item->key,
|
||||
HASH_REMOVE, NULL) == NULL)
|
||||
elog(ERROR, "hash table corrupted");
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/*
|
||||
* Hash functions for lexemes. They are strings, but not NULL terminated,
|
||||
* so we need a special hash function.
|
||||
*/
|
||||
static uint32
|
||||
lexeme_hash(const void *key, Size keysize)
|
||||
{
|
||||
const LexemeHashKey *l = (const LexemeHashKey *) key;
|
||||
|
||||
return DatumGetUInt32(hash_any((const unsigned char *) l->lexeme,
|
||||
l->length));
|
||||
}
|
||||
|
||||
/*
|
||||
* Matching function for lexemes, to be used in hashtable lookups.
|
||||
*/
|
||||
static int
|
||||
lexeme_match(const void *key1, const void *key2, Size keysize)
|
||||
{
|
||||
const LexemeHashKey *d1 = (const LexemeHashKey *) key1;
|
||||
const LexemeHashKey *d2 = (const LexemeHashKey *) key2;
|
||||
|
||||
/* The lexemes need to have the same length, and be memcmp-equal */
|
||||
if (d1->length == d2->length &&
|
||||
memcmp(d1->lexeme, d2->lexeme, d1->length) == 0)
|
||||
return 0;
|
||||
else
|
||||
return 1;
|
||||
}
|
||||
|
||||
/*
|
||||
* qsort() comparator for TrackItems - LC style (descending sort)
|
||||
*/
|
||||
static int
|
||||
trackitem_compare_desc(const void *e1, const void *e2)
|
||||
{
|
||||
const TrackItem * const *t1 = (const TrackItem * const *) e1;
|
||||
const TrackItem * const *t2 = (const TrackItem * const *) e2;
|
||||
|
||||
return (*t2)->frequency - (*t1)->frequency;
|
||||
}
|
@ -37,7 +37,7 @@
|
||||
* Portions Copyright (c) 1996-2008, PostgreSQL Global Development Group
|
||||
* Portions Copyright (c) 1994, Regents of the University of California
|
||||
*
|
||||
* $PostgreSQL: pgsql/src/include/catalog/catversion.h,v 1.466 2008/07/11 21:06:29 tgl Exp $
|
||||
* $PostgreSQL: pgsql/src/include/catalog/catversion.h,v 1.467 2008/07/14 00:51:45 tgl Exp $
|
||||
*
|
||||
*-------------------------------------------------------------------------
|
||||
*/
|
||||
@ -53,6 +53,6 @@
|
||||
*/
|
||||
|
||||
/* yyyymmddN */
|
||||
#define CATALOG_VERSION_NO 200807111
|
||||
#define CATALOG_VERSION_NO 200807131
|
||||
|
||||
#endif
|
||||
|
@ -8,7 +8,7 @@
|
||||
* Portions Copyright (c) 1996-2008, PostgreSQL Global Development Group
|
||||
* Portions Copyright (c) 1994, Regents of the University of California
|
||||
*
|
||||
* $PostgreSQL: pgsql/src/include/catalog/pg_operator.h,v 1.160 2008/06/17 19:10:56 tgl Exp $
|
||||
* $PostgreSQL: pgsql/src/include/catalog/pg_operator.h,v 1.161 2008/07/14 00:51:45 tgl Exp $
|
||||
*
|
||||
* NOTES
|
||||
* the genbki.sh script reads this file and generates .bki
|
||||
@ -105,6 +105,7 @@ DATA(insert OID = 95 ( "<" PGNSP PGUID b f f 21 21 16 520 524 int2lt scalar
|
||||
DATA(insert OID = 96 ( "=" PGNSP PGUID b t t 23 23 16 96 518 int4eq eqsel eqjoinsel ));
|
||||
DATA(insert OID = 97 ( "<" PGNSP PGUID b f f 23 23 16 521 525 int4lt scalarltsel scalarltjoinsel ));
