import file=tpch_schema
----

import file=tpch_stats
----

# --------------------------------------------------
# Q2
# Minimum Cost Supplier
# Finds which supplier should be selected to place an order for a given part in
# a given region.
#
# Finds, in a given region, for each part of a certain type and size, the
# supplier who can supply it at minimum cost. If several suppliers in that
# region offer the desired part type and size at the same (minimum) cost, the
# query lists the parts from suppliers with the 100 highest account balances.
# For each supplier, the query lists the supplier's account balance, name and
# nation; the part's number and manufacturer; the supplier's address, phone
# number and comment information.
#
# TODO:
#   1. Allow Select to be pushed below Ordinality used to add key column
#   2. Add decorrelation rule for Ordinality/RowKey
# --------------------------------------------------
stats-quality database=tpch set=save_tables_prefix=q2
SELECT
    s_acctbal,
    s_name,
    n_name,
    p_partkey,
    p_mfgr,
    s_address,
    s_phone,
    s_comment
FROM
    part,
    supplier,
    partsupp,
    nation,
    region
WHERE
    p_partkey = ps_partkey
    AND s_suppkey = ps_suppkey
    AND p_size = 15
    AND p_type LIKE '%BRASS'
    AND s_nationkey = n_nationkey
    AND n_regionkey = r_regionkey
    AND r_name = 'EUROPE'
    AND ps_supplycost = (
        SELECT
            min(ps_supplycost)
        FROM
            partsupp,
            supplier,
            nation,
            region
        WHERE
            p_partkey = ps_partkey
            AND s_suppkey = ps_suppkey
            AND s_nationkey = n_nationkey
            AND n_regionkey = r_regionkey
            AND r_name = 'EUROPE'
    )
ORDER BY
    s_acctbal DESC,
    n_name,
    s_name,
    p_partkey
LIMIT 100;
----
----
project
 ├── save-table-name: q2_project_1
 ├── columns: s_acctbal:17(float!null) s_name:13(char!null) n_name:29(char!null) p_partkey:1(int!null) p_mfgr:3(char!null) s_address:14(varchar!null) s_phone:16(char!null) s_comment:18(varchar!null)
 ├── cardinality: [0 - 100]
 ├── stats: [rows=1.000013, distinct(1)=1, null(1)=0, distinct(3)=0.906664, null(3)=0, distinct(13)=0.632263, null(13)=0, distinct(14)=0.632263, null(14)=0, distinct(16)=0.632263, null(16)=0, distinct(17)=0.632263, null(17)=0, distinct(18)=0.632263, null(18)=0, distinct(29)=0.632263, null(29)=0]
 ├── fd: (1)-->(3)
 ├── ordering: -17,+29,+13,+1
 └── limit
      ├── save-table-name: q2_limit_2
      ├── columns: p_partkey:1(int!null) p_mfgr:3(char!null) p_type:5(varchar!null) p_size:6(int!null) s_name:13(char!null) s_address:14(varchar!null) s_phone:16(char!null) s_acctbal:17(float!null) s_comment:18(varchar!null) ps_partkey:21(int!null) ps_suppkey:22(int!null) ps_supplycost:24(float!null) n_name:29(char!null) min:66(float!null)
      ├── internal-ordering: -17,+29,+13,+(1|21) opt(6)
      ├── cardinality: [0 - 100]
      ├── stats: [rows=1.000013, distinct(1)=1, null(1)=0, distinct(3)=0.906664, null(3)=0, distinct(5)=0.99706, null(5)=0, distinct(6)=0.632263, null(6)=0, distinct(13)=0.632263, null(13)=0, distinct(14)=0.632263, null(14)=0, distinct(16)=0.632263, null(16)=0, distinct(17)=0.632263, null(17)=0, distinct(18)=0.632263, null(18)=0, distinct(21)=1, null(21)=0, distinct(22)=0.632251, null(22)=0, distinct(24)=0.632263, null(24)=0, distinct(29)=0.632263, null(29)=0, distinct(66)=0.632263, null(66)=0]
      ├── key: (21,22)
      ├── fd: ()-->(6), (1)-->(3,5), (21,22)-->(13,14,16-18,24,29,66), (22)-->(13,14,16-18,29), (24)==(66), (66)==(24), (1)==(21), (21)==(1)
      ├── ordering: -17,+29,+13,+(1|21) opt(6) [actual: -17,+29,+13,+21]
      ├── inner-join (lookup part)
      │    ├── save-table-name: q2_lookup_join_3
      │    ├── columns: p_partkey:1(int!null) p_mfgr:3(char!null) p_type:5(varchar!null) p_size:6(int!null) s_name:13(char!null) s_address:14(varchar!null) s_phone:16(char!null) s_acctbal:17(float!null) s_comment:18(varchar!null) ps_partkey:21(int!null) ps_suppkey:22(int!null) ps_supplycost:24(float!null) n_name:29(char!null) min:66(float!null)
      │    ├── key columns: [21] = [1]
      │    ├── lookup columns are key
      │    ├── stats: [rows=1.000013, distinct(1)=1, null(1)=0, distinct(3)=0.906664, null(3)=0, distinct(5)=0.99706, null(5)=0, distinct(6)=0.632263, null(6)=0, distinct(13)=0.632263, null(13)=0, distinct(14)=0.632263, null(14)=0, distinct(16)=0.632263, null(16)=0, distinct(17)=0.632263, null(17)=0, distinct(18)=0.632263, null(18)=0, distinct(21)=1, null(21)=0, distinct(22)=0.632251, null(22)=0, distinct(24)=0.632263, null(24)=0, distinct(29)=0.632263, null(29)=0, distinct(66)=0.632263, null(66)=0]
      │    ├── key: (21,22)
      │    ├── fd: ()-->(6), (1)-->(3,5), (21,22)-->(13,14,16-18,24,29,66), (22)-->(13,14,16-18,29), (24)==(66), (66)==(24), (1)==(21), (21)==(1)
      │    ├── ordering: -17,+29,+13,+(1|21) opt(6) [actual: -17,+29,+13,+21]
      │    ├── limit hint: 100.00
      │    ├── sort
      │    │    ├── save-table-name: q2_sort_4
      │    │    ├── columns: s_name:13(char!null) s_address:14(varchar!null) s_phone:16(char!null) s_acctbal:17(float!null) s_comment:18(varchar!null) ps_partkey:21(int!null) ps_suppkey:22(int!null) ps_supplycost:24(float!null) n_name:29(char!null) min:66(float!null)
      │    │    ├── stats: [rows=1, distinct(13)=1, null(13)=0, distinct(14)=1, null(14)=0, distinct(16)=1, null(16)=0, distinct(17)=1, null(17)=0, distinct(18)=1, null(18)=0, distinct(21)=1, null(21)=0, distinct(22)=0.999954, null(22)=0, distinct(24)=1, null(24)=0, distinct(29)=1, null(29)=0, distinct(66)=1, null(66)=0]
      │    │    ├── key: (21,22)
      │    │    ├── fd: (21,22)-->(13,14,16-18,24,29,66), (22)-->(13,14,16-18,29), (24)==(66), (66)==(24)
      │    │    ├── ordering: -17,+29,+13,+21
      │    │    └── select
      │    │         ├── save-table-name: q2_select_5
      │    │         ├── columns: s_name:13(char!null) s_address:14(varchar!null) s_phone:16(char!null) s_acctbal:17(float!null) s_comment:18(varchar!null) ps_partkey:21(int!null) ps_suppkey:22(int!null) ps_supplycost:24(float!null) n_name:29(char!null) min:66(float!null)
      │    │         ├── stats: [rows=1, distinct(13)=1, null(13)=0, distinct(14)=1, null(14)=0, distinct(16)=1, null(16)=0, distinct(17)=1, null(17)=0, distinct(18)=1, null(18)=0, distinct(21)=1, null(21)=0, distinct(22)=0.999954, null(22)=0, distinct(24)=1, null(24)=0, distinct(29)=1, null(29)=0, distinct(66)=1, null(66)=0]
      │    │         ├── key: (21,22)
      │    │         ├── fd: (21,22)-->(13,14,16-18,24,29,66), (22)-->(13,14,16-18,29), (24)==(66), (66)==(24)
      │    │         ├── group-by (hash)
      │    │         │    ├── save-table-name: q2_group_by_6
      │    │         │    ├── columns: s_name:13(char!null) s_address:14(varchar!null) s_phone:16(char!null) s_acctbal:17(float!null) s_comment:18(varchar!null) ps_partkey:21(int!null) ps_suppkey:22(int!null) ps_supplycost:24(float!null) n_name:29(char!null) min:66(float!null)
      │    │         │    ├── grouping columns: ps_partkey:21(int!null) ps_suppkey:22(int!null)
      │    │         │    ├── stats: [rows=113913.7, distinct(13)=113914, null(13)=0, distinct(14)=113914, null(14)=0, distinct(16)=113914, null(16)=0, distinct(17)=113914, null(17)=0, distinct(18)=113914, null(18)=0, distinct(21)=110568, null(21)=0, distinct(22)=9920, null(22)=0, distinct(24)=113914, null(24)=0, distinct(29)=113914, null(29)=0, distinct(66)=113914, null(66)=0, distinct(21,22)=113914, null(21,22)=0]
      │    │         │    ├── key: (21,22)
      │    │         │    ├── fd: (21,22)-->(13,14,16-18,24,29,66), (22)-->(13,14,16-18,29)
      │    │         │    ├── inner-join (hash)
      │    │         │    │    ├── save-table-name: q2_inner_join_7
      │    │         │    │    ├── columns: s_suppkey:12(int!null) s_name:13(char!null) s_address:14(varchar!null) s_nationkey:15(int!null) s_phone:16(char!null) s_acctbal:17(float!null) s_comment:18(varchar!null) ps_partkey:21(int!null) ps_suppkey:22(int!null) ps_supplycost:24(float!null) n_nationkey:28(int!null) n_name:29(char!null) n_regionkey:30(int!null) r_regionkey:34(int!null) r_name:35(char!null) ps_partkey:39(int!null) ps_suppkey:40(int!null) ps_supplycost:42(float!null) s_suppkey:46(int!null) s_nationkey:49(int!null) n_nationkey:55(int!null) n_regionkey:57(int!null) r_regionkey:61(int!null) r_name:62(char!null)
