*
* Copyright (c) 1996-2008, PostgreSQL Global Development Group
*
- * $PostgreSQL: pgsql/src/backend/catalog/system_views.sql,v 1.52 2008/05/15 00:17:39 tgl Exp $
+ * $PostgreSQL: pgsql/src/backend/catalog/system_views.sql,v 1.53 2008/07/14 00:51:45 tgl Exp $
*/
CREATE VIEW pg_roles AS
stanullfrac AS null_frac,
stawidth AS avg_width,
stadistinct AS n_distinct,
- CASE 1
- WHEN stakind1 THEN stavalues1
- WHEN stakind2 THEN stavalues2
- WHEN stakind3 THEN stavalues3
- WHEN stakind4 THEN stavalues4
- END AS most_common_vals,
- CASE 1
- WHEN stakind1 THEN stanumbers1
- WHEN stakind2 THEN stanumbers2
- WHEN stakind3 THEN stanumbers3
- WHEN stakind4 THEN stanumbers4
- END AS most_common_freqs,
- CASE 2
- WHEN stakind1 THEN stavalues1
- WHEN stakind2 THEN stavalues2
- WHEN stakind3 THEN stavalues3
- WHEN stakind4 THEN stavalues4
- END AS histogram_bounds,
- CASE 3
- WHEN stakind1 THEN stanumbers1[1]
- WHEN stakind2 THEN stanumbers2[1]
- WHEN stakind3 THEN stanumbers3[1]
- WHEN stakind4 THEN stanumbers4[1]
- END AS correlation
+ CASE
+ WHEN stakind1 IN (1, 4) THEN stavalues1
+ WHEN stakind2 IN (1, 4) THEN stavalues2
+ WHEN stakind3 IN (1, 4) THEN stavalues3
+ WHEN stakind4 IN (1, 4) THEN stavalues4
+ END AS most_common_vals,
+ CASE
+ WHEN stakind1 IN (1, 4) THEN stanumbers1
+ WHEN stakind2 IN (1, 4) THEN stanumbers2
+ WHEN stakind3 IN (1, 4) THEN stanumbers3
+ WHEN stakind4 IN (1, 4) THEN stanumbers4
+ END AS most_common_freqs,
+ CASE
+ WHEN stakind1 = 2 THEN stavalues1
+ WHEN stakind2 = 2 THEN stavalues2
+ WHEN stakind3 = 2 THEN stavalues3
+ WHEN stakind4 = 2 THEN stavalues4
+ END AS histogram_bounds,
+ CASE
+ WHEN stakind1 = 3 THEN stanumbers1[1]
+ WHEN stakind2 = 3 THEN stanumbers2[1]
+ WHEN stakind3 = 3 THEN stanumbers3[1]
+ WHEN stakind4 = 3 THEN stanumbers4[1]
+ END AS correlation
FROM pg_statistic s JOIN pg_class c ON (c.oid = s.starelid)
JOIN pg_attribute a ON (c.oid = attrelid AND attnum = s.staattnum)
LEFT JOIN pg_namespace n ON (n.oid = c.relnamespace)
--- /dev/null
+/*-------------------------------------------------------------------------
+ *
+ * ts_typanalyze.c
+ * functions for gathering statistics from tsvector columns
+ *
+ * Portions Copyright (c) 1996-2008, PostgreSQL Global Development Group
+ *
+ *
+ * IDENTIFICATION
+ * $PostgreSQL: pgsql/src/backend/tsearch/ts_typanalyze.c,v 1.1 2008/07/14 00:51:45 tgl Exp $
+ *
+ *-------------------------------------------------------------------------
+ */
+#include "postgres.h"
+
+#include "access/hash.h"
+#include "catalog/pg_operator.h"
+#include "commands/vacuum.h"
+#include "tsearch/ts_type.h"
+#include "utils/builtins.h"
+#include "utils/hsearch.h"
+
+
+/* A hash key for lexemes */
+typedef struct
+{
+ char *lexeme; /* lexeme (not NULL terminated!) */
+ int length; /* its length in bytes */
+} LexemeHashKey;
+
+/* A hash table entry for the Lossy Counting algorithm */
+typedef struct
+{
+ LexemeHashKey key; /* This is 'e' from the LC algorithm. */
+ int frequency; /* This is 'f'. */
+ int delta; /* And this is 'delta'. */
+} TrackItem;
+
+static void compute_tsvector_stats(VacAttrStats *stats,
+ AnalyzeAttrFetchFunc fetchfunc,
+ int samplerows,
+ double totalrows);
+static void prune_lexemes_hashtable(HTAB *lexemes_tab, int b_current);
+static uint32 lexeme_hash(const void *key, Size keysize);
+static int lexeme_match(const void *key1, const void *key2, Size keysize);
+static int trackitem_compare_desc(const void *e1, const void *e2);
+
+
+/*
+ * ts_typanalyze -- a custom typanalyze function for tsvector columns
+ */
+Datum
