github.com/cockroachdb/cockroach@v20.2.0-alpha.1+incompatible/pkg/sql/opt/memo/testdata/stats_quality/tpch/q02 (about) 1 import file=tpch_schema 2 ---- 3 4 import file=tpch_stats 5 ---- 6 7 # -------------------------------------------------- 8 # Q2 9 # Minimum Cost Supplier 10 # Finds which supplier should be selected to place an order for a given part in 11 # a given region. 12 # 13 # Finds, in a given region, for each part of a certain type and size, the 14 # supplier who can supply it at minimum cost. If several suppliers in that 15 # region offer the desired part type and size at the same (minimum) cost, the 16 # query lists the parts from suppliers with the 100 highest account balances. 17 # For each supplier, the query lists the supplier's account balance, name and 18 # nation; the part's number and manufacturer; the supplier's address, phone 19 # number and comment information. 20 # 21 # TODO: 22 # 1. Join ordering 23 # 2. Push down equivalent column comparisons 24 # 3. Allow Select to be pushed below Ordinality used to add key column 25 # 4. Add decorrelation rule for Ordinality/RowKey 26 # -------------------------------------------------- 27 save-tables database=tpch save-tables-prefix=q2 28 SELECT 29 s_acctbal, 30 s_name, 31 n_name, 32 p_partkey, 33 p_mfgr, 34 s_address, 35 s_phone, 36 s_comment 37 FROM 38 part, 39 supplier, 40 partsupp, 41 nation, 42 region 43 WHERE 44 p_partkey = ps_partkey 45 AND s_suppkey = ps_suppkey 46 AND p_size = 15 47 AND p_type LIKE '%BRASS' 48 AND s_nationkey = n_nationkey 49 AND n_regionkey = r_regionkey 50 AND r_name = 'EUROPE' 51 AND ps_supplycost = ( 52 SELECT 53 min(ps_supplycost) 54 FROM 55 partsupp, 56 supplier, 57 nation, 58 region 59 WHERE 60 p_partkey = ps_partkey 61 AND s_suppkey = ps_suppkey 62 AND s_nationkey = n_nationkey 63 AND n_regionkey = r_regionkey 64 AND r_name = 'EUROPE' 65 ) 66 ORDER BY 67 s_acctbal DESC, 68 n_name, 69 s_name, 70 p_partkey 71 LIMIT 100; 72 ---- 73 project 74 ├── save-table-name: q2_project_1 75 ├── columns: s_acctbal:15(float!null) s_name:11(char!null) n_name:23(char!null) p_partkey:1(int!null) p_mfgr:3(char!null) s_address:12(varchar!null) s_phone:14(char!null) s_comment:16(varchar!null) 76 ├── cardinality: [0 - 100] 77 ├── stats: [rows=1, distinct(1)=1, null(1)=0, distinct(3)=1, null(3)=0, distinct(11)=1, null(11)=0, distinct(12)=1, null(12)=0, distinct(14)=1, null(14)=0, distinct(15)=1, null(15)=0, distinct(16)=1, null(16)=0, distinct(23)=1, null(23)=0] 78 ├── fd: (1)-->(3) 79 ├── ordering: -15,+23,+11,+1 80 └── limit 81 ├── save-table-name: q2_limit_2 82 ├── columns: p_partkey:1(int!null) p_mfgr:3(char!null) s_name:11(char!null) s_address:12(varchar!null) s_phone:14(char!null) s_acctbal:15(float!null) s_comment:16(varchar!null) ps_partkey:17(int!null) ps_suppkey:18(int!null) ps_supplycost:20(float!null) n_name:23(char!null) min:48(float!null) 83 ├── internal-ordering: -15,+23,+11,+(1|17) 84 ├── cardinality: [0 - 100] 85 ├── stats: [rows=1, distinct(1)=1, null(1)=0, distinct(3)=1, null(3)=0, distinct(11)=1, null(11)=0, distinct(12)=1, null(12)=0, distinct(14)=1, null(14)=0, distinct(15)=1, null(15)=0, distinct(16)=1, null(16)=0, distinct(17)=0.999910488, null(17)=0, distinct(18)=0.999982066, null(18)=0, distinct(20)=1, null(20)=0, distinct(23)=1, null(23)=0, distinct(48)=1, null(48)=0] 86 ├── key: (17,18) 87 ├── fd: (1)-->(3), (17,18)-->(1,3,11,12,14-16,20,23,48), (1)==(17), (17)==(1), (18)-->(11,12,14-16,23), (20)==(48), (48)==(20) 88 ├── ordering: -15,+23,+11,+(1|17) [actual: -15,+23,+11,+1] 89 ├── sort 90 │ ├── save-table-name: q2_sort_3 91 │ ├── columns: p_partkey:1(int!null) p_mfgr:3(char!null) s_name:11(char!null) s_address:12(varchar!null) s_phone:14(char!null) s_acctbal:15(float!null) s_comment:16(varchar!null) ps_partkey:17(int!null) ps_suppkey:18(int!null) ps_supplycost:20(float!null) n_name:23(char!null) min:48(float!null) 92 │ ├── stats: [rows=1, distinct(1)=1, null(1)=0, distinct(3)=1, null(3)=0, distinct(11)=1, null(11)=0, distinct(12)=1, null(12)=0, distinct(14)=1, null(14)=0, distinct(15)=1, null(15)=0, distinct(16)=1, null(16)=0, distinct(17)=0.999910488, null(17)=0, distinct(18)=0.999982066, null(18)=0, distinct(20)=1, null(20)=0, distinct(23)=1, null(23)=0, distinct(48)=1, null(48)=0] 93 │ ├── key: (17,18) 94 │ ├── fd: (1)-->(3), (17,18)-->(1,3,11,12,14-16,20,23,48), (1)==(17), (17)==(1), (18)-->(11,12,14-16,23), (20)==(48), (48)==(20) 95 │ ├── ordering: -15,+23,+11,+(1|17) [actual: -15,+23,+11,+1] 96 │ ├── limit hint: 100.00 97 │ └── select 98 │ ├── save-table-name: q2_select_4 99 │ ├── columns: p_partkey:1(int!null) p_mfgr:3(char!null) s_name:11(char!null) s_address:12(varchar!null) s_phone:14(char!null) s_acctbal:15(float!null) s_comment:16(varchar!null) ps_partkey:17(int!null) ps_suppkey:18(int!null) ps_supplycost:20(float!null) n_name:23(char!null) min:48(float!null) 100 │ ├── stats: [rows=1, distinct(1)=1, null(1)=0, distinct(3)=1, null(3)=0, distinct(11)=1, null(11)=0, distinct(12)=1, null(12)=0, distinct(14)=1, null(14)=0, distinct(15)=1, null(15)=0, distinct(16)=1, null(16)=0, distinct(17)=0.999910488, null(17)=0, distinct(18)=0.999982066, null(18)=0, distinct(20)=1, null(20)=0, distinct(23)=1, null(23)=0, distinct(48)=1, null(48)=0] 101 │ ├── key: (17,18) 102 │ ├── fd: (1)-->(3), (17,18)-->(1,3,11,12,14-16,20,23,48), (1)==(17), (17)==(1), (18)-->(11,12,14-16,23), (20)==(48), (48)==(20) 103 │ ├── group-by 104 │ │ ├── save-table-name: q2_group_by_5 105 │ │ ├── columns: p_partkey:1(int!null) p_mfgr:3(char!null) s_name:11(char!null) s_address:12(varchar!null) s_phone:14(char!null) s_acctbal:15(float!null) s_comment:16(varchar!null) ps_partkey:17(int!null) ps_suppkey:18(int!null) ps_supplycost:20(float!null) n_name:23(char!null) min:48(float!null) 106 │ │ ├── grouping columns: ps_partkey:17(int!null) ps_suppkey:18(int!null) 107 │ │ ├── stats: [rows=1487.22684, distinct(1)=1487.22684, null(1)=0, distinct(3)=1487.22684, null(3)=0, distinct(11)=1487.22684, null(11)=0, distinct(12)=1487.22684, null(12)=0, distinct(14)=1487.22684, null(14)=0, distinct(15)=1487.22684, null(15)=0, distinct(16)=1487.22684, null(16)=0, distinct(17)=1174.55443, null(17)=0, distinct(18)=1411.92479, null(18)=0, distinct(20)=1487.22684, null(20)=0, distinct(23)=1487.22684, null(23)=0, distinct(48)=1487.22684, null(48)=0, distinct(17,18)=1487.22684, null(17,18)=0] 108 │ │ ├── key: (17,18) 109 │ │ ├── fd: (1)-->(3), (17,18)-->(1,3,11,12,14-16,20,23,48), (1)==(17), (17)==(1), (18)-->(11,12,14-16,23) 110 │ │ ├── inner-join (hash) 111 │ │ │ ├── save-table-name: q2_inner_join_6 112 │ │ │ ├── columns: p_partkey:1(int!null) p_mfgr:3(char!null) p_type:5(varchar!null) p_size:6(int!null) s_suppkey:10(int!null) s_name:11(char!null) s_address:12(varchar!null) s_nationkey:13(int!null) s_phone:14(char!null) s_acctbal:15(float!null) s_comment:16(varchar!null) ps_partkey:17(int!null) ps_suppkey:18(int!null) ps_supplycost:20(float!null) n_nationkey:22(int!null) n_name:23(char!null) n_regionkey:24(int!null) r_regionkey:26(int!null) r_name:27(char!null) ps_partkey:29(int!null) ps_suppkey:30(int!null) ps_supplycost:32(float!null) s_suppkey:34(int!null) s_nationkey:37(int!null) n_nationkey:41(int!null) n_regionkey:43(int!null) r_regionkey:45(int!null) r_name:46(char!null) 113 │ │ │ ├── stats: [rows=2837.30948, distinct(1)=1333.31636, null(1)=0, distinct(3)=5, null(3)=0, distinct(5)=149.999649, null(5)=0, distinct(6)=1, null(6)=0, distinct(10)=1411.92479, null(10)=0, distinct(11)=1412.48485, null(11)=0, distinct(12)=1412.56423, null(12)=0, distinct(13)=5, null(13)=0, distinct(14)=1412.56423, null(14)=0, distinct(15)=1412.30169, null(15)=0, distinct(16)=1412.03742, null(16)=0, distinct(17)=1174.55443, null(17)=0, distinct(18)=1411.92479, null(18)=0, distinct(20)=1482.68691, null(20)=0, distinct(22)=5, null(22)=0, distinct(23)=5, null(23)=0, distinct(24)=1, null(24)=0, distinct(26)=1, null(26)=0, distinct(27)=0.996222107, null(27)=0, distinct(29)=1333.31636, null(29)=0, distinct(30)=1448.52495, null(30)=0, distinct(32)=2787.75127, null(32)=0, distinct(34)=1448.52495, null(34)=0, distinct(37)=5, null(37)=0, distinct(41)=5, null(41)=0, distinct(43)=1, null(43)=0, distinct(45)=1, null(45)=0, distinct(46)=0.996222107, null(46)=0, distinct(17,18)=1487.22684, null(17,18)=0] 