SELECT EXTRACT(? FROM TRANSACTION_TIMESTAMP()), a.schemaname, a.relname,
a.indexrelname, idx_scan, idx_tup_read, idx_tup_fetch, idx_blks_read,
idx_blks_hit
FROM pg_stat_all_indexes a, pg_statio_all_indexes b
SELECT a.attrelid, a.attnum, a.attname, format_type(atttypid, atttypmod) AS type, a.attstattarget, a.attstorage, a.attnotnull, a.attisdropped, s.stawidth as avg_width, s.stadistinct as n_distinct, CASE WHEN s.stakind1 = ? THEN s.stanumbers1[?] display full query string
60
0.178
0.003
statsinfo
dbt2
SELECT i.oid AS indexrelid, c.oid AS relid, i.reltablespace, i.relname AS indexrelname, i.relam, i.relpages, i.reltuples, i.reloptions, x.indisunique, x.indisprimary, x.indisclustered, x.indisvalid, x.indkey, display full query string
60
0.141
0.002
statsinfo
dbt2
SELECT s.funcid, n.oid AS nspid, s.funcname, pg_get_function_arguments(funcid) AS argtypes, s.calls, s.total_time, s.self_time FROM pg_stat_user_functions s JOIN pg_namespace n ON s.schemaname = n.nspname WHERE n.nspname <> ALL ((? || $1 || ?)::t display full query string
SELECT EXTRACT(? FROM TRANSACTION_TIMESTAMP()), a.schemaname, a.relname,
a.indexrelname, idx_scan, idx_tup_read, idx_tup_fetch, idx_blks_read,
idx_blks_hit
FROM pg_stat_all_indexes a, pg_statio_all_indexes b
SELECT s.funcid, n.oid AS nspid, s.funcname, pg_get_function_arguments(funcid) AS argtypes, s.calls, s.total_time, s.self_time FROM pg_stat_user_functions s JOIN pg_namespace n ON s.schemaname = n.nspname WHERE n.nspname <> ALL ((? || $1 || ?)::t display full query string
SELECT a.attrelid, a.attnum, a.attname, format_type(atttypid, atttypmod) AS type, a.attstattarget, a.attstorage, a.attnotnull, a.attisdropped, s.stawidth as avg_width, s.stadistinct as n_distinct, CASE WHEN s.stakind1 = ? THEN s.stanumbers1[?] display full query string
DECLARE mycursor CURSOR FOR SELECT new_order(7, 10, 1017, 1, 12, make_new_order_info(83968, 7, 2...;SELECT w_tax
FROM warehouse
WHERE w_id = $1;SELECT d_tax, d_next_o_id
FROM district
WHERE d_w_id = $1
DECLARE mycursor CURSOR FOR SELECT new_order(2, 3, 71, 1, 10, make_new_order_info(89856, 2, 4), ...;SELECT w_tax
FROM warehouse
WHERE w_id = $1;SELECT d_tax, d_next_o_id
FROM district
WHERE d_w_id = $1
DECLARE mycursor CURSOR FOR SELECT new_order(9, 6, 1776, 1, 15, make_new_order_info(30711, 9, 8)...;SELECT w_tax
FROM warehouse
WHERE w_id = $1;SELECT d_tax, d_next_o_id
FROM district
WHERE d_w_id = $1
DECLARE mycursor CURSOR FOR SELECT new_order(10, 8, 2223, 1, 15, make_new_order_info(14302, 10, ...;SELECT w_tax
FROM warehouse
WHERE w_id = $1;SELECT d_tax, d_next_o_id
FROM district
WHERE d_w_id = $1
SELECT delivery(2, 3);SELECT no_o_id
FROM new_order
WHERE no_w_id = $1
AND no_d_id = $2ORDER BY no_o_id LIMIT 1;DELETE FROM new_order
WHERE no_o_id = $1
DECLARE mycursor CURSOR FOR SELECT new_order(3, 2, 736, 1, 11, make_new_order_info(49102, 3, 2),...;SELECT w_tax
FROM warehouse
WHERE w_id = $1;SELECT d_tax, d_next_o_id
FROM district
WHERE d_w_id = $1
DECLARE mycursor CURSOR FOR SELECT new_order(3, 6, 2034, 1, 14, make_new_order_info(88702, 3, 9)...;SELECT w_tax
FROM warehouse
WHERE w_id = $1;SELECT d_tax, d_next_o_id
FROM district
WHERE d_w_id = $1
DECLARE mycursor CURSOR FOR SELECT new_order(8, 6, 8, 1, 9, make_new_order_info(8020, 8, 5), mak...;SELECT w_tax
FROM warehouse
WHERE w_id = $1;SELECT d_tax, d_next_o_id
FROM district
WHERE d_w_id = $1
SELECT c.oid AS relid, c.relnamespace, c.reltablespace, c.relname, c.reltoastrelid, x.indexrelid AS reltoastidxid, c.relkind, c.relpages, c.reltuples, c.reloptions, pg_relation_size(c.oid), pg_stat_get_numscans(c.oid) AS seq_scan, pg_stat_get_tuples_returned(c.oid) AS seq_tup_read, sum(pg_stat_get_numscans(i.indexrelid))::bigint AS idx_scan, sum(pg_stat_get_tuples_fetched(i.indexrelid))::bigint + pg_stat_get_tuples_fetched(c.oid) AS idx_tup_fetch, pg_stat_get_tuples_inserted(c.oid) AS n_tup_ins, pg_stat_get_tuples_updated(c.oid) AS n_tup_upd, pg_stat_get_tuples_deleted(c.oid) AS n_tup_del, pg_stat_get_tuples_hot_updated(c.oid) AS n_tup_hot_upd, pg_stat_get_live_tuples(c.oid) AS n_live_tup, pg_stat_get_dead_tuples(c.oid) AS n_dead_tup, pg_stat_get_mod_since_analyze(c.oid) AS n_mod_since_analyze, pg_stat_get_blocks_fetched(c.oid) - pg_stat_get_blocks_hit(c.oid) AS heap_blks_read, pg_stat_get_blocks_hit(c.oid) AS heap_blks_hit, sum(pg_stat_get_blocks_fetched(i.indexrelid) - pg_stat_get_blocks_hit(i.indexrelid))::bigint AS idx_blks_read, sum(pg_stat_get_blocks_hit(i.indexrelid))::bigint AS idx_blks_hit, pg_stat_get_blocks_fetched(t.oid) - pg_stat_get_blocks_hit(t.oid) AS toast_blks_read, pg_stat_get_blocks_hit(t.oid) AS toast_blks_hit, pg_stat_get_blocks_fetched(x.indexrelid) - pg_stat_get_blocks_hit(x.indexrelid) AS tidx_blks_read, pg_stat_get_blocks_hit(x.indexrelid) AS tidx_blks_hit, pg_stat_get_last_vacuum_time(c.oid) as last_vacuum, pg_stat_get_last_autovacuum_time(c.oid) as last_autovacuum, pg_stat_get_last_analyze_time(c.oid) as last_analyze, pg_stat_get_last_autoanalyze_time(c.oid) as last_autoanalyze FROM pg_class c LEFT JOIN pg_index i ON c.oid = i.indrelid LEFT JOIN pg_class t ON c.reltoastrelid = t.oid LEFT JOIN pg_index x ON c.reltoastrelid = x.indrelid LEFT JOIN pg_namespace n ON c.relnamespace = n.oid WHERE c.relkind IN (?, ?) AND n.nspname <> ALL ((? || $1 || ?)::text[]) GROUP BY c.oid, c.relnamespace, c.reltablespace, c.relname, c.reltoastrelid, c.relkind, c.relpages, c.reltuples, c.reloptions, t.oid, x.indexrelid
SELECT EXTRACT(? FROM TRANSACTION_TIMESTAMP()), datname, numbackends,
xact_commit, xact_rollback, blks_read, blks_hit, tup_returned,
tup_fetched, tup_inserted, tup_updated, tup_deleted
FROM pg_stat_database
;
SELECT EXTRACT(? FROM TRANSACTION_TIMESTAMP()), a.schemaname, a.relname,
seq_scan, seq_tup_read, idx_scan, idx_tup_fetch, n_tup_ins, n_tup_upd,
n_tup_del, n_tup_hot_upd, n_live_tup, n_dead_tup, heap_blks_read,
heap_blks_hit, idx_blks_read, idx_blks_hit, toast_blks_read,
toast_blks_hit, tidx_blks_read, tidx_blks_hit
FROM pg_statio_all_tables a, pg_stat_all_tables b
WHERE a.relid = b.relid
;
SELECT EXTRACT(? FROM TRANSACTION_TIMESTAMP()), a.schemaname, a.relname,
a.indexrelname, idx_scan, idx_tup_read, idx_tup_fetch, idx_blks_read,
idx_blks_hit
FROM pg_stat_all_indexes a, pg_statio_all_indexes b
WHERE a.indexrelid = b.indexrelid
;
SELECT EXTRACT(? FROM TRANSACTION_TIMESTAMP()), relname, pid, mode, granted
FROM pg_locks, pg_class
WHERE relfilenode = relation
ORDER BY relname;
;
SELECT EXTRACT(? FROM TRANSACTION_TIMESTAMP()), datname, pid, usesysid,
usename, application_name, client_addr, client_port, backend_start,
xact_start, query_start, waiting, query
FROM pg_stat_activity
;
