github.com/cockroachdb/cockroach@v20.2.0-alpha.1+incompatible/pkg/sql/opt/memo/testdata/stats_quality/tpch/q07 (about) 1 import file=tpch_schema 2 ---- 3 4 import file=tpch_stats 5 ---- 6 7 # -------------------------------------------------- 8 # Q7 9 # Volume Shipping 10 # Determines the value of goods shipped between certain nations to help in the 11 # re-negotiation of shipping contracts. 12 # 13 # Finds, for two given nations, the gross discounted revenues derived from 14 # lineitems in which parts were shipped from a supplier in either nation to a 15 # customer in the other nation during 1995 and 1996. The query lists the 16 # supplier nation, the customer nation, the year, and the revenue from shipments 17 # that took place in that year. The query orders the answer by Supplier nation, 18 # Customer nation, and year (all ascending). 19 # 20 # TODO: 21 # 1. Join ordering 22 # -------------------------------------------------- 23 save-tables database=tpch save-tables-prefix=q7 24 SELECT 25 supp_nation, 26 cust_nation, 27 l_year, sum(volume) AS revenue 28 FROM ( 29 SELECT 30 n1.n_name AS supp_nation, 31 n2.n_name AS cust_nation, 32 extract(year FROM l_shipdate) AS l_year, 33 l_extendedprice * (1 - l_discount) AS volume 34 FROM 35 supplier, 36 lineitem, 37 orders, 38 customer, 39 nation n1, 40 nation n2 41 WHERE 42 s_suppkey = l_suppkey 43 AND o_orderkey = l_orderkey 44 AND c_custkey = o_custkey 45 AND s_nationkey = n1.n_nationkey 46 AND c_nationkey = n2.n_nationkey 47 AND ( 48 (n1.n_name = 'FRANCE' AND n2.n_name = 'GERMANY') 49 or (n1.n_name = 'GERMANY' AND n2.n_name = 'FRANCE') 50 ) 51 AND l_shipdate BETWEEN DATE '1995-01-01' AND DATE '1996-12-31' 52 ) AS shipping 53 GROUP BY 54 supp_nation, 55 cust_nation, 56 l_year 57 ORDER BY 58 supp_nation, 59 cust_nation, 60 l_year; 61 ---- 62 sort 63 ├── save-table-name: q7_sort_1 64 ├── columns: supp_nation:42(char!null) cust_nation:46(char!null) l_year:49(float) revenue:51(float!null) 65 ├── immutable 66 ├── stats: [rows=974.320532, distinct(42)=1.33333333, null(42)=0, distinct(46)=1.33333333, null(46)=0, distinct(49)=730.981616, null(49)=0, distinct(51)=974.320532, null(51)=0, distinct(42,46,49)=974.320532, null(42,46,49)=0] 67 ├── key: (42,46,49) 68 ├── fd: (42,46,49)-->(51) 69 ├── ordering: +42,+46,+49 70 └── group-by 71 ├── save-table-name: q7_group_by_2 72 ├── columns: n1.n_name:42(char!null) n2.n_name:46(char!null) l_year:49(float) sum:51(float!null) 73 ├── grouping columns: n1.n_name:42(char!null) n2.n_name:46(char!null) l_year:49(float) 74 ├── immutable 75 ├── stats: [rows=974.320532, distinct(42)=1.33333333, null(42)=0, distinct(46)=1.33333333, null(46)=0, distinct(49)=730.981616, null(49)=0, distinct(51)=974.320532, null(51)=0, distinct(42,46,49)=974.320532, null(42,46,49)=0] 76 ├── key: (42,46,49) 77 ├── fd: (42,46,49)-->(51) 78 ├── project 79 │ ├── save-table-name: q7_project_3 80 │ ├── columns: l_year:49(float) volume:50(float!null) n1.n_name:42(char!null) n2.n_name:46(char!null) 