      │    │         │    │    ├── stats: [rows=233690.5, distinct(12)=9920, null(12)=0, distinct(13)=9990, null(13)=0, distinct(14)=10000, null(14)=0, distinct(15)=5, null(15)=0, distinct(16)=10000, null(16)=0, distinct(17)=9967, null(17)=0, distinct(18)=9934, null(18)=0, distinct(21)=110568, null(21)=0, distinct(22)=9920, null(22)=0, distinct(24)=76388.7, null(24)=0, distinct(28)=5, null(28)=0, distinct(29)=5, null(29)=0, distinct(30)=1, null(30)=0, distinct(34)=1, null(34)=0, distinct(35)=0.996222, null(35)=0, distinct(39)=110568, null(39)=0, distinct(40)=1844.81, null(40)=0, distinct(42)=75888.9, null(42)=0, distinct(46)=1844.81, null(46)=0, distinct(49)=5, null(49)=0, distinct(55)=5, null(55)=0, distinct(57)=1, null(57)=0, distinct(61)=1, null(61)=0, distinct(62)=0.996222, null(62)=0, distinct(21,22)=113914, null(21,22)=0]
      │    │         │    │    ├── key: (22,39,46)
      │    │         │    │    ├── fd: ()-->(35,62), (12)-->(13-18), (21,22)-->(24), (28)-->(29,30), (39,40)-->(42), (46)-->(49), (55)-->(57), (12)==(22), (22)==(12), (30)==(34), (34)==(30), (15)==(28), (28)==(15), (57)==(61), (61)==(57), (49)==(55), (55)==(49), (40)==(46), (46)==(40), (21)==(39), (39)==(21)
      │    │         │    │    ├── inner-join (hash)
      │    │         │    │    │    ├── save-table-name: q2_inner_join_8
      │    │         │    │    │    ├── columns: s_suppkey:12(int!null) s_name:13(char!null) s_address:14(varchar!null) s_nationkey:15(int!null) s_phone:16(char!null) s_acctbal:17(float!null) s_comment:18(varchar!null) ps_partkey:21(int!null) ps_suppkey:22(int!null) ps_supplycost:24(float!null) n_nationkey:28(int!null) n_name:29(char!null) n_regionkey:30(int!null) r_regionkey:34(int!null) r_name:35(char!null)
      │    │         │    │    │    ├── multiplicity: left-rows(zero-or-one), right-rows(zero-or-more)
      │    │         │    │    │    ├── stats: [rows=161290.3, distinct(12)=9920, null(12)=0, distinct(13)=9990, null(13)=0, distinct(14)=10000, null(14)=0, distinct(15)=5, null(15)=0, distinct(16)=10000, null(16)=0, distinct(17)=9967, null(17)=0, distinct(18)=9934, null(18)=0, distinct(21)=111321, null(21)=0, distinct(22)=9920, null(22)=0, distinct(24)=80888.4, null(24)=0, distinct(28)=5, null(28)=0, distinct(29)=5, null(29)=0, distinct(30)=1, null(30)=0, distinct(34)=1, null(34)=0, distinct(35)=0.996222, null(35)=0, distinct(21,22)=140582, null(21,22)=0]
      │    │         │    │    │    ├── key: (21,22)
      │    │         │    │    │    ├── fd: ()-->(35), (12)-->(13-18), (21,22)-->(24), (28)-->(29,30), (12)==(22), (22)==(12), (30)==(34), (34)==(30), (15)==(28), (28)==(15)
      │    │         │    │    │    ├── scan partsupp
      │    │         │    │    │    │    ├── save-table-name: q2_scan_9
      │    │         │    │    │    │    ├── columns: ps_partkey:21(int!null) ps_suppkey:22(int!null) ps_supplycost:24(float!null)
      │    │         │    │    │    │    ├── stats: [rows=800000, distinct(21)=199241, null(21)=0, distinct(22)=9920, null(22)=0, distinct(24)=100379, null(24)=0, distinct(21,22)=798302, null(21,22)=0]
      │    │         │    │    │    │    │   histogram(21)=  0 79.993 3912.7 79.993 3933.7 79.993 3920.7 79.993 3917.7 79.993 3929.7 79.993 3912.7 79.993 3932.7 79.993 3918.7 158.99 3914.7 79.993 3928.7 79.993  3910.7 79.993  3904.7 79.993  3924.7 79.993  3914.7 79.993  3909.7 79.993  3917.7 79.993  3926.7 79.993  3913.7 79.993  3905.7 79.993  3912.7 79.993  3931.7 79.993  3926.7 79.993  3926.7 79.993  3906.7 79.993  3923.7 79.993  3904.7 79.993  3904.7 79.993  3907.7 158.99  3979.6 79.993  3906.7 79.993  3914.7 79.993  3918.7 79.993  3917.7 79.993  3826.7 158.99  3936.7 79.993  3908.7 79.993  3926.7 79.993  3930.7 79.993  3967.6 79.993  3910.7 79.993  3922.7 79.993  3914.7 79.993  3913.7 79.993  3915.7 79.993  3919.7 79.993  3916.7 79.993  3920.7 79.993  3926.7 79.993  3908.7 79.993  3904.7 158.99  3926.7 79.993  3922.7 79.993  3918.7 79.993  3908.7 79.993  3919.7 79.993  3908.7 79.993  3907.7 79.993  3916.7 79.993  3917.7 79.993  3905.7 79.993  3918.7 79.993  3940.7 79.993  3916.7 79.993  3923.7 79.993  3909.7 79.993  3915.7 79.993  3911.7 79.993  3915.7 79.993  3914.7 79.993  3948.6 79.993  3924.7 79.993  3916.7 79.993  3943.7 79.993  3933.7 79.993  3915.7 79.993  3916.7 79.993  3914.7 79.993  3919.7 79.993  3916.7 79.993  3912.7 79.993  3904.7 79.993  3913.7 79.993  3909.7 79.993  3914.7 79.993  3910.7 79.993  3923.7 79.993  3913.7 79.993  3914.7 79.993  3921.7 79.993  3927.7 79.993  3921.7 79.993  3924.7 158.99  3910.7 79.993  3916.7 79.993  3949.6 79.993  3922.7 79.993  3915.7 79.993  3942.7 79.993  3915.7 79.993  3917.7 79.993  3842.7  158.99  3911.7  79.993  3923.7  79.993  3923.7  79.993  3906.7  79.993  3925.7  79.993  3951.6  79.993  3933.7  79.993  3916.7  79.993  3903.7  79.993  3923.7  79.993  3932.7  79.993  3928.7  79.993  3905.7  79.993  3921.7  79.993  3920.7  79.993  3910.7  79.993  3912.7  79.993  3916.7  79.993  3922.7  79.993  3911.7  79.993  3906.7  79.993  3921.7  79.993  3911.7  79.993  3911.7  79.993  3926.7  79.993  3912.7  79.993  3945.6  79.993  3910.7  79.993  3922.7  79.993  3918.7  79.993  3911.7  79.993  3917.7  79.993  3945.6  79.993  3926.7  79.993  3926.7  79.993  3917.7  79.993  3904.7  79.993  3925.7  79.993  3912.7  79.993  3912.7  79.993  3954.6  79.993  3915.7  79.993  3912.7  79.993  3910.7  79.993  3909.7  79.993  3911.7  79.993  3903.7  79.993  3915.7  79.993  3949.6  79.993  3923.7  79.993  3921.7  79.993  3909.7  79.993  3905.7  79.993  3988.6  79.993  3988.6  79.993  3999.6  79.993  4003.6  79.993  3998.6  79.993  4021.6  79.993  4027.6  79.993  4005.6  79.993  3999.6  79.993  3997.6  79.993  3988.6  79.993  3989.6  79.993  4004.6  79.993  3984.6  79.993  3999.6  79.993  3999.6  79.993  4019.6  79.993  4011.6  79.993  4020.6  79.993  4012.6  79.993  3996.6  79.993  4029.6  79.993  4004.6  158.99  3912.7  79.993  3995.6  79.993  3989.6  79.993  3991.6  79.993  3986.6  79.993  3986.6  79.993  4006.6  79.993  3988.6  79.993  3989.6  79.993  3989.6  79.993  3998.6  79.993  4012.6  79.993  4017.6  79.993  4017.6  79.993  3996.6  79.993  3994.6  79.993  4009.6  79.993  3995.6  79.993  3996.6  79.993  3991.6  79.993  4006.6  79.993  4020.6  79.993
      │    │         │    │    │    │    │                 <---- 13 --------- 942 --------- 2097 -------- 3127 -------- 4125 -------- 5247 -------- 6181 -------- 7326 -------- 8333 -------- 9292 -------- 10410 -------- 11308 -------- 12057 -------- 13131 -------- 14088 -------- 14972 -------- 15975 -------- 17072 -------- 18019 -------- 18798 -------- 19734 -------- 20877 -------- 21973 -------- 23067 -------- 23887 -------- 24957 -------- 25716 -------- 26450 -------- 27291 -------- 28733 -------- 29539 -------- 30499 -------- 31512 -------- 32509 -------- 33286 -------- 34464 -------- 35311 -------- 36406 -------- 37541 -------- 38918 -------- 39818 -------- 40879 -------- 41843 -------- 42789 -------- 43757 -------- 44778 -------- 45769 -------- 46806 -------- 47899 -------- 48763 -------- 49507 -------- 50607 -------- 51663 -------- 52669 -------- 53525 -------- 54549 -------- 55415 -------- 56261 -------- 57242 -------- 58242 -------- 59036 -------- 60050 -------- 61259 -------- 62240 -------- 63307 -------- 64178 -------- 65152 -------- 66063 -------- 67040 -------- 68005 -------- 69273 -------- 70354 -------- 71339 -------- 72569 -------- 73724 -------- 74695 -------- 75684 -------- 76646 -------- 77670 -------- 78657 -------- 79587 -------- 80331 -------- 81281 -------- 82150 -------- 83115 -------- 84014 -------- 85082 -------- 86031 -------- 86990 -------- 88034 -------- 89138 -------- 90187 -------- 91260 -------- 92150 -------- 93140 -------- 94413 -------- 95469 -------- 96443 -------- 97666 -------- 98637 -------- 99633 -------- 100664 -------- 101572 -------- 102643 -------- 103706 -------- 104522 -------- 105605 -------- 106892 -------- 108047 -------- 109036 -------- 109721 -------- 110790 -------- 111938 -------- 113052 -------- 113830 -------- 114873 -------- 115912 -------- 116814 -------- 117737 -------- 118721 -------- 119776 -------- 120692 -------- 121500 -------- 122545 -------- 123457 -------- 124366 -------- 125466 -------- 126391 -------- 127638 -------- 128533 -------- 129586 -------- 130602 -------- 131508 -------- 132509 -------- 133756 -------- 134848 -------- 135944 -------- 136945 -------- 137706 -------- 138791 -------- 139720 -------- 140657 -------- 141959 -------- 142929 -------- 143854 -------- 144743 -------- 145629 -------- 146548 -------- 147238 -------- 148209 -------- 149481 -------- 150548 -------- 151598 -------- 152481 -------- 153250 -------- 154137 -------- 155017 -------- 156060 -------- 157143 -------- 158169 -------- 159406 -------- 160686 -------- 161794 -------- 162837 -------- 163860 -------- 164730 -------- 165623 -------- 166716 -------- 167485 -------- 168526 -------- 169568 -------- 170793 -------- 171958 -------- 173192 -------- 174365 -------- 175367 -------- 176660 -------- 177754 -------- 178681 -------- 179672 -------- 180568 -------- 181502 -------- 182344 -------- 183171 -------- 184286 -------- 185174 -------- 186068 -------- 186966 -------- 187997 -------- 189168 -------- 190375 -------- 191583 -------- 192588 -------- 193575 -------- 194722 -------- 195713 -------- 196725 -------- 197653 -------- 198767 -------- 199999