|
||||
DATA(insert OID = 98 ( "=" PGNSP PGUID b t t 25 25 16 98 531 texteq eqsel eqjoinsel ));
|
||||
#define TextEqualOperator 98
|
||||
|
||||
DATA(insert OID = 349 ( "||" PGNSP PGUID b f f 2277 2283 2277 0 0 array_append - - ));
|
||||
DATA(insert OID = 374 ( "||" PGNSP PGUID b f f 2283 2277 2277 0 0 array_prepend - - ));
|
||||
|
@ -7,7 +7,7 @@
|
||||
* Portions Copyright (c) 1996-2008, PostgreSQL Global Development Group
|
||||
* Portions Copyright (c) 1994, Regents of the University of California
|
||||
*
|
||||
* $PostgreSQL: pgsql/src/include/catalog/pg_proc.h,v 1.504 2008/07/03 20:58:46 tgl Exp $
|
||||
* $PostgreSQL: pgsql/src/include/catalog/pg_proc.h,v 1.505 2008/07/14 00:51:45 tgl Exp $
|
||||
*
|
||||
* NOTES
|
||||
* The script catalog/genbki.sh reads this file and generates .bki
|
||||
@ -4313,6 +4313,9 @@ DESCR("GiST tsquery support");
|
||||
DATA(insert OID = 3701 ( gtsquery_consistent PGNSP PGUID 12 1 0 f f t f i 5 16 "2281 2281 23 26 2281" _null_ _null_ _null_ gtsquery_consistent - _null_ _null_ ));
|
||||
DESCR("GiST tsquery support");
|
||||
|
||||
DATA(insert OID = 3688 ( ts_typanalyze PGNSP PGUID 12 1 0 f f t f s 1 16 "2281" _null_ _null_ _null_ ts_typanalyze - _null_ _null_ ));
|
||||
DESCR("tsvector typanalyze");
|
||||
|
||||
DATA(insert OID = 3689 ( ts_stat PGNSP PGUID 12 10 10000 f f t t v 1 2249 "25" "{25,25,23,23}" "{i,o,o,o}" "{query,word,ndoc,nentry}" ts_stat1 - _null_ _null_ ));
|
||||
DESCR("statistics of tsvector column");
|
||||
DATA(insert OID = 3690 ( ts_stat PGNSP PGUID 12 10 10000 f f t t v 2 2249 "25 25" "{25,25,25,23,23}" "{i,i,o,o,o}" "{query,weights,word,ndoc,nentry}" ts_stat2 - _null_ _null_ ));
|
||||
|
@ -8,7 +8,7 @@
|
||||
* Portions Copyright (c) 1996-2008, PostgreSQL Global Development Group
|
||||
* Portions Copyright (c) 1994, Regents of the University of California
|
||||
*
|
||||
* $PostgreSQL: pgsql/src/include/catalog/pg_statistic.h,v 1.35 2008/03/27 03:57:34 tgl Exp $
|
||||
* $PostgreSQL: pgsql/src/include/catalog/pg_statistic.h,v 1.36 2008/07/14 00:51:45 tgl Exp $
|
||||
*
|
||||
* NOTES
|
||||
* the genbki.sh script reads this file and generates .bki
|
||||
@ -237,4 +237,19 @@ typedef FormData_pg_statistic *Form_pg_statistic;
|
||||
*/
|
||||
#define STATISTIC_KIND_CORRELATION 3
|
||||
|
||||
/*
|
||||
* A "most common elements" slot is similar to a "most common values" slot,
|
||||
* except that it stores the most common non-null *elements* of the column
|
||||
* values. This is useful when the column datatype is an array or some other
|
||||
* type with identifiable elements (for instance, tsvector). staop contains
|
||||
* the equality operator appropriate to the element type. stavalues contains
|
||||
* the most common element values, and stanumbers their frequencies, with the
|
||||
* same rules as for MCV slots.