SELECT a.attrelid, a.attnum, a.attname, format_type(atttypid, atttypmod) AS type, a.attstattarget, a.attstorage, a.attnotnull, a.attisdropped, s.stawidth as avg_width, s.stadistinct as n_distinct, CASE 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 ? END AS correlation FROM pg_attribute a LEFT JOIN pg_class c ON a.attrelid = c.oid LEFT JOIN pg_statistic s ON a.attnum = s.staattnum AND a.attrelid = s.starelid AND NOT s.stainherit LEFT JOIN pg_namespace n ON c.relnamespace = n.oid WHERE a.attnum > ? AND c.relkind IN (?, ?) AND n.nspname <> ALL ((? || $1 || ?)::text[])
SELECT i.oid AS indexrelid, c.oid AS relid, i.reltablespace, i.relname AS indexrelname, i.relam, i.relpages, i.reltuples, i.reloptions, x.indisunique, x.indisprimary, x.indisclustered, x.indisvalid, x.indkey, pg_get_indexdef(i.oid), pg_relation_size(i.oid), pg_stat_get_numscans(i.oid) AS idx_scan, pg_stat_get_tuples_returned(i.oid) AS idx_tup_read, pg_stat_get_tuples_fetched(i.oid) AS idx_tup_fetch, pg_stat_get_blocks_fetched(i.oid) - pg_stat_get_blocks_hit(i.oid) AS idx_blks_read, pg_stat_get_blocks_hit(i.oid) AS idx_blks_hit FROM pg_class c JOIN pg_index x ON c.oid = x.indrelid JOIN pg_class i ON i.oid = x.indexrelid JOIN pg_namespace n ON n.oid = c.relnamespace WHERE c.relkind IN (?, ?) AND n.nspname <> ALL ((? || $1 || ?)::text[])
SELECT s.funcid, n.oid AS nspid, s.funcname, pg_get_function_arguments(funcid) AS argtypes, s.calls, s.total_time, s.self_time FROM pg_stat_user_functions s JOIN pg_namespace n ON s.schemaname = n.nspname WHERE n.nspname <> ALL ((? || $1 || ?)::text[])
Nested Loop (cost=1.15..2.69 rows=1 width=261)
-> Hash Join (cost=1.02..2.41 rows=1 width=201)
Hash Cond: (s.usesysid = u.oid)
-> Function Scan on pg_stat_get_activity s (cost=0.00..1.00 rows=100 width=137)
-> Hash (cost=1.01..1.01 rows=1 width=68)
Buckets: 1024 Batches: 1 Memory Usage: 1kB
-> Seq Scan on pg_authid u (cost=0.00..1.01 rows=1 width=68)
-> Index Scan using pg_database_oid_index on pg_database d (cost=0.13..0.27 rows=1 width=68)
Index Cond: (oid = s.datid)
SELECT EXTRACT(? FROM TRANSACTION_TIMESTAMP()), datname, pid, usesysid,
usename, application_name, client_addr, client_port, backend_start,
xact_start, query_start, waiting, query
FROM pg_stat_activity
;
SELECT EXTRACT(? FROM TRANSACTION_TIMESTAMP()), datname, numbackends,
xact_commit, xact_rollback, blks_read, blks_hit, tup_returned,
tup_fetched, tup_inserted, tup_updated, tup_deleted
FROM pg_stat_database
;
Nested Loop Left (cost=29.18..50.96 rows=6 width=200)
Join Filter: (n.oid = c.relnamespace)
-> Nested Loop (cost=29.18..49.21 rows=6 width=140)
Join Filter: (x.indexrelid = i.oid)
-> Nested Loop (cost=29.03..45.38 rows=12 width=80)
-> Hash Join (cost=28.89..42.66 rows=12 width=76)
Hash Cond: (c_1.oid = x_1.indrelid)
-> Seq Scan on pg_class c_1 (cost=0.00..13.34 rows=84 width=8)
Filter: (relkind = ANY ('{r,t,m}'::"char"[]))
-> Hash (cost=28.34..28.34 rows=44 width=80)
Buckets: 1024 Batches: 1 Memory Usage: 14kB
-> Hash Join (cost=21.64..28.34 rows=44 width=80)
Hash Cond: (x_1.indexrelid = x.indexrelid)
-> Seq Scan on pg_index x_1 (cost=0.00..5.64 rows=164 width=8)
-> Hash (cost=21.09..21.09 rows=44 width=72)
Buckets: 1024 Batches: 1 Memory Usage: 13kB
-> Hash Join (cost=14.39..21.09 rows=44 width=72)
Hash Cond: (x.indrelid = c.oid)
-> Seq Scan on pg_index x (cost=0.00..5.64 rows=164 width=8)
-> Hash (cost=13.34..13.34 rows=84 width=72)
Buckets: 1024 Batches: 1 Memory Usage: 9kB
-> Seq Scan on pg_class c (cost=0.00..13.34 rows=84 width=72)
Filter: (relkind = ANY ('{r,t,m}'::"char"[]))
-> Index Only Scan using pg_class_oid_index on pg_class i_1 (cost=0.15..0.22 rows=1 width=4)
Index Cond: (oid = x.indexrelid)
-> Index Scan using pg_class_oid_index on pg_class i (cost=0.15..0.31 rows=1 width=68)
Index Cond: (oid = i_1.oid)
-> Materialize (cost=0.00..1.09 rows=6 width=68)
-> Seq Scan on pg_namespace n (cost=0.00..1.06 rows=6 width=68)
SELECT EXTRACT(? FROM TRANSACTION_TIMESTAMP()), a.schemaname, a.relname,
a.indexrelname, idx_scan, idx_tup_read, idx_tup_fetch, idx_blks_read,
idx_blks_hit
FROM pg_stat_all_indexes a, pg_statio_all_indexes b
WHERE a.indexrelid = b.indexrelid
;
SELECT EXTRACT(? FROM TRANSACTION_TIMESTAMP()), relname, pid, mode, granted
FROM pg_locks, pg_class
WHERE relfilenode = relation
ORDER BY relname;
;
Hash Join (cost=2.33..112.39 rows=54 width=72)
Hash Cond: (p.pronamespace = n_1.oid)
-> Seq Scan on pg_proc p (cost=0.00..108.37 rows=162 width=72)
Filter: ((prolang <> 12::oid) AND (pg_stat_get_function_calls(oid) IS NOT NULL))
-> Hash (cost=2.31..2.31 rows=2 width=8)
Buckets: 1024 Batches: 1 Memory Usage: 1kB
-> Hash Join (cost=1.20..2.31 rows=2 width=8)
Hash Cond: (n_1.nspname = n.nspname)
-> Seq Scan on pg_namespace n_1 (cost=0.00..1.06 rows=6 width=68)
-> Hash (cost=1.18..1.18 rows=2 width=68)
Buckets: 1024 Batches: 1 Memory Usage: 1kB
-> Seq Scan on pg_namespace n (cost=0.00..1.18 rows=2 width=68)
Filter: ((nspname)::text <> ALL (('{pg_catalog, pg_toast, information_schema, statsinfo}'::cstring)::text[]))
SELECT s.funcid, n.oid AS nspid, s.funcname, pg_get_function_arguments(funcid) AS argtypes, s.calls, s.total_time, s.self_time FROM pg_stat_user_functions s JOIN pg_namespace n ON s.schemaname = n.nspname WHERE n.nspname <> ALL ((? || $1 || ?)::text[])
HashAggregate (cost=40.88..43.68 rows=28 width=133)
Group Key: c.oid, c.relnamespace, c.reltablespace, c.relname, c.reltoastrelid, c.relkind, c.relpages, c.reltuples, c.reloptions, t.oid, x.indexrelid
-> Hash Left Join (cost=25.11..39.41 rows=28 width=133)
Hash Cond: (c.reltoastrelid = x.indrelid)
-> Nested Loop Left (cost=17.42..31.24 rows=28 width=129)
-> Hash Right Join (cost=17.27..23.68 rows=28 width=125)
Hash Cond: (i.indrelid = c.oid)
-> Seq Scan on pg_index i (cost=0.00..5.64 rows=164 width=8)
-> Hash (cost=16.92..16.92 rows=28 width=121)
Buckets: 1024 Batches: 1 Memory Usage: 2kB
-> Hash Left Join (cost=1.14..16.92 rows=28 width=121)
Hash Cond: (c.relnamespace = n.oid)
Filter: ((n.nspname)::text <> ALL (('{pg_catalog, pg_toast, information_schema, statsinfo}'::cstring)::text[]))
-> Seq Scan on pg_class c (cost=0.00..12.95 rows=84 width=121)
Filter: (relkind = ANY ('{r,t}'::"char"[]))
-> Hash (cost=1.06..1.06 rows=6 width=68)
Buckets: 1024 Batches: 1 Memory Usage: 1kB
-> Seq Scan on pg_namespace n (cost=0.00..1.06 rows=6 width=68)
-> Index Only Scan using pg_class_oid_index on pg_class t (cost=0.15..0.26 rows=1 width=4)
Index Cond: (oid = c.reltoastrelid)
-> Hash (cost=5.64..5.64 rows=164 width=8)
Buckets: 1024 Batches: 1 Memory Usage: 5kB
-> Seq Scan on pg_index x (cost=0.00..5.64 rows=164 width=8)