114 │ │ │ ├── key: (18,29,34) 115 │ │ │ ├── fd: ()-->(6,27,46), (1)-->(3,5), (10)-->(11-16), (17,18)-->(20), (22)-->(23,24), (24)==(26), (26)==(24), (10)==(18), (18)==(10), (13)==(22), (22)==(13), (1)==(17,29), (17)==(1,29), (29,30)-->(32), (34)-->(37), (41)-->(43), (43)==(45), (45)==(43), (37)==(41), (41)==(37), (30)==(34), (34)==(30), (29)==(1,17) 116 │ │ │ ├── inner-join (hash) 117 │ │ │ │ ├── save-table-name: q2_inner_join_7 118 │ │ │ │ ├── columns: ps_partkey:29(int!null) ps_suppkey:30(int!null) ps_supplycost:32(float!null) s_suppkey:34(int!null) s_nationkey:37(int!null) n_nationkey:41(int!null) n_regionkey:43(int!null) r_regionkey:45(int!null) r_name:46(char!null) 119 │ │ │ │ ├── stats: [rows=161290.323, distinct(29)=110568.431, null(29)=0, distinct(30)=1844.80594, null(30)=0, distinct(32)=80252.0719, null(32)=0, distinct(34)=1844.80594, null(34)=0, distinct(37)=5, null(37)=0, distinct(41)=5, null(41)=0, distinct(43)=1, null(43)=0, distinct(45)=1, null(45)=0, distinct(46)=0.996222107, null(46)=0] 120 │ │ │ │ ├── key: (29,34) 121 │ │ │ │ ├── fd: ()-->(46), (29,30)-->(32), (34)-->(37), (41)-->(43), (43)==(45), (45)==(43), (37)==(41), (41)==(37), (30)==(34), (34)==(30) 122 │ │ │ │ ├── scan partsupp 123 │ │ │ │ │ ├── save-table-name: q2_scan_8 124 │ │ │ │ │ ├── columns: ps_partkey:29(int!null) ps_suppkey:30(int!null) ps_supplycost:32(float!null) 125 │ │ │ │ │ ├── stats: [rows=800000, distinct(29)=199241, null(29)=0, distinct(30)=9920, null(30)=0, distinct(32)=100379, null(32)=0] 126 │ │ │ │ │ │ histogram(29)= 0 80 3920 80 3920 80 3920 80 3920 80 3840 160 3840 160 3920 80 3920 80 3920 80 3920 80 3920 160 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3840 160 3920 80 3920 80 3920 80 3920 80 3920 160 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3840 160 3920 80 3920 80 3920 160 3920 80 3920 160 3920 80 3920 80 3920 80 3920 80 3920 80 3920 160 3920 80 3920 80 3920 80 3920 80 3920 80 3920 160 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 3920 160 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 127 │ │ │ │ │ │ <--- 4 ------ 793 ------ 1856 ------ 2808 ------ 3809 ------ 4923 ------ 5975 ------ 6944 ------ 8085 ------ 8945 ------ 9831 ------ 10952 ------ 11932 ------ 12775 ------ 13849 ------ 14925 ------ 16016 ------ 16828 ------ 17768 ------ 18705 ------ 19631 ------ 20600 ------ 21491 ------ 22254 ------ 23327 ------ 24491 ------ 25470 ------ 26331 ------ 27327 ------ 28308 ------ 29359 ------ 30542 ------ 31592 ------ 32495 ------ 33408 ------ 34624 ------ 35726 ------ 36676 ------ 37637 ------ 38485 ------ 39368 ------ 40372 ------ 41034 ------ 42185 ------ 43333 ------ 44466 ------ 45440 ------ 46571 ------ 47469 ------ 48346 ------ 49379 ------ 50571 ------ 51830 ------ 52967 ------ 53673 ------ 54656 ------ 55504 ------ 56539 ------ 57393 ------ 58366 ------ 59577 ------ 60559 ------ 61676 ------ 62471 ------ 63421 ------ 64449 ------ 65409 ------ 66254 ------ 67127 ------ 68127 ------ 69177 ------ 70183 ------ 71209 ------ 72101 ------ 73102 ------ 73994 ------ 74899 ------ 76016 ------ 77098 ------ 77842 ------ 79137 ------ 80242 ------ 81364 ------ 82331 ------ 83158 ------ 84283 ------ 85282 ------ 86437 ------ 87450 ------ 88419 ------ 89493 ------ 90478 ------ 91468 ------ 92552 ------ 93200 ------ 94191 ------ 95067 ------ 96272 ------ 97228 ------ 98126 ------ 99198 ------ 100219 ------ 101057 ------ 102038 ------ 102775 ------ 103711 ------ 104623 ------ 105710 ------ 106734 ------ 107932 ------ 109255 ------ 110220 ------ 111235 ------ 112174 ------ 113260 ------ 114081 ------ 115103 ------ 115864 ------ 116794 ------ 117741 ------ 118712 ------ 119470 ------ 120528 ------ 121572 ------ 122536 ------ 123629 ------ 124404 ------ 125301 ------ 126257 ------ 127139 ------ 128267 ------ 129258 ------ 130442 ------ 131845 ------ 133164 ------ 134005 ------ 135076 ------ 135868 ------ 137297 ------ 138777 ------ 139806 ------ 140741 ------ 141896 ------ 142719 ------ 143727 ------ 144645 ------ 145510 ------ 146507 ------ 147449 ------ 148467 ------ 149635 ------ 150563 ------ 151751 ------ 152613 ------ 153416 ------ 154612 ------ 155853 ------ 156866 ------ 158311 ------ 159230 ------ 160390 ------ 161455 ------ 162555 ------ 163435 ------ 164549 ------ 165663 ------ 166891 ------ 167757 ------ 168732 ------ 169644 ------ 170532 ------ 171671 ------ 172778 ------ 173599 ------ 174321 ------ 175624 ------ 176663 ------ 177632 ------ 178555 ------ 179551 ------ 180510 ------ 181682 ------ 182648 ------ 183408 ------ 184543 ------ 185722 ------ 186713 ------ 187787 ------ 188730 ------ 189604 ------ 190711 ------ 191690 ------ 192692 ------ 193702 ------ 194685 ------ 195725 ------ 196730 ------ 197724 ------ 198701 ------ 199973 128 │ │ │ │ │ │ histogram(30)= 0 80 3920 240 3920 80 3920 160 3920 80 3920 240 3920 80 3760 320 3680 320 3920 80 3920 160 3920 240 3920 80 3920 160 3840 160 3920 80 3920 80 3760 240 3840 160 3920 80 3840 160 3680 320 3920 80 3840 160 3840 160 3760 320 3840 160 3840 160 3920 80 3840 240 3920 80 3920 80 3840 160 3760 240 3920 160 3920 80 3920 80 3920 80 3920 320 3920 80 3920 160 3840 400 3760 240 3920 160 3920 160 3600 480 3920 80 3680 320 3840 160 3840 160 3920 240 3840 160 3920 160 3920 80 3920 160 3920 80 3760 240 3920 80 3920 80 3840 320 3840 160 3840 160 3920 240 3840 480 3920 160 3840 240 3920 160 3920 160 3920 80 3840 160 3920 80 3920 80 3920 80 3920 80 3840 240 3840 240 3920 80 3840 320 3920 80 3920 80 3920 240 3840 240 3920 160 3920 80 3840 160 3840 240 3920 240 3840 80 3680 320 3920 160 3840 160 3840 80 3920 80 3840 160 3840 160 3920 80 3920 80 3840 160 3920 80 3920 160 3840 240 3840 80 3840 160 3760 160 3920 80 3920 80 3840 240 3760 240 3840 80 3920 160 3840 80 3920 80 3920 80 3920 80 3920 160 3840 80 3920 80 3760 240 3920 80 3920 160 3760 160 3920 160 3840 80 3920 160 3840 160 3840 160 3600 320 3920 160 3840 80 3920 80 3680 320 3840 240 3760 160 3920 80 3920 80 3920 80 3920 80 3920 80 3680 320 3920 160 3840 160 3760 160 3920 240 3840 160 3840 240 3600 320 3840 80 3840 80 3920 160 3760 160 3840 160 3840 320 3840 80 3840 160 3760 240 3840 80 3840 240 3760 160 3840 160 3840 160 3920 240 3760 160 3840 80 3920 160 3680 240 3840 160 3840 160 3760 240 3920 80 3920 240 3760 160 3760 240 3840 80 3840 240 3840 240 3760 320 3760 240 3840 80 3840 160 3840 240 3760 320 3760 160 3840 160 3840 160 3840 80 3760 160 3840 80 3840 160 3920 160 3840 80 3920 80 3840 160 3920 80 3840 240 3840 80 3920 80 3760 240 3920 240 3840 80 3680 240 129 │ │ │ │ │ │ <--- 2 ------ 49 ------ 90 ------ 141 ------ 183 ------ 235 ------ 278 ------ 319 ------ 360 ------ 406 ------ 458 ------ 511 ------ 561 ------ 622 ------ 674 ------ 731 ------ 781 ------ 822 ------ 882 ------ 934 ------ 988 ------ 1026 ------ 1072 ------ 1114 ------ 1188 ------ 1245 ------ 1291 ------ 1335 ------ 1380 ------ 1433 ------ 1488 ------ 1537 ------ 1590 ------ 1642 ------ 1692 ------ 1751 ------ 1807 ------ 1846 ------ 1887 ------ 1939 ------ 1994 ------ 2045 ------ 2097 ------ 2139 ------ 2190 ------ 2240 ------ 2293 ------ 2344 ------ 2385 ------ 2427 ------ 2484 ------ 2538 ------ 2601 ------ 2651 ------ 2730 ------ 2781 ------ 2825 ------ 2874 ------ 2938 ------ 2978 ------ 3034 ------ 3086 ------ 3139 ------ 3179 ------ 3231 ------ 3274 ------ 3334 ------ 3387 ------ 3431 ------ 3477 ------ 3530 ------ 3581 ------ 3633 ------ 3680 ------ 3725 ------ 3775 ------ 3820 ------ 3876 ------ 3923 ------ 3982 ------ 4036 ------ 4078 ------ 4116 ------ 4183 ------ 4227 ------ 4275 ------ 4336 ------ 4376 ------ 4424 ------ 4481 ------ 4537 ------ 4582 ------ 4630 ------ 4680 ------ 4727 ------ 4779 ------ 4828 ------ 4881 ------ 4938 ------ 4986 ------ 5040 ------ 5087 ------ 5138 ------ 5188 ------ 5237 ------ 5280 ------ 5318 ------ 5358 ------ 5405 ------ 5459 ------ 5516 ------ 5561 ------ 5615 ------ 5681 ------ 5744 ------ 5790 ------ 5847 ------ 5885 ------ 5927 ------ 5991 ------ 6042 ------ 6111 ------ 6165 ------ 6207 ------ 6259 ------ 6313 ------ 6359 ------ 6418 ------ 6471 ------ 6530 ------ 6587 ------ 6626 ------ 6672 ------ 6739 ------ 6784 ------ 6837 ------ 6886 ------ 6952 ------ 6994 ------ 7040 ------ 7081 ------ 7134 ------ 7178 ------ 7232 ------ 7280 ------ 7330 ------ 7378 ------ 7435 ------ 7486 ------ 7537 ------ 7593 ------ 7636 ------ 7680 ------ 7737 ------ 7788 ------ 7836 ------ 7877 ------ 7928 ------ 7993 ------ 8036 ------ 8083 ------ 8135 ------ 8180 ------ 8221 ------ 8263 ------ 8313 ------ 8352 ------ 8399 ------ 8453 ------ 8517 ------ 8566 ------ 8612 ------ 8664 ------ 8716 ------ 8766 ------ 8821 ------ 8871 ------ 8922 ------ 8956 ------ 9007 ------ 9050 ------ 9100 ------ 9154 ------ 9203 ------ 9246 ------ 9311 ------ 9358 ------ 9407 ------ 9470 ------ 9525 ------ 9564 ------ 9633 ------ 9672 ------ 9730 ------ 9778 ------ 9824 ------ 9868 ------ 9919 ------ 9959 ------ 10000 130 │ │ │ │ │ ├── key: (29,30) 131 │ │ │ │ │ └── fd: (29,30)-->(32) 132 │ │ │ │ ├── inner-join (lookup supplier@s_nk) 133 │ │ │ │ │ ├── save-table-name: q2_lookup_join_9 134 │ │ │ │ │ ├── columns: s_suppkey:34(int!null) s_nationkey:37(int!null) n_nationkey:41(int!null) n_regionkey:43(int!null) r_regionkey:45(int!null) r_name:46(char!null) 135 │ │ │ │ │ ├── key columns: [41] = [37] 136 │ │ │ │ │ ├── stats: [rows=2000, distinct(34)=1844.80594, null(34)=0, distinct(37)=5, null(37)=0, distinct(41)=5, null(41)=0, distinct(43)=1, null(43)=0, distinct(45)=1, null(45)=0, distinct(46)=0.996222107, null(46)=0] 137 │ │ │ │ │ ├── key: (34) 138 │ │ │ │ │ ├── fd: ()-->(46), (34)-->(37), (41)-->(43), (43)==(45), (45)==(43), (37)==(41), (41)==(37) 139 │ │ │ │ │ ├── inner-join (merge) 140 │ │ │ │ │ │ ├── save-table-name: q2_merge_join_10 141 │ │ │ │ │ │ ├── columns: n_nationkey:41(int!null) n_regionkey:43(int!null) r_regionkey:45(int!null) r_name:46(char!null) 142 │ │ │ │ │ │ ├── left ordering: +43 143 │ │ │ │ │ │ ├── right ordering: +45 144 │ │ │ │ │ │ ├── stats: [rows=5, distinct(41)=5, null(41)=0, distinct(43)=1, null(43)=0, distinct(45)=1, null(45)=0, distinct(46)=0.996222107, null(46)=0] 145 │ │ │ │ │ │ ├── key: (41) 146 │ │ │ │ │ │ ├── fd: ()-->(46), (41)-->(43), (43)==(45), (45)==(43) 147 │ │ │ │ │ │ ├── scan nation@n_rk 148 │ │ │ │ │ │ │ ├── save-table-name: q2_scan_11 149 │ │ │ │ │ │ │ ├── columns: n_nationkey:41(int!null) n_regionkey:43(int!null) 150 │ │ │ │ │ │ │ ├── stats: [rows=25, distinct(41)=25, null(41)=0, distinct(43)=5, null(43)=0] 151 │ │ │ │ │ │ │ │ histogram(41)= 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 152 │ │ │ │ │ │ │ │ <--- 0 --- 1 --- 2 --- 3 --- 4 --- 5 --- 6 --- 7 --- 8 --- 9 --- 10 --- 11 --- 12 --- 13 --- 14 --- 15 --- 16 --- 17 --- 18 --- 19 --- 20 --- 21 --- 22 --- 23 --- 24 153 │ │ │ │ │ │ │ │ histogram(43)= 0 5 0 5 0 5 0 5 0 5 154 │ │ │ │ │ │ │ │ <--- 0 --- 1 --- 2 --- 3 --- 4 155 │ │ │ │ │ │ │ ├── key: (41) 156 │ │ │ │ │ │ │ ├── fd: (41)-->(43) 157 │ │ │ │ │ │ │ └── ordering: +43 158 │ │ │ │ │ │ ├── select 159 │ │ │ │ │ │ │ ├── save-table-name: q2_select_12 160 │ │ │ │ │ │ │ ├── columns: r_regionkey:45(int!null) r_name:46(char!null) 161 │ │ │ │ │ │ │ ├── stats: [rows=1, distinct(45)=1, null(45)=0, distinct(46)=1, null(46)=0] 162 │ │ │ │ │ │ │ ├── key: (45) 163 │ │ │ │ │ │ │ ├── fd: ()-->(46) 164 │ │ │ │ │ │ │ ├── ordering: +45 opt(46) [actual: +45] 165 │ │ │ │ │ │ │ ├── scan region 166 │ │ │ │ │ │ │ │ ├── save-table-name: q2_scan_13 167 │ │ │ │ │ │ │ │ ├── columns: r_regionkey:45(int!null) r_name:46(char!null) 168 │ │ │ │ │ │ │ │ ├── stats: [rows=5, distinct(45)=5, null(45)=0, distinct(46)=5, null(46)=0] 169 │ │ │ │ │ │ │ │ │ histogram(45)= 0 1 0 1 0 1 0 1 0 1 170 │ │ │ │ │ │ │ │ │ <--- 0 --- 1 --- 2 --- 3 --- 4 171 │ │ │ │ │ │ │ │ ├── key: (45) 172 │ │ │ │ │ │ │ │ ├── fd: (45)-->(46) 173 │ │ │ │ │ │ │ │ └── ordering: +45 opt(46) [actual: +45] 174 │ │ │ │ │ │ │ └── filters 175 │ │ │ │ │ │ │ └── r_name:46 = 'EUROPE' [type=bool, outer=(46), constraints=(/46: [/'EUROPE' - /'EUROPE']; tight), fd=()-->(46)] 176 │ │ │ │ │ │ └── filters (true) 177 │ │ │ │ │ └── filters (true) 178 │ │ │ │ └── filters 179 │ │ │ │ └── s_suppkey:34 = ps_suppkey:30 [type=bool, outer=(30,34), constraints=(/30: (/NULL - ]; /34: (/NULL - ]), fd=(30)==(34), (34)==(30)] 180 │ │ │ ├── inner-join (hash) 181 │ │ │ │ ├── save-table-name: q2_inner_join_14 182 │ │ │ │ ├── columns: p_partkey:1(int!null) p_mfgr:3(char!null) p_type:5(varchar!null) p_size:6(int!null) s_suppkey:10(int!null) s_name:11(char!null) s_address:12(varchar!null) s_nationkey:13(int!null) s_phone:14(char!null) s_acctbal:15(float!null) s_comment:16(varchar!null) ps_partkey:17(int!null) ps_suppkey:18(int!null) ps_supplycost:20(float!null) n_nationkey:22(int!null) n_name:23(char!null) n_regionkey:24(int!null) r_regionkey:26(int!null) r_name:27(char!null) 183 │ │ │ │ ├── stats: [rows=1945.04451, distinct(1)=1333.31636, null(1)=0, distinct(3)=5, null(3)=0, distinct(5)=149.99965, null(5)=0, distinct(6)=1, null(6)=0, distinct(10)=1766.2414, null(10)=0, distinct(11)=1767.4156, null(11)=0, distinct(12)=1767.58209, null(12)=0, distinct(13)=5, null(13)=0, distinct(14)=1767.58209, null(14)=0, distinct(15)=1767.03149, null(15)=0, distinct(16)=1766.47747, null(16)=0, distinct(17)=1333.31636, null(17)=0, distinct(18)=1766.2414, null(18)=0, distinct(20)=1921.6712, null(20)=0, distinct(22)=5, null(22)=0, distinct(23)=5, null(23)=0, distinct(24)=1, null(24)=0, distinct(26)=1, null(26)=0, distinct(27)=0.996222107, null(27)=0, distinct(17,18)=1932.15798, null(17,18)=0] 184 │ │ │ │ ├── key: (17,18) 185 │ │ │ │ ├── fd: ()-->(6,27), (1)-->(3,5), (10)-->(11-16), (17,18)-->(20), (22)-->(23,24), (24)==(26), (26)==(24), (10)==(18), (18)==(10), (13)==(22), (22)==(13), (1)==(17), (17)==(1) 186 │ │ │ │ ├── inner-join (hash) 187 │ │ │ │ │ ├── save-table-name: q2_inner_join_15 188 │ │ │ │ │ ├── columns: s_suppkey:10(int!null) s_name:11(char!null) s_address:12(varchar!null) s_nationkey:13(int!null) s_phone:14(char!null) s_acctbal:15(float!null) s_comment:16(varchar!null) ps_partkey:17(int!null) ps_suppkey:18(int!null) ps_supplycost:20(float!null) n_nationkey:22(int!null) n_name:23(char!null) n_regionkey:24(int!null) r_regionkey:26(int!null) r_name:27(char!null) 189 │ │ │ │ │ ├── stats: [rows=161290.323, distinct(10)=9920, null(10)=0, distinct(11)=9989.99903, null(11)=0, distinct(12)=9999.99901, null(12)=0, distinct(13)=5, null(13)=0, distinct(14)=9999.99901, null(14)=0, distinct(15)=9966.99907, null(15)=0, distinct(16)=9933.99912, null(16)=0, distinct(17)=110564.957, null(17)=0, distinct(18)=9920, null(18)=0, distinct(20)=80250.5069, null(20)=0, distinct(22)=5, null(22)=0, distinct(23)=5, null(23)=0, distinct(24)=1, null(24)=0, distinct(26)=1, null(26)=0, distinct(27)=0.996222107, null(27)=0, distinct(17,18)=146040.974, null(17,18)=0] 190 │ │ │ │ │ ├── key: (17,18) 191 │ │ │ │ │ ├── fd: ()-->(27), (10)-->(11-16), (17,18)-->(20), (22)-->(23,24), (24)==(26), (26)==(24), (10)==(18), (18)==(10), (13)==(22), (22)==(13) 192 │ │ │ │ │ ├── scan partsupp 193 │ │ │ │ │ │ ├── save-table-name: q2_scan_16 194 │ │ │ │ │ │ ├── columns: ps_partkey:17(int!null) ps_suppkey:18(int!null) ps_supplycost:20(float!null) 