      │    │         │    │    │    │    │   histogram(22)=  0 160 3920 160  3920  80   3920  160  3920  160  3920  240  3760  240  3920  80   3840  240  3920  240  3840  320  3760  240  3920  80   3840  160  3920  240  3920  320  3920  80   3920  80   3920  80   3840  160  3920  240   3760  240   3920   80   3840  160   3920   80   3920  160   3920   80   3920  160   3920   80   3920  160   3920   80   3760  240   3840  240   3920   80   3920   80   3840  240   3760  240   3920   80   3840  160   3840  160   3920   80   3920   80   3920  160   3760  240   3920  240   3920   80   3920  160   3920   80   3840  160   3920  160   3920   80   3840  160   3840  240   3920  160   3840  160   3920  160   3920   80   3840  160   3920  160   3840  160   3840  160   3920   80   3920  160   3920  160   3920   80   3920   80   3840  160   3840  160   3840  160   3920   80   3920   80   3840  240   3840  160   3920  320   3840  160   3840  240   3920   80   3920   80   3760  240   3840  160   3920  160   3920   80   3840  240   3920   80   3920   80   3920  160   3920   80   3920   80   3920   80   3920   80   3840  160   3920   80   3920  160   3760  320   3920   80   3920   80   3840  160   3920  240   3920   80   3920   80   3920   80   3920  160   3840  160   3760  400   3760  240   3680  320   3840  240   3840   80   3840  160   3840  160   3920   80   3920   80   3920   80   3840  160   3920   80   3760  240   3920   80   3840  240   3840   80   3840  160   3920  240   3840   80   3840   80   3840  160   3920   80   3760  240   3920   80   3920  160   3840  160   3760  240   3760  240   3840   80   3920  160   3840   80   3920   80   3920   80   3840  400   3760  160   3840   80   3840  160   3760  160   3840  240   3840  160   3680  320   3760  160   3920   80   3920   80   3920   80   3920   80   3920   80   3840  160   3760  240   3840  160   3920   80   3840  160   3920  240   3840  160   3840   80   3840  160   3840   80   3920   80   3920   80   3920  160   3840  160   3840  160   3840  160   3760  160   3920   80   3920   80   3920   80   3920   80   3760  240   3920   80   3920  320   3760  160   3840   80   3840   80   3920  160   3840   80   3920  160   3760  160   3920   80   3920   80   3920  160   3840  160   3840   80   3840  160   3920   80   3920   80   3920   80   3840  160   3840  240   3840  160   3840   80   3920   80   3840  240   3840   80   3920   80   3920   80   3840   160
      │    │         │    │    │    │    │                 <--- 2 ------ 50 ------ 104 ------ 153 ------ 213 ------ 281 ------ 320 ------ 366 ------ 411 ------ 462 ------ 515 ------ 548 ------ 600 ------ 649 ------ 697 ------ 743 ------ 793 ------ 845 ------ 893 ------ 953 ------ 1006 ------ 1052 ------ 1103 ------ 1158 ------ 1199 ------ 1246 ------ 1302 ------ 1375 ------ 1418 ------ 1475 ------ 1524 ------ 1563 ------ 1628 ------ 1689 ------ 1740 ------ 1799 ------ 1850 ------ 1901 ------ 1948 ------ 2017 ------ 2055 ------ 2099 ------ 2157 ------ 2214 ------ 2267 ------ 2319 ------ 2373 ------ 2428 ------ 2478 ------ 2546 ------ 2602 ------ 2657 ------ 2707 ------ 2760 ------ 2808 ------ 2852 ------ 2913 ------ 2968 ------ 3030 ------ 3069 ------ 3115 ------ 3165 ------ 3210 ------ 3256 ------ 3306 ------ 3365 ------ 3419 ------ 3469 ------ 3523 ------ 3576 ------ 3641 ------ 3694 ------ 3738 ------ 3806 ------ 3851 ------ 3900 ------ 3957 ------ 4004 ------ 4050 ------ 4095 ------ 4145 ------ 4201 ------ 4251 ------ 4293 ------ 4335 ------ 4380 ------ 4432 ------ 4484 ------ 4541 ------ 4593 ------ 4650 ------ 4706 ------ 4744 ------ 4804 ------ 4845 ------ 4897 ------ 4945 ------ 4992 ------ 5044 ------ 5108 ------ 5160 ------ 5207 ------ 5261 ------ 5319 ------ 5358 ------ 5404 ------ 5450 ------ 5490 ------ 5538 ------ 5590 ------ 5639 ------ 5686 ------ 5742 ------ 5788 ------ 5837 ------ 5884 ------ 5940 ------ 5985 ------ 6037 ------ 6090 ------ 6135 ------ 6185 ------ 6228 ------ 6271 ------ 6323 ------ 6376 ------ 6434 ------ 6474 ------ 6527 ------ 6586 ------ 6633 ------ 6674 ------ 6711 ------ 6751 ------ 6797 ------ 6835 ------ 6880 ------ 6918 ------ 6982 ------ 7026 ------ 7069 ------ 7123 ------ 7179 ------ 7238 ------ 7287 ------ 7336 ------ 7388 ------ 7438 ------ 7480 ------ 7528 ------ 7574 ------ 7620 ------ 7664 ------ 7706 ------ 7755 ------ 7805 ------ 7847 ------ 7896 ------ 7954 ------ 8014 ------ 8064 ------ 8108 ------ 8159 ------ 8207 ------ 8250 ------ 8304 ------ 8361 ------ 8410 ------ 8462 ------ 8513 ------ 8562 ------ 8608 ------ 8644 ------ 8706 ------ 8752 ------ 8799 ------ 8840 ------ 8902 ------ 8954 ------ 8995 ------ 9063 ------ 9106 ------ 9152 ------ 9202 ------ 9256 ------ 9310 ------ 9362 ------ 9409 ------ 9462 ------ 9504 ------ 9551 ------ 9598 ------ 9644 ------ 9689 ------ 9741 ------ 9800 ------ 9855 ------ 9896 ------ 9945 ------ 10000
      │    │         │    │    │    │    │   histogram(24)=  0   80   7.9984e+05    80
      │    │         │    │    │    │    │                 <--- 1.14 ------------ 999.93
      │    │         │    │    │    │    ├── key: (21,22)
      │    │         │    │    │    │    └── fd: (21,22)-->(24)
      │    │         │    │    │    ├── inner-join (hash)
      │    │         │    │    │    │    ├── save-table-name: q2_inner_join_10
      │    │         │    │    │    │    ├── columns: s_suppkey:12(int!null) s_name:13(char!null) s_address:14(varchar!null) s_nationkey:15(int!null) s_phone:16(char!null) s_acctbal:17(float!null) s_comment:18(varchar!null) n_nationkey:28(int!null) n_name:29(char!null) n_regionkey:30(int!null) r_regionkey:34(int!null) r_name:35(char!null)
      │    │         │    │    │    │    ├── multiplicity: left-rows(zero-or-one), right-rows(zero-or-more)
      │    │         │    │    │    │    ├── stats: [rows=2000, distinct(12)=1844.81, null(12)=0, distinct(13)=1846.09, null(13)=0, distinct(14)=1846.27, null(14)=0, distinct(15)=5, null(15)=0, distinct(16)=1846.27, null(16)=0, distinct(17)=1845.67, null(17)=0, distinct(18)=1845.06, null(18)=0, distinct(28)=5, null(28)=0, distinct(29)=5, null(29)=0, distinct(30)=1, null(30)=0, distinct(34)=1, null(34)=0, distinct(35)=0.996222, null(35)=0]
      │    │         │    │    │    │    ├── key: (12)
      │    │         │    │    │    │    ├── fd: ()-->(35), (12)-->(13-18), (28)-->(29,30), (30)==(34), (34)==(30), (15)==(28), (28)==(15)
      │    │         │    │    │    │    ├── scan supplier
      │    │         │    │    │    │    │    ├── save-table-name: q2_scan_11
      │    │         │    │    │    │    │    ├── columns: s_suppkey:12(int!null) s_name:13(char!null) s_address:14(varchar!null) s_nationkey:15(int!null) s_phone:16(char!null) s_acctbal:17(float!null) s_comment:18(varchar!null)
      │    │         │    │    │    │    │    ├── stats: [rows=10000, distinct(12)=9920, null(12)=0, distinct(13)=9990, null(13)=0, distinct(14)=10000, null(14)=0, distinct(15)=25, null(15)=0, distinct(16)=10000, null(16)=0, distinct(17)=9967, null(17)=0, distinct(18)=9934, null(18)=0]
      │    │         │    │    │    │    │    │   histogram(12)=  0           0            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    0           0
      │    │         │    │    │    │    │    │                 <--- -9223372036854775808 --- 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 --- 9223372036854775807
      │    │         │    │    │    │    │    │   histogram(13)=  0           1            9998           1
      │    │         │    │    │    │    │    │                 <--- 'Supplier#000000001' ------ 'Supplier#000010000'
      │    │         │    │    │    │    │    │   histogram(14)=  0                     1                     9998                1
      │    │         │    │    │    │    │    │                 <--- '  9aW1wwnBJJPnCx,nox0MA48Y0zpI1IeVfYZ' ------ 'zzfDhdtZcvmVzA8rNFU,Yctj1zBN'
      │    │         │    │    │    │    │    │   histogram(15)=  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
      │    │         │    │    │    │    │    │                 <--- 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