81 │ ├── immutable 82 │ ├── stats: [rows=7741.78379, distinct(42)=1.33333333, null(42)=0, distinct(46)=1.33333333, null(46)=0, distinct(49)=730.981616, null(49)=0, distinct(50)=7579.92926, null(50)=0, distinct(42,46,49)=974.320532, null(42,46,49)=0] 83 │ ├── inner-join (hash) 84 │ │ ├── save-table-name: q7_inner_join_4 85 │ │ ├── columns: s_suppkey:1(int!null) s_nationkey:4(int!null) l_orderkey:8(int!null) l_suppkey:10(int!null) l_extendedprice:13(float!null) l_discount:14(float!null) l_shipdate:18(date!null) o_orderkey:24(int!null) o_custkey:25(int!null) c_custkey:33(int!null) c_nationkey:36(int!null) n1.n_nationkey:41(int!null) n1.n_name:42(char!null) n2.n_nationkey:45(int!null) n2.n_name:46(char!null) 86 │ │ ├── stats: [rows=7741.78379, distinct(1)=7741.78379, null(1)=0, distinct(4)=1.29975178, null(4)=0, distinct(8)=7488.03308, null(8)=0, distinct(10)=7741.78379, null(10)=0, distinct(13)=7569.91685, null(13)=0, distinct(14)=11, null(14)=0, distinct(18)=730.981616, null(18)=0, distinct(24)=7488.03308, null(24)=0, distinct(25)=4946.3467, null(25)=0, distinct(33)=4946.3467, null(33)=0, distinct(36)=1.29975178, null(36)=0, distinct(41)=1.29975178, null(41)=0, distinct(42)=1.33333333, null(42)=0, distinct(45)=1.29975178, null(45)=0, distinct(46)=1.33333333, null(46)=0, distinct(13,14)=7579.92926, null(13,14)=0, distinct(18,42,46)=974.320532, null(18,42,46)=0] 87 │ │ ├── fd: (1)-->(4), (24)-->(25), (33)-->(36), (41)-->(42), (45)-->(46), (36)==(45), (45)==(36), (25)==(33), (33)==(25), (8)==(24), (24)==(8), (1)==(10), (10)==(1), (4)==(41), (41)==(4) 88 │ │ ├── inner-join (lookup lineitem) 89 │ │ │ ├── save-table-name: q7_lookup_join_5 90 │ │ │ ├── columns: l_orderkey:8(int!null) l_suppkey:10(int!null) l_extendedprice:13(float!null) l_discount:14(float!null) l_shipdate:18(date!null) o_orderkey:24(int!null) o_custkey:25(int!null) c_custkey:33(int!null) c_nationkey:36(int!null) n1.n_nationkey:41(int!null) n1.n_name:42(char!null) n2.n_nationkey:45(int!null) n2.n_name:46(char!null) 91 │ │ │ ├── key columns: [24] = [8] 92 │ │ │ ├── stats: [rows=191996.238, distinct(8)=115496.88, null(8)=0, distinct(10)=9919.99996, null(10)=0, distinct(13)=171759.779, null(13)=0, distinct(14)=11, null(14)=0, distinct(18)=731, null(18)=0, distinct(24)=115496.88, null(24)=0, distinct(25)=7944.47548, null(25)=0, distinct(33)=7944.47548, null(33)=0, distinct(36)=1.29975178, null(36)=0, distinct(41)=1.29975178, null(41)=0, distinct(42)=1.33333333, null(42)=0, distinct(45)=1.29975178, null(45)=0, distinct(46)=1.33333333, null(46)=0, distinct(13,14)=182544.701, null(13,14)=0, distinct(18,42,46)=974.666667, null(18,42,46)=0] 93 │ │ │ ├── fd: (24)-->(25), (33)-->(36), (41)-->(42), (45)-->(46), (36)==(45), (45)==(36), (25)==(33), (33)==(25), (8)==(24), (24)==(8) 94 │ │ │ ├── inner-join (lookup orders@o_ck) 95 │ │ │ │ ├── save-table-name: q7_lookup_join_6 96 │ │ │ │ ├── columns: o_orderkey:24(int!null) o_custkey:25(int!null) c_custkey:33(int!null) c_nationkey:36(int!null) n1.n_nationkey:41(int!null) n1.n_name:42(char!null) n2.n_nationkey:45(int!null) n2.n_name:46(char!null) 97 │ │ │ │ ├── key columns: [33] = [25] 98 │ │ │ │ ├── stats: [rows=120185.085, distinct(24)=115496.88, null(24)=0, distinct(25)=7944.47548, null(25)=0, distinct(33)=7944.47548, null(33)=0, distinct(36)=1.29975178, null(36)=0, distinct(41)=1.29975178, null(41)=0, distinct(42)=1.33333333, null(42)=0, distinct(45)=1.29975178, null(45)=0, distinct(46)=1.33333333, null(46)=0, distinct(42,46)=1.33333333, null(42,46)=0] 99 │ │ │ │ ├── key: (24,41) 100 │ │ │ │ ├── fd: (24)-->(25), (33)-->(36), (41)-->(42), (45)-->(46), (36)==(45), (45)==(36), (25)==(33), (33)==(25) 101 │ │ │ │ ├── inner-join (lookup customer@c_nk) 102 │ │ │ │ │ ├── save-table-name: q7_lookup_join_7 103 │ │ │ │ │ ├── columns: c_custkey:33(int!null) c_nationkey:36(int!null) n1.n_nationkey:41(int!null) n1.n_name:42(char!null) n2.n_nationkey:45(int!null) n2.n_name:46(char!null) 104 │ │ │ │ │ ├── key columns: [45] = [36] 105 │ │ │ │ │ ├── stats: [rows=8000, distinct(33)=7944.47548, null(33)=0, distinct(36)=1.29975178, null(36)=0, distinct(41)=1.29975178, null(41)=0, distinct(42)=1.33333333, null(42)=0, distinct(45)=1.29975178, null(45)=0, distinct(46)=1.33333333, null(46)=0, distinct(42,46)=1.33333333, null(42,46)=0] 106 │ │ │ │ │ ├── key: (33,41) 107 │ │ │ │ │ ├── fd: (33)-->(36), (41)-->(42), (45)-->(46), (36)==(45), (45)==(36) 108 │ │ │ │ │ ├── inner-join (cross) 109 │ │ │ │ │ │ ├── save-table-name: q7_inner_join_8 110 │ │ │ │ │ │ ├── columns: n1.n_nationkey:41(int!null) n1.n_name:42(char!null) n2.n_nationkey:45(int!null) n2.n_name:46(char!null) 111 │ │ │ │ │ │ ├── stats: [rows=1.33333333, distinct(41)=1.29975178, null(41)=0, distinct(42)=1.33333333, null(42)=0, distinct(45)=1.29975178, null(45)=0, distinct(46)=1.33333333, null(46)=0, distinct(42,46)=1.33333333, null(42,46)=0] 112 │ │ │ │ │ │ ├── key: (41,45) 113 │ │ │ │ │ │ ├── fd: (41)-->(42), (45)-->(46) 114 │ │ │ │ │ │ ├── scan n1 115 │ │ │ │ │ │ │ ├── save-table-name: q7_scan_9 116 │ │ │ │ │ │ │ ├── columns: n1.n_nationkey:41(int!null) n1.n_name:42(char!null) 117 │ │ │ │ │ │ │ ├── stats: [rows=25, distinct(41)=25, null(41)=0, distinct(42)=25, null(42)=0] 118 │ │ │ │ │ │ │ │ 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 1 119 │ │ │ │ │ │ │ │ <--- 0 --- 1 --- 2 --- 3 --- 4 --- 5 --- 6 --- 7 --- 8 --- 9 --- 10 --- 11 --- 12 --- 13 --- 14 --- 15 --- 16 --- 17 --- 18 --- 19 --- 20 --- 21 --- 22 --- 23 --- 24 120 │ │ │ │ │ │ │ ├── key: (41) 121 │ │ │ │ │ │ │ └── fd: (41)-->(42) 122 │ │ │ │ │ │ ├── scan n2 123 │ │ │ │ │ │ │ ├── save-table-name: q7_scan_10 124 │ │ │ │ │ │ │ ├── columns: n2.n_nationkey:45(int!null) n2.n_name:46(char!null) 125 │ │ │ │ │ │ │ ├── stats: [rows=25, distinct(45)=25, null(45)=0, distinct(46)=25, null(46)=0] 126 │ │ │ │ │ │ │ │ histogram(45)= 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 1 127 │ │ │ │ │ │ │ │ <--- 0 --- 1 --- 2 --- 3 --- 4 --- 5 --- 6 --- 7 --- 8 --- 9 --- 10 --- 11 --- 12 --- 