github.com/cockroachdb/cockroach@v20.2.0-alpha.1+incompatible/pkg/sql/opt/memo/testdata/stats_quality/tpch/q15 (about) 1 import file=tpch_schema 2 ---- 3 4 import file=tpch_stats 5 ---- 6 7 # -------------------------------------------------- 8 # Q15 9 # Top Supplier 10 # Determines the top supplier so it can be rewarded, given more business, or 11 # identified for special recognition. 12 # 13 # Finds the supplier who contributed the most to the overall revenue for parts 14 # shipped during a given quarter of a given year. In case of a tie, the query 15 # lists all suppliers whose contribution was equal to the maximum, presented in 16 # supplier number order. 17 # -------------------------------------------------- 18 exec-ddl 19 CREATE VIEW revenue0 (supplier_no, total_revenue) AS 20 SELECT 21 l_suppkey, 22 sum(l_extendedprice * (1 - l_discount)) 23 FROM 24 lineitem 25 WHERE 26 l_shipdate >= DATE '1996-01-01' 27 AND l_shipdate < DATE '1996-01-01' + INTERVAL '3' MONTH 28 GROUP BY 29 l_suppkey; 30 ---- 31 32 save-tables database=tpch save-tables-prefix=q15 33 SELECT 34 s_suppkey, 35 s_name, 36 s_address, 37 s_phone, 38 total_revenue 39 FROM 40 supplier, 41 revenue0 42 WHERE 43 s_suppkey = supplier_no 44 AND total_revenue = ( 45 SELECT 46 max(total_revenue) 47 FROM 48 revenue0 49 ) 50 ORDER BY 51 s_suppkey; 52 ---- 53 project 54 ├── save-table-name: q15_project_1 55 ├── columns: s_suppkey:1(int!null) s_name:2(char!null) s_address:3(varchar!null) s_phone:5(char!null) total_revenue:25(float!null) 56 ├── stats: [rows=3333.33333, distinct(1)=3306.66667, null(1)=0, distinct(2)=2834.3606, null(2)=0, distinct(3)=2834.80729, null(3)=0, distinct(5)=2834.80729, null(5)=0, distinct(25)=2100.04396, null(25)=0] 57 ├── key: (1) 58 ├── fd: (1)-->(2,3,5,25) 59 ├── ordering: +1 60 └── inner-join (merge) 61 ├── save-table-name: q15_merge_join_2 62 ├── columns: s_suppkey:1(int!null) s_name:2(char!null) s_address:3(varchar!null) s_phone:5(char!null) l_suppkey:10(int!null) sum:25(float!null) 63 ├── left ordering: +1 64 ├── right ordering: +10 65 ├── stats: [rows=3333.33333, distinct(1)=3306.66667, null(1)=0, distinct(2)=2834.3606, null(2)=0, distinct(3)=2834.80729, null(3)=0, distinct(5)=2834.80729, null(5)=0, distinct(10)=3306.66667, null(10)=0, distinct(25)=2100.04396, null(25)=0] 66 ├── key: (10) 67 ├── fd: (1)-->(2,3,5), (10)-->(25), (1)==(10), (10)==(1) 68 ├── ordering: +(1|10) [actual: +1] 69 ├── scan supplier 70 │ ├── save-table-name: q15_scan_3 71 │ ├── columns: s_suppkey:1(int!null) s_name:2(char!null) s_address:3(varchar!null) s_phone:5(char!null) 72 │ ├── stats: [rows=10000, distinct(1)=9920, null(1)=0, distinct(2)=9990, null(2)=0, distinct(3)=10000, null(3)=0, distinct(5)=10000, null(5)=0] 73 │ │ 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 74 │ │ <--- 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 75 │ ├── key: (1) 76 │ ├── fd: (1)-->(2,3,5) 77 │ └── ordering: +1 78 ├── sort 79 │ ├── save-table-name: q15_sort_4 80 │ ├── columns: l_suppkey:10(int!null) sum:25(float!null) 81 │ ├── stats: [rows=3306.66667, distinct(10)=3306.66667, null(10)=0, distinct(25)=3306.66667, null(25)=0] 82 │ ├── key: (10) 83 │ ├── fd: (10)-->(25) 84 │ ├── ordering: +10 85 │ └── select 86 │ ├── save-table-name: q15_select_5 87 │ ├── columns: l_suppkey:10(int!null) sum:25(float!null) 88 │ ├── stats: [rows=3306.66667, distinct(10)=3306.66667, null(10)=0, distinct(25)=3306.66667, null(25)=0] 89 │ ├── key: (10) 90 │ ├── fd: (10)-->(25) 91 │ ├── group-by 92 │ │ ├── save-table-name: q15_group_by_6 93 │ │ ├── columns: l_suppkey:10(int!null) sum:25(float!null) 94 │ │ ├── grouping columns: l_suppkey:10(int!null) 95 │ │ ├── stats: [rows=9920, distinct(10)=9920, null(10)=0, distinct(25)=9920, null(25)=0] 96 │ │ ├── key: (10) 97 │ │ ├── fd: (10)-->(25) 98 │ │ ├── project 99 │ │ │ ├── save-table-name: q15_project_7 100 │ │ │ ├── columns: column24:24(float!null) l_suppkey:10(int!null) 101 │ │ │ ├── stats: [rows=259635.063, distinct(10)=9920, null(10)=0, distinct(24)=259635.063, null(24)=0] 102 │ │ │ ├── index-join lineitem 103 │ │ │ │ ├── save-table-name: q15_index_join_8 104 │ │ │ │ ├── columns: l_suppkey:10(int!null) l_extendedprice:13(float!null) l_discount:14(float!null) l_shipdate:18(date!null) 105 │ │ │ │ ├── stats: [rows=259635.063, distinct(10)=9920, null(10)=0, distinct(13)=230767.055, null(13)=0, distinct(14)=11, null(14)=0, distinct(18)=91, null(18)=0, distinct(13,14)=259635.063, null(13,14)=0] 106 │ │ │ │ │ histogram(18)= 0 0 28205 2400 25805 3600 26405 4800 25805 3000 27005 3600 27005 3000 27605 3600 27005 5401 12820 2564.1 107 │ │ │ │ │ <--- '1995-12-31' ------- '1996-01-12' ------- '1996-01-22' ------- '1996-02-01' ------- '1996-02-10' ------- '1996-02-21' ------- '1996-03-02' ------- '1996-03-13' ------- '1996-03-25' ------- '1996-03-31' 108 │ │ │ │ └── scan lineitem@l_sd 109 │ │ │ │ ├── save-table-name: q15_scan_9 110 │ │ │ │ ├── columns: l_orderkey:8(int!null) l_linenumber:11(int!null) l_shipdate:18(date!null) 111 │ │ │ │ ├── constraint: /18/8/11: [/'1996-01-01' - /'1996-03-31'] 112 │ │ │ │ ├── stats: [rows=259635.063, distinct(8)=243635.718, null(8)=0, distinct(11)=7, null(11)=0, distinct(18)=91, null(18)=0] 113 │ │ │ │ │ histogram(8)= 0 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 114 │ │ │ │ │ <--- 326 --------- 28929 -------- 50503 -------- 89793 -------- 115938 -------- 146944 -------- 176768 -------- 211201 -------- 237860 -------- 266885 -------- 297604 -------- 330021 -------- 365889 -------- 398951 -------- 426117 -------- 451328 -------- 472134 -------- 499590 -------- 529284 -------- 557254 -------- 589154 -------- 619394 -------- 642951 -------- 670113 -------- 692931 -------- 721157 -------- 751687 -------- 777766 -------- 804582 -------- 836740 -------- 868868 -------- 898912 -------- 922500 -------- 946403 -------- 984870 -------- 1007936 -------- 1030117 -------- 1062275 -------- 1093572 -------- 1120709 -------- 1150981 -------- 1182786 -------- 1206406 -------- 1234116 -------- 1260961 -------- 1290502 -------- 1329510 -------- 1355426 -------- 1381313 -------- 1409796 -------- 1445254 -------- 1479233 -------- 1504935 -------- 1531079 -------- 1559650 -------- 1583616 -------- 1617504 -------- 1655749 -------- 1685185 -------- 1718183 -------- 1747716 -------- 1772131 -------- 1802372 -------- 1833315 -------- 1862403 -------- 1897894 -------- 1922819 -------- 1954405 -------- 1979329 -------- 2009859 -------- 2041670 -------- 2070851 -------- 2093828 -------- 2127973 -------- 2167777 -------- 2194883 -------- 2227814 -------- 2262437 -------- 2296353 -------- 2321024 -------- 2346051 -------- 2376257 -------- 2404932 -------- 2446273 -------- 2474081 -------- 2504515 -------- 2535302 -------- 2561413 -------- 2592737 -------- 2616801 -------- 2646112 -------- 2676546 -------- 2702116 -------- 2732454 -------- 2765382 -------- 2799495 -------- 2828866 -------- 2868737 -------- 