SELECT c.oid AS relid, c.relnamespace, c.reltablespace, c.relname, c.reltoastrelid, x.indexrelid AS reltoastidxid, c.relkind, c.relpages, c.reltuples, c.reloptions, pg_relation_size(c.oid), pg_stat_get_numscans(c.oid) AS seq_scan, pg_stat_get_tuples_returned(c.oid) AS seq_tup_read, sum(pg_stat_get_numscans(i.indexrelid))::bigint AS idx_scan, sum(pg_stat_get_tuples_fetched(i.indexrelid))::bigint + pg_stat_get_tuples_fetched(c.oid) AS idx_tup_fetch, pg_stat_get_tuples_inserted(c.oid) AS n_tup_ins, pg_stat_get_tuples_updated(c.oid) AS n_tup_upd, pg_stat_get_tuples_deleted(c.oid) AS n_tup_del, pg_stat_get_tuples_hot_updated(c.oid) AS n_tup_hot_upd, pg_stat_get_live_tuples(c.oid) AS n_live_tup, pg_stat_get_dead_tuples(c.oid) AS n_dead_tup, pg_stat_get_mod_since_analyze(c.oid) AS n_mod_since_analyze, pg_stat_get_blocks_fetched(c.oid) - pg_stat_get_blocks_hit(c.oid) AS heap_blks_read, pg_stat_get_blocks_hit(c.oid) AS heap_blks_hit, sum(pg_stat_get_blocks_fetched(i.indexrelid) - pg_stat_get_blocks_hit(i.indexrelid))::bigint AS idx_blks_read, sum(pg_stat_get_blocks_hit(i.indexrelid))::bigint AS idx_blks_hit, pg_stat_get_blocks_fetched(t.oid) - pg_stat_get_blocks_hit(t.oid) AS toast_blks_read, pg_stat_get_blocks_hit(t.oid) AS toast_blks_hit, pg_stat_get_blocks_fetched(x.indexrelid) - pg_stat_get_blocks_hit(x.indexrelid) AS tidx_blks_read, pg_stat_get_blocks_hit(x.indexrelid) AS tidx_blks_hit, pg_stat_get_last_vacuum_time(c.oid) as last_vacuum, pg_stat_get_last_autovacuum_time(c.oid) as last_autovacuum, pg_stat_get_last_analyze_time(c.oid) as last_analyze, pg_stat_get_last_autoanalyze_time(c.oid) as last_autoanalyze FROM pg_class c LEFT JOIN pg_index i ON c.oid = i.indrelid LEFT JOIN pg_class t ON c.reltoastrelid = t.oid LEFT JOIN pg_index x ON c.reltoastrelid = x.indrelid LEFT JOIN pg_namespace n ON c.relnamespace = n.oid WHERE c.relkind IN (?, ?) AND n.nspname <> ALL ((? || $1 || ?)::text[]) GROUP BY c.oid, c.relnamespace, c.reltablespace, c.relname, c.reltoastrelid, c.relkind, c.relpages, c.reltuples, c.reloptions, t.oid, x.indexrelid
SELECT EXTRACT(? FROM TRANSACTION_TIMESTAMP()), a.schemaname, a.relname,
seq_scan, seq_tup_read, idx_scan, idx_tup_fetch, n_tup_ins, n_tup_upd,
n_tup_del, n_tup_hot_upd, n_live_tup, n_dead_tup, heap_blks_read,
heap_blks_hit, idx_blks_read, idx_blks_hit, toast_blks_read,
toast_blks_hit, tidx_blks_read, tidx_blks_hit
FROM pg_statio_all_tables a, pg_stat_all_tables b
WHERE a.relid = b.relid
;
Nested Loop (cost=15.25..28.53 rows=15 width=151)
-> Hash Join (cost=15.10..21.51 rows=15 width=39)
Hash Cond: (x.indrelid = c.oid)
-> Seq Scan on pg_index x (cost=0.00..5.64 rows=164 width=39)
-> Hash (cost=14.75..14.75 rows=28 width=4)
Buckets: 1024 Batches: 1 Memory Usage: 1kB
-> Hash Join (cost=1.20..14.75 rows=28 width=4)
Hash Cond: (c.relnamespace = n.oid)
-> Seq Scan on pg_class c (cost=0.00..12.95 rows=84 width=8)
Filter: (relkind = ANY ('{r,t}'::"char"[]))
-> Hash (cost=1.18..1.18 rows=2 width=4)
Buckets: 1024 Batches: 1 Memory Usage: 1kB
-> Seq Scan on pg_namespace n (cost=0.00..1.18 rows=2 width=4)
Filter: ((nspname)::text <> ALL (('{pg_catalog, pg_toast, information_schema, statsinfo}'::cstring)::text[]))
-> Index Scan using pg_class_oid_index on pg_class i (cost=0.15..0.44 rows=1 width=116)
Index Cond: (oid = x.indexrelid)
SELECT i.oid AS indexrelid, c.oid AS relid, i.reltablespace, i.relname AS indexrelname, i.relam, i.relpages, i.reltuples, i.reloptions, x.indisunique, x.indisprimary, x.indisclustered, x.indisvalid, x.indkey, pg_get_indexdef(i.oid), pg_relation_size(i.oid), pg_stat_get_numscans(i.oid) AS idx_scan, pg_stat_get_tuples_returned(i.oid) AS idx_tup_read, pg_stat_get_tuples_fetched(i.oid) AS idx_tup_fetch, pg_stat_get_blocks_fetched(i.oid) - pg_stat_get_blocks_hit(i.oid) AS idx_blks_read, pg_stat_get_blocks_hit(i.oid) AS idx_blks_hit FROM pg_class c JOIN pg_index x ON c.oid = x.indrelid JOIN pg_class i ON i.oid = x.indexrelid JOIN pg_namespace n ON n.oid = c.relnamespace WHERE c.relkind IN (?, ?) AND n.nspname <> ALL ((? || $1 || ?)::text[])
Hash Right Join (cost=106.06..155.68 rows=173 width=229)
Hash Cond: ((s.staattnum = a.attnum) AND (s.starelid = a.attrelid))
-> Seq Scan on pg_statistic s (cost=0.00..41.91 rows=246 width=150)
Filter: (NOT stainherit)
-> Hash (cost=103.47..103.47 rows=173 width=85)
Buckets: 1024 Batches: 1 Memory Usage: 11kB
-> Hash Join (cost=17.27..103.47 rows=173 width=85)
Hash Cond: (a.attrelid = c.oid)
-> Seq Scan on pg_attribute a (cost=0.00..77.14 rows=1954 width=85)
Filter: (attnum > 0)
-> Hash (cost=16.92..16.92 rows=28 width=4)
Buckets: 1024 Batches: 1 Memory Usage: 1kB
-> Hash Left Join (cost=1.14..16.92 rows=28 width=4)
Hash Cond: (c.relnamespace = n.oid)
Filter: ((n.nspname)::text <> ALL (('{pg_catalog, pg_toast, information_schema, statsinfo}'::cstring)::text[]))
-> Seq Scan on pg_class c (cost=0.00..12.95 rows=84 width=8)
Filter: (relkind = ANY ('{r,t}'::"char"[]))
-> Hash (cost=1.06..1.06 rows=6 width=68)
Buckets: 1024 Batches: 1 Memory Usage: 1kB
-> Seq Scan on pg_namespace n (cost=0.00..1.06 rows=6 width=68)
SELECT a.attrelid, a.attnum, a.attname, format_type(atttypid, atttypmod) AS type, a.attstattarget, a.attstorage, a.attnotnull, a.attisdropped, s.stawidth as avg_width, s.stadistinct as n_distinct, CASE 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 ? END AS correlation FROM pg_attribute a LEFT JOIN pg_class c ON a.attrelid = c.oid LEFT JOIN pg_statistic s ON a.attnum = s.staattnum AND a.attrelid = s.starelid AND NOT s.stainherit LEFT JOIN pg_namespace n ON c.relnamespace = n.oid WHERE a.attnum > ? AND c.relkind IN (?, ?) AND n.nspname <> ALL ((? || $1 || ?)::text[])
DECLARE mycursor CURSOR FOR SELECT new_order(7, 10, 1017, 1, 12, make_new_order_info(83968, 7, 2...;SELECT w_tax
FROM warehouse
WHERE w_id = $1;SELECT d_tax, d_next_o_id
FROM district
WHERE d_w_id = $1
AND d_id = $2
FOR UPDATE;UPDATE district
SET d_next_o_id = d_next_o_id + 1
WHERE d_w_id = $1
AND d_id = $2;SELECT c_discount, c_last, c_credit
FROM customer
WHERE c_w_id = $1
AND c_d_id = $2
AND c_id...;INSERT INTO new_order (no_o_id, no_w_id, no_d_id)
VALUES ($1, $2, $3);INSERT INTO orders (o_id, o_d_id, o_w_id, o_c_id, o_entry_d,
o_carrier_id, o_ol_cnt, o_all...;SELECT i_price, i_name, i_data
FROM item
WHERE i_id = $1;SELECT s_quantity, $1, s_data
FROM stock
WHERE s_i_id = $2
AND s_w_id = $3;UPDATE stock
SET s_quantity = s_quantity - $1
WHERE s_i_id = $2
AND s_w_id = $3;INSERT INTO order_line (ol_o_id, ol_d_id, ol_w_id, ol_number,
ol_i_id, ol_supply_w_id, ol_del...;SELECT i_price, i_name, i_data
FROM item
WHERE i_id = $1;SELECT s_quantity, $1, s_data
FROM sto...;
SELECT payment(8, 3, 0, 8, 3, 'CALLYBARABLE', 2287.110000);SELECT w_name, w_street_1, w_street_2, w_city, w_state, w_zip
FROM warehouse
WHERE w_id = $1;UPDATE warehouse
SET w_ytd = w_ytd + $1
WHERE w_id = $2;SELECT d_name, d_street_1, d_street_2, d_city, d_state, d_zip
FROM district
WHERE d_id = $1
AN...;UPDATE district
SET d_ytd = d_ytd + $1
WHERE d_id = $2
AND d_w_id = $3;SELECT c_id
FROM customer
WHERE c_w_id = $1
AND c_d_id = $2
AND c_last = $3
ORDER BY c_first ASC;
SELECT payment(7, 4, 0, 6, 1, 'ESEOUGHTOUGHT', 3180.460000);SELECT w_name, w_street_1, w_street_2, w_city, w_state, w_zip
FROM warehouse