|
||||
*
|
||||
* Note: in current usage for tsvector columns, the stavalues elements are of
|
||||
* type text, even though their representation within tsvector is not
|
||||
* exactly text.
|
||||
*/
|
||||
#define STATISTIC_KIND_MCELEM 4
|
||||
|
||||
#endif /* PG_STATISTIC_H */
|
||||
|
@ -8,7 +8,7 @@
|
||||
* Portions Copyright (c) 1996-2008, PostgreSQL Global Development Group
|
||||
* Portions Copyright (c) 1994, Regents of the University of California
|
||||
*
|
||||
* $PostgreSQL: pgsql/src/include/catalog/pg_type.h,v 1.196 2008/06/24 17:58:27 tgl Exp $
|
||||
* $PostgreSQL: pgsql/src/include/catalog/pg_type.h,v 1.197 2008/07/14 00:51:45 tgl Exp $
|
||||
*
|
||||
* NOTES
|
||||
* the genbki.sh script reads this file and generates .bki
|
||||
@ -543,7 +543,7 @@ DESCR("UUID datatype");
|
||||
DATA(insert OID = 2951 ( _uuid PGNSP PGUID -1 f b t \054 0 2950 0 array_in array_out array_recv array_send - - - i x f 0 -1 0 _null_ _null_ ));
|
||||
|
||||
/* text search */
|
||||
DATA(insert OID = 3614 ( tsvector PGNSP PGUID -1 f b t \054 0 0 3643 tsvectorin tsvectorout tsvectorrecv tsvectorsend - - - i x f 0 -1 0 _null_ _null_ ));
|
||||
DATA(insert OID = 3614 ( tsvector PGNSP PGUID -1 f b t \054 0 0 3643 tsvectorin tsvectorout tsvectorrecv tsvectorsend - - ts_typanalyze i x f 0 -1 0 _null_ _null_ ));
|
||||
DESCR("text representation for text search");
|
||||
#define TSVECTOROID 3614
|
||||
DATA(insert OID = 3642 ( gtsvector PGNSP PGUID -1 f b t \054 0 0 3644 gtsvectorin gtsvectorout - - - - - i p f 0 -1 0 _null_ _null_ ));
|
||||
|
@ -5,7 +5,7 @@
|
||||
*
|
||||
* Copyright (c) 1998-2008, PostgreSQL Global Development Group
|
||||
*
|
||||
* $PostgreSQL: pgsql/src/include/tsearch/ts_type.h,v 1.12 2008/06/10 08:55:50 heikki Exp $
|
||||
* $PostgreSQL: pgsql/src/include/tsearch/ts_type.h,v 1.13 2008/07/14 00:51:45 tgl Exp $
|
||||
*
|
||||
*-------------------------------------------------------------------------
|
||||
*/
|
||||
@ -153,6 +153,8 @@ extern Datum ts_rankcd_wtt(PG_FUNCTION_ARGS);
|
||||
extern Datum ts_rankcd_ttf(PG_FUNCTION_ARGS);
|
||||
extern Datum ts_rankcd_wttf(PG_FUNCTION_ARGS);
|
||||
|
||||
extern Datum ts_typanalyze(PG_FUNCTION_ARGS);
|
||||
|
||||
|
||||
/*
|
||||
* TSQuery
|
||||
|
@ -1276,8 +1276,8 @@ drop table cchild;
|
||||
-- Check that ruleutils are working
|
||||
--
|
||||
SELECT viewname, definition FROM pg_views WHERE schemaname <> 'information_schema' ORDER BY viewname;
|
||||
viewname | definition
|
||||
--------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
viewname | definition
|
||||
--------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
|
||||
iexit | SELECT ih.name, ih.thepath, interpt_pp(ih.thepath, r.thepath) AS exit FROM ihighway ih, ramp r WHERE (ih.thepath ## r.thepath);