+ts_typanalyze(PG_FUNCTION_ARGS)
+{
+ VacAttrStats *stats = (VacAttrStats *) PG_GETARG_POINTER(0);
+ Form_pg_attribute attr = stats->attr;
+
+ /* If the attstattarget column is negative, use the default value */
+ /* NB: it is okay to scribble on stats->attr since it's a copy */
+ if (attr->attstattarget < 0)
+ attr->attstattarget = default_statistics_target;
+
+ stats->compute_stats = compute_tsvector_stats;
+ /* see comment about the choice of minrows from analyze.c */
+ stats->minrows = 300 * attr->attstattarget;
+
+ PG_RETURN_BOOL(true);
+}
+
+/*
+ * compute_tsvector_stats() -- compute statistics for a tsvector column
+ *
+ * This functions computes statistics that are useful for determining @@
+ * operations' selectivity, along with the fraction of non-null rows and
+ * average width.
+ *
+ * Instead of finding the most common values, as we do for most datatypes,
+ * we're looking for the most common lexemes. This is more useful, because
+ * there most probably won't be any two rows with the same tsvector and thus
+ * the notion of a MCV is a bit bogus with this datatype. With a list of the
+ * most common lexemes we can do a better job at figuring out @@ selectivity.
+ *
+ * For the same reasons we assume that tsvector columns are unique when
+ * determining the number of distinct values.
+ *
+ * The algorithm used is Lossy Counting, as proposed in the paper "Approximate
+ * frequency counts over data streams" by G. S. Manku and R. Motwani, in
+ * Proceedings of the 28th International Conference on Very Large Data Bases,
+ * Hong Kong, China, August 2002, section 4.2. The paper is available at
+ * http://www.vldb.org/conf/2002/S10P03.pdf
+ *
+ * The Lossy Counting (aka LC) algorithm goes like this:
+ * Let D be a set of triples (e, f, d), where e is an element value, f is
+ * that element's frequency (occurrence count) and d is the maximum error in
+ * f. We start with D empty and process the elements in batches of size
+ * w. (The batch size is also known as "bucket size".) Let the current batch
+ * number be b_current, starting with 1. For each element e we either
+ * increment its f count, if it's already in D, or insert a new triple into D
+ * with values (e, 1, b_current - 1). After processing each batch we prune D,
+ * by removing from it all elements with f + d <= b_current. Finally, we
+ * gather elements with largest f. The LC paper proves error bounds on f
+ * dependent on the batch size w, and shows that the required table size
+ * is no more than a few times w.
+ *
+ * We use a hashtable for the D structure and a bucket width of
+ * statistic_target * 100, where 100 is an arbitrarily chosen constant, meant
+ * to approximate the number of lexemes in a single tsvector.
+ */
+static void
+compute_tsvector_stats(VacAttrStats *stats,
+ AnalyzeAttrFetchFunc fetchfunc,
+ int samplerows,
+ double totalrows)
+{
+ int num_mcelem;
+ int null_cnt = 0;
+ double total_width = 0;
+ /* This is D from the LC algorithm. */
+ HTAB *lexemes_tab;
+ HASHCTL hash_ctl;
+ HASH_SEQ_STATUS scan_status;
+ /* This is the current bucket number from the LC algorithm */
+ int b_current;
+ /* This is 'w' from the LC algorithm */
+ int bucket_width;
+ int vector_no,
+ lexeme_no;
+ LexemeHashKey hash_key;
+ TrackItem *item;
+
+ /* We want statistic_target * 100 lexemes in the MCELEM array */
+ num_mcelem = stats->attr->attstattarget * 100;
+
+ /*
+ * We set bucket width equal to the target number of result lexemes.
+ * This is probably about right but perhaps might need to be scaled
+ * up or down a bit?