      │    │         │    │    │    │    │    │   histogram(16)=  0          1          9998          1
      │    │         │    │    │    │    │    │                 <--- '10-102-116-6785' ------ '34-998-900-4911'
      │    │         │    │    │    │    │    │   histogram(17)=  0     1     9998     1
      │    │         │    │    │    │    │    │                 <--- -998.22 ------ 9999.72
      │    │         │    │    │    │    │    │   histogram(18)=  0                     1                      9998                                   1
      │    │         │    │    │    │    │    │                 <--- ' about the blithely express foxes. bli' ------ 'zzle furiously. bold accounts haggle furiously ironic excuses. fur'
      │    │         │    │    │    │    │    ├── key: (12)
      │    │         │    │    │    │    │    └── fd: (12)-->(13-18)
      │    │         │    │    │    │    ├── inner-join (hash)
      │    │         │    │    │    │    │    ├── save-table-name: q2_inner_join_12
      │    │         │    │    │    │    │    ├── columns: n_nationkey:28(int!null) n_name:29(char!null) n_regionkey:30(int!null) r_regionkey:34(int!null) r_name:35(char!null)
      │    │         │    │    │    │    │    ├── multiplicity: left-rows(zero-or-one), right-rows(zero-or-more)
      │    │         │    │    │    │    │    ├── stats: [rows=5, distinct(28)=5, null(28)=0, distinct(29)=5, null(29)=0, distinct(30)=1, null(30)=0, distinct(34)=1, null(34)=0, distinct(35)=0.996222, null(35)=0]
      │    │         │    │    │    │    │    ├── key: (28)
      │    │         │    │    │    │    │    ├── fd: ()-->(35), (28)-->(29,30), (30)==(34), (34)==(30)
      │    │         │    │    │    │    │    ├── scan nation
      │    │         │    │    │    │    │    │    ├── save-table-name: q2_scan_13
      │    │         │    │    │    │    │    │    ├── columns: n_nationkey:28(int!null) n_name:29(char!null) n_regionkey:30(int!null)
      │    │         │    │    │    │    │    │    ├── stats: [rows=25, distinct(28)=25, null(28)=0, distinct(29)=25, null(29)=0, distinct(30)=5, null(30)=0]
      │    │         │    │    │    │    │    │    │   histogram(28)=  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
      │    │         │    │    │    │    │    │    │                 <--- 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
      │    │         │    │    │    │    │    │    │   histogram(29)=  0      1      23      1
      │    │         │    │    │    │    │    │    │                 <--- 'ALGERIA' ---- 'VIETNAM'
      │    │         │    │    │    │    │    │    │   histogram(30)=  0  5  0  5  0  5  0  5  0  5
      │    │         │    │    │    │    │    │    │                 <--- 0 --- 1 --- 2 --- 3 --- 4
      │    │         │    │    │    │    │    │    ├── key: (28)
      │    │         │    │    │    │    │    │    └── fd: (28)-->(29,30)
      │    │         │    │    │    │    │    ├── select
      │    │         │    │    │    │    │    │    ├── save-table-name: q2_select_14
      │    │         │    │    │    │    │    │    ├── columns: r_regionkey:34(int!null) r_name:35(char!null)
      │    │         │    │    │    │    │    │    ├── stats: [rows=1, distinct(34)=1, null(34)=0, distinct(35)=1, null(35)=0]
      │    │         │    │    │    │    │    │    │   histogram(35)=  0     1
      │    │         │    │    │    │    │    │    │                 <--- 'EUROPE'
      │    │         │    │    │    │    │    │    ├── key: (34)
      │    │         │    │    │    │    │    │    ├── fd: ()-->(35)
      │    │         │    │    │    │    │    │    ├── scan region
      │    │         │    │    │    │    │    │    │    ├── save-table-name: q2_scan_15
      │    │         │    │    │    │    │    │    │    ├── columns: r_regionkey:34(int!null) r_name:35(char!null)
      │    │         │    │    │    │    │    │    │    ├── stats: [rows=5, distinct(34)=5, null(34)=0, distinct(35)=5, null(35)=0]
      │    │         │    │    │    │    │    │    │    │   histogram(34)=  0  1  0  1  0  1  0  1  0  1
      │    │         │    │    │    │    │    │    │    │                 <--- 0 --- 1 --- 2 --- 3 --- 4
      │    │         │    │    │    │    │    │    │    │   histogram(35)=  0     1      3        1
      │    │         │    │    │    │    │    │    │    │                 <--- 'AFRICA' --- 'MIDDLE EAST'
      │    │         │    │    │    │    │    │    │    ├── key: (34)
      │    │         │    │    │    │    │    │    │    └── fd: (34)-->(35)
      │    │         │    │    │    │    │    │    └── filters
      │    │         │    │    │    │    │    │         └── r_name:35 = 'EUROPE' [type=bool, outer=(35), constraints=(/35: [/'EUROPE' - /'EUROPE']; tight), fd=()-->(35)]
      │    │         │    │    │    │    │    └── filters
      │    │         │    │    │    │    │         └── n_regionkey:30 = r_regionkey:34 [type=bool, outer=(30,34), constraints=(/30: (/NULL - ]; /34: (/NULL - ]), fd=(30)==(34), (34)==(30)]
      │    │         │    │    │    │    └── filters
      │    │         │    │    │    │         └── s_nationkey:15 = n_nationkey:28 [type=bool, outer=(15,28), constraints=(/15: (/NULL - ]; /28: (/NULL - ]), fd=(15)==(28), (28)==(15)]
      │    │         │    │    │    └── filters
      │    │         │    │    │         └── s_suppkey:12 = ps_suppkey:22 [type=bool, outer=(12,22), constraints=(/12: (/NULL - ]; /22: (/NULL - ]), fd=(12)==(22), (22)==(12)]
      │    │         │    │    ├── inner-join (hash)
      │    │         │    │    │    ├── save-table-name: q2_inner_join_16
      │    │         │    │    │    ├── columns: ps_partkey:39(int!null) ps_suppkey:40(int!null) ps_supplycost:42(float!null) s_suppkey:46(int!null) s_nationkey:49(int!null) n_nationkey:55(int!null) n_regionkey:57(int!null) r_regionkey:61(int!null) r_name:62(char!null)
      │    │         │    │    │    ├── multiplicity: left-rows(zero-or-one), right-rows(zero-or-more)
      │    │         │    │    │    ├── stats: [rows=161290.3, distinct(39)=110568, null(39)=0, distinct(40)=1844.81, null(40)=0, distinct(42)=80252.1, null(42)=0, distinct(46)=1844.81, null(46)=0, distinct(49)=5, null(49)=0, distinct(55)=5, null(55)=0, distinct(57)=1, null(57)=0, distinct(61)=1, null(61)=0, distinct(62)=0.996222, null(62)=0]
      │    │         │    │    │    ├── key: (39,46)
      │    │         │    │    │    ├── fd: ()-->(62), (39,40)-->(42), (46)-->(49), (55)-->(57), (57)==(61), (61)==(57), (49)==(55), (55)==(49), (40)==(46), (46)==(40)
      │    │         │    │    │    ├── scan partsupp
      │    │         │    │    │    │    ├── save-table-name: q2_scan_17
      │    │         │    │    │    │    ├── columns: ps_partkey:39(int!null) ps_suppkey:40(int!null) ps_supplycost:42(float!null)
      │    │         │    │    │    │    ├── stats: [rows=800000, distinct(39)=199241, null(39)=0, distinct(40)=9920, null(40)=0, distinct(42)=100379, null(42)=0]
      │    │         │    │    │    │    │   histogram(39)=  0 79.993 3912.7 79.993 3933.7 79.993 3920.7 79.993 3917.7 79.993 3929.7 79.993 3912.7 79.993 3932.7 79.993 3918.7 158.99 3914.7 79.993 3928.7 79.993  3910.7 79.993  3904.7 79.993  3924.7 79.993  3914.7 79.993  3909.7 79.993  3917.7 79.993  3926.7 79.993  3913.7 79.993  3905.7 79.993  3912.7 79.993  3931.7 79.993  3926.7 79.993  3926.7 79.993  3906.7 79.993  3923.7 79.993  3904.7 79.993  3904.7 79.993  3907.7 158.99  3979.6 79.993  3906.7 79.993  3914.7 79.993  3918.7 79.993  3917.7 79.993  3826.7 158.99  3936.7 79.993  3908.7 79.993  3926.7 79.993  3930.7 79.993  3967.6 79.993  3910.7 79.993  3922.7 79.993  3914.7 79.993  3913.7 79.993  3915.7 79.993  3919.7 79.993  3916.7 79.993  3920.7 79.993  3926.7 79.993  3908.7 79.993  3904.7 158.99  3926.7 79.993  3922.7 79.993  3918.7 79.993  3908.7 79.993  3919.7 79.993  3908.7 79.993  3907.7 79.993  3916.7 79.993  3917.7 79.993  3905.7 79.993  3918.7 79.993  3940.7 79.993  3916.7 79.993  3923.7 79.993  3909.7 79.993  3915.7 79.993  3911.7 79.993  3915.7 79.993  3914.7 79.993  3948.6 79.993  3924.7 79.993  3916.7 79.993  3943.7 79.993  3933.7 79.993  3915.7 79.993  3916.7 79.993  3914.7 79.993  3919.7 79.993  3916.7 79.993  3912.7 79.993  3904.7 79.993  3913.7 79.993  3909.7 79.993  3914.7 79.993  3910.7 79.993  3923.7 79.993  3913.7 79.993  3914.7 79.993  3921.7 79.993  3927.7 79.993  3921.7 79.993  3924.7 158.99  3910.7 79.993  3916.7 79.993  3949.6 79.993  3922.7 79.993  3915.7 79.993  3942.7 79.993  3915.7 79.993  3917.7 79.993  3842.7  158.99  3911.7  79.993  3923.7  79.993  3923.7  79.993  3906.7  79.993  3925.7  79.993  3951.6  79.993  3933.7  79.993  3916.7  79.993  