|
||||
pg_cursors | SELECT c.name, c.statement, c.is_holdable, c.is_binary, c.is_scrollable, c.creation_time FROM pg_cursor() c(name text, statement text, is_holdable boolean, is_binary boolean, is_scrollable boolean, creation_time timestamp with time zone);
|
||||
pg_group | SELECT pg_authid.rolname AS groname, pg_authid.oid AS grosysid, ARRAY(SELECT pg_auth_members.member FROM pg_auth_members WHERE (pg_auth_members.roleid = pg_authid.oid)) AS grolist FROM pg_authid WHERE (NOT pg_authid.rolcanlogin);
|
||||
@ -1308,7 +1308,7 @@ SELECT viewname, definition FROM pg_views WHERE schemaname <> 'information_schem
|
||||
pg_statio_user_indexes | SELECT pg_statio_all_indexes.relid, pg_statio_all_indexes.indexrelid, pg_statio_all_indexes.schemaname, pg_statio_all_indexes.relname, pg_statio_all_indexes.indexrelname, pg_statio_all_indexes.idx_blks_read, pg_statio_all_indexes.idx_blks_hit FROM pg_statio_all_indexes WHERE ((pg_statio_all_indexes.schemaname <> ALL (ARRAY['pg_catalog'::name, 'information_schema'::name])) AND (pg_statio_all_indexes.schemaname !~ '^pg_toast'::text));
|
||||
pg_statio_user_sequences | SELECT pg_statio_all_sequences.relid, pg_statio_all_sequences.schemaname, pg_statio_all_sequences.relname, pg_statio_all_sequences.blks_read, pg_statio_all_sequences.blks_hit FROM pg_statio_all_sequences WHERE ((pg_statio_all_sequences.schemaname <> ALL (ARRAY['pg_catalog'::name, 'information_schema'::name])) AND (pg_statio_all_sequences.schemaname !~ '^pg_toast'::text));
|
||||
pg_statio_user_tables | SELECT pg_statio_all_tables.relid, pg_statio_all_tables.schemaname, pg_statio_all_tables.relname, pg_statio_all_tables.heap_blks_read, pg_statio_all_tables.heap_blks_hit, pg_statio_all_tables.idx_blks_read, pg_statio_all_tables.idx_blks_hit, pg_statio_all_tables.toast_blks_read, pg_statio_all_tables.toast_blks_hit, pg_statio_all_tables.tidx_blks_read, pg_statio_all_tables.tidx_blks_hit FROM pg_statio_all_tables WHERE ((pg_statio_all_tables.schemaname <> ALL (ARRAY['pg_catalog'::name, 'information_schema'::name])) AND (pg_statio_all_tables.schemaname !~ '^pg_toast'::text));
|
||||
pg_stats | SELECT n.nspname AS schemaname, c.relname AS tablename, a.attname, s.stanullfrac AS null_frac, s.stawidth AS avg_width, s.stadistinct AS n_distinct, CASE 1 WHEN s.stakind1 THEN s.stavalues1 WHEN s.stakind2 THEN s.stavalues2 WHEN s.stakind3 THEN s.stavalues3 WHEN s.stakind4 THEN s.stavalues4 ELSE NULL::anyarray END AS most_common_vals, CASE 1 WHEN s.stakind1 THEN s.stanumbers1 WHEN s.stakind2 THEN s.stanumbers2 WHEN s.stakind3 THEN s.stanumbers3 WHEN s.stakind4 THEN s.stanumbers4 ELSE NULL::real[] END AS most_common_freqs, CASE 2 WHEN s.stakind1 THEN s.stavalues1 WHEN s.stakind2 THEN s.stavalues2 WHEN s.stakind3 THEN s.stavalues3 WHEN