WHERE w_id = $1;UPDATE warehouse
SET w_ytd = w_ytd + $1
WHERE w_id = $2;SELECT d_name, d_street_1, d_street_2, d_city, d_state, d_zip
FROM district
WHERE d_id = $1
AN...;UPDATE district
SET d_ytd = d_ytd + $1
WHERE d_id = $2
AND d_w_id = $3;SELECT c_id
FROM customer
WHERE c_w_id = $1
AND c_d_id = $2
AND c_last = $3
ORDER BY c_first ASC;SELECT c_first, c_middle, c_last, c_street_1, c_street_2, c_city,
c_state, c_zip, c_phone...;UPDATE customer
SET c_balance = c_balance - $1,
c_ytd_payment = c_ytd_payment + 1
WHERE c_id...;
DECLARE mycursor CURSOR FOR SELECT new_order(2, 3, 71, 1, 10, make_new_order_info(89856, 2, 4), ...;SELECT w_tax
FROM warehouse
WHERE w_id = $1;SELECT d_tax, d_next_o_id
FROM district
WHERE d_w_id = $1
AND d_id = $2
FOR UPDATE;UPDATE district
SET d_next_o_id = d_next_o_id + 1
WHERE d_w_id = $1
AND d_id = $2;SELECT c_discount, c_last, c_credit
FROM customer
WHERE c_w_id = $1
AND c_d_id = $2
AND c_id...;INSERT INTO new_order (no_o_id, no_w_id, no_d_id)
VALUES ($1, $2, $3);INSERT INTO orders (o_id, o_d_id, o_w_id, o_c_id, o_entry_d,
o_carrier_id, o_ol_cnt, o_all...;SELECT i_price, i_name, i_data
FROM item
WHERE i_id = $1;SELECT s_quantity, $1, s_data
FROM stock
WHERE s_i_id = $2
AND s_w_id = $3;UPDATE stock
SET s_quantity = s_quantity - $1
WHERE s_i_id = $2
AND s_w_id = $3;INSERT INTO order_line (ol_o_id, ol_d_id, ol_w_id, ol_number,
ol_i_id, ol_supply_w_id, ol_del...;SELECT i_price, i_name, i_data
FROM item
WHERE i_id = $1;SELECT s_quantity, $1, s_data
FROM sto...;
SELECT payment(1, 10, 1982, 1, 10, '', 1534.610000);SELECT w_name, w_street_1, w_street_2, w_city, w_state, w_zip
FROM warehouse
WHERE w_id = $1;UPDATE warehouse
SET w_ytd = w_ytd + $1
WHERE w_id = $2;SELECT d_name, d_street_1, d_street_2, d_city, d_state, d_zip
FROM district
WHERE d_id = $1
AN...;UPDATE district
SET d_ytd = d_ytd + $1
WHERE d_id = $2
AND d_w_id = $3;SELECT c_first, c_middle, c_last, c_street_1, c_street_2, c_city,
c_state, c_zip, c_phone...;
DECLARE mycursor CURSOR FOR SELECT new_order(9, 6, 1776, 1, 15, make_new_order_info(30711, 9, 8)...;SELECT w_tax
FROM warehouse
WHERE w_id = $1;SELECT d_tax, d_next_o_id
FROM district
WHERE d_w_id = $1
AND d_id = $2
FOR UPDATE;UPDATE district
SET d_next_o_id = d_next_o_id + 1
WHERE d_w_id = $1
AND d_id = $2;SELECT c_discount, c_last, c_credit
FROM customer
WHERE c_w_id = $1
AND c_d_id = $2
AND c_id...;INSERT INTO new_order (no_o_id, no_w_id, no_d_id)
VALUES ($1, $2, $3);INSERT INTO orders (o_id, o_d_id, o_w_id, o_c_id, o_entry_d,
o_carrier_id, o_ol_cnt, o_all...;SELECT i_price, i_name, i_data
FROM item
WHERE i_id = $1;SELECT s_quantity, $1, s_data
FROM stock
WHERE s_i_id = $2
AND s_w_id = $3;UPDATE stock
SET s_quantity = s_quantity - $1
WHERE s_i_id = $2
AND s_w_id = $3;INSERT INTO order_line (ol_o_id, ol_d_id, ol_w_id, ol_number,
ol_i_id, ol_supply_w_id, ol_del...;SELECT i_price, i_name, i_data
FROM item
WHERE i_id = $1;SELECT s_quantity, $1, s_data
FROM sto...;
DECLARE mycursor CURSOR FOR SELECT new_order(10, 8, 2223, 1, 15, make_new_order_info(14302, 10, ...;SELECT w_tax
FROM warehouse
WHERE w_id = $1;SELECT d_tax, d_next_o_id
FROM district
WHERE d_w_id = $1
AND d_id = $2
FOR UPDATE;UPDATE district
SET d_next_o_id = d_next_o_id + 1
WHERE d_w_id = $1
AND d_id = $2;SELECT c_discount, c_last, c_credit
FROM customer
WHERE c_w_id = $1
AND c_d_id = $2
AND c_id...;INSERT INTO new_order (no_o_id, no_w_id, no_d_id)
VALUES ($1, $2, $3);INSERT INTO orders (o_id, o_d_id, o_w_id, o_c_id, o_entry_d,
o_carrier_id, o_ol_cnt, o_all...;SELECT i_price, i_name, i_data
FROM item
WHERE i_id = $1;SELECT s_quantity, $1, s_data
FROM stock
WHERE s_i_id = $2
AND s_w_id = $3;UPDATE stock
SET s_quantity = s_quantity - $1
WHERE s_i_id = $2
AND s_w_id = $3;INSERT INTO order_line (ol_o_id, ol_d_id, ol_w_id, ol_number,
ol_i_id, ol_supply_w_id, ol_del...;SELECT i_price, i_name, i_data
FROM item
WHERE i_id = $1;SELECT s_quantity, $1, s_data
FROM sto...;
SELECT payment(5, 6, 686, 5, 6, '', 3196.450000);SELECT w_name, w_street_1, w_street_2, w_city, w_state, w_zip
FROM warehouse
WHERE w_id = $1;UPDATE warehouse
SET w_ytd = w_ytd + $1
WHERE w_id = $2;SELECT d_name, d_street_1, d_street_2, d_city, d_state, d_zip
FROM district
WHERE d_id = $1
AN...;UPDATE district
SET d_ytd = d_ytd + $1
WHERE d_id = $2
AND d_w_id = $3;SELECT c_first, c_middle, c_last, c_street_1, c_street_2, c_city,
c_state, c_zip, c_phone...;UPDATE customer
SET c_balance = c_balance - $1,
c_ytd_payment = c_ytd_payment + 1
WHERE c_id...;INSERT INTO history (h_c_id, h_c_d_id, h_c_w_id, h_d_id, h_w_id,
h_date, h_amount, h_data...;
SELECT payment(7, 5, 0, 7, 5, 'EINGABLEBAR', 2012.920000);SELECT w_name, w_street_1, w_street_2, w_city, w_state, w_zip
FROM warehouse
WHERE w_id = $1;UPDATE warehouse
SET w_ytd = w_ytd + $1
WHERE w_id = $2;SELECT d_name, d_street_1, d_street_2, d_city, d_state, d_zip
FROM district
WHERE d_id = $1
AN...;UPDATE district
SET d_ytd = d_ytd + $1
WHERE d_id = $2
AND d_w_id = $3;SELECT c_id
FROM customer
WHERE c_w_id = $1
AND c_d_id = $2
AND c_last = $3
ORDER BY c_first ASC;SELECT c_first, c_middle, c_last, c_street_1, c_street_2, c_city,
c_state, c_zip, c_phone...;UPDATE customer
SET c_balance = c_balance - $1,
c_ytd_payment = c_ytd_payment + 1
WHERE c_id...;INSERT INTO history (h_c_id, h_c_d_id, h_c_w_id, h_d_id, h_w_id,
h_date, h_amount, h_data...;
SELECT delivery(2, 3);SELECT no_o_id
FROM new_order
WHERE no_w_id = $1
AND no_d_id = $2ORDER BY no_o_id LIMIT 1;DELETE FROM new_order
WHERE no_o_id = $1
AND no_w_id = $2
AND no_d_id = $3;SELECT o_c_id
FROM orders
WHERE o_id = $1
AND o_w_id = $2
AND o_d_id = $3;UPDATE orders
SET o_carrier_id = $1
WHERE o_id = $2
AND o_w_id = $3
AND o_d_id = $4;UPDATE order_line
SET ol_delivery_d = current_timestamp
WHERE ol_o_id = $1
AND ol_w_id = $2
...;SELECT SUM(ol_amount * ol_quantity)
FROM order_line
WHERE ol_o_id = $1
AND ol_w_id = $2
AND ...;UPDATE customer
SET c_delivery_cnt = c_delivery_cnt + 1,
c_balance = c_balance + $1
WHERE c_...;SELECT no_o_id
FROM new_order
WHERE no_w_id = $1
AND no_d_id = $2ORDER BY no_o_id LIMIT 1;DELETE FROM new_order
WHERE no_o_id = $1
AND no_w_id = $2
AND no_d_id = $3;SELECT o_c_id
FROM orders
WHERE o_id = $1
AND o_w_id = $2
AND o_d_id = $3;UPDATE orders
SET o_carrier_id = $1
WHERE o_id = $2
AND o_w_id = $3
AND o_d_id = $4;
SELECT payment(6, 2, 0, 6, 2, 'BAROUGHTOUGHT', 2532.660000);SELECT w_name, w_street_1, w_street_2, w_city, w_state, w_zip
FROM warehouse
WHERE w_id = $1;UPDATE warehouse
SET w_ytd = w_ytd + $1
WHERE w_id = $2;SELECT d_name, d_street_1, d_street_2, d_city, d_state, d_zip
FROM district
WHERE d_id = $1
AN...;UPDATE district
SET d_ytd = d_ytd + $1
WHERE d_id = $2
AND d_w_id = $3;SELECT c_id
FROM customer
WHERE c_w_id = $1
AND c_d_id = $2
AND c_last = $3
ORDER BY c_first ASC;
DECLARE mycursor CURSOR FOR SELECT new_order(3, 2, 736, 1, 11, make_new_order_info(49102, 3, 2),...;SELECT w_tax