3903.7  79.993  3923.7  79.993  3932.7  79.993  3928.7  79.993  3905.7  79.993  3921.7  79.993  3920.7  79.993  3910.7  79.993  3912.7  79.993  3916.7  79.993  3922.7  79.993  3911.7  79.993  3906.7  79.993  3921.7  79.993  3911.7  79.993  3911.7  79.993  3926.7  79.993  3912.7  79.993  3945.6  79.993  3910.7  79.993  3922.7  79.993  3918.7  79.993  3911.7  79.993  3917.7  79.993  3945.6  79.993  3926.7  79.993  3926.7  79.993  3917.7  79.993  3904.7  79.993  3925.7  79.993  3912.7  79.993  3912.7  79.993  3954.6  79.993  3915.7  79.993  3912.7  79.993  3910.7  79.993  3909.7  79.993  3911.7  79.993  3903.7  79.993  3915.7  79.993  3949.6  79.993  3923.7  79.993  3921.7  79.993  3909.7  79.993  3905.7  79.993  3988.6  79.993  3988.6  79.993  3999.6  79.993  4003.6  79.993  3998.6  79.993  4021.6  79.993  4027.6  79.993  4005.6  79.993  3999.6  79.993  3997.6  79.993  3988.6  79.993  3989.6  79.993  4004.6  79.993  3984.6  79.993  3999.6  79.993  3999.6  79.993  4019.6  79.993  4011.6  79.993  4020.6  79.993  4012.6  79.993  3996.6  79.993  4029.6  79.993  4004.6  158.99  3912.7  79.993  3995.6  79.993  3989.6  79.993  3991.6  79.993  3986.6  79.993  3986.6  79.993  4006.6  79.993  3988.6  79.993  3989.6  79.993  3989.6  79.993  3998.6  79.993  4012.6  79.993  4017.6  79.993  4017.6  79.993  3996.6  79.993  3994.6  79.993  4009.6  79.993  3995.6  79.993  3996.6  79.993  3991.6  79.993  4006.6  79.993  4020.6  79.993
      │    │         │    │    │    │    │                 <---- 13 --------- 942 --------- 2097 -------- 3127 -------- 4125 -------- 5247 -------- 6181 -------- 7326 -------- 8333 -------- 9292 -------- 10410 -------- 11308 -------- 12057 -------- 13131 -------- 14088 -------- 14972 -------- 15975 -------- 17072 -------- 18019 -------- 18798 -------- 19734 -------- 20877 -------- 21973 -------- 23067 -------- 23887 -------- 24957 -------- 25716 -------- 26450 -------- 27291 -------- 28733 -------- 29539 -------- 30499 -------- 31512 -------- 32509 -------- 33286 -------- 34464 -------- 35311 -------- 36406 -------- 37541 -------- 38918 -------- 39818 -------- 40879 -------- 41843 -------- 42789 -------- 43757 -------- 44778 -------- 45769 -------- 46806 -------- 47899 -------- 48763 -------- 49507 -------- 50607 -------- 51663 -------- 52669 -------- 53525 -------- 54549 -------- 55415 -------- 56261 -------- 57242 -------- 58242 -------- 59036 -------- 60050 -------- 61259 -------- 62240 -------- 63307 -------- 64178 -------- 65152 -------- 66063 -------- 67040 -------- 68005 -------- 69273 -------- 70354 -------- 71339 -------- 72569 -------- 73724 -------- 74695 -------- 75684 -------- 76646 -------- 77670 -------- 78657 -------- 79587 -------- 80331 -------- 81281 -------- 82150 -------- 83115 -------- 84014 -------- 85082 -------- 86031 -------- 86990 -------- 88034 -------- 89138 -------- 90187 -------- 91260 -------- 92150 -------- 93140 -------- 94413 -------- 95469 -------- 96443 -------- 97666 -------- 98637 -------- 99633 -------- 100664 -------- 101572 -------- 102643 -------- 103706 -------- 104522 -------- 105605 -------- 106892 -------- 108047 -------- 109036 -------- 109721 -------- 110790 -------- 111938 -------- 113052 -------- 113830 -------- 114873 -------- 115912 -------- 116814 -------- 117737 -------- 118721 -------- 119776 -------- 120692 -------- 121500 -------- 122545 -------- 123457 -------- 124366 -------- 125466 -------- 126391 -------- 127638 -------- 128533 -------- 129586 -------- 130602 -------- 131508 -------- 132509 -------- 133756 -------- 134848 -------- 135944 -------- 136945 -------- 137706 -------- 138791 -------- 139720 -------- 140657 -------- 141959 -------- 142929 -------- 143854 -------- 144743 -------- 145629 -------- 146548 -------- 147238 -------- 148209 -------- 149481 -------- 150548 -------- 151598 -------- 152481 -------- 153250 -------- 154137 -------- 155017 -------- 156060 -------- 157143 -------- 158169 -------- 159406 -------- 160686 -------- 161794 -------- 162837 -------- 163860 -------- 164730 -------- 165623 -------- 166716 -------- 167485 -------- 168526 -------- 169568 -------- 170793 -------- 171958 -------- 173192 -------- 174365 -------- 175367 -------- 176660 -------- 177754 -------- 178681 -------- 179672 -------- 180568 -------- 181502 -------- 182344 -------- 183171 -------- 184286 -------- 185174 -------- 186068 -------- 186966 -------- 187997 -------- 189168 -------- 190375 -------- 191583 -------- 192588 -------- 193575 -------- 194722 -------- 195713 -------- 196725 -------- 197653 -------- 198767 -------- 199999
      │    │         │    │    │    │    │   histogram(40)=  0 160 3920 160  3920  80   3920  160  3920  160  3920  240  3760  240  3920  80   3840  240  3920  240  3840  320  3760  240  3920  80   3840  160  3920  240  3920  320  3920  80   3920  80   3920  80   3840  160  3920  240   3760  240   3920   80   3840  160   3920   80   3920  160   3920   80   3920  160   3920   80   3920  160   3920   80   3760  240   3840  240   3920   80   3920   80   3840  240   3760  240   3920   80   3840  160   3840  160   3920   80   3920   80   3920  160   3760  240   3920  240   3920   80   3920  160   3920   80   3840  160   3920  160   3920   80   3840  160   3840  240   3920  160   3840  160   3920  160   3920   80   3840  160   3920  160   3840  160   3840  160   3920   80   3920  160   3920  160   3920   80   3920   80   3840  160   3840  160   3840  160   3920   80   3920   80   3840  240   3840  160   3920  320   3840  160   3840  240   3920   80   3920   80   3760  240   3840  160   3920  160   3920   80   3840  240   3920   80   3920   80   3920  160   3920   80   3920   80   3920   80   3920   80   3840  160   3920   80   3920  160   3760  320   3920   80   3920   80   3840  160   3920  240   3920   80   3920   80   3920   80   3920  160   3840  160   3760  400   3760  240   3680  320   3840  240   3840   80   3840  160   3840  160   3920   80   3920   80   3920   80   3840  160   3920   80   3760  240   3920   80   3840  240   3840   80   3840  160   3920  240   3840   80   3840   80   3840  160   3920   80   3760  240   3920   80   3920  160   3840  160   3760  240   3760  240   3840   80   3920  160   3840   80   3920   80   3920   80   3840  400   3760  160   3840   80   3840  160   3760  160   3840  240   3840  160   3680  320   3760  160   3920   80   3920   80   3920   80   3920   80   3920   80   3840  160   3760  240   3840  160   3920   80   3840  160   3920  240   3840  160   3840   80   3840  160   3840   80   3920   80   3920   80   3920  160   3840  160   3840  160   3840  160   3760  160   3920   80   3920   80   3920   80   3920   80   3760  240   3920   80   3920  320   3760  160   3840   80   3840   80   3920  160   3840   80   3920  160   3760  160   3920   80   3920   80   3920  160   3840  160   3840   80   3840  160   3920   80   3920   80   3920   80   3840  160   3840  240   3840  160   3840   80   3920   80   3840  240   3840   80   3920   80   3920   80   3840   160
      │    │         │    │    │    │    │                 <--- 2 ------ 50 ------ 104 ------ 153 ------ 213 ------ 281 ------ 320 ------ 366 ------ 411 ------ 462 ------ 515 ------ 548 ------ 600 ------ 649 ------ 697 ------ 743 ------ 793 ------ 845 ------ 893 ------ 953 ------ 1006 ------ 1052 ------ 1103 ------ 1158 ------ 1199 ------ 1246 ------ 1302 ------ 1375 ------ 1418 ------ 1475 ------ 1524 ------ 1563 ------ 1628 ------ 1689 ------ 1740 ------ 1799 ------ 1850 ------ 1901 ------ 1948 ------ 2017 ------ 2055 ------ 2099 ------ 2157 ------ 2214 ------ 2267 ------ 2319 ------ 2373 ------ 2428 ------ 2478 ------ 2546 ------ 2602 ------ 2657 ------ 2707 ------ 2760 ------ 2808 ------ 2852 ------ 2913 ------ 2968 ------ 3030 ------ 3069 ------ 3115 ------ 3165 ------ 3210 ------ 3256 ------ 3306 ------ 3365 ------ 3419 ------ 3469 ------ 3523 ------ 3576 ------ 3641 ------ 3694 ------ 3738 ------ 3806 ------ 3851 ------ 3900 ------ 3957 ------ 4004 ------ 4050 ------ 4095 ------ 4145 ------ 4201 ------ 4251 ------ 4293 ------ 4335 ------ 4380 ------ 4432 ------ 4484 ------ 4541 ------ 4593 ------ 4650 ------ 4706 ------ 4744 ------ 4804 ------ 4845 ------ 4897 ------ 4945 ------ 4992 ------ 5044 ------ 5108 ------ 5160 ------ 5207 ------ 5261 ------ 5319 ------ 5358 ------ 5404 ------ 5450 ------ 5490 ------ 5538 ------ 5590 ------ 5639 ------ 5686 ------ 5742 ------ 5788 ------ 5837 ------ 5884 ------ 5940 ------ 5985 ------ 6037 ------ 6090 ------ 6135 ------ 6185 ------ 6228 ------ 6271 ------ 6323 ------ 6376 ------ 6434 ------ 6474 ------ 6527 ------ 6586 ------ 6633 ------ 6674 ------ 6711 ------ 6751 ------ 6797 ------ 6835 ------ 6880 ------ 6918 ------ 6982 ------ 7026 ------ 7069 ------ 7123 ------ 7179 ------ 7238 ------ 7287 ------ 7336 ------ 7388 ------ 7438 ------ 7480 ------ 7528 ------ 7574 ------ 7620 ------ 7664 ------ 7706 ------ 7755 ------ 7805 ------ 7847 ------ 7896 ------ 7954 ------ 8014 ------ 8064 ------ 8108 ------ 8159 ------ 8207 ------ 8250 ------ 8304 ------ 8361 ------ 8410 ------ 8462 ------ 8513 ------ 8562 ------ 8608 ------ 8644 ------ 8706 ------ 8752 ------ 8799 ------ 8840 ------ 8902 ------ 8954 ------ 8995 ------ 9063 ------ 9106 ------ 9152 ------ 9202 ------ 9256 ------ 9310 ------ 9362 ------ 9409 ------ 9462 ------ 9504 ------ 9551 ------ 9598 ------ 9644 ------ 9689 ------ 9741 ------ 9800 ------ 9855 ------ 9896 ------ 9945 ------ 10000