+ */
+ bucket_width = num_mcelem;
+
+ /*
+ * Create the hashtable. It will be in local memory, so we don't need to
+ * worry about initial size too much. Also we don't need to pay any
+ * attention to locking and memory management.
+ */
+ MemSet(&hash_ctl, 0, sizeof(hash_ctl));
+ hash_ctl.keysize = sizeof(LexemeHashKey);
+ hash_ctl.entrysize = sizeof(TrackItem);
+ hash_ctl.hash = lexeme_hash;
+ hash_ctl.match = lexeme_match;
+ hash_ctl.hcxt = CurrentMemoryContext;
+ lexemes_tab = hash_create("Analyzed lexemes table",
+ bucket_width * 4,
+ &hash_ctl,
+ HASH_ELEM | HASH_FUNCTION | HASH_COMPARE | HASH_CONTEXT);
+
+ /* Initialize counters. */
+ b_current = 1;
+ lexeme_no = 1;
+
+ /* Loop over the tsvectors. */
+ for (vector_no = 0; vector_no < samplerows; vector_no++)
+ {
+ Datum value;
+ bool isnull;
+ TSVector vector;
+ WordEntry *curentryptr;
+ char *lexemesptr;
+ int j;
+
+ vacuum_delay_point();
+
+ value = fetchfunc(stats, vector_no, &isnull);
+
+ /*
+ * Check for null/nonnull.
+ */
+ if (isnull)
+ {
+ null_cnt++;
+ continue;
+ }
+
+ /*
+ * Add up widths for average-width calculation. Since it's a
+ * tsvector, we know it's varlena. As in the regular
+ * compute_minimal_stats function, we use the toasted width for this
+ * calculation.
+ */
+ total_width += VARSIZE_ANY(DatumGetPointer(value));
+
+ /*
+ * Now detoast the tsvector if needed.
+ */
+ vector = DatumGetTSVector(value);
+
+ /*
+ * We loop through the lexemes in the tsvector and add them to our
+ * tracking hashtable. Note: the hashtable entries will point into
+ * the (detoasted) tsvector value, therefore we cannot free that
+ * storage until we're done.
+ */
+ lexemesptr = STRPTR(vector);
+ curentryptr = ARRPTR(vector);
+ for (j = 0; j < vector->size; j++)
+ {
+ bool found;
+
+ /* Construct a hash key */
+ hash_key.lexeme = lexemesptr + curentryptr->pos;
+ hash_key.length = curentryptr->len;
+
+ /* Lookup current lexeme in hashtable, adding it if new */
+ item = (TrackItem *) hash_search(lexemes_tab,
+ (const void *) &hash_key,
+ HASH_ENTER, &found);
+
+ if (found)
+ {
+ /* The lexeme is already on the tracking list */
+ item->frequency++;
+ }
+ else
+ {
+ /* Initialize new tracking list element */
+ item->frequency = 1;
+ item->delta = b_current - 1;
+ }
+
+ /* We prune the D structure after processing each bucket */
+ if (lexeme_no % bucket_width == 0)
+ {
+ prune_lexemes_hashtable(lexemes_tab, b_current);
+ b_current++;
+ }
+
+ /* Advance to the next WordEntry in the tsvector */
+ lexeme_no++;
+ curentryptr++;
+ }
+ }
+
+ /* We can only compute real stats if we found some non-null values. */
+ if (null_cnt < samplerows)
+ {
+ int nonnull_cnt = samplerows - null_cnt;
+ int i;
+ TrackItem **sort_table;
+ int track_len;
+
+ stats->stats_valid = true;
+ /* Do the simple null-frac and average width stats */
+ stats->stanullfrac = (double) null_cnt / (double) samplerows;
+ stats->stawidth = total_width / (double) nonnull_cnt;
+
+ /* Assume it's a unique column (see notes above) */
+ stats->stadistinct = -1.0;
+
+ /*
+ * Determine the top-N lexemes by simply copying pointers from the
+ * hashtable into an array and applying qsort()
+ */
+ track_len = hash_get_num_entries(lexemes_tab);
+
+ sort_table = (TrackItem **) palloc(sizeof(TrackItem *) * track_len);
+
+ hash_seq_init(&scan_status, lexemes_tab);
+ i = 0;
+ while ((item = (TrackItem *) hash_seq_search(&scan_status)) != NULL)
+ {
+ sort_table[i++] = item;
+ }
+ Assert(i == track_len);
+
+ 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;
+}
-- 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);
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);
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