FROM warehouse
WHERE w_id = $1;SELECT d_tax, d_next_o_id
FROM district
WHERE d_w_id = $1
AND d_id = $2
FOR UPDATE;UPDATE district
SET d_next_o_id = d_next_o_id + 1
WHERE d_w_id = $1
AND d_id = $2;SELECT c_discount, c_last, c_credit
FROM customer
WHERE c_w_id = $1
AND c_d_id = $2
AND c_id...;INSERT INTO new_order (no_o_id, no_w_id, no_d_id)
VALUES ($1, $2, $3);INSERT INTO orders (o_id, o_d_id, o_w_id, o_c_id, o_entry_d,
o_carrier_id, o_ol_cnt, o_all...;SELECT i_price, i_name, i_data
FROM item
WHERE i_id = $1;SELECT s_quantity, $1, s_data
FROM stock
WHERE s_i_id = $2
AND s_w_id = $3;UPDATE stock
SET s_quantity = s_quantity - $1
WHERE s_i_id = $2
AND s_w_id = $3;INSERT INTO order_line (ol_o_id, ol_d_id, ol_w_id, ol_number,
ol_i_id, ol_supply_w_id, ol_del...;SELECT i_price, i_name, i_data
FROM item
WHERE i_id = $1;SELECT s_quantity, $1, s_data
FROM sto...;
DECLARE mycursor CURSOR FOR SELECT new_order(3, 6, 2034, 1, 14, make_new_order_info(88702, 3, 9)...;SELECT w_tax
FROM warehouse
WHERE w_id = $1;SELECT d_tax, d_next_o_id
FROM district
WHERE d_w_id = $1
AND d_id = $2
FOR UPDATE;UPDATE district
SET d_next_o_id = d_next_o_id + 1
WHERE d_w_id = $1
AND d_id = $2;SELECT c_discount, c_last, c_credit
FROM customer
WHERE c_w_id = $1
AND c_d_id = $2
AND c_id...;INSERT INTO new_order (no_o_id, no_w_id, no_d_id)
VALUES ($1, $2, $3);INSERT INTO orders (o_id, o_d_id, o_w_id, o_c_id, o_entry_d,
o_carrier_id, o_ol_cnt, o_all...;SELECT i_price, i_name, i_data
FROM item
WHERE i_id = $1;SELECT s_quantity, $1, s_data
FROM stock
WHERE s_i_id = $2
AND s_w_id = $3;UPDATE stock
SET s_quantity = s_quantity - $1
WHERE s_i_id = $2
AND s_w_id = $3;INSERT INTO order_line (ol_o_id, ol_d_id, ol_w_id, ol_number,
ol_i_id, ol_supply_w_id, ol_del...;SELECT i_price, i_name, i_data
FROM item
WHERE i_id = $1;SELECT s_quantity, $1, s_data
FROM sto...;
SELECT payment(1, 9, 924, 1, 9, '', 690.670000);SELECT w_name, w_street_1, w_street_2, w_city, w_state, w_zip
FROM warehouse
WHERE w_id = $1;UPDATE warehouse
SET w_ytd = w_ytd + $1
WHERE w_id = $2;SELECT d_name, d_street_1, d_street_2, d_city, d_state, d_zip
FROM district
WHERE d_id = $1
AN...;UPDATE district
SET d_ytd = d_ytd + $1
WHERE d_id = $2
AND d_w_id = $3;SELECT c_first, c_middle, c_last, c_street_1, c_street_2, c_city,
c_state, c_zip, c_phone...;UPDATE customer
SET c_balance = c_balance - $1,
c_ytd_payment = c_ytd_payment + 1,
c_dat...;INSERT INTO history (h_c_id, h_c_d_id, h_c_w_id, h_d_id, h_w_id,
h_date, h_amount, h_data...;
SELECT payment(3, 5, 0, 3, 5, 'BARANTIPRI', 1983.660000);SELECT w_name, w_street_1, w_street_2, w_city, w_state, w_zip
FROM warehouse
WHERE w_id = $1;UPDATE warehouse
SET w_ytd = w_ytd + $1
WHERE w_id = $2;SELECT d_name, d_street_1, d_street_2, d_city, d_state, d_zip
FROM district
WHERE d_id = $1
AN...;UPDATE district
SET d_ytd = d_ytd + $1
WHERE d_id = $2
AND d_w_id = $3;SELECT c_id
FROM customer
WHERE c_w_id = $1
AND c_d_id = $2
AND c_last = $3
ORDER BY c_first ASC;
SELECT payment(7, 1, 0, 7, 1, 'ABLEOUGHTESE', 4318.190000);SELECT w_name, w_street_1, w_street_2, w_city, w_state, w_zip
FROM warehouse
WHERE w_id = $1;UPDATE warehouse
SET w_ytd = w_ytd + $1
WHERE w_id = $2;SELECT d_name, d_street_1, d_street_2, d_city, d_state, d_zip
FROM district
WHERE d_id = $1
AN...;UPDATE district
SET d_ytd = d_ytd + $1
WHERE d_id = $2
AND d_w_id = $3;SELECT c_id
FROM customer
WHERE c_w_id = $1
AND c_d_id = $2
AND c_last = $3
ORDER BY c_first ASC;
DECLARE mycursor CURSOR FOR SELECT new_order(8, 6, 8, 1, 9, make_new_order_info(8020, 8, 5), mak...;SELECT w_tax
FROM warehouse
WHERE w_id = $1;SELECT d_tax, d_next_o_id
FROM district
WHERE d_w_id = $1
AND d_id = $2
FOR UPDATE;UPDATE district
SET d_next_o_id = d_next_o_id + 1
WHERE d_w_id = $1
AND d_id = $2;SELECT c_discount, c_last, c_credit
FROM customer
WHERE c_w_id = $1
AND c_d_id = $2
AND c_id...;INSERT INTO new_order (no_o_id, no_w_id, no_d_id)
VALUES ($1, $2, $3);INSERT INTO orders (o_id, o_d_id, o_w_id, o_c_id, o_entry_d,
o_carrier_id, o_ol_cnt, o_all...;SELECT i_price, i_name, i_data
FROM item
WHERE i_id = $1;SELECT s_quantity, $1, s_data
FROM stock
WHERE s_i_id = $2
AND s_w_id = $3;UPDATE stock
SET s_quantity = s_quantity - $1
WHERE s_i_id = $2
AND s_w_id = $3;INSERT INTO order_line (ol_o_id, ol_d_id, ol_w_id, ol_number,
ol_i_id, ol_supply_w_id, ol_del...;SELECT i_price, i_name, i_data
FROM item
WHERE i_id = $1;SELECT s_quantity, $1, s_data
FROM sto...;
SELECT payment(8, 10, 902, 8, 10, '', 4936.950000);SELECT w_name, w_street_1, w_street_2, w_city, w_state, w_zip
FROM warehouse
WHERE w_id = $1;UPDATE warehouse
SET w_ytd = w_ytd + $1
WHERE w_id = $2;SELECT d_name, d_street_1, d_street_2, d_city, d_state, d_zip
FROM district
WHERE d_id = $1
AN...;UPDATE district
SET d_ytd = d_ytd + $1
WHERE d_id = $2
AND d_w_id = $3;SELECT c_first, c_middle, c_last, c_street_1, c_street_2, c_city,
c_state, c_zip, c_phone...;UPDATE customer
SET c_balance = c_balance - $1,
c_ytd_payment = c_ytd_payment + 1
WHERE c_id...;INSERT INTO history (h_c_id, h_c_d_id, h_c_w_id, h_d_id, h_w_id,
h_date, h_amount, h_data...;
SELECT payment(7, 4, 0, 6, 1, 'ESEOUGHTOUGHT', 3180.460000);SELECT w_name, w_street_1, w_street_2, w_city, w_state, w_zip\
FROM warehouse\
WHERE w_id = $1;UPDATE warehouse\
SET w_ytd = w_ytd + $1\
WHERE w_id = $2;SELECT d_name, d_street_1, d_street_2, d_city, d_state, d_zip\
FROM district\
WHERE d_id = $1\
AN...;UPDATE district\
SET d_ytd = d_ytd + $1\
WHERE d_id = $2\
AND d_w_id = $3;SELECT c_id\
FROM customer\
WHERE c_w_id = $1\
AND c_d_id = $2\
AND c_last = $3\
ORDER BY c_first ASC;\
SELECT payment(7, 4, 0, 6, 1, 'ESEOUGHTOUGHT', 3180.460000);SELECT w_name, w_street_1, w_street_2, w_city, w_state, w_zip\
FROM warehouse\
WHERE w_id = $1;UPDATE warehouse\
SET w_ytd = w_ytd + $1\
WHERE w_id = $2;SELECT d_name, d_street_1, d_street_2, d_city, d_state, d_zip\
FROM district\
WHERE d_id = $1\
AN...;UPDATE district\
SET d_ytd = d_ytd + $1\
WHERE d_id = $2\
AND d_w_id = $3;SELECT c_id\
FROM customer\
WHERE c_w_id = $1\
AND c_d_id = $2\
AND c_last = $3\
ORDER BY c_first ASC;SELECT c_first, c_middle, c_last, c_street_1, c_street_2, c_city,\
c_state, c_zip, c_phone...;UPDATE customer\
SET c_balance = c_balance - $1,\
c_ytd_payment = c_ytd_payment + 1\
WHERE c_id...;
SELECT payment(8, 3, 0, 8, 3, 'CALLYBARABLE', 2287.110000);SELECT w_name, w_street_1, w_street_2, w_city, w_state, w_zip\
FROM warehouse\
WHERE w_id = $1;UPDATE warehouse\
SET w_ytd = w_ytd + $1\
WHERE w_id = $2;SELECT d_name, d_street_1, d_street_2, d_city, d_state, d_zip\
FROM district\
WHERE d_id = $1\
AN...;UPDATE district\
SET d_ytd = d_ytd + $1\
WHERE d_id = $2\
AND d_w_id = $3;SELECT c_id\
FROM customer\
WHERE c_w_id = $1\
AND c_d_id = $2\
AND c_last = $3\
ORDER BY c_first ASC;