      │    │         │    │    │    │    │   histogram(42)=  0   80   7.9984e+05    80
      │    │         │    │    │    │    │                 <--- 1.14 ------------ 999.93
      │    │         │    │    │    │    ├── key: (39,40)
      │    │         │    │    │    │    └── fd: (39,40)-->(42)
      │    │         │    │    │    ├── inner-join (lookup supplier@s_nk)
      │    │         │    │    │    │    ├── save-table-name: q2_lookup_join_18
      │    │         │    │    │    │    ├── columns: s_suppkey:46(int!null) s_nationkey:49(int!null) n_nationkey:55(int!null) n_regionkey:57(int!null) r_regionkey:61(int!null) r_name:62(char!null)
      │    │         │    │    │    │    ├── key columns: [55] = [49]
      │    │         │    │    │    │    ├── stats: [rows=2000, distinct(46)=1844.81, null(46)=0, distinct(49)=5, null(49)=0, distinct(55)=5, null(55)=0, distinct(57)=1, null(57)=0, distinct(61)=1, null(61)=0, distinct(62)=0.996222, null(62)=0]
      │    │         │    │    │    │    ├── key: (46)
      │    │         │    │    │    │    ├── fd: ()-->(62), (46)-->(49), (55)-->(57), (57)==(61), (61)==(57), (49)==(55), (55)==(49)
      │    │         │    │    │    │    ├── inner-join (lookup nation@n_rk)
      │    │         │    │    │    │    │    ├── save-table-name: q2_lookup_join_19
      │    │         │    │    │    │    │    ├── columns: n_nationkey:55(int!null) n_regionkey:57(int!null) r_regionkey:61(int!null) r_name:62(char!null)
      │    │         │    │    │    │    │    ├── key columns: [61] = [57]
      │    │         │    │    │    │    │    ├── stats: [rows=5, distinct(55)=5, null(55)=0, distinct(57)=1, null(57)=0, distinct(61)=1, null(61)=0, distinct(62)=0.996222, null(62)=0]
      │    │         │    │    │    │    │    ├── key: (55)
      │    │         │    │    │    │    │    ├── fd: ()-->(62), (55)-->(57), (57)==(61), (61)==(57)
      │    │         │    │    │    │    │    ├── select
      │    │         │    │    │    │    │    │    ├── save-table-name: q2_select_20
      │    │         │    │    │    │    │    │    ├── columns: r_regionkey:61(int!null) r_name:62(char!null)
      │    │         │    │    │    │    │    │    ├── stats: [rows=1, distinct(61)=1, null(61)=0, distinct(62)=1, null(62)=0]
      │    │         │    │    │    │    │    │    │   histogram(62)=  0     1
      │    │         │    │    │    │    │    │    │                 <--- 'EUROPE'
      │    │         │    │    │    │    │    │    ├── key: (61)
      │    │         │    │    │    │    │    │    ├── fd: ()-->(62)
      │    │         │    │    │    │    │    │    ├── scan region
      │    │         │    │    │    │    │    │    │    ├── save-table-name: q2_scan_21
      │    │         │    │    │    │    │    │    │    ├── columns: r_regionkey:61(int!null) r_name:62(char!null)
      │    │         │    │    │    │    │    │    │    ├── stats: [rows=5, distinct(61)=5, null(61)=0, distinct(62)=5, null(62)=0]
      │    │         │    │    │    │    │    │    │    │   histogram(61)=  0  1  0  1  0  1  0  1  0  1
      │    │         │    │    │    │    │    │    │    │                 <--- 0 --- 1 --- 2 --- 3 --- 4
      │    │         │    │    │    │    │    │    │    │   histogram(62)=  0     1      3        1
      │    │         │    │    │    │    │    │    │    │                 <--- 'AFRICA' --- 'MIDDLE EAST'
      │    │         │    │    │    │    │    │    │    ├── key: (61)
      │    │         │    │    │    │    │    │    │    └── fd: (61)-->(62)
      │    │         │    │    │    │    │    │    └── filters
      │    │         │    │    │    │    │    │         └── r_name:62 = 'EUROPE' [type=bool, outer=(62), constraints=(/62: [/'EUROPE' - /'EUROPE']; tight), fd=()-->(62)]
      │    │         │    │    │    │    │    └── filters (true)
      │    │         │    │    │    │    └── filters (true)
      │    │         │    │    │    └── filters
      │    │         │    │    │         └── s_suppkey:46 = ps_suppkey:40 [type=bool, outer=(40,46), constraints=(/40: (/NULL - ]; /46: (/NULL - ]), fd=(40)==(46), (46)==(40)]
      │    │         │    │    └── filters
      │    │         │    │         └── ps_partkey:21 = ps_partkey:39 [type=bool, outer=(21,39), constraints=(/21: (/NULL - ]; /39: (/NULL - ]), fd=(21)==(39), (39)==(21)]
      │    │         │    └── aggregations
      │    │         │         ├── min [as=min:66, type=float, outer=(42)]
      │    │         │         │    └── ps_supplycost:42 [type=float]
      │    │         │         ├── const-agg [as=s_name:13, type=char, outer=(13)]
      │    │         │         │    └── s_name:13 [type=char]
      │    │         │         ├── const-agg [as=s_address:14, type=varchar, outer=(14)]
      │    │         │         │    └── s_address:14 [type=varchar]
      │    │         │         ├── const-agg [as=s_phone:16, type=char, outer=(16)]
      │    │         │         │    └── s_phone:16 [type=char]
      │    │         │         ├── const-agg [as=s_acctbal:17, type=float, outer=(17)]
      │    │         │         │    └── s_acctbal:17 [type=float]
      │    │         │         ├── const-agg [as=s_comment:18, type=varchar, outer=(18)]
      │    │         │         │    └── s_comment:18 [type=varchar]
      │    │         │         ├── const-agg [as=ps_supplycost:24, type=float, outer=(24)]
      │    │         │         │    └── ps_supplycost:24 [type=float]
      │    │         │         └── const-agg [as=n_name:29, type=char, outer=(29)]
      │    │         │              └── n_name:29 [type=char]
      │    │         └── filters
      │    │              └── ps_supplycost:24 = min:66 [type=bool, outer=(24,66), constraints=(/24: (/NULL - ]; /66: (/NULL - ]), fd=(24)==(66), (66)==(24)]
      │    └── filters
      │         ├── p_size:6 = 15 [type=bool, outer=(6), constraints=(/6: [/15 - /15]; tight), fd=()-->(6)]
      │         └── p_type:5 LIKE '%BRASS' [type=bool, outer=(5), constraints=(/5: (/NULL - ])]
      └── 100 [type=int]

----Stats for q2_project_1----
column_names  row_count  distinct_count  null_count
{n_name}      100        5               0
{p_mfgr}      100        5               0
{p_partkey}   100        100             0
{s_acctbal}   100        94              0
{s_address}   100        94              0
{s_comment}   100        94              0
{s_name}      100        94              0
{s_phone}     100        94              0
~~~~
column_names  row_count_est  row_count_err  distinct_count_est  distinct_count_err  null_count_est  null_count_err
{n_name}      1.00           100.00 <==     1.00                5.00 <==            0.00            1.00
{p_mfgr}      1.00           100.00 <==     1.00                5.00 <==            0.00            1.00
{p_partkey}   1.00           100.00 <==     1.00                100.00 <==          0.00            1.00
{s_acctbal}   1.00           100.00 <==     1.00                94.00 <==           0.00            1.00
{s_address}   1.00           100.00 <==     1.00                94.00 <==           0.00            1.00
{s_comment}   1.00           100.00 <==     1.00                94.00 <==           0.00            1.00
{s_name}      1.00           100.00 <==     1.00                94.00 <==           0.00            1.00
{s_phone}     1.00           100.00 <==     1.00                94.00 <==           0.00            1.00

----Stats for q2_limit_2----
column_names     row_count  distinct_count  null_count
{min}            100        95              0
{n_name}         100        5               0
{p_mfgr}         100        5               0
{p_partkey}      100        100             0
{p_size}         100        1               0
{p_type}         100        26              0
{ps_partkey}     100        100             0
{ps_suppkey}     100        94              0