13 --- 14 --- 15 --- 16 --- 17 --- 18 --- 19 --- 20 --- 21 --- 22 --- 23 --- 24 128 │ │ │ │ │ │ │ ├── key: (45) 129 │ │ │ │ │ │ │ └── fd: (45)-->(46) 130 │ │ │ │ │ │ └── filters 131 │ │ │ │ │ │ └── ((n1.n_name:42 = 'FRANCE') AND (n2.n_name:46 = 'GERMANY')) OR ((n1.n_name:42 = 'GERMANY') AND (n2.n_name:46 = 'FRANCE')) [type=bool, outer=(42,46), constraints=(/42: [/'FRANCE' - /'FRANCE'] [/'GERMANY' - /'GERMANY']; /46: [/'FRANCE' - /'FRANCE'] [/'GERMANY' - /'GERMANY'])] 132 │ │ │ │ │ └── filters (true) 133 │ │ │ │ └── filters (true) 134 │ │ │ └── filters 135 │ │ │ └── (l_shipdate:18 >= '1995-01-01') AND (l_shipdate:18 <= '1996-12-31') [type=bool, outer=(18), constraints=(/18: [/'1995-01-01' - /'1996-12-31']; tight)] 136 │ │ ├── scan supplier@s_nk 137 │ │ │ ├── save-table-name: q7_scan_11 138 │ │ │ ├── columns: s_suppkey:1(int!null) s_nationkey:4(int!null) 139 │ │ │ ├── stats: [rows=10000, distinct(1)=9920, null(1)=0, distinct(4)=25, null(4)=0] 140 │ │ │ │ histogram(1)= 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 1 141 │ │ │ │ <--- 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 142 │ │ │ │ histogram(4)= 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 0 393 143 │ │ │ │ <--- 0 --- 1 --- 2 --- 3 --- 4 --- 5 --- 6 --- 7 --- 8 --- 9 --- 10 --- 11 --- 12 --- 13 --- 14 --- 15 --- 16 --- 17 --- 18 --- 19 --- 20 --- 21 --- 22 --- 23 --- 24 144 │ │ │ ├── key: (1) 145 │ │ │ └── fd: (1)-->(4) 146 │ │ └── filters 147 │ │ ├── s_suppkey:1 = l_suppkey:10 [type=bool, outer=(1,10), constraints=(/1: (/NULL - ]; /10: (/NULL - ]), fd=(1)==(10), (10)==(1)] 148 │ │ └── s_nationkey:4 = n1.n_nationkey:41 [type=bool, outer=(4,41), constraints=(/4: (/NULL - ]; /41: (/NULL - ]), fd=(4)==(41), (41)==(4)] 149 │ └── projections 150 │ ├── extract('year', l_shipdate:18) [as=l_year:49, type=float, outer=(18), immutable] 151 │ └── l_extendedprice:13 * (1.0 - l_discount:14) [as=volume:50, type=float, outer=(13,14)] 152 └── aggregations 153 └── sum [as=sum:51, type=float, outer=(50)] 154 └── volume:50 [type=float] 155 156 stats table=q7_sort_1 157 ---- 158 column_names row_count distinct_count null_count 159 {cust_nation} 4 2 0 160 {l_year} 4 2 0 161 {revenue} 4 4 0 162 {supp_nation} 4 2 0 163 ~~~~ 164 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 165 {cust_nation} 974.00 243.50 <== 1.00 2.00 <== 0.00 1.00 166 {l_year} 974.00 243.50 <== 731.00 365.50 <== 0.00 1.00 167 {revenue} 974.00 243.50 <== 974.00 243.50 <== 0.00 1.00 168 {supp_nation} 974.00 243.50 <== 1.00 2.00 <== 0.00 1.00 169 170 stats table=q7_group_by_2 171 ---- 172 column_names row_count distinct_count null_count 173 {l_year} 4 2 0 174 {n_name_1} 4 2 0 175 {n_name} 4 2 0 176 {sum} 4 4 0 177 ~~~~ 178 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 179 {l_year} 974.00 243.50 <== 731.00 365.50 <== 0.00 1.00 180 {n_name} 974.00 243.50 <== 1.00 2.00 <== 0.00 1.00 181 {n_name_1} 974.00 243.50 <== 1.00 2.00 <== 0.00 1.00 182 {sum} 974.00 243.50 <== 974.00 243.50 <== 0.00 1.00 183 184 