SELECT payment(8, 3, 0, 8, 3, 'CALLYBARABLE', 2287.110000);SELECT w_name, w_street_1, w_street_2, w_city, w_state, w_zip\
FROM warehouse\
WHERE w_id = $1;UPDATE warehouse\
SET w_ytd = w_ytd + $1\
WHERE w_id = $2;SELECT d_name, d_street_1, d_street_2, d_city, d_state, d_zip\
FROM district\
WHERE d_id = $1\
AN...;UPDATE district\
SET d_ytd = d_ytd + $1\
WHERE d_id = $2\
AND d_w_id = $3;SELECT c_id\
FROM customer\
WHERE c_w_id = $1\
AND c_d_id = $2\
AND c_last = $3\
ORDER BY c_first ASC;\
This table shows the overview of entire this report.
Database system identifier: An ID which you will see using pg_controldata
Host name: Name of the host this instance resides on
Port ID: Port ID this server is listening on
PostgreSQL version: Version of PostgreSQL
Begins at: Timestamp of the earliest snapshot in this report
Ends at: Timestamp of the latest snapshot in this report
Period: Period of this report
Datbase size: Database size at the time of the latest snapshot in this report
Number of commits: Number of transactions committed during the period of this report
Number of rollbakcs: Number of transactions rollbacked during the period of this report
Each line in this table shows statistic overview of a database.
Database: Database name
MiB: Size of the database at the time of the last snapshot in MiB.
+MiB: Increase or decrease in the database size during this report period in MiB.
Commit/s: Average frequency of commits during this report period.
Rollback/s: Average frequency of rollbacks during this report period.
Hit%: Shared buffer's hit rate throughout this report period.
Gets/s: Average number of blocks per second requested during this report period.
Reads/s: Average number of blocks per second read from disks during this report period.
Rows/s: Average number of rows per second fetched from tables and indexes during thie report period.
* Small values may be shown as zero by round off.
This graph shows the trend of number of transactions per seconds.
[database name] size: Size of the database in bytes.
This table shows the number of canceled queries for every database due to conflict with some activities on master during this report period. This table have values only when the instance is a standby server.
Database: Database name
On tablespaces: Number of queries that have been canceled due to dropped table space.
On locks: Number of queries that have been canceled due to lock timeouts.
On snapshots: Number of queries that have been canceled due to old snapshots.
On bufferpins: Number of queries that have been canceled due to pinned buffers.
On deadlocks: Number of queries that have been canceled due to deadlocks.
This table shows the overview of Write Ahead Logs.
Total size: Total size of write ahead log (WAL or XLOG, stands on
transactions log) written out during this report period in MiB
Average output rate: Average output rate of WAL throughout this report period in MiB/s
Number of archived files: Number of successfully archived WAL segment files during this report period. Available on pg_statsinfo 3.1 or later and PostgreSQL 9.4 or later
Number of archiving errors: Number of WAL archiving errors occurred during this report period. Available on pg_statsinfo 3.1 or later and PostgreSQL 9.4 or later
Latest WAL file: File name of the WAL segment file currently written to. Available on pg_statsinfo 3.1 or later
Last archived file: File name of the WAL segment file most recently archived. Available on pg_statsinfo 3.1 or later and PostgreSQL 9.4 and later
This graph shows the trend of the rate of WAL output. One of the
lines shows amount of WAL written during every snapshot interval and
the another shows the amount divided by the snapshot interval.
Axes
Horizontal axis: Time
Left side vertial axis: Axis for Bytes/snapshot shown below.
Right side vertial axis: Axis for write rate shown below.
Legend
Bytes/snapshot: Amount of WAL written during every snapshot interval in bytes.
Write rate: Average write rate of WAL for every snapshot interval in bytes/s
This table shows the average percentage of time the backends spend in different state throughout this report period.
idle: Average percentage of time spent by the backends waiting a new client command throughout this report period
idle in xact: Average percentage of time spent by the backends waiting a command in a transaction throughout this report period
waiting: Average percentage of time spent by the backends waiting on a lock throughout this report period
running: Average percentage of time spent by the backends executing a query throughout this report period
The data in this table is collected by the interval specified with the configuration parameter pg_statsinfo.sampling_interval (5 seconds by default).
This graph shows the percentage of time the backends spend in different states over time.
Axes
Horizontal axis: Time
Vertial axis: Percentage
Legend
idle: Percentage of time spent by the backends waiting a new client command
idle in xact: Percentage of time spent by the backends waiting a command in a transaction
waiting: Percentage of time spent by the backends waiting on a lock
running: Percentage of time spent by the backends executing a query
This graph shows average for every snapshot interval of the percentage of states collected by the interval specified with the configuration parameter pg_statsinfo.sampling_interval (5 seconds by default).
This table shows the overview of the background writer process's activity.
Written buffers by bgwriter: Average number of buffers per second written by the background writer.
Written buffers by backends: Average number of buffers per second written directly by backends.
bgwriter scans quitted earlier: Average number of times per second the background writer stopped a cleaning scan because it had written too many buffers.
fsyncs executed on backends: Average number of times per second a backend had to execute its own fsync call because the checkpointer could not keep room for the fsync request.
Allocated buffers: Average number of buffers allocated per second.
This graph shows the trend of the background writer process's activity.
Axes
Horizontal axis: Time
Left side vertial axis: Buffers per second
Right side vertial axis: Frequency per second
Legend
Written buffers by bgwriter(L): Average number of buffers per second written by the background writer.
Written buffers by backends(L): Average number of buffers per second written directly by a backend.
Allocated buffers(L): Average number of buffers allocated per second.
bgwriter scans quitted earlier(R): Average number of times per second the background writer stopped a cleaning scan because it had written too many buffers.
fsyncs executed on backends(R): Average number of times per second a backend had to execute its own fsync call because the checkpointer could not keep room for the fsync request.