2910625 -------- 2938464 -------- 2963140 -------- 3003302 -------- 3043264 -------- 3069123 -------- 3095909 -------- 3126693 -------- 3160485 -------- 3196039 -------- 3229504 -------- 3259712 -------- 3286439 -------- 3318852 -------- 3346821 -------- 3370119 -------- 3395204 -------- 3425888 -------- 3448611 -------- 3476130 -------- 3502372 -------- 3529474 -------- 3556390 -------- 3583553 -------- 3612550 -------- 3647875 -------- 3679140 -------- 3702661 -------- 3738017 -------- 3778050 -------- 3806114 -------- 3839074 -------- 3872805 -------- 3905697 -------- 3926212 -------- 3959841 -------- 3997281 -------- 4033861 -------- 4063591 -------- 4097831 -------- 4124807 -------- 4158656 -------- 4195748 -------- 4234274 -------- 4269952 -------- 4298949 -------- 4332806 -------- 4364705 -------- 4398246 -------- 4430695 -------- 4466403 -------- 4494662 -------- 4524420 -------- 4558561 -------- 4601092 -------- 4632871 -------- 4658694 -------- 4690501 -------- 4728066 -------- 4758657 -------- 4788294 -------- 4818597 -------- 4855874 -------- 4890913 -------- 4915366 -------- 4940709 -------- 4972357 -------- 4995298 -------- 5019523 -------- 5043329 -------- 5077376 -------- 5109920 -------- 5136582 -------- 5161152 -------- 5191846 -------- 5219973 -------- 5251015 -------- 5282021 -------- 5312355 -------- 5343207 -------- 5381318 -------- 5416163 -------- 5445382 -------- 5476933 -------- 5509185 -------- 5539237 -------- 5566818 -------- 5588739 -------- 5620481 -------- 5644001 -------- 5667010 -------- 5689476 -------- 5724709 -------- 5755398 -------- 5790598 -------- 5819425 -------- 5846341 -------- 5874656 -------- 5908067 -------- 5933572 -------- 5962659 -------- 5999971 115 │ │ │ │ │ histogram(18)= 0 0 28205 2400 25805 3600 26405 4800 25805 3000 27005 3600 27005 3000 27605 3600 27005 5401 12820 2564.1 116 │ │ │ │ │ <--- '1995-12-31' ------- '1996-01-12' ------- '1996-01-22' ------- '1996-02-01' ------- '1996-02-10' ------- '1996-02-21' ------- '1996-03-02' ------- '1996-03-13' ------- '1996-03-25' ------- '1996-03-31' 117 │ │ │ │ ├── key: (8,11) 118 │ │ │ │ └── fd: (8,11)-->(18) 119 │ │ │ └── projections 120 │ │ │ └── l_extendedprice:13 * (1.0 - l_discount:14) [as=column24:24, type=float, outer=(13,14)] 121 │ │ └── aggregations 122 │ │ └── sum [as=sum:25, type=float, outer=(24)] 123 │ │ └── column24:24 [type=float] 124 │ └── filters 125 │ └── eq [type=bool, outer=(25), subquery, constraints=(/25: (/NULL - ])] 126 │ ├── sum:25 [type=float] 127 │ └── subquery [type=float] 128 │ └── scalar-group-by 129 │ ├── save-table-name: q15_scalar_group_by_10 130 │ ├── columns: max:44(float) 131 │ ├── cardinality: [1 - 1] 132 │ ├── stats: [rows=1, distinct(44)=1, null(44)=0] 133 │ ├── key: () 134 │ ├── fd: ()-->(44) 135 │ ├── group-by 136 │ │ ├── save-table-name: q15_group_by_11 137 │ │ ├── columns: l_suppkey:28(int!null) sum:43(float!null) 138 │ │ ├── grouping columns: l_suppkey:28(int!null) 139 │ │ ├── stats: [rows=9920, distinct(28)=9920, null(28)=0, distinct(43)=9920, null(43)=0] 140 │ │ ├── key: (28) 141 │ │ ├── fd: (28)-->(43) 142 │ │ ├── project 143 │ │ │ ├── save-table-name: q15_project_12 144 │ │ │ ├── columns: column42:42(float!null) l_suppkey:28(int!null) 145 │ │ │ ├── stats: [rows=259635.063, distinct(28)=9920, null(28)=0, distinct(42)=259635.063, null(42)=0] 146 │ │ │ ├── index-join lineitem 147 │ │ │ │ ├── save-table-name: q15_index_join_13 148 │ │ │ │ ├── columns: l_suppkey:28(int!null) l_extendedprice:31(float!null) l_discount:32(float!null) l_shipdate:36(date!null) 149 │ │ │ │ ├── stats: [rows=259635.063, distinct(28)=9920, null(28)=0, distinct(31)=230767.055, null(31)=0, distinct(32)=11, null(32)=0, distinct(36)=91, null(36)=0, distinct(31,32)=259635.063, null(31,32)=0] 150 │ │ │ │ │ histogram(36)= 0 0 28205 2400 25805 3600 26405 4800 25805 3000 27005 3600 27005 3000 27605 3600 27005 5401 12820 2564.1 151 │ │ │ │ │ <--- '1995-12-31' ------- '1996-01-12' ------- '1996-01-22' ------- '1996-02-01' ------- '1996-02-10' ------- '1996-02-21' ------- '1996-03-02' ------- '1996-03-13' ------- '1996-03-25' ------- '1996-03-31' 152 │ │ │ │ └── scan lineitem@l_sd 153 │ │ │ │ ├── save-table-name: q15_scan_14 154 │ │ │ │ ├── columns: l_orderkey:26(int!null) l_linenumber:29(int!null) l_shipdate:36(date!null) 155 │ │ │ │ ├── constraint: /36/26/29: [/'1996-01-01' - /'1996-03-31'] 156 │ │ │ │ ├── stats: [rows=259635.063, distinct(26)=243635.718, null(26)=0, distinct(29)=7, null(29)=0, distinct(36)=91, null(36)=0] 157 │ │ │ │ │ histogram(26)= 0 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1272.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 1298.2 25.958 158 │ │ │ │ │ <--- 326 --------- 28929 -------- 50503 -------- 89793 -------- 115938 -------- 146944 -------- 176768 -------- 211201 -------- 237860 -------- 266885 -------- 297604 -------- 330021 -------- 365889 -------- 398951 -------- 426117 -------- 451328 -------- 472134 -------- 499590 -------- 529284 -------- 557254 -------- 589154 -------- 619394 -------- 642951 -------- 670113 -------- 692931 -------- 721157 -------- 751687 -------- 777766 -------- 804582 -------- 836740 -------- 868868 -------- 898912 -------- 922500 -------- 946403 -------- 984870 -------- 1007936 -------- 1030117 -------- 1062275 -------- 1093572 -------- 1120709 -------- 1150981 -------- 1182786 -------- 1206406 -------- 1234116 -------- 1260961 -------- 1290502 -------- 1329510 -------- 1355426 -------- 1381313 -------- 1409796 -------- 1445254 -------- 1479233 -------- 1504935 -------- 1531079 -------- 1559650 -------- 1583616 -------- 1617504 -------- 1655749 -------- 1685185 -------- 1718183 -------- 1747716 -------- 1772131 -------- 1802372 -------- 1833315 -------- 1862403 -------- 1897894 -------- 1922819 -------- 1954405 -------- 1979329 -------- 2009859 -------- 2041670 -------- 2070851 -------- 2093828 -------- 2127973 -------- 2167777 -------- 2194883 -------- 2227814 -------- 2262437 -------- 2296353 -------- 2321024 -------- 2346051 -------- 2376257 -------- 2404932 -------- 2446273 -------- 2474081 -------- 2504515 -------- 2535302 -------- 2561413 -------- 2592737 -------- 2616801 -------- 2646112 -------- 2676546 -------- 2702116 -------- 2732454 -------- 2765382 -------- 2799495 -------- 2828866 -------- 2868737 -------- 2910625 -------- 2938464 -------- 2963140 -------- 3003302 -------- 3043264 -------- 3069123 -------- 3095909 -------- 3126693 -------- 3160485 -------- 3196039 -------- 3229504 -------- 3259712 -------- 3286439 -------- 3318852 -------- 3346821 -------- 3370119 -------- 3395204 -------- 3425888 -------- 3448611 -------- 3476130 -------- 3502372 -------- 3529474 -------- 3556390 -------- 3583553 -------- 3612550 -------- 3647875 -------- 3679140 -------- 3702661 -------- 3738017 -------- 3778050 -------- 3806114 -------- 3839074 -------- 3872805 -------- 3905697 -------- 3926212 -------- 3959841 -------- 