stats table=q7_project_3 185 ---- 186 column_names row_count distinct_count null_count 187 {l_year} 5924 2 0 188 {n_name_1} 5924 2 0 189 {n_name} 5924 2 0 190 {volume} 5924 5904 0 191 ~~~~ 192 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 193 {l_year} 7742.00 1.31 731.00 365.50 <== 0.00 1.00 194 {n_name} 7742.00 1.31 1.00 2.00 <== 0.00 1.00 195 {n_name_1} 7742.00 1.31 1.00 2.00 <== 0.00 1.00 196 {volume} 7742.00 1.31 7580.00 1.28 0.00 1.00 197 198 stats table=q7_inner_join_4 199 ---- 200 column_names row_count distinct_count null_count 201 {c_custkey} 5924 3902 0 202 {c_nationkey} 5924 2 0 203 {l_discount} 5924 11 0 204 {l_extendedprice} 5924 5876 0 205 {l_orderkey} 5924 5445 0 206 {l_shipdate} 5924 731 0 207 {l_suppkey} 5924 796 0 208 {n_name_1} 5924 2 0 209 {n_name} 5924 2 0 210 {n_nationkey_1} 5924 2 0 211 {n_nationkey} 5924 2 0 212 {o_custkey} 5924 3902 0 213 {o_orderkey} 5924 5445 0 214 {s_nationkey} 5924 2 0 215 {s_suppkey} 5924 796 0 216 ~~~~ 217 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 218 {c_custkey} 7742.00 1.31 4946.00 1.27 0.00 1.00 219 {c_nationkey} 7742.00 1.31 1.00 2.00 <== 0.00 1.00 220 {l_discount} 7742.00 1.31 11.00 1.00 0.00 1.00 221 {l_extendedprice} 7742.00 1.31 7570.00 1.29 0.00 1.00 222 {l_orderkey} 7742.00 1.31 7488.00 1.38 0.00 1.00 223 {l_shipdate} 7742.00 1.31 731.00 1.00 0.00 1.00 224 {l_suppkey} 7742.00 1.31 7742.00 9.73 <== 0.00 1.00 225 {n_name} 7742.00 1.31 1.00 2.00 <== 0.00 1.00 226 {n_name_1} 7742.00 1.31 1.00 2.00 <== 0.00 1.00 227 {n_nationkey} 7742.00 1.31 1.00 2.00 <== 0.00 1.00 228 {n_nationkey_1} 7742.00 1.31 1.00 2.00 <== 0.00 1.00 229 {o_custkey} 7742.00 1.31 4946.00 1.27 0.00 1.00 230 {o_orderkey} 7742.00 1.31 7488.00 1.38 0.00 1.00 231 {s_nationkey} 7742.00 1.31 1.00 2.00 <== 0.00 1.00 232 {s_suppkey} 7742.00 1.31 7742.00 9.73 <== 0.00 1.00 233 234 stats table=q7_lookup_join_5 235 ---- 236 column_names row_count distinct_count null_count 237 {c_custkey} 148370 7980 0 238 {c_nationkey} 148370 2 0 239 {l_discount} 148370 11 0 240 {l_extendedprice} 148370 135829 0 241 {l_orderkey} 148370 39757 0 242 {l_shipdate} 148370 731 0 243 {l_suppkey} 148370 9920 0 244 {n_name_1} 148370 2 0 245 {n_name} 148370 2 0 246 {n_nationkey_1} 148370 2 0 247 {n_nationkey} 148370 2 0 248 {o_custkey} 148370 7980 0 249 {o_orderkey} 148370 39757 0 250 ~~~~ 251 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 252 {c_custkey} 191996.00 1.29 7944.00 1.00 0.00 1.00 253 {c_nationkey} 191996.00 1.29 1.00 2.00 <== 0.00 1.00 254 {l_discount} 191996.00 1.29 11.00 1.00 0.00 1.00 255 {l_extendedprice} 191996.00 1.29 171760.00 1.26 0.00 1.00 256 {l_orderkey} 191996.00 1.29 115497.00 2.91 <== 0.00 1.00 257 {l_shipdate} 191996.00 1.29 731.00 1.00 0.00 1.00 258 {l_suppkey} 191996.00 1.29 9920.00 1.00 0.00 1.00 259 {n_name} 191996.00 1.29 1.00 2.00 <== 0.00 1.00 260 {n_name_1} 191996.00 1.29 1.00 2.00 <== 0.00 1.00 261 {n_nationkey} 191996.00 1.29 1.00 2.00 <== 0.00 1.00 262 {n_nationkey_1} 191996.00 1.29 1.00 