This graph shows the trend of percentage of time the CPU spends in different states.
Legend
Horizontal axis: Time
Vertial axis: Percentage
Legend
user: Percentage of time spent by the processes in user mode
system: Percentage of time spent by the processes in kernel mode
iowait: Percentage of time spent by the processes waiting for I/O to complete
idle: Percentage of time spent by the process waiting to run
This graph shows average percentage for every snapshot interval.
This graph shows system load averages over time.
Axes
Horizontal axis: Time
Vertial axis: Load average
Legend
1min: Load average for past one minute
5min: Load average for past five minutes
15min: Load average for past fifteen minutes
This graph shows itemized memory usage over time. The values are read from /proc/meminfo.
Axes
Horizontal axis: Time
Vertial axis: Memory usage in bytes. Alters by clicking "change scale" button between linear scale and log scale.
Legend
memfree: The amount of physical RAM left unused by the system.
buffers: The amount of physical RAM used for file buffers.
cached: The amount of physical RAM used as cache memory.
swap: The amount of swap under use.
dirty: The amount of memory waiting to be written back to the disk.
Each row in this table shows the overview of a table space.
Tablespace: Name of tablespace
Location: Path in the file system that this tablespace is located in
Device: Major and minor device numbers
Used: The amount of disk space used in the device in Mebibytes
Avail: The amount of available disk space in Mebibytes
Remain: Percentage of available space against the whole device
* Small values may be shown as zero by round off.
This section consists of one overview table and two graphs.
Each row in the Disk Usage per Table shows the disk usage
overview of one table.
Database: Name of the database this table resides in
Schema: Name of the schema this table belongs to
Table: Name of this table
Size: Size of this table in Mebibytes
Table reads: Number of PostgreSQL disk blocks read from disk accessing this table
Index reads: Number of PostgresQL disk blocks read from disk accessing all indexes on this table
Toast reads: Number of disk blocks read from disk reading this table's TOAST table and its index (if any)
* Small values may be shown as zero by round off.
The Table Size Chart shows the table size ratios in different tables.
The Disk Read Chart shows the ratios of the number of blocks read
from a table and its belongings in different tables.
This section consists of one overview table and three trend
graphs. The graphs are hidden at first and comes out by clicking the
corresponding links.
The I/O Usage Table shows the overview of I/O usage throughout the report period. Each row represents one device.
Device name: Name of the device
Containing table spaces: List of table spaces located in the device
Read: Device read statistics
Total bytes (MiB): Read bytes throughout the report period in Mebibytes
Peak rate (KiB/s): Maximum read rate during the report period in Kibibytes per seconds. Available on pg_statsinfo 3.1 or later
Total time (ms): Sum of the time spent to read this device in milliseconds throughout this report period
Write: Device write statistics
Total bytes (MiB): Write bytes throughout the report period in Mebibytes
Peak rate (KiB/s): maximum write rate during the report period in Kibibytes. Available on pg_statsinfo 3.1 or later
Total time (ms): Sum of the time spent to write to this device in milliseconds
Average I/O queue: Average length of I/O queue throughout this report period
Total I/O time (ms): Sum of the time spent by I/O operations in milliseconds. This field corresponds to "weighted # of milliseconds spent doing I/Os" in /proc/diskstats
* Small values may be shown as zero by round off.
The I/O Rate Graph shows the read/write rate over snapshots. The values are the average in a snapshot.
Axes
Horizontal axis: Time
Vertial axis: I/O rate in bytes per seconds
Legend
[device] read: Read I/O rate
[device] write: Write I/O rate
The I/O Peak Rate Graph shows the read/write peak rate over snapshots. The values are the maximum within a snapshot. Available on pg_statsinfo 3.1 or later.
Axes
Horizontal axis: Time
Vertial axis: I/O peak rate in every snapshot in bytes per seconeds
Legend
[device] read: Read I/O rate
[device] write: Write I/O rate
The I/O Time Graph shows the time spent by reading from or writing
to the device over snapshots. The values are percentage of I/O time
against real time and are the sums over all processes simultaneously
running so they may go above 100 % for certain load.
Axes
Horizontal axis: Time
Vertial axis: Percentage of I/O Time against real time
Legend
[device] avg read time: Read time
[device] avg write time: Write time
Each row in this table shows the update activity overview of a table. The rows are shown in descending order of the "Total" field at first.
Database: Name of the database this table resides in
Schema: Name of the schema this table belongs to
Table: Name of this table
INSERT: Number of rows inserted during this report period
UPDATE: Number of rows updated during this report period including HOT updates
DELETE: Number of rows deleted during this report period
Total: The sum of the three fields above
HOT (%): Percentage of HOT updates against all UPDATEs
Each row in this table shows the scan activity overview of a
table. The rows are shown in descending order of the "Seq scan" field at
first.
Database: Name of the database this table resides in
Schema: Name of the schema this table belongs to
Table: Name of this table
Seq scan: Number of sequential scans ran on this table during this report period
Seq tup read: Number of tuples fetched by sequential scans on this table during this report period
Tup per seq: Average number of tuples fetched by one sequential scan throughout this report period
Hit ratio: Cache hit ratio in percent of this table averaged throughout this report period
Each rows in this table shows some figures related to filling factor of one table at the time of the latest snapshot in reportin period. The rows are shown in descending order of the "Tuples" field at first.
Database: Name of the database this table resides in
Schema: Name of the schama this table belongs to
Table: Name of this table
Tuples: Number of live tuples in this table
Logical pages: Estimated pages required to store all live tuples
Physical pages: Number of pages allocated to this table
Each row in this table shows the fragmentation (correlation
between physical and logical ordering) of one column. The correlation
factor closer to zero means the stronger fragmentation of column. The rows are shown in descending order of the "Correlation" field at first.
Database: Name of the database that the table containig this column resides in
Schema: Name of the schema that the table containing this columns belongs to
Table: Name of the table this column belongs to
Column: Name of this column
Correlation: Correlation factor of the values of this column
Each row in this table shows usage statistics of one function. The rows are shown in descending order of the "Time/call" field at first.
Database: Name of the database this function resides in
Schema: Name of the schema this function belongs to
Function: Name of this function
Calls: Number of times this function has been called during this report period
Total time: Total time spent in this function and all other functions called by it during this report period in milliseconds
Self time: Total time spent in this function itself during this report period in milliseconds
Time/call: Average total time per one call throughout this report period in milliseconds
Each row in this table shows execution statistics of a
query. Multiple execitions by diffent users or on different databases
of a statement have their own rows. This feature requires
pg_stat_statsments to be installed.
User: Name of the user who executed this statement
Database: Name of the database in which this statement was executed
Query: Text of a representative statement
Calls: Number of times this statement executed during this report period
Total time: Total time spent in this statement during this report period in seconds
Time/call: Average total time per call throughout this report period in seconds
Each row in this table shows execution statistics itemized by execution plan. Clicking Query ID opens the itemized execution plan statistics. This feature requires pg_stat_statements and pg_store_plans to be installed.
Query ID: Hash code of this query. This field is calculated by
pg_stat_statements on PostgreSQL 9.4 or later and is of
pg_store_plans' own calculation otherwise. So query identification may
be different from pg_stat_statement in some cases for the older
versions of PosgreSQL.
User: Name of the user who executed this statement
Database: Name of the database in which the statement was executed
Plan count: Number of plans executed for the statemnet
Calls: Number of times this statement executed
Total time: Total time spent in this statment during this report period in seconds
Time/call: Average time per execution of this query throughout thie report period in seconds
Block read time: Total time this query spent to read blocks during this report time in milliseconds. This and the next field requires track_io_timing to be enabled.
Block write time: Total time this query spent to write blocks during this report time in milliseconds.
Query: Query string corresponding the plans listed. Shown by clicking Query ID
Plan details: Execution summaries of individual plans. Shown by clicking Query ID
Plan ID: Hash code which identifies plans.
Calls: Number of times this plan exected during this report period
Total time: Total time spent in single execution throughout this report period in seconds
Time/call: Average time per execution of this plan throughout this report period in seconds
Block read time: Total time this plan spent to read blocks during this report period in milliseconds. This field and the next field requires track_io_timing to be enabled.
Block write time: Total time this plan spent to write blocks during this report period in millisecond
First call: Time when this plan first executed
Last call: Time when this plan last executed
Plan: Plan string. This string holds numbers in last execution, which are omitted in calculating plan IDs.
This table shows the list of long lasting transactions. Every
snapshot holds certain number of longest transactions at the time of
creation and the entries of the same transaction over snapshots are
merged on generating report then the merged transactions are shown in
this table, in descending order of their duration at
first. Transactions are identified by the set of "PID", "Client
address" and "Xact Start". pg_statsinfo.long_transaction_max specifies
how many long transactions every snapshot records.
PID: PID of the backend process where the transaction running on
Client address: Client IP address connected to the backend process
Xact Start: Time when the transaction has started
Duration: Time elapsed since the transaction started
Last query: Query string that last executed in the transaction
This table shows lock conflicts observed druing this report period.