{ps_supplycost}  100        95              0
{s_acctbal}      100        94              0
{s_address}      100        94              0
{s_comment}      100        94              0
{s_name}         100        94              0
{s_phone}        100        94              0
~~~~
column_names     row_count_est  row_count_err  distinct_count_est  distinct_count_err  null_count_est  null_count_err
{min}            1.00           100.00 <==     1.00                95.00 <==           0.00            1.00
{n_name}         1.00           100.00 <==     1.00                5.00 <==            0.00            1.00
{p_mfgr}         1.00           100.00 <==     1.00                5.00 <==            0.00            1.00
{p_partkey}      1.00           100.00 <==     1.00                100.00 <==          0.00            1.00
{p_size}         1.00           100.00 <==     1.00                1.00                0.00            1.00
{p_type}         1.00           100.00 <==     1.00                26.00 <==           0.00            1.00
{ps_partkey}     1.00           100.00 <==     1.00                100.00 <==          0.00            1.00
{ps_suppkey}     1.00           100.00 <==     1.00                94.00 <==           0.00            1.00
{ps_supplycost}  1.00           100.00 <==     1.00                95.00 <==           0.00            1.00
{s_acctbal}      1.00           100.00 <==     1.00                94.00 <==           0.00            1.00
{s_address}      1.00           100.00 <==     1.00                94.00 <==           0.00            1.00
{s_comment}      1.00           100.00 <==     1.00                94.00 <==           0.00            1.00
{s_name}         1.00           100.00 <==     1.00                94.00 <==           0.00            1.00
{s_phone}        1.00           100.00 <==     1.00                94.00 <==           0.00            1.00

----Stats for q2_lookup_join_3----
column_names     row_count  distinct_count  null_count
{min}            100        95              0
{n_name}         100        5               0
{p_mfgr}         100        5               0
{p_partkey}      100        100             0
{p_size}         100        1               0
{p_type}         100        26              0
{ps_partkey}     100        100             0
{ps_suppkey}     100        94              0
{ps_supplycost}  100        95              0
{s_acctbal}      100        94              0
{s_address}      100        94              0
{s_comment}      100        94              0
{s_name}         100        94              0
{s_phone}        100        94              0
~~~~
column_names     row_count_est  row_count_err  distinct_count_est  distinct_count_err  null_count_est  null_count_err
{min}            1.00           100.00 <==     1.00                95.00 <==           0.00            1.00
{n_name}         1.00           100.00 <==     1.00                5.00 <==            0.00            1.00
{p_mfgr}         1.00           100.00 <==     1.00                5.00 <==            0.00            1.00
{p_partkey}      1.00           100.00 <==     1.00                100.00 <==          0.00            1.00
{p_size}         1.00           100.00 <==     1.00                1.00                0.00            1.00
{p_type}         1.00           100.00 <==     1.00                26.00 <==           0.00            1.00
{ps_partkey}     1.00           100.00 <==     1.00                100.00 <==          0.00            1.00
{ps_suppkey}     1.00           100.00 <==     1.00                94.00 <==           0.00            1.00
{ps_supplycost}  1.00           100.00 <==     1.00                95.00 <==           0.00            1.00
{s_acctbal}      1.00           100.00 <==     1.00                94.00 <==           0.00            1.00
{s_address}      1.00           100.00 <==     1.00                94.00 <==           0.00            1.00
{s_comment}      1.00           100.00 <==     1.00                94.00 <==           0.00            1.00
{s_name}         1.00           100.00 <==     1.00                94.00 <==           0.00            1.00
{s_phone}        1.00           100.00 <==     1.00                94.00 <==           0.00            1.00

----Stats for q2_sort_4----
column_names     row_count  distinct_count  null_count
{min}            32700      1000            0
{n_name}         32700      5               0
{ps_partkey}     32700      32444           0
{ps_suppkey}     32700      553             0
{ps_supplycost}  32700      1000            0
{s_acctbal}      32700      553             0
{s_address}      32700      553             0
{s_comment}      32700      553             0
{s_name}         32700      553             0
{s_phone}        32700      553             0
~~~~
column_names     row_count_est  row_count_err  distinct_count_est  distinct_count_err  null_count_est  null_count_err
{min}            1.00           32700.00 <==   1.00                1000.00 <==         0.00            1.00
{n_name}         1.00           32700.00 <==   1.00                5.00 <==            0.00            1.00
{ps_partkey}     1.00           32700.00 <==   1.00                32444.00 <==        0.00            1.00
{ps_suppkey}     1.00           32700.00 <==   1.00                553.00 <==          0.00            1.00
{ps_supplycost}  1.00           32700.00 <==   1.00                1000.00 <==         0.00            1.00
{s_acctbal}      1.00           32700.00 <==   1.00                553.00 <==          0.00            1.00
{s_address}      1.00           32700.00 <==   1.00                553.00 <==          0.00            1.00
{s_comment}      1.00           32700.00 <==   1.00                553.00 <==          0.00            1.00
{s_name}         1.00           32700.00 <==   1.00                553.00 <==          0.00            1.00
{s_phone}        1.00           32700.00 <==   1.00                553.00 <==          0.00            1.00

----Stats for q2_select_5----
column_names     row_count  distinct_count  null_count
{min}            117375     1000            0
{n_name}         117375     5               0
{ps_partkey}     117375     116575          0
{ps_suppkey}     117375     1981            0
{ps_supplycost}  117375     1000            0
{s_acctbal}      117375     1979            0
{s_address}      117375     1981            0
{s_comment}      117375     1981            0
{s_name}         117375     1981            0
{s_phone}        117375     1981            0
~~~~
column_names     row_count_est  row_count_err  distinct_count_est  distinct_count_err  null_count_est  null_count_err
{min}            1.00           117375.00 <==  1.00                1000.00 <==         0.00            1.00
{n_name}         1.00           117375.00 <==  1.00                5.00 <==            0.00            1.00
{ps_partkey}     1.00           117375.00 <==  1.00                116575.00 <==       0.00            1.00
{ps_suppkey}     1.00           117375.00 <==  1.00                1981.00 <==         0.00            1.00
{ps_supplycost}  1.00           117375.00 <==  1.00                1000.00 <==         0.00            1.00
{s_acctbal}      1.00           117375.00 <==  1.00                1979.00 <==         0.00            1.00
{s_address}      1.00           117375.00 <==  1.00                1981.00 <==         0.00            1.00
{s_comment}      1.00           117375.00 <==  1.00                1981.00 <==         0.00            1.00
{s_name}         1.00           117375.00 <==  1.00                1981.00 <==         0.00            1.00
{s_phone}        1.00           117375.00 <==  1.00                1981.00 <==         0.00            1.00

----Stats for q2_group_by_6----
column_names     row_count  distinct_count  null_count
{min}            158480     1000            0
{n_name}         158480     5               0
{ps_partkey}     158480     116575          0
{ps_suppkey}     158480     1981            0
{ps_supplycost}  158480     1000            0
{s_acctbal}      158480     1979            0
{s_address}      158480     1981            0
{s_comment}      158480     1981            0
{s_name}         158480     1981            0
{s_phone}        158480     1981            0
~~~~
column_names     row_count_est  row_count_err  distinct_count_est  distinct_count_err  null_count_est  null_count_err
{min}            113914.00      1.39           113914.00           113.91 <==          0.00            1.00
{n_name}         113914.00      1.39           113914.00           22782.80 <==        0.00            1.00