195 │ │ │ │ │ │ ├── stats: [rows=800000, distinct(17)=199241, null(17)=0, distinct(18)=9920, null(18)=0, distinct(20)=100379, null(20)=0, distinct(17,18)=798302, null(17,18)=0] 196 │ │ │ │ │ │ │ histogram(17)= 0 80 3920 80 3920 80 3920 80 3920 80 3840 160 3840 160 3920 80 3920 80 3920 80 3920 80 3920 160 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3840 160 3920 80 3920 80 3920 80 3920 80 3920 160 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3840 160 3920 80 3920 80 3920 160 3920 80 3920 160 3920 80 3920 80 3920 80 3920 80 3920 80 3920 160 3920 80 3920 80 3920 80 3920 80 3920 80 3920 160 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 3920 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 3920 160 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 4000 80 197 │ │ │ │ │ │ │ <--- 4 ------ 793 ------ 1856 ------ 2808 ------ 3809 ------ 4923 ------ 5975 ------ 6944 ------ 8085 ------ 8945 ------ 9831 ------ 10952 ------ 11932 ------ 12775 ------ 13849 ------ 14925 ------ 16016 ------ 16828 ------ 17768 ------ 18705 ------ 19631 ------ 20600 ------ 21491 ------ 22254 ------ 23327 ------ 24491 ------ 25470 ------ 26331 ------ 27327 ------ 28308 ------ 29359 ------ 30542 ------ 31592 ------ 32495 ------ 33408 ------ 34624 ------ 35726 ------ 36676 ------ 37637 ------ 38485 ------ 39368 ------ 40372 ------ 41034 ------ 42185 ------ 43333 ------ 44466 ------ 45440 ------ 46571 ------ 47469 ------ 48346 ------ 49379 ------ 50571 ------ 51830 ------ 52967 ------ 53673 ------ 54656 ------ 55504 ------ 56539 ------ 57393 ------ 58366 ------ 59577 ------ 60559 ------ 61676 ------ 62471 ------ 63421 ------ 64449 ------ 65409 ------ 66254 ------ 67127 ------ 68127 ------ 69177 ------ 70183 ------ 71209 ------ 72101 ------ 73102 ------ 73994 ------ 74899 ------ 76016 ------ 77098 ------ 77842 ------ 79137 ------ 80242 ------ 81364 ------ 82331 ------ 83158 ------ 84283 ------ 85282 ------ 86437 ------ 87450 ------ 88419 ------ 89493 ------ 90478 ------ 91468 ------ 92552 ------ 93200 ------ 94191 ------ 95067 ------ 96272 ------ 97228 ------ 98126 ------ 99198 ------ 100219 ------ 101057 ------ 102038 ------ 102775 ------ 103711 ------ 104623 ------ 105710 ------ 106734 ------ 107932 ------ 109255 ------ 110220 ------ 111235 ------ 112174 ------ 113260 ------ 114081 ------ 115103 ------ 115864 ------ 116794 ------ 117741 ------ 118712 ------ 119470 ------ 120528 ------ 121572 ------ 122536 ------ 123629 ------ 124404 ------ 125301 ------ 126257 ------ 127139 ------ 128267 ------ 129258 ------ 130442 ------ 131845 ------ 133164 ------ 134005 ------ 135076 ------ 135868 ------ 137297 ------ 138777 ------ 139806 ------ 140741 ------ 141896 ------ 142719 ------ 143727 ------ 144645 ------ 145510 ------ 146507 ------ 147449 ------ 148467 ------ 149635 ------ 150563 ------ 151751 ------ 152613 ------ 153416 ------ 154612 ------ 155853 ------ 156866 ------ 158311 ------ 159230 ------ 160390 ------ 161455 ------ 162555 ------ 163435 ------ 164549 ------ 165663 ------ 166891 ------ 167757 ------ 168732 ------ 169644 ------ 170532 ------ 171671 ------ 172778 ------ 173599 ------ 174321 ------ 175624 ------ 176663 ------ 177632 ------ 178555 ------ 179551 ------ 180510 ------ 181682 ------ 182648 ------ 183408 ------ 184543 ------ 185722 ------ 186713 ------ 187787 ------ 188730 ------ 189604 ------ 190711 ------ 191690 ------ 192692 ------ 193702 ------ 194685 ------ 195725 ------ 196730 ------ 197724 ------ 198701 ------ 199973 198 │ │ │ │ │ │ │ histogram(18)= 0 80 3920 240 3920 80 3920 160 3920 80 3920 240 3920 80 3760 320 3680 320 3920 80 3920 160 3920 240 3920 80 3920 160 3840 160 3920 80 3920 80 3760 240 3840 160 3920 80 3840 160 3680 320 3920 80 3840 160 3840 160 3760 320 3840 160 3840 160 3920 80 3840 240 3920 80 3920 80 3840 160 3760 240 3920 160 3920 80 3920 80 3920 80 3920 320 3920 80 3920 160 3840 400 3760 240 3920 160 3920 160 3600 480 3920 80 3680 320 3840 160 3840 160 3920 240 3840 160 3920 160 3920 80 3920 160 3920 80 3760 240 3920 80 3920 80 3840 320 3840 160 3840 160 3920 240 3840 480 3920 160 3840 240 3920 160 3920 160 3920 80 3840 160 3920 80 3920 80 3920 80 3920 80 3840 240 3840 240 3920 80 3840 320 3920 80 3920 80 3920 240 3840 240 3920 160 3920 80 3840 160 3840 240 3920 240 3840 80 3680 320 3920 160 3840 160 3840 80 3920 80 3840 160 3840 160 3920 80 3920 80 3840 160 3920 80 3920 160 3840 240 3840 80 3840 160 3760 160 3920 80 3920 80 3840 240 3760 240 3840 80 3920 160 3840 80 3920 80 3920 80 3920 80 3920 160 3840 80 3920 80 3760 240 3920 80 3920 160 3760 160 3920 160 3840 80 3920 160 3840 160 3840 160 3600 320 3920 160 3840 80 3920 80 3680 320 3840 240 3760 160 3920 80 3920 80 3920 80 3920 80 3920 80 3680 320 3920 160 3840 160 3760 160 3920 240 3840 160 3840 240 3600 320 3840 80 3840 80 3920 160 3760 160 3840 160 3840 320 3840 80 3840 160 3760 240 3840 80 3840 240 3760 160 3840 160 3840 160 3920 240 3760 160 3840 80 3920 160 3680 240 3840 160 3840 160 3760 240 3920 80 3920 240 3760 160 3760 240 3840 80 3840 240 3840 240 3760 320 3760 240 3840 80 3840 160 3840 240 3760 320 3760 160 3840 160 3840 160 3840 80 3760 160 3840 80 3840 160 3920 160 3840 80 3920 80 3840 160 3920 80 3840 240 3840 80 3920 80 3760 240 3920 240 3840 80 3680 240 199 │ │ │ │ │ │ │ <--- 2 ------ 49 ------ 90 ------ 141 ------ 183 ------ 235 ------ 278 ------ 319 ------ 360 ------ 406 ------ 458 ------ 511 ------ 561 ------ 622 ------ 674 ------ 731 ------ 781 ------ 822 ------ 882 ------ 934 ------ 988 ------ 1026 ------ 1072 ------ 1114 ------ 1188 ------ 1245 ------ 1291 ------ 1335 ------ 1380 ------ 1433 ------ 1488 ------ 1537 ------ 1590 ------ 1642 ------ 1692 ------ 1751 ------ 1807 ------ 1846 ------ 1887 ------ 1939 ------ 1994 ------ 2045 ------ 2097 ------ 2139 ------ 2190 ------ 2240 ------ 2293 ------ 2344 ------ 2385 ------ 2427 ------ 2484 ------ 2538 ------ 2601 ------ 2651 ------ 2730 ------ 2781 ------ 2825 ------ 2874 ------ 2938 ------ 2978 ------ 3034 ------ 3086 ------ 3139 ------ 3179 ------ 3231 ------ 3274 ------ 3334 ------ 3387 ------ 3431 ------ 3477 ------ 3530 ------ 3581 ------ 3633 ------ 3680 ------ 3725 ------ 3775 ------ 3820 ------ 3876 ------ 3923 ------ 3982 ------ 4036 ------ 4078 ------ 4116 ------ 4183 ------ 4227 ------ 4275 ------ 4336 ------ 4376 ------ 4424 ------ 4481 ------ 4537 ------ 4582 ------ 4630 ------ 4680 ------ 4727 ------ 4779 ------ 4828 ------ 4881 ------ 4938 ------ 4986 ------ 5040 ------ 5087 ------ 5138 ------ 5188 ------ 5237 ------ 5280 ------ 5318 ------ 5358 ------ 5405 ------ 5459 ------ 5516 ------ 5561 ------ 5615 ------ 5681 ------ 5744 ------ 5790 ------ 5847 ------ 5885 ------ 5927 ------ 5991 ------ 6042 ------ 6111 ------ 6165 ------ 6207 ------ 6259 ------ 6313 ------ 6359 ------ 6418 ------ 6471 ------ 6530 ------ 6587 ------ 6626 ------ 6672 ------ 6739 ------ 6784 ------ 6837 ------ 6886 ------ 6952 ------ 6994 ------ 7040 ------ 7081 ------ 7134 ------ 7178 ------ 7232 ------ 7280 ------ 7330 ------ 7378 ------ 7435 ------ 7486 ------ 7537 ------ 7593 ------ 7636 ------ 7680 ------ 7737 ------ 7788 ------ 7836 ------ 7877 ------ 7928 ------ 7993 ------ 8036 ------ 8083 ------ 8135 ------ 8180 ------ 8221 ------ 8263 ------ 8313 ------ 8352 ------ 8399 ------ 8453 ------ 8517 ------ 8566 ------ 8612 ------ 8664 ------ 8716 ------ 8766 ------ 8821 ------ 8871 ------ 8922 ------ 8956 ------ 9007 ------ 9050 ------ 9100 ------ 9154 ------ 9203 ------ 9246 ------ 9311 ------ 9358 ------ 9407 ------ 9470 ------ 9525 ------ 9564 ------ 9633 ------ 9672 ------ 9730 ------ 9778 ------ 9824 ------ 9868 ------ 9919 ------ 9959 ------ 10000 200 │ │ │ │ │ │ ├── key: (17,18) 201 │ │ │ │ │ │ └── fd: (17,18)-->(20) 202 │ │ │ │ │ ├── inner-join (hash) 203 │ │ │ │ │ │ ├── save-table-name: q2_inner_join_17 204 │ │ │ │ │ │ ├── columns: s_suppkey:10(int!null) s_name:11(char!null) s_address:12(varchar!null) s_nationkey:13(int!null) s_phone:14(char!null) s_acctbal:15(float!null) s_comment:16(varchar!null) n_nationkey:22(int!null) n_name:23(char!null) n_regionkey:24(int!null) r_regionkey:26(int!null) r_name:27(char!null) 205 │ │ │ │ │ │ ├── stats: [rows=2000, distinct(10)=1844.80594, null(10)=0, distinct(11)=1846.09084, null(11)=0, distinct(12)=1846.27302, null(12)=0, distinct(13)=5, null(13)=0, distinct(14)=1846.27302, null(14)=0, distinct(15)=1845.67052, null(15)=0, distinct(16)=1845.06427, null(16)=0, distinct(22)=5, null(22)=0, distinct(23)=5, null(23)=0, distinct(24)=1, null(24)=0, distinct(26)=1, null(26)=0, distinct(27)=0.996222107, null(27)=0] 206 │ │ │ │ │ │ ├── key: (10) 207 │ │ │ │ │ │ ├── fd: ()-->(27), (22)-->(23,24), (24)==(26), (26)==(24), (10)-->(11-16), (13)==(22), (22)==(13) 208 │ │ │ │ │ │ ├── scan supplier 209 │ │ │ │ │ │ │ ├── save-table-name: q2_scan_18 210 │ │ │ │ │ │ │ ├── columns: s_suppkey:10(int!null) s_name:11(char!null) s_address:12(varchar!null) s_nationkey:13(int!null) s_phone:14(char!null) s_acctbal:15(float!null) s_comment:16(varchar!null) 211 │ │ │ │ │ │ │ ├── stats: [rows=10000, distinct(10)=9920, null(10)=0, distinct(11)=9990, null(11)=0, distinct(12)=10000, null(12)=0, distinct(13)=25, null(13)=0, distinct(14)=10000, null(14)=0, distinct(15)=9967, null(15)=0, distinct(16)=9934, null(16)=0] 212 │ │ │ │ │ │ │ │ histogram(10)= 0 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 49 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 50 1 213 │ │ │ │ │ │ │ │ <--- 1 ---- 51 ---- 101 ---- 151 ---- 201 ---- 251 ---- 301 ---- 351 ---- 401 ---- 451 ---- 501 ---- 551 ---- 601 ---- 651 ---- 701 ---- 751 ---- 801 ---- 851 ---- 901 ---- 951 ---- 1001 ---- 1051 ---- 1101 ---- 1151 ---- 1201 ---- 1251 ---- 1301 ---- 1351 ---- 1401 ---- 1451 ---- 1501 ---- 1551 ---- 1601 ---- 1651 ---- 1701 ---- 1751 ---- 1801 ---- 1851 ---- 1901 ---- 1951 ---- 2001 ---- 2051 ---- 2101 ---- 2151 ---- 2201 ---- 2251 ---- 2301 ---- 2351 ---- 2401 ---- 2451 ---- 2501 ---- 2551 ---- 2601 ---- 2651 ---- 2701 ---- 2751 ---- 2801 ---- 2851 ---- 2901 ---- 2951 ---- 3001 ---- 3051 ---- 3101 ---- 3151 ---- 3201 ---- 3251 ---- 3301 ---- 3351 ---- 3401 ---- 3451 ---- 3501 ---- 3551 ---- 3601 ---- 3651 ---- 3701 ---- 3751 ---- 3801 ---- 3851 ---- 3901 ---- 3951 ---- 4001 ---- 4051 ---- 4101 ---- 4151 ---- 4201 ---- 4251 ---- 4301 ---- 4351 ---- 4401 ---- 4451 ---- 4501 ---- 4551 ---- 4601 ---- 4651 ---- 4701 ---- 4751 ---- 4801 ---- 4851 ---- 4901 ---- 4951 ---- 5001 ---- 5051 ---- 5101 ---- 5151 ---- 5201 ---- 5251 ---- 5301 ---- 5351 ---- 5401 ---- 5451 ---- 5501 ---- 5551 ---- 5601 ---- 5651 ---- 5701 ---- 5751 ---- 5801 ---- 5851 ---- 5901 ---- 5951 ---- 6001 ---- 6051 ---- 6101 ---- 6151 ---- 6201 ---- 6251 ---- 6301 ---- 6351 ---- 6401 ---- 6451 ---- 6501 ---- 6551 ---- 6601 ---- 6651 ---- 6701 ---- 6751 ---- 6801 ---- 6851 ---- 6901 ---- 6951 ---- 7001 ---- 7051 ---- 7101 ---- 7151 ---- 7201 ---- 7251 ---- 7301 ---- 7351 ---- 7401 ---- 7451 ---- 7501 ---- 7552 ---- 7603 ---- 7654 ---- 7705 ---- 7756 ---- 7807 ---- 7858 ---- 7909 ---- 7960 ---- 8011 ---- 8062 ---- 8113 ---- 8164 ---- 8215 ---- 8266 ---- 8317 ---- 8368 ---- 8419 ---- 8470 ---- 8521 ---- 8572 ---- 8623 ---- 8674 ---- 8725 ---- 8776 ---- 8827 ---- 8878 ---- 8929 ---- 8980 ---- 9031 ---- 9082 ---- 9133 ---- 9184 ---- 9235 ---- 9286 ---- 9337 ---- 9388 ---- 9439 ---- 9490 ---- 9541 ---- 9592 ---- 9643 ---- 9694 ---- 9745 ---- 9796 ---- 9847 ---- 9898 ---- 9949 ---- 10000 214 │ │ │ │ │ │ │ │ histogram(13)= 0 420 0 413 0 397 0 412 0 415 0 380 0 402 0 396 0 415 0 405 0 393 0 438 0 377 0 362 0 376 0 373 0 406 0 421 0 407 0 398 0 411 0 399 0 401 0 390 0 393 215 │ │ │ │ │ │ │ │ <--- 0 --- 1 --- 2 --- 3 --- 4 --- 5 --- 6 --- 7 --- 8 --- 9 --- 10 --- 11 --- 12 --- 13 --- 14 --- 15 --- 16 --- 17 --- 18 --- 19 --- 20 --- 21 --- 22 --- 23 --- 24 216 │ │ │ │ │ │ │ ├── key: (10) 217 │ │ │ │ │ │ │ └── fd: (10)-->(11-16) 218 │ │ │ │ │ │ ├── inner-join (hash) 219 │ │ │ │ │ │ │ ├── save-table-name: q2_inner_join_19 220 │ │ │ │ │ │ │ ├── columns: n_nationkey:22(int!null) n_name:23(char!null) n_regionkey:24(int!null) r_regionkey:26(int!null) r_name:27(char!null) 221 │ │ │ │ │ │ │ ├── stats: [rows=5, distinct(22)=5, null(22)=0, distinct(23)=5, null(23)=0, distinct(24)=1, null(24)=0, distinct(26)=1, null(26)=0, distinct(27)=0.996222107, null(27)=0] 222 │ │ │ │ │ │ │ ├── key: (22) 223 │ │ │ │ │ │ │ ├── fd: ()-->(27), (22)-->(23,24), (24)==(26), (26)==(24) 224 │ │ │ │ │ │ │ ├── scan nation 225 │ │ │ │ │ │ │ │ ├── save-table-name: q2_scan_20 226 │ │ │ │ │ │ │ │ ├── columns: n_nationkey:22(int!null) n_name:23(char!null) n_regionkey:24(int!null) 227 │ │ │ │ │ │ │ │ ├── stats: [rows=25, distinct(22)=25, null(22)=0, distinct(23)=25, null(23)=0, distinct(24)=5, null(24)=0] 228 │ │ │ │ │ │ │ │ │ histogram(22)= 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 229 │ │ │ │ │ │ │ │ │ <--- 0 --- 1 --- 2 --- 3 --- 4 --- 5 --- 6 --- 7 --- 8 --- 9 --- 10 --- 11 --- 12 --- 13 --- 14 --- 15 --- 16 --- 17 --- 18 --- 19 --- 20 --- 21 --- 22 --- 23 --- 24 230 │ │ │ │ │ │ │ │ │ histogram(24)= 0 5 0 5 0 5 0 5 0 5 231 │ │ │ │ │ │ │ │ │ <--- 0 --- 1 --- 2 --- 3 --- 4 232 │ │ │ │ │ │ │ │ ├── key: (22) 233 │ │ │ │ │ │ │ │ └── fd: (22)-->(23,24) 234 │ │ │ │ │ │ │ ├── select 235 │ │ │ │ │ │ │ │ ├── save-table-name: q2_select_21 236 │ │ │ │ │ │ │ │ ├── columns: r_regionkey:26(int!null) r_name:27(char!null) 237 │ │ │ │ │ │ │ │ ├── stats: [rows=1, distinct(26)=1, null(26)=0, distinct(27)=1, null(27)=0] 238 │ │ │ │ │ │ │ │ ├── key: (26) 239 │ │ │ │ │ │ │ │ ├── fd: ()-->(27) 240 │ │ │ │ │ │ │ │ ├── scan region 241 │ │ │ │ │ │ │ │ │ ├── save-table-name: q2_scan_22 242 │ │ │ │ │ │ │ │ │ ├── columns: r_regionkey:26(int!null) r_name:27(char!null) 243 │ │ │ │ │ │ │ │ │ ├── stats: [rows=5, distinct(26)=5, null(26)=0, distinct(27)=5, null(27)=0] 244 │ │ │ │ │ │ │ │ │ │ histogram(26)= 0 1 0 1 0 1 0 1 0 1 245 │ │ │ │ │ │ │ │ │ │ <--- 0 --- 1 --- 2 --- 3 --- 4 246 │ │ │ │ │ │ │ │ │ ├── key: (26) 247 │ │ │ │ │ │ │ │ │ └── fd: (26)-->(27) 248 │ │ │ │ │ │ │ │ └── filters 249 │ │ │ │ │ │ │ │ └── r_name:27 = 'EUROPE' [type=bool, outer=(27), constraints=(/27: [/'EUROPE' - /'EUROPE']; tight), fd=()-->(27)] 250 │ │ │ │ │ │ │ └── filters 251 │ │ │ │ │ │ │ └── n_regionkey:24 = r_regionkey:26 [type=bool, outer=(24,26), constraints=(/24: (/NULL - ]; /26: (/NULL - ]), fd=(24)==(26), (26)==(24)] 252 │ │ │ │ │ │ └── filters 253 │ │ │ │ │ │ └── s_nationkey:13 = n_nationkey:22 [type=bool, outer=(13,22), constraints=(/13: (/NULL - ]; /22: (/NULL - ]), fd=(13)==(22), (22)==(13)] 254 │ │ │ │ │ └── filters 255 │ │ │ │ │ └── s_suppkey:10 = ps_suppkey:18 [type=bool, outer=(10,18), constraints=(/10: (/NULL - ]; /18: (/NULL - ]), fd=(10)==(18), (18)==(10)] 256 │ │ │ │ ├── select 257 │ │ │ │ │ ├── save-table-name: q2_select_23 258 │ │ │ │ │ ├── columns: p_partkey:1(int!null) p_mfgr:3(char!null) p_type:5(varchar!null) p_size:6(int!null) 259 │ │ │ │ │ ├── stats: [rows=1333.33333, distinct(1)=1333.31636, null(1)=0, distinct(3)=5, null(3)=0, distinct(5)=150, null(5)=0, distinct(6)=1, null(6)=0] 260 │ │ │ │ │ ├── key: (1) 261 │ │ │ │ │ ├── fd: ()-->(6), (1)-->(3,5) 262 │ │ │ │ │ ├── scan part 263 │ │ │ │ │ │ ├── save-table-name: q2_scan_24 264 │ │ │ │ │ │ ├── columns: p_partkey:1(int!null) p_mfgr:3(char!null) p_type:5(varchar!null) p_size:6(int!null) 265 │ │ │ │ │ │ ├── stats: [rows=200000, distinct(1)=199241, null(1)=0, distinct(3)=5, null(3)=0, distinct(5)=150, null(5)=0, distinct(6)=50, null(6)=0] 266 │ │ │ │ │ │ │ histogram(1)= 0 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 980 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 