2.00 <== 0.00 1.00 263 {o_custkey} 191996.00 1.29 7944.00 1.00 0.00 1.00 264 {o_orderkey} 191996.00 1.29 115497.00 2.91 <== 0.00 1.00 265 266 stats table=q7_lookup_join_6 267 ---- 268 column_names row_count distinct_count null_count 269 {c_custkey} 121324 8132 0 270 {c_nationkey} 121324 2 0 271 {n_name_1} 121324 2 0 272 {n_name} 121324 2 0 273 {n_nationkey_1} 121324 2 0 274 {n_nationkey} 121324 2 0 275 {o_custkey} 121324 8132 0 276 {o_orderkey} 121324 120984 0 277 ~~~~ 278 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 279 {c_custkey} 120185.00 1.01 7944.00 1.02 0.00 1.00 280 {c_nationkey} 120185.00 1.01 1.00 2.00 <== 0.00 1.00 281 {n_name} 120185.00 1.01 1.00 2.00 <== 0.00 1.00 282 {n_name_1} 120185.00 1.01 1.00 2.00 <== 0.00 1.00 283 {n_nationkey} 120185.00 1.01 1.00 2.00 <== 0.00 1.00 284 {n_nationkey_1} 120185.00 1.01 1.00 2.00 <== 0.00 1.00 285 {o_custkey} 120185.00 1.01 7944.00 1.02 0.00 1.00 286 {o_orderkey} 120185.00 1.01 115497.00 1.05 0.00 1.00 287 288 stats table=q7_lookup_join_7 289 ---- 290 column_names row_count distinct_count null_count 291 {c_custkey} 12008 12045 0 292 {c_nationkey} 12008 2 0 293 {n_name_1} 12008 2 0 294 {n_name} 12008 2 0 295 {n_nationkey_1} 12008 2 0 296 {n_nationkey} 12008 2 0 297 ~~~~ 298 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 299 {c_custkey} 8000.00 1.50 7944.00 1.52 0.00 1.00 300 {c_nationkey} 8000.00 1.50 1.00 2.00 <== 0.00 1.00 301 {n_name} 8000.00 1.50 1.00 2.00 <== 0.00 1.00 302 {n_name_1} 8000.00 1.50 1.00 2.00 <== 0.00 1.00 303 {n_nationkey} 8000.00 1.50 1.00 2.00 <== 0.00 1.00 304 {n_nationkey_1} 8000.00 1.50 1.00 2.00 <== 0.00 1.00 305 306 stats table=q7_inner_join_8 307 ---- 308 column_names row_count distinct_count null_count 309 {n_name_1} 2 2 0 310 {n_name} 2 2 0 311 {n_nationkey_1} 2 2 0 312 {n_nationkey} 2 2 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 2.00 <== 1.00 2.00 <== 0.00 1.00 316 {n_name_1} 1.00 2.00 <== 1.00 2.00 <== 0.00 1.00 317 {n_nationkey} 1.00 2.00 <== 1.00 2.00 <== 0.00 1.00 318 {n_nationkey_1} 1.00 2.00 <== 1.00 2.00 <== 0.00 1.00 319 320 stats table=q7_scan_9 321 ---- 322 column_names row_count distinct_count null_count 323 {n_name} 25 25 0 324 {n_nationkey} 25 25 0 325 ~~~~ 326 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 327 {n_name} 25.00 1.00 25.00 1.00 0.00 1.00 328 {n_nationkey} 25.00 1.00 25.00 1.00 0.00 1.00 329 330 stats table=q7_scan_10 331 ---- 332 column_names row_count distinct_count null_count 333 {n_name} 25 25 0 334 {n_nationkey} 25 25 0 335 ~~~~ 336 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 337 {n_name} 25.00 1.00 25.00 1.00 0.00 1.00 338 {n_nationkey} 25.00 1.00 25.00 1.00 0.00 1.00 339 340 stats table=q7_scan_11 341 ---- 342 column_names row_count distinct_count null_count 343 {s_nationkey} 10000 25 0 344 {s_suppkey} 10000 9920 0 345 ~~~~ 346 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 347 {s_nationkey} 10000.00 1.00 25.00 1.00 0.00 1.00 348 {s_suppkey} 10000.00 1.00 9920.00 1.00 0.00 1.00