Database: Name of the database where this conflict occurs
Schema: Name of the schema of the relation where this conflict occurs. This field left blank if the conflict is occurred on other than a relation.
Relation: Name of the relation where this coflict occurs. This field left blank if the conflict is occurred on other than a relation.
Duration: Time spent to wait for the lock to be acquired
Blockee PID: Process ID of the blocked backend
Blocker PID: Process ID of the blocking backend
Blocker GID: Group ID of the blocking backend
Blockee query: Query string wating for the lock
Blocker query: Queries executed in the blocking transaction. This field is no longer than 1000 bytes so it may be cut off at the middle of the queries
This table shows the summary of checkpoint activity.
Number of checkpoints: Number of checkpoints completed during this report period
Caused by timeout: Number of checkpoints started by chckpoint timeout
Caused by xlogs: Number of checkpoints started by XLOG growth
Average written buffers: Average number of the written buffers by each checkpoint throughout this report period
Maximum written buffers: Number of the buffers written by the checkpoint that have written largest number of buffers throughout this report period
Average checkpoint duration: Average duration of checkpoints cmopleted during this report period, in seconds
Maximum checkpoint duration: Duration of the checkpoint with the longest completion time in this report period, in seconds
This table shows the overview of autovacuum activities. Each row
corresponds to one table on which logged that autovacuums are done. This shows only
tables that autovacuum has been done at least once in this report
period.
Database: Name of the database this table resides in
Schema: Name of the schema this table belongs to
Table: Name of this table
Count: Number of autovacuum executed on this table
Avg index scans: Average number of indexes involved in each vacuum on table
Avg removed rows: Avarage number of rows that each autovacuum removed throughout this report period
Avg remain rows: Average number of rows that each autovacuum had not removed throughout this report period. This includes "Avg remain dead".
Avg remain dead: Average number of dead rows that each autovacuum cannot be removed. Available for pg_statsinfo 3.1 or higher and PostgreSQL 9.4 or later
Avg duration: Average time each autovacuum during this report period took, in seconds
Max duration: Maximum duration among all autovacuums executed during this report period, in secods
Cancels: Number of cancelled autovacuum trial during this report period. Available on pg_statsinfo 3.0 or later and PostgresQL 9.3 and later
o
This feature reuiqres autovacuum logs so set
log_autovacuum_min_duration to 0 to make this feature fully
available. Less logging reduces the completeness this table.
This table shows the I/O statistics for autovacuums. Each row
corresponds to one table reported in autovacuum logs. This feature is available on PostgreSQL 9.2 or later.
Database: Name of the database this table resides in
Schema: Name of the schema this table belongs to
Table: Name of the table
Avg page hit: Average number of buffers that each autovacuum read from shared buffers throughout this report period
Avg page miss: Average number of buffers that each autovacuum read from disks throughout this report period
Avg page dirtied: Average number of buffers that each autovacuum has dirtied throughout this report period
Avg read rate: Average time that each autovacuum spent to read disks throughout this report period in MB/s
Avg write rate: Average time that each autovacuum spent to write disks throughout this report period in MB/s
This table shows the overview of autoanalyze activities. Each row
corresponds to one table reported in autoanalyze logs.
Database: Name of the database this table resides in
Schema: Name of the schema this table belongs to
Table: Name of this table
Count: Number of autoanalyze executed on this table during this report period
Total duration: Total time of each autoanalyze execution on this table during this report period
Avg duration: Average time of each autoanalyze execution on this table throughout this report period
Max duration: Execution time of autoanalyze on this table which took longest, in seconds
Last analyzed: Time when the last autoanalyze ran on this table. Available on pg_statsinfo 3.0
Cancels: Number of autoanalyze cancellation occurred on this table. Available on pg_statsinfo 3.1 or later
Max modified rows: Maximum number of rows modified during autovacuum intervals throughout this report period. Available on pg_statsinfo 3.1 or later and PostgreSQL 9.4 and later.
This feature requires autovanalyze logs so set
log_autovacuum_min_duration to 0 to make this feature fully
available. Less logging reduces the completeness this table.
This graph shows how many rows are inserted, updated or deleted since last analyze for each table in percentage to all tuples including dead tuples, which is related to the threshold of autoanalyze.
Axes
Horizontal axis: Time
Vertial axis: Percentage of modified rows against all rows including dead tuples stored in the table
Legend
[table] ratio: Percentage of modified rows for the table
To avoid losing readability of the graph, only ten largest tables in number of tuples are shown in this graph. The values are calculated as pg_stat_get_mod_since_analyze(table) / (reltuples of the table).
This table lists the cancellation events of autovacuums and autoanalyzes occurred during this report period.
Time: timestamp
Database: Name of the database the table resides in
Schema: Name of the schema the table belongs to
Table: Name of the table where the cancellation occurred
Activity: Canclled activity, either of ANALYZE or VACUUM
Causal query: Query string caused the cancellation
This table shows the overview of replication activities at the end
of reporting period. One column is shown for one replication
session.
Session user: Name of the user logged into this WAL sender process
Application name: Application name that is connected to this WAL sender
Client address: IP address of the client connected to this WAL sender
Client host: Host name of the client connected to this WAL sender
Client port: TCP port number that the client is using for communication with this WAL sender
Started at: Time when this process was started
State: Current WAL sender state
Current location: Current transaction log position and WAL segment name on this cluster
Sent location: Last transaction log position and WAL segment name sent on this connection
Write location: Last transaction log position and WAL segment name written to disk by this standby server
Flush location: Last transaction log position and WAL segment name flushed to disk by this standby server
Replay location: Last transaction log position and WAL segment name replayed into the database on this standby server
Average replay delay: Average delay amount of replay on standby server
Peak replay delay: Peak delay amount of replay on standby server
Sync priority: Priority of the standby server for being chosen as the synchronous standby
Sync state: Synchronous state of this standby server
This graph shows how far the standby servers are behind this server.
Axes
Horizontal axis: Time
Vertical axis: Delays in bytes
Legend
[address]: [port-number] flush: Delay amount of flush on standby server. * Synchronous standby is prefixed by [sync] and drawn by thick line.
[address]: [port-number] replay: Delay amount of replay on standby server. * Synchronous standby is prefixed by [sync] and drawn by thick line
Each rows in this table shows the overview of a database table.
Database: Name of the database this table resides in
Schema: Name of the schema this table belongs to
Table: Name of this table
Columns: Number of user columns in this table
Rows: Number of rows in this table. Available only on pg_statsinfo 3.0 or later
MiB: Size of this table at the end of this report period in Mebibytes
+MiB: Increase or decrease in size of this table during this report period in Mebibytes
Table scans: Number of sequential scans executed during this report period
Index scans: Number of index scans executed during this report period
* Small values may be shown as zero by round off.
Each rows in this table shows the overview of a index.
Database: Name of the databsae this index resides in
Schema: Name of the schema this index belongs to
Index: Name of this table
Table: Name of the table this index belongs to
MiB: Size of this index at the end of this report period in Mebibytes
+MiB: Increase or descrease in size of this index during this report period in Mebibytes
Scans: Number of scans executed on this index during this report period
Rows/scan: Average number of live heap tuples fetched by each simple index scan using this index throughout this report period
Reads: Number of (PostgreSQL) blocks read from disk on accessing this index during this report period
Hits: Number of buffer hits in this index during this report period
Keys: List of keys of this index
* Small values may be shown as zero by round off.
This table lists all run-time parameters.
Name: Name of the parameter
Setting: Current value of the parameter if it is not changed though this report period. Shows the transition elsewise.
Unit: Implicit unit of this parameter
Source: Source of the value at the end of this report period
This table lists the alerts issued during this report period.
Time: Time when this alert issued
Message: Alert message body
Changing alert settings.
Update the alert setting table of the repository database to change alert settings.
Please see the pg_statsinfo manual for details.
e.g. Change the threshold of Rollback per seconds to "3000" for instance 1.
UPDATE statsrepo.alert SET rollback_tps = 3000 WHERE instid = 1;
This table shows the summary for profiling using system tap.
Processing: Name of the condition probed
Executes: Frequency counter for the condition
The log viewer shows the server log lines sotred in repository. This allows you to narrow down or search logs for specific events easily on GUI.
Search Options
This section determines how to restrict log lines fetched from repository. The fetched lines are shown in the Log Table below.
ELEVEL: Error message level
USERNAME: User name
DATABASE: Database name
MESSAGE: Error message (POSIX regexps for ~ operators of PostgreSQL)
The Log Table
Each row in this table shows one log line. The first row in this table is quick filter fields, which will cleared by the Filter Reset button. You can select columns to show by the "Column" button. The following is the list of all available columns.
timestamp: Timestamp
username: User name
database: Database name
pid: Process ID
client_addr: Client IP address
session_id: Session ID
session_line_num: Number of the log line for each session or process
ps_display: Command tag
session_start: Process start time stamp
vxid: Virtual transaction ID
xid: Transaction ID
elevel: Error severity
sqlstate: SQLSTATE code
message: Error message
detail: error message detail
hint: Hint
query: Internal query that led to the error
query_pos: Character count of the error position therein
context: Error context
user_query: User query that led to the error
user_query_pos: Character count of the error position therein
location: Location of the error in the PostgreSQL source code