1000 20 267 │ │ │ │ │ │ │ <--- 27 ----- 1110 ----- 2241 ----- 3086 ----- 4134 ----- 5302 ----- 6222 ----- 7308 ----- 8249 ----- 9171 ----- 10049 ----- 10958 ----- 11832 ----- 13025 ----- 14063 ----- 14953 ----- 16249 ----- 17419 ----- 18363 ----- 19412 ----- 20257 ----- 21190 ----- 22110 ----- 23045 ----- 23956 ----- 24962 ----- 25942 ----- 26990 ----- 27934 ----- 28876 ----- 29513 ----- 30326 ----- 31259 ----- 32300 ----- 33577 ----- 34550 ----- 35562 ----- 36498 ----- 37475 ----- 38584 ----- 39641 ----- 40548 ----- 41605 ----- 42527 ----- 43612 ----- 44702 ----- 45701 ----- 46726 ----- 47795 ----- 48935 ----- 50152 ----- 51183 ----- 52001 ----- 52904 ----- 53868 ----- 54808 ----- 55986 ----- 57155 ----- 58516 ----- 59526 ----- 60557 ----- 61547 ----- 62369 ----- 63672 ----- 64583 ----- 65360 ----- 66147 ----- 67201 ----- 68142 ----- 69145 ----- 70209 ----- 71141 ----- 71923 ----- 73031 ----- 73987 ----- 74974 ----- 76170 ----- 77138 ----- 77849 ----- 78931 ----- 79832 ----- 80761 ----- 81843 ----- 82834 ----- 84032 ----- 85072 ----- 86287 ----- 87302 ----- 88422 ----- 89432 ----- 90550 ----- 91463 ----- 92249 ----- 93385 ----- 94789 ----- 96013 ----- 96893 ----- 98000 ----- 99008 ----- 100166 ----- 101263 ----- 102351 ----- 103236 ----- 104121 ----- 105363 ----- 106329 ----- 107325 ----- 108231 ----- 109054 ----- 110019 ----- 111185 ----- 112112 ----- 112908 ----- 113904 ----- 114785 ----- 115410 ----- 116526 ----- 117559 ----- 118310 ----- 119073 ----- 120034 ----- 120817 ----- 121744 ----- 122566 ----- 123720 ----- 124813 ----- 125835 ----- 126622 ----- 127651 ----- 128328 ----- 129315 ----- 130244 ----- 131450 ----- 132439 ----- 133288 ----- 134164 ----- 135298 ----- 136347 ----- 137243 ----- 138256 ----- 139427 ----- 140374 ----- 141371 ----- 142302 ----- 143322 ----- 144335 ----- 145333 ----- 146212 ----- 147321 ----- 148591 ----- 149594 ------ 150514 ------ 151361 ------ 152059 ------ 153070 ------ 154059 ------ 155259 ------ 156473 ------ 157690 ------ 158703 ------ 159675 ------ 160597 ------ 161668 ------ 162737 ------ 163955 ------ 164942 ------ 165924 ------ 167059 ------ 167866 ------ 169034 ------ 169935 ------ 170712 ------ 171806 ------ 172841 ------ 174078 ------ 175347 ------ 176430 ------ 177346 ------ 178566 ------ 179515 ------ 180677 ------ 181729 ------ 182983 ------ 183814 ------ 184892 ------ 185696 ------ 186611 ------ 187744 ------ 188974 ------ 189911 ------ 190671 ------ 191607 ------ 192820 ------ 193789 ------ 195057 ------ 196224 ------ 197231 ------ 198281 ------ 199119 ------ 199999 268 │ │ │ │ │ │ ├── key: (1) 269 │ │ │ │ │ │ └── fd: (1)-->(3,5,6) 270 │ │ │ │ │ └── filters 271 │ │ │ │ │ ├── p_size:6 = 15 [type=bool, outer=(6), constraints=(/6: [/15 - /15]; tight), fd=()-->(6)] 272 │ │ │ │ │ └── p_type:5 LIKE '%BRASS' [type=bool, outer=(5), constraints=(/5: (/NULL - ])] 273 │ │ │ │ └── filters 274 │ │ │ │ └── p_partkey:1 = ps_partkey:17 [type=bool, outer=(1,17), constraints=(/1: (/NULL - ]; /17: (/NULL - ]), fd=(1)==(17), (17)==(1)] 275 │ │ │ └── filters 276 │ │ │ └── p_partkey:1 = ps_partkey:29 [type=bool, outer=(1,29), constraints=(/1: (/NULL - ]; /29: (/NULL - ]), fd=(1)==(29), (29)==(1)] 277 │ │ └── aggregations 278 │ │ ├── min [as=min:48, type=float, outer=(32)] 279 │ │ │ └── ps_supplycost:32 [type=float] 280 │ │ ├── const-agg [as=s_name:11, type=char, outer=(11)] 281 │ │ │ └── s_name:11 [type=char] 282 │ │ ├── const-agg [as=s_address:12, type=varchar, outer=(12)] 283 │ │ │ └── s_address:12 [type=varchar] 284 │ │ ├── const-agg [as=s_phone:14, type=char, outer=(14)] 285 │ │ │ └── s_phone:14 [type=char] 286 │ │ ├── const-agg [as=s_acctbal:15, type=float, outer=(15)] 287 │ │ │ └── s_acctbal:15 [type=float] 288 │ │ ├── const-agg [as=s_comment:16, type=varchar, outer=(16)] 289 │ │ │ └── s_comment:16 [type=varchar] 290 │ │ ├── const-agg [as=ps_supplycost:20, type=float, outer=(20)] 291 │ │ │ └── ps_supplycost:20 [type=float] 292 │ │ ├── const-agg [as=n_name:23, type=char, outer=(23)] 293 │ │ │ └── n_name:23 [type=char] 294 │ │ ├── const-agg [as=p_mfgr:3, type=char, outer=(3)] 295 │ │ │ └── p_mfgr:3 [type=char] 296 │ │ └── const-agg [as=p_partkey:1, type=int, outer=(1)] 297 │ │ └── p_partkey:1 [type=int] 298 │ └── filters 299 │ └── ps_supplycost:20 = min:48 [type=bool, outer=(20,48), constraints=(/20: (/NULL - ]; /48: (/NULL - ]), fd=(20)==(48), (48)==(20)] 300 └── 100 [type=int] 301 302 stats table=q2_project_1 303 ---- 304 column_names row_count distinct_count null_count 305 {n_name} 100 5 0 306 {p_mfgr} 100 5 0 307 {p_partkey} 100 100 0 308 {s_acctbal} 100 89 0 309 {s_address} 100 89 0 310 {s_comment} 100 89 0 311 {s_name} 100 89 0 312 {s_phone} 100 89 0 313 ~~~~ 314 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 315 {n_name} 1.00 100.00 <== 1.00 5.00 <== 0.00 1.00 316 {p_mfgr} 1.00 100.00 <== 1.00 5.00 <== 0.00 1.00 317 {p_partkey} 1.00 100.00 <== 1.00 100.00 <== 0.00 1.00 318 {s_acctbal} 1.00 100.00 <== 1.00 89.00 <== 0.00 1.00 319 {s_address} 1.00 100.00 <== 1.00 89.00 <== 0.00 1.00 320 {s_comment} 1.00 100.00 <== 1.00 89.00 <== 0.00 1.00 321 {s_name} 1.00 100.00 <== 1.00 89.00 <== 0.00 1.00 322 {s_phone} 1.00 100.00 <== 1.00 89.00 <== 0.00 1.00 323 324 stats table=q2_limit_2 325 ---- 326 column_names row_count distinct_count null_count 327 {min} 100 100 0 328 {n_name} 100 5 0 329 {p_mfgr} 100 5 0 330 {p_partkey} 100 100 0 331 {ps_partkey} 100 100 0 332 {ps_suppkey} 100 89 0 333 {ps_supplycost} 100 100 0 334 {s_acctbal} 100 89 0 335 {s_address} 100 89 0 336 {s_comment} 100 89 0 337 {s_name} 100 89 0 338 {s_phone} 100 89 0 339 ~~~~ 340 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 341 {min} 1.00 100.00 <== 1.00 100.00 <== 0.00 1.00 342 {n_name} 1.00 100.00 <== 1.00 5.00 <== 0.00 1.00 343 {p_mfgr} 1.00 100.00 <== 1.00 5.00 <== 0.00 1.00 344 {p_partkey} 1.00 100.00 <== 1.00 100.00 <== 0.00 1.00 345 {ps_partkey} 1.00 100.00 <== 1.00 100.00 <== 0.00 1.00 346 {ps_suppkey} 1.00 100.00 <== 1.00 89.00 <== 0.00 1.00 347 {ps_supplycost} 1.00 100.00 <== 1.00 100.00 <== 0.00 1.00 348 {s_acctbal} 1.00 100.00 <== 1.00 89.00 <== 0.00 1.00 349 {s_address} 1.00 100.00 <== 1.00 89.00 <== 0.00 1.00 350 {s_comment} 1.00 100.00 <== 1.00 89.00 <== 0.00 1.00 351 {s_name} 1.00 100.00 <== 1.00 89.00 <== 0.00 1.00 352 {s_phone} 1.00 100.00 <== 1.00 89.00 <== 0.00 1.00 353 354 stats table=q2_sort_3 355 ---- 356 column_names row_count distinct_count null_count 357 {min} 100 100 0 358 {n_name} 100 5 0 359 {p_mfgr} 100 5 0 360 {p_partkey} 100 100 0 361 {ps_partkey} 100 100 0 362 {ps_suppkey} 100 89 0 363 {ps_supplycost} 100 100 0 364 {s_acctbal} 100 89 0 365 {s_address} 100 89 0 366 {s_comment} 100 89 0 367 {s_name} 100 89 0 368 {s_phone} 100 89 0 369 ~~~~ 370 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 371 {min} 1.00 100.00 <== 1.00 100.00 <== 0.00 1.00 372 {n_name} 1.00 100.00 <== 1.00 5.00 <== 0.00 1.00 373 {p_mfgr} 1.00 100.00 <== 1.00 5.00 <== 0.00 1.00 374 {p_partkey} 1.00 100.00 <== 1.00 100.00 <== 0.00 1.00 375 {ps_partkey} 1.00 100.00 <== 1.00 100.00 <== 0.00 1.00 376 {ps_suppkey} 1.00 100.00 <== 1.00 89.00 <== 0.00 1.00 377 {ps_supplycost} 1.00 100.00 <== 1.00 100.00 <== 0.00 1.00 378 {s_acctbal} 1.00 100.00 <== 1.00 89.00 <== 0.00 1.00 379 {s_address} 1.00 100.00 <== 1.00 89.00 <== 0.00 1.00 380 {s_comment} 1.00 100.00 <== 1.00 89.00 <== 0.00 1.00 381 {s_name} 1.00 100.00 <== 1.00 89.00 <== 0.00 1.00 382 {s_phone} 1.00 100.00 <== 1.00 89.00 <== 0.00 1.00 383 384 stats table=q2_select_4 385 ---- 386 column_names row_count distinct_count null_count 387 {min} 460 458 0 388 {n_name} 460 5 0 389 {p_mfgr} 460 5 0 390 {p_partkey} 460 460 0 391 {ps_partkey} 460 460 0 392 {ps_suppkey} 460 406 0 393 {ps_supplycost} 460 458 0 394 {s_acctbal} 460 406 0 395 {s_address} 460 406 0 396 {s_comment} 460 406 0 397 {s_name} 460 406 0 398 {s_phone} 460 406 0 399 ~~~~ 400 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 401 {min} 1.00 460.00 <== 1.00 458.00 <== 0.00 1.00 402 {n_name} 1.00 460.00 <== 1.00 5.00 <== 0.00 1.00 403 {p_mfgr} 1.00 460.00 <== 1.00 5.00 <== 0.00 1.00 404 {p_partkey} 1.00 460.00 <== 1.00 460.00 <== 0.00 1.00 405 {ps_partkey} 1.00 460.00 <== 1.00 460.00 <== 0.00 1.00 406 {ps_suppkey} 1.00 460.00 <== 1.00 406.00 <== 0.00 1.00 407 {ps_supplycost} 1.00 460.00 <== 1.00 458.00 <== 0.00 1.00 408 {s_acctbal} 1.00 460.00 <== 1.00 406.00 <== 0.00 1.00 409 {s_address} 1.00 460.00 <== 1.00 406.00 <== 0.00 1.00 410 {s_comment} 1.00 460.00 <== 1.00 406.00 <== 0.00 1.00 411 {s_name} 1.00 460.00 <== 1.00 406.00 <== 0.00 1.00 412 {s_phone} 1.00 460.00 <== 1.00 406.00 <== 0.00 1.00 413 414 stats table=q2_group_by_5 415 ---- 416 column_names row_count distinct_count null_count 417 {min} 642 458 0 418 {n_name} 642 5 0 419 {p_mfgr} 642 5 0 420 {p_partkey} 642 460 0 421 {ps_partkey} 642 460 0 422 {ps_suppkey} 642 548 0 423 {ps_supplycost} 642 640 0 424 {s_acctbal} 642 548 0 425 {s_address} 642 548 0 426 {s_comment} 642 548 0 427 {s_name} 642 548 0 428 {s_phone} 642 548 0 429 ~~~~ 430 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 431 {min} 1487.00 2.32 <== 1487.00 3.25 <== 0.00 1.00 432 {n_name} 1487.00 2.32 <== 1487.00 297.40 <== 0.00 1.00 433 {p_mfgr} 1487.00 2.32 <== 1487.00 297.40 <== 0.00 1.00 434 {p_partkey} 1487.00 2.32 <== 1487.00 3.23 <== 0.00 1.00 435 {ps_partkey} 1487.00 2.32 <== 1175.00 2.55 <== 0.00 1.00 436 {ps_suppkey} 1487.00 2.32 <== 1412.00 2.58 <== 0.00 1.00 437 {ps_supplycost} 1487.00 2.32 <== 1487.00 2.32 <== 0.00 1.00 438 {s_acctbal} 1487.00 2.32 <== 1487.00 2.71 <== 0.00 1.00 439 {s_address} 1487.00 2.32 <== 1487.00 2.71 <== 0.00 1.00 440 {s_comment} 1487.00 2.32 <== 1487.00 2.71 <== 0.00 1.00 441 {s_name} 1487.00 2.32 <== 1487.00 2.71 <== 0.00 1.00 442 {s_phone} 1487.00 2.32 <== 1487.00 2.71 <== 0.00 1.00 443 444 stats table=q2_inner_join_6 445 ---- 446 column_names row_count distinct_count null_count 447 {n_name} 1070 5 0 448 {n_nationkey_1} 1070 5 0 449 {n_nationkey} 1070 5 0 450 {n_regionkey_1} 1070 1 0 451 {n_regionkey} 1070 1 0 452 {p_mfgr} 1070 5 0 453 {p_partkey} 1070 460 0 454 {p_size} 1070 1 0 455 {p_type} 1070 30 0 456 {ps_partkey_1} 1070 460 0 457 {ps_partkey} 1070 460 0 458 {ps_suppkey_1} 1070 548 0 459 {ps_suppkey} 1070 548 0 460 {ps_supplycost_1} 1070 640 0 461 {ps_supplycost} 1070 640 0 462 {r_name_1} 1070 1 0 463 {r_name} 1070 1 0 464 {r_regionkey_1} 1070 1 0 465 {r_regionkey} 1070 1 0 466 {s_acctbal} 1070 548 0 467 {s_address} 1070 548 0 468 {s_comment} 1070 548 0 469 {s_name} 1070 548 0 470 {s_nationkey_1} 1070 5 0 471 {s_nationkey} 1070 5 0 472 {s_phone} 1070 548 0 473 {s_suppkey_1} 1070 548 0 474 {s_suppkey} 1070 548 0 475 ~~~~ 476 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 477 {n_name} 2837.00 2.65 <== 5.00 1.00 0.00 1.00 478 {n_nationkey} 2837.00 2.65 <== 5.00 1.00 0.00 1.00 479 {n_nationkey_1} 2837.00 2.65 <== 5.00 1.00 0.00 1.00 480 {n_regionkey} 2837.00 2.65 <== 1.00 1.00 0.00 1.00 481 {n_regionkey_1} 2837.00 2.65 <== 1.00 1.00 0.00 1.00 482 {p_mfgr} 2837.00 2.65 <== 5.00 1.00 0.00 1.00 483 {p_partkey} 2837.00 2.65 <== 1333.00 2.90 <== 0.00 1.00 484 {p_size} 2837.00 2.65 <== 1.00 1.00 0.00 1.00 485 {p_type} 2837.00 2.65 <== 150.00 5.00 <== 0.00 1.00 486 {ps_partkey} 2837.00 2.65 <== 1175.00 2.55 <== 0.00 1.00 487 {ps_partkey_1} 2837.00 2.65 <== 1333.00 2.90 <== 0.00 1.00 488 {ps_suppkey} 2837.00 2.65 <== 1412.00 2.58 <== 0.00 1.00 489 {ps_suppkey_1} 2837.00 2.65 <== 1449.00 2.64 <== 0.00 1.00 490 {ps_supplycost} 2837.00 2.65 <== 1483.00 2.32 <== 0.00 1.00 491 {ps_supplycost_1} 2837.00 2.65 <== 2788.00 4.36 <== 0.00 1.00 492 {r_name} 2837.00 2.65 <== 1.00 1.00 0.00 1.00 493 {r_name_1} 2837.00 2.65 <== 1.00 1.00 0.00 1.00 494 {r_regionkey} 2837.00 2.65 <== 1.00 1.00 0.00 1.00 495 {r_regionkey_1} 2837.00 2.65 <== 1.00 1.00 0.00 1.00 496 {s_acctbal} 2837.00 2.65 <== 1412.00 2.58 <== 0.00 1.00 497 {s_address} 2837.00 2.65 <== 1413.00 2.58 <== 0.00 1.00 498 {s_comment} 2837.00 2.65 <== 1412.00 2.58 <== 0.00 1.00 499 {s_name} 2837.00 2.65 <== 1412.00 2.58 <== 0.00 1.00 500 {s_nationkey} 2837.00 2.65 <== 5.00 1.00 0.00 1.00 501 {s_nationkey_1} 2837.00 2.65 <== 5.00 1.00 0.00 1.00 502 {s_phone} 2837.00 2.65 <== 1413.00 2.58 <== 0.00 1.00 503 {s_suppkey} 2837.00 2.65 <== 1412.00 2.58 <== 0.00 1.00 504 {s_suppkey_1} 2837.00 2.65 <== 1449.00 2.64 <== 0.00 1.00 505 506 stats table=q2_inner_join_7 507 ---- 508 column_names row_count distinct_count null_count 509 {n_nationkey} 158960 5 0 510 {n_regionkey} 158960 1 0 511 {ps_partkey} 158960 117007 0 512 {ps_suppkey} 158960 1987 0 513 {ps_supplycost} 158960 79812 0 514 {r_name} 158960 1 0 515 {r_regionkey} 158960 1 0 516 {s_nationkey} 158960 5 0 517 {s_suppkey} 158960 1987 0 518 ~~~~ 519 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 520 {n_nationkey} 161290.00 1.01 5.00 1.00 0.00 1.00 521 {n_regionkey} 161290.00 1.01 1.00 1.00 0.00 1.00 522 {ps_partkey} 161290.00 1.01 110568.00 1.06 0.00 1.00 523 {ps_suppkey} 161290.00 1.01 1845.00 1.08 0.00 1.00 524 {ps_supplycost} 161290.00 1.01 80252.00 1.01 0.00 1.00 525 {r_name} 161290.00 1.01 1.00 1.00 0.00 1.00 526 {r_regionkey} 161290.00 1.01 1.00 1.00 0.00 1.00 527 {s_nationkey} 161290.00 1.01 5.00 1.00 0.00 1.00 528 {s_suppkey} 161290.00 1.01 1845.00 1.08 0.00 1.00 529 530 stats table=q2_scan_8 531 ---- 532 column_names row_count distinct_count null_count 533 {ps_partkey} 800000 199241 0 534 {ps_suppkey} 800000 9920 0 535 {ps_supplycost} 800000 100379 0 536 ~~~~ 537 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 538 {ps_partkey} 800000.00 1.00 199241.00 1.00 0.00 1.00 539 {ps_suppkey} 800000.00 1.00 9920.00 1.00 0.00 1.00 540 {ps_supplycost} 800000.00 1.00 100379.00 1.00 0.00 1.00 541 542 stats table=q2_lookup_join_9 543 ---- 544 column_names row_count distinct_count null_count 545 {n_nationkey} 1987 5 0 546 {n_regionkey} 1987 1 0 547 {r_name} 1987 1 0 548 {r_regionkey} 1987 1 0 549 {s_nationkey} 1987 5 0 550 {s_suppkey} 1987 1987 0 551 ~~~~ 552 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 553 {n_nationkey} 2000.00 1.01 5.00 1.00 0.00 1.00 554 {n_regionkey} 2000.00 1.01 1.00 1.00 0.00 1.00 555 {r_name} 2000.00 1.01 1.00 1.00 0.00 1.00 556 {r_regionkey} 2000.00 1.01 1.00 1.00 0.00 1.00 557 {s_nationkey} 2000.00 1.01 5.00 1.00 0.00 1.00 558 {s_suppkey} 2000.00 1.01 1845.00 1.08 0.00 1.00 559 560 stats table=q2_merge_join_10 561 ---- 562 column_names row_count distinct_count null_count 563 {n_nationkey} 5 5 0 564 {n_regionkey} 5 1 0 565 {r_name} 5 1 0 566 {r_regionkey} 5 1 0 567 ~~~~ 568 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 569 {n_nationkey} 5.00 1.00 5.00 1.00 0.00 1.00 570 {n_regionkey} 5.00 1.00 1.00 1.00 0.00 1.00 571 {r_name} 5.00 1.00 1.00 1.00 0.00 1.00 572 {r_regionkey} 5.00 1.00 1.00 1.00 0.00 1.00 573 574 stats table=q2_scan_11 575 ---- 576 column_names row_count distinct_count null_count 577 {n_nationkey} 25 25 0 578 {n_regionkey} 25 5 0 579 ~~~~ 580 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 581 {n_nationkey} 25.00 1.00 25.00 1.00 0.00 1.00 582 {n_regionkey} 25.00 1.00 5.00 1.00 0.00 1.00 583 584 stats table=q2_select_12 585 ---- 586 column_names row_count distinct_count null_count 587 {r_name} 1 1 0 588 {r_regionkey} 1 1 0 589 ~~~~ 590 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 591 {r_name} 1.00 1.00 1.00 1.00 0.00 1.00 592 {r_regionkey} 1.00 1.00 1.00 1.00 0.00 1.00 593 594 stats table=q2_scan_13 595 ---- 596 column_names row_count distinct_count null_count 597 {r_name} 5 5 0 598 {r_regionkey} 5 5 0 599 ~~~~ 600 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 601 {r_name} 5.00 1.00 5.00 1.00 0.00 1.00 602 {r_regionkey} 5.00 1.00 5.00 