3997281 -------- 4033861 -------- 4063591 -------- 4097831 -------- 4124807 -------- 4158656 -------- 4195748 -------- 4234274 -------- 4269952 -------- 4298949 -------- 4332806 -------- 4364705 -------- 4398246 -------- 4430695 -------- 4466403 -------- 4494662 -------- 4524420 -------- 4558561 -------- 4601092 -------- 4632871 -------- 4658694 -------- 4690501 -------- 4728066 -------- 4758657 -------- 4788294 -------- 4818597 -------- 4855874 -------- 4890913 -------- 4915366 -------- 4940709 -------- 4972357 -------- 4995298 -------- 5019523 -------- 5043329 -------- 5077376 -------- 5109920 -------- 5136582 -------- 5161152 -------- 5191846 -------- 5219973 -------- 5251015 -------- 5282021 -------- 5312355 -------- 5343207 -------- 5381318 -------- 5416163 -------- 5445382 -------- 5476933 -------- 5509185 -------- 5539237 -------- 5566818 -------- 5588739 -------- 5620481 -------- 5644001 -------- 5667010 -------- 5689476 -------- 5724709 -------- 5755398 -------- 5790598 -------- 5819425 -------- 5846341 -------- 5874656 -------- 5908067 -------- 5933572 -------- 5962659 -------- 5999971 159 │ │ │ │ │ histogram(36)= 0 0 28205 2400 25805 3600 26405 4800 25805 3000 27005 3600 27005 3000 27605 3600 27005 5401 12820 2564.1 160 │ │ │ │ │ <--- '1995-12-31' ------- '1996-01-12' ------- '1996-01-22' ------- '1996-02-01' ------- '1996-02-10' ------- '1996-02-21' ------- '1996-03-02' ------- '1996-03-13' ------- '1996-03-25' ------- '1996-03-31' 161 │ │ │ │ ├── key: (26,29) 162 │ │ │ │ └── fd: (26,29)-->(36) 163 │ │ │ └── projections 164 │ │ │ └── l_extendedprice:31 * (1.0 - l_discount:32) [as=column42:42, type=float, outer=(31,32)] 165 │ │ └── aggregations 166 │ │ └── sum [as=sum:43, type=float, outer=(42)] 167 │ │ └── column42:42 [type=float] 168 │ └── aggregations 169 │ └── max [as=max:44, type=float, outer=(43)] 170 │ └── sum:43 [type=float] 171 └── filters (true) 172 173 stats table=q15_project_1 174 ---- 175 column_names row_count distinct_count null_count 176 {s_address} 1 1 0 177 {s_name} 1 1 0 178 {s_phone} 1 1 0 179 {s_suppkey} 1 1 0 180 {total_revenue} 1 1 0 181 ~~~~ 182 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 183 {s_address} 3333.00 3333.00 <== 2835.00 2835.00 <== 0.00 1.00 184 {s_name} 3333.00 3333.00 <== 2834.00 2834.00 <== 0.00 1.00 185 {s_phone} 3333.00 3333.00 <== 2835.00 2835.00 <== 0.00 1.00 186 {s_suppkey} 3333.00 3333.00 <== 3307.00 3307.00 <== 0.00 1.00 187 {total_revenue} 3333.00 3333.00 <== 2100.00 2100.00 <== 0.00 1.00 188 189 stats table=q15_merge_join_2 190 ---- 191 column_names row_count distinct_count null_count 192 {l_suppkey} 1 1 0 193 {s_address} 1 1 0 194 {s_name} 1 1 0 195 {s_phone} 1 1 0 196 {s_suppkey} 1 1 0 197 {sum} 1 1 0 198 ~~~~ 199 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 200 {l_suppkey} 3333.00 3333.00 <== 3307.00 3307.00 <== 0.00 1.00 201 {s_address} 3333.00 3333.00 <== 2835.00 2835.00 <== 0.00 1.00 202 {s_name} 3333.00 3333.00 <== 2834.00 2834.00 <== 0.00 1.00 203 {s_phone} 3333.00 3333.00 <== 2835.00 2835.00 <== 0.00 1.00 204 {s_suppkey} 3333.00 3333.00 <== 3307.00 3307.00 <== 0.00 1.00 205 {sum} 3333.00 3333.00 <== 2100.00 2100.00 <== 0.00 1.00 206 207 stats table=q15_scan_3 208 ---- 209 column_names row_count distinct_count null_count 210 {s_address} 10000 10027 0 211 {s_name} 10000 9990 0 212 {s_phone} 10000 10021 0 213 {s_suppkey} 10000 9920 0 214 ~~~~ 215 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 216 {s_address} 10000.00 1.00 10000.00 1.00 0.00 1.00 217 {s_name} 10000.00 1.00 9990.00 1.00 0.00 1.00 218 {s_phone} 10000.00 1.00 10000.00 1.00 0.00 1.00 219 {s_suppkey} 10000.00 1.00 9920.00 1.00 0.00 1.00 220 221 stats table=q15_sort_4 222 ---- 223 column_names row_count distinct_count null_count 224 {l_suppkey} 1 1 0 225 {sum} 1 1 0 226 ~~~~ 227 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 228 {l_suppkey} 3307.00 3307.00 <== 3307.00 3307.00 <== 0.00 1.00 229 {sum} 3307.00 3307.00 <== 3307.00 3307.00 <== 0.00 1.00 230 231 stats table=q15_select_5 232 ---- 233 column_names row_count distinct_count null_count 234 {l_suppkey} 1 1 0 235 {sum} 1 1 0 236 ~~~~ 237 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 238 {l_suppkey} 3307.00 3307.00 <== 3307.00 3307.00 <== 0.00 1.00 239 {sum} 3307.00 3307.00 <== 3307.00 3307.00 <== 0.00 1.00 240 241 stats table=q15_group_by_6 242 ---- 243 column_names row_count distinct_count null_count 244 {l_suppkey} 10000 9920 0 245 {sum} 10000 10011 0 246 ~~~~ 247 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 248 {l_suppkey} 9920.00 1.01 9920.00 1.00 0.00 1.00 249 {sum} 9920.00 1.01 9920.00 1.01 0.00 1.00 250 251 stats table=q15_project_7 252 ---- 253 column_names row_count distinct_count null_count 254 {column24} 225954 220864 0 255 {l_suppkey} 225954 9920 0 256 ~~~~ 257 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 258 {column24} 259635.00 1.15 259635.00 1.18 0.00 1.00 259 {l_suppkey} 259635.00 1.15 9920.00 1.00 0.00 1.00 260 261 stats table=q15_index_join_8 262 ---- 263 column_names row_count distinct_count null_count 264 {l_discount} 225954 11 0 265 {l_extendedprice} 225954 196692 0 266 {l_shipdate} 225954 91 0 267 {l_suppkey} 225954 9920 0 268 ~~~~ 269 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 270 {l_discount} 259635.00 1.15 11.00 1.00 0.00 1.00 271 {l_extendedprice} 259635.00 1.15 230767.00 1.17 0.00 1.00 272 {l_shipdate} 259635.00 1.15 91.00 1.00 0.00 1.00 273 {l_suppkey} 259635.00 1.15 9920.00 1.00 0.00 1.00 274 275 stats table=q15_scalar_group_by_10 276 ---- 277 column_names row_count distinct_count null_count 278 {max} 1 1 0 279 ~~~~ 280 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 281 {max} 1.00 1.00 1.00 1.00 0.00 1.00 282 283 stats table=q15_group_by_11 284 ---- 285 column_names row_count distinct_count null_count 286 {l_suppkey} 10000 9920 0 287 {sum} 10000 10011 0 288 ~~~~ 289 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 290 {l_suppkey} 9920.00 1.01 9920.00 1.00 0.00 1.00 291 {sum} 9920.00 1.01 9920.00 1.01 0.00 1.00 292 293 stats table=q15_project_12 294 ---- 295 column_names row_count distinct_count null_count 296 {column42} 225954 220864 0 297 {l_suppkey} 225954 9920 0 298 ~~~~ 299 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 300 {column42} 259635.00 1.15 259635.00 1.18 0.00 1.00 301 {l_suppkey} 259635.00 1.15 9920.00 1.00 0.00 1.00 302 303 stats table=q15_index_join_13 304 ---- 305 column_names row_count distinct_count null_count 306 {l_discount} 225954 11 0 307 {l_extendedprice} 225954 196692 0 308 {l_shipdate} 225954 91 0 309 {l_suppkey} 225954 9920 0 310 ~~~~ 311 column_names row_count_est row_count_err distinct_count_est distinct_count_err null_count_est null_count_err 312 {l_discount} 259635.00 1.15 11.00 1.00 0.00 1.00 313 {l_extendedprice} 259635.00 1.15 230767.00 1.17 0.00 1.00 314 {l_shipdate} 259635.00 1.15 91.00 1.00 0.00 1.00 315 {l_suppkey} 259635.00 1.15 9920.00 1.00 0.00 1.00