s.stakind4 THEN s.stavalues4 ELSE NULL::anyarray END AS histogram_bounds, CASE 3 WHEN s.stakind1 THEN s.stanumbers1[1] WHEN s.stakind2 THEN s.stanumbers2[1] WHEN s.stakind3 THEN s.stanumbers3[1] WHEN s.stakind4 THEN s.stanumbers4[1] ELSE NULL::real END AS correlation FROM (((pg_statistic s JOIN pg_class c ON ((c.oid = s.starelid))) JOIN pg_attribute a ON (((c.oid = a.attrelid) AND (a.attnum = s.staattnum)))) LEFT JOIN pg_namespace n ON ((n.oid = c.relnamespace))) WHERE has_table_privilege(c.oid, 'select'::text);
|
||||
pg_stats | SELECT n.nspname AS schemaname, c.relname AS tablename, a.attname, s.stanullfrac AS null_frac, s.stawidth AS avg_width, s.stadistinct AS n_distinct, CASE WHEN (s.stakind1 = ANY (ARRAY[1, 4])) THEN s.stavalues1 WHEN (s.stakind2 = ANY (ARRAY[1, 4])) THEN s.stavalues2 WHEN (s.stakind3 = ANY (ARRAY[1, 4])) THEN s.stavalues3 WHEN (s.stakind4 = ANY (ARRAY[1, 4])) THEN s.stavalues4 ELSE NULL::anyarray END AS most_common_vals, CASE WHEN (s.stakind1 = ANY (ARRAY[1, 4])) THEN s.stanumbers1 WHEN (s.stakind2 = ANY (ARRAY[1, 4])) THEN s.stanumbers2 WHEN (s.stakind3 = ANY (ARRAY[1, 4])) THEN s.stanumbers3 WHEN (s.stakind4 = ANY (ARRAY[1, 4])) THEN s.stanumbers4 ELSE NULL::real[] END AS most_common_freqs, CASE WHEN (s.stakind1 = 2) THEN s.stavalues1 WHEN (s.stakind2 = 2) THEN s.stavalues2 WHEN (s.stakind3 = 2) THEN s.stavalues3 WHEN (s.stakind4 = 2) THEN s.stavalues4 ELSE NULL::anyarray END AS histogram_bounds, CASE WHEN (s.stakind1 = 3) THEN s.stanumbers1[1] WHEN (s.stakind2 = 3) THEN s.stanumbers2[1] WHEN (s.stakind3 = 3) THEN s.stanumbers3[1] WHEN (s.stakind4 = 3) THEN s.stanumbers4[1] ELSE NULL::real END AS correlation FROM (((pg_statistic s JOIN pg_class c ON ((c.oid = s.starelid))) JOIN pg_attribute a ON (((c.oid = a.attrelid) AND (a.attnum = s.staattnum)))) LEFT JOIN pg_namespace n ON ((n.oid = c.relnamespace))) WHERE has_table_privilege(c.oid, 'select'::text);
|
||||
pg_tables | SELECT n.nspname AS schemaname, c.relname AS tablename, pg_get_userbyid(c.relowner) AS tableowner, t.spcname AS tablespace, c.relhasindex AS hasindexes, c.relhasrules AS hasrules, (c.reltriggers > 0) AS hastriggers FROM ((pg_class c LEFT JOIN pg_namespace n ON ((n.oid = c.relnamespace))) LEFT JOIN pg_tablespace t ON ((t.oid = c.reltablespace))) WHERE (c.relkind = 'r'::"char");
|
||||
pg_timezone_abbrevs | SELECT pg_timezone_abbrevs.abbrev, pg_timezone_abbrevs.utc_offset, pg_timezone_abbrevs.is_dst FROM pg_timezone_abbrevs() pg_timezone_abbrevs(abbrev, utc_offset, is_dst);
|
||||
pg_timezone_names | SELECT pg_timezone_names.name, pg_timezone_names.abbrev, pg_timezone_names.utc_offset, pg_timezone_names.is_dst FROM pg_timezone_names() pg_timezone_names(name, abbrev, utc_offset, is_dst);
|
||||
|
Loading…
Reference in New Issue
Block a user