1.00 0.00 1.00 603 604 stats table=q2_inner_join_14 605 ---- 606 column_names row_count distinct_count null_count 607 {n_name} 642 5 0 608 {n_nationkey} 642 5 0 609 {n_regionkey} 642 1 0 610 {p_mfgr} 642 5 0 611 {p_partkey} 642 460 0 612 {p_size} 642 1 0 613 {p_type} 642 30 0 614 {ps_partkey} 642 460 0 615 {ps_suppkey} 642 548 0 616 {ps_supplycost} 642 640 0 617 {r_name} 642 1 0 618 {r_regionkey} 642 1 0 619 {s_acctbal} 642 548 0 620 {s_address} 642 548 0 621 {s_comment} 642 548 0 622 {s_name} 642 548 0 623 {s_nationkey} 642 5 0 624 {s_phone} 642 548 0 625 {s_suppkey} 642 548 0 626 ~~~~ 627 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 628 {n_name} 1945.00 3.03 <== 5.00 1.00 0.00 1.00 629 {n_nationkey} 1945.00 3.03 <== 5.00 1.00 0.00 1.00 630 {n_regionkey} 1945.00 3.03 <== 1.00 1.00 0.00 1.00 631 {p_mfgr} 1945.00 3.03 <== 5.00 1.00 0.00 1.00 632 {p_partkey} 1945.00 3.03 <== 1333.00 2.90 <== 0.00 1.00 633 {p_size} 1945.00 3.03 <== 1.00 1.00 0.00 1.00 634 {p_type} 1945.00 3.03 <== 150.00 5.00 <== 0.00 1.00 635 {ps_partkey} 1945.00 3.03 <== 1333.00 2.90 <== 0.00 1.00 636 {ps_suppkey} 1945.00 3.03 <== 1766.00 3.22 <== 0.00 1.00 637 {ps_supplycost} 1945.00 3.03 <== 1922.00 3.00 <== 0.00 1.00 638 {r_name} 1945.00 3.03 <== 1.00 1.00 0.00 1.00 639 {r_regionkey} 1945.00 3.03 <== 1.00 1.00 0.00 1.00 640 {s_acctbal} 1945.00 3.03 <== 1767.00 3.22 <== 0.00 1.00 641 {s_address} 1945.00 3.03 <== 1768.00 3.23 <== 0.00 1.00 642 {s_comment} 1945.00 3.03 <== 1766.00 3.22 <== 0.00 1.00 643 {s_name} 1945.00 3.03 <== 1767.00 3.22 <== 0.00 1.00 644 {s_nationkey} 1945.00 3.03 <== 5.00 1.00 0.00 1.00 645 {s_phone} 1945.00 3.03 <== 1768.00 3.23 <== 0.00 1.00 646 {s_suppkey} 1945.00 3.03 <== 1766.00 3.22 <== 0.00 1.00 647 648 stats table=q2_inner_join_15 649 ---- 650 column_names row_count distinct_count null_count 651 {n_name} 158960 5 0 652 {n_nationkey} 158960 5 0 653 {n_regionkey} 158960 1 0 654 {ps_partkey} 158960 117007 0 655 {ps_suppkey} 158960 1987 0 656 {ps_supplycost} 158960 79812 0 657 {r_name} 158960 1 0 658 {r_regionkey} 158960 1 0 659 {s_acctbal} 158960 1983 0 660 {s_address} 158960 1986 0 661 {s_comment} 158960 1987 0 662 {s_name} 158960 1987 0 663 {s_nationkey} 158960 5 0 664 {s_phone} 158960 1987 0 665 {s_suppkey} 158960 1987 0 666 ~~~~ 667 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 668 {n_name} 161290.00 1.01 5.00 1.00 0.00 1.00 669 {n_nationkey} 161290.00 1.01 5.00 1.00 0.00 1.00 670 {n_regionkey} 161290.00 1.01 1.00 1.00 0.00 1.00 671 {ps_partkey} 161290.00 1.01 110565.00 1.06 0.00 1.00 672 {ps_suppkey} 161290.00 1.01 9920.00 4.99 <== 0.00 1.00 673 {ps_supplycost} 161290.00 1.01 80251.00 1.01 0.00 1.00 674 {r_name} 161290.00 1.01 1.00 1.00 0.00 1.00 675 {r_regionkey} 161290.00 1.01 1.00 1.00 0.00 1.00 676 {s_acctbal} 161290.00 1.01 9967.00 5.03 <== 0.00 1.00 677 {s_address} 161290.00 1.01 10000.00 5.04 <== 0.00 1.00 678 {s_comment} 161290.00 1.01 9934.00 5.00 <== 0.00 1.00 679 {s_name} 161290.00 1.01 9990.00 5.03 <== 0.00 1.00 680 {s_nationkey} 161290.00 1.01 5.00 1.00 0.00 1.00 681 {s_phone} 161290.00 1.01 10000.00 5.03 <== 0.00 1.00 682 {s_suppkey} 161290.00 1.01 9920.00 4.99 <== 0.00 1.00 683 684 stats table=q2_scan_16 685 ---- 686 column_names row_count distinct_count null_count 687 {ps_partkey} 800000 199241 0 688 {ps_suppkey} 800000 9920 0 689 {ps_supplycost} 800000 100379 0 690 ~~~~ 691 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 692 {ps_partkey} 800000.00 1.00 199241.00 1.00 0.00 1.00 693 {ps_suppkey} 800000.00 1.00 9920.00 1.00 0.00 1.00 694 {ps_supplycost} 800000.00 1.00 100379.00 1.00 0.00 1.00 695 696 stats table=q2_inner_join_17 697 ---- 698 column_names row_count distinct_count null_count 699 {n_name} 1987 5 0 700 {n_nationkey} 1987 5 0 701 {n_regionkey} 1987 1 0 702 {r_name} 1987 1 0 703 {r_regionkey} 1987 1 0 704 {s_acctbal} 1987 1983 0 705 {s_address} 1987 1986 0 706 {s_comment} 1987 1987 0 707 {s_name} 1987 1987 0 708 {s_nationkey} 1987 5 0 709 {s_phone} 1987 1987 0 710 {s_suppkey} 1987 1987 0 711 ~~~~ 712 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 713 {n_name} 2000.00 1.01 5.00 1.00 0.00 1.00 714 {n_nationkey} 2000.00 1.01 5.00 1.00 0.00 1.00 715 {n_regionkey} 2000.00 1.01 1.00 1.00 0.00 1.00 716 {r_name} 2000.00 1.01 1.00 1.00 0.00 1.00 717 {r_regionkey} 2000.00 1.01 1.00 1.00 0.00 1.00 718 {s_acctbal} 2000.00 1.01 1846.00 1.07 0.00 1.00 719 {s_address} 2000.00 1.01 1846.00 1.08 0.00 1.00 720 {s_comment} 2000.00 1.01 1845.00 1.08 0.00 1.00 721 {s_name} 2000.00 1.01 1846.00 1.08 0.00 1.00 722 {s_nationkey} 2000.00 1.01 5.00 1.00 0.00 1.00 723 {s_phone} 2000.00 1.01 1846.00 1.08 0.00 1.00 724 {s_suppkey} 2000.00 1.01 1845.00 1.08 0.00 1.00 725 726 stats table=q2_scan_18 727 ---- 728 column_names row_count distinct_count null_count 729 {s_acctbal} 10000 9967 0 730 {s_address} 10000 10027 0 731 {s_comment} 10000 9934 0 732 {s_name} 10000 9990 0 733 {s_nationkey} 10000 25 0 734 {s_phone} 10000 10021 0 735 {s_suppkey} 10000 9920 0 736 ~~~~ 737 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 738 {s_acctbal} 10000.00 1.00 9967.00 1.00 0.00 1.00 739 {s_address} 10000.00 1.00 10000.00 1.00 0.00 1.00 740 {s_comment} 10000.00 1.00 9934.00 1.00 0.00 1.00 741 {s_name} 10000.00 1.00 9990.00 1.00 0.00 1.00 742 {s_nationkey} 10000.00 1.00 25.00 1.00 0.00 1.00 743 {s_phone} 10000.00 1.00 10000.00 1.00 0.00 1.00 744 {s_suppkey} 10000.00 1.00 9920.00 1.00 0.00 1.00 745 746 stats table=q2_inner_join_19 747 ---- 748 column_names row_count distinct_count null_count 749 {n_name} 5 5 0 750 {n_nationkey} 5 5 0 751 {n_regionkey} 5 1 0 752 {r_name} 5 1 0 753 {r_regionkey} 5 1 0 754 ~~~~ 755 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 756 {n_name} 5.00 1.00 5.00 1.00 0.00 1.00 757 {n_nationkey} 5.00 1.00 5.00 1.00 0.00 1.00 758 {n_regionkey} 5.00 1.00 1.00 1.00 0.00 1.00 759 {r_name} 5.00 1.00 1.00 1.00 0.00 1.00 760 {r_regionkey} 5.00 1.00 1.00 1.00 0.00 1.00 761 762 stats table=q2_scan_20 763 ---- 764 column_names row_count distinct_count null_count 765 {n_name} 25 25 0 766 {n_nationkey} 25 25 0 767 {n_regionkey} 25 5 0 768 ~~~~ 769 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 770 {n_name} 25.00 1.00 25.00 1.00 0.00 1.00 771 {n_nationkey} 25.00 1.00 25.00 1.00 0.00 1.00 772 {n_regionkey} 25.00 1.00 5.00 1.00 0.00 1.00 773 774 stats table=q2_select_21 775 ---- 776 column_names row_count distinct_count null_count 777 {r_name} 1 1 0 778 {r_regionkey} 1 1 0 779 ~~~~ 780 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 781 {r_name} 1.00 1.00 1.00 1.00 0.00 1.00 782 {r_regionkey} 1.00 1.00 1.00 1.00 0.00 1.00 783 784 stats table=q2_scan_22 785 ---- 786 column_names row_count distinct_count null_count 787 {r_name} 5 5 0 788 {r_regionkey} 5 5 0 789 ~~~~ 790 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 791 {r_name} 5.00 1.00 5.00 1.00 0.00 1.00 792 {r_regionkey} 5.00 1.00 5.00 1.00 0.00 1.00 793 794 stats table=q2_select_23 795 ---- 796 column_names row_count distinct_count null_count 797 {p_mfgr} 747 5 0 798 {p_partkey} 747 747 0 799 {p_size} 747 1 0 800 {p_type} 747 30 0 801 ~~~~ 802 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 803 {p_mfgr} 1333.00 1.78 5.00 1.00 0.00 1.00 804 {p_partkey} 1333.00 1.78 1333.00 1.78 0.00 1.00 805 {p_size} 1333.00 1.78 1.00 1.00 0.00 1.00 806 {p_type} 1333.00 1.78 150.00 5.00 <== 0.00 1.00 807 808 stats table=q2_scan_24 809 ---- 810 column_names row_count distinct_count null_count 811 {p_mfgr} 200000 5 0 812 {p_partkey} 200000 199241 0 813 {p_size} 200000 50 0 814 {p_type} 200000 150 0 815 ~~~~ 816 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 817 {p_mfgr} 200000.00 1.00 5.00 1.00 0.00 1.00 818 {p_partkey} 200000.00 1.00 199241.00 1.00 0.00 1.00 819 {p_size} 200000.00 1.00 50.00 1.00 0.00 1.00 820 {p_type} 200000.00 1.00 150.00 1.00 0.00 1.00