{ps_partkey}     113914.00      1.39           110568.00           1.05                0.00            1.00
{ps_suppkey}     113914.00      1.39           9920.00             5.01 <==            0.00            1.00
{ps_supplycost}  113914.00      1.39           113914.00           113.91 <==          0.00            1.00
{s_acctbal}      113914.00      1.39           113914.00           57.56 <==           0.00            1.00
{s_address}      113914.00      1.39           113914.00           57.50 <==           0.00            1.00
{s_comment}      113914.00      1.39           113914.00           57.50 <==           0.00            1.00
{s_name}         113914.00      1.39           113914.00           57.50 <==           0.00            1.00
{s_phone}        113914.00      1.39           113914.00           57.50 <==           0.00            1.00

----Stats for q2_inner_join_7----
column_names       row_count  distinct_count  null_count
{n_name}           252562     5               0
{n_nationkey_1}    252562     5               0
{n_nationkey}      252562     5               0
{n_regionkey_1}    252562     1               0
{n_regionkey}      252562     1               0
{ps_partkey_1}     252562     116575          0
{ps_partkey}       252562     116575          0
{ps_suppkey_1}     252562     1981            0
{ps_suppkey}       252562     1981            0
{ps_supplycost_1}  252562     1000            0
{ps_supplycost}    252562     1000            0
{r_name_1}         252562     1               0
{r_name}           252562     1               0
{r_regionkey_1}    252562     1               0
{r_regionkey}      252562     1               0
{s_acctbal}        252562     1979            0
{s_address}        252562     1981            0
{s_comment}        252562     1981            0
{s_name}           252562     1981            0
{s_nationkey_1}    252562     5               0
{s_nationkey}      252562     5               0
{s_phone}          252562     1981            0
{s_suppkey_1}      252562     1981            0
{s_suppkey}        252562     1981            0
~~~~
column_names       row_count_est  row_count_err  distinct_count_est  distinct_count_err  null_count_est  null_count_err
{n_name}           233690.00      1.08           5.00                1.00                0.00            1.00
{n_nationkey}      233690.00      1.08           5.00                1.00                0.00            1.00
{n_nationkey_1}    233690.00      1.08           5.00                1.00                0.00            1.00
{n_regionkey}      233690.00      1.08           1.00                1.00                0.00            1.00
{n_regionkey_1}    233690.00      1.08           1.00                1.00                0.00            1.00
{ps_partkey}       233690.00      1.08           110568.00           1.05                0.00            1.00
{ps_partkey_1}     233690.00      1.08           110568.00           1.05                0.00            1.00
{ps_suppkey}       233690.00      1.08           9920.00             5.01 <==            0.00            1.00
{ps_suppkey_1}     233690.00      1.08           1845.00             1.07                0.00            1.00
{ps_supplycost}    233690.00      1.08           76389.00            76.39 <==           0.00            1.00
{ps_supplycost_1}  233690.00      1.08           75889.00            75.89 <==           0.00            1.00
{r_name}           233690.00      1.08           1.00                1.00                0.00            1.00
{r_name_1}         233690.00      1.08           1.00                1.00                0.00            1.00
{r_regionkey}      233690.00      1.08           1.00                1.00                0.00            1.00
{r_regionkey_1}    233690.00      1.08           1.00                1.00                0.00            1.00
{s_acctbal}        233690.00      1.08           9967.00             5.04 <==            0.00            1.00
{s_address}        233690.00      1.08           10000.00            5.05 <==            0.00            1.00
{s_comment}        233690.00      1.08           9934.00             5.01 <==            0.00            1.00
{s_name}           233690.00      1.08           9990.00             5.04 <==            0.00            1.00
{s_nationkey}      233690.00      1.08           5.00                1.00                0.00            1.00
{s_nationkey_1}    233690.00      1.08           5.00                1.00                0.00            1.00
{s_phone}          233690.00      1.08           10000.00            5.05 <==            0.00            1.00
{s_suppkey}        233690.00      1.08           9920.00             5.01 <==            0.00            1.00
{s_suppkey_1}      233690.00      1.08           1845.00             1.07                0.00            1.00

----Stats for q2_inner_join_8----
column_names     row_count  distinct_count  null_count
{n_name}         158480     5               0
{n_nationkey}    158480     5               0
{n_regionkey}    158480     1               0
{ps_partkey}     158480     116575          0
{ps_suppkey}     158480     1981            0
{ps_supplycost}  158480     1000            0
{r_name}         158480     1               0
{r_regionkey}    158480     1               0
{s_acctbal}      158480     1979            0
{s_address}      158480     1981            0
{s_comment}      158480     1981            0
{s_name}         158480     1981            0
{s_nationkey}    158480     5               0
{s_phone}        158480     1981            0
{s_suppkey}      158480     1981            0
~~~~
column_names     row_count_est  row_count_err  distinct_count_est  distinct_count_err  null_count_est  null_count_err
{n_name}         161290.00      1.02           5.00                1.00                0.00            1.00
{n_nationkey}    161290.00      1.02           5.00                1.00                0.00            1.00
{n_regionkey}    161290.00      1.02           1.00                1.00                0.00            1.00
{ps_partkey}     161290.00      1.02           111321.00           1.05                0.00            1.00
{ps_suppkey}     161290.00      1.02           9920.00             5.01 <==            0.00            1.00
{ps_supplycost}  161290.00      1.02           80888.00            80.89 <==           0.00            1.00
{r_name}         161290.00      1.02           1.00                1.00                0.00            1.00
{r_regionkey}    161290.00      1.02           1.00                1.00                0.00            1.00
{s_acctbal}      161290.00      1.02           9967.00             5.04 <==            0.00            1.00
{s_address}      161290.00      1.02           10000.00            5.05 <==            0.00            1.00
{s_comment}      161290.00      1.02           9934.00             5.01 <==            0.00            1.00
{s_name}         161290.00      1.02           9990.00             5.04 <==            0.00            1.00
{s_nationkey}    161290.00      1.02           5.00                1.00                0.00            1.00
{s_phone}        161290.00      1.02           10000.00            5.05 <==            0.00            1.00
{s_suppkey}      161290.00      1.02           9920.00             5.01 <==            0.00            1.00

----Stats for q2_scan_9----
column_names     row_count  distinct_count  null_count
{ps_partkey}     800000     199241          0
{ps_suppkey}     800000     9920            0
{ps_supplycost}  800000     1000            0
~~~~
column_names     row_count_est  row_count_err  distinct_count_est  distinct_count_err  null_count_est  null_count_err
{ps_partkey}     800000.00      1.00           199241.00           1.00                0.00            1.00
{ps_suppkey}     800000.00      1.00           9920.00             1.00                0.00            1.00
{ps_supplycost}  800000.00      1.00           100379.00           100.38 <==          0.00            1.00

----Stats for q2_inner_join_10----
column_names   row_count  distinct_count  null_count
{n_name}       1981       5               0
{n_nationkey}  1981       5               0
{n_regionkey}  1981       1               0
{r_name}       1981       1               0
{r_regionkey}  1981       1               0
{s_acctbal}    1981       1979            0
{s_address}    1981       1981            0
{s_comment}    1981       1981            0
{s_name}       1981       1981            0
{s_nationkey}  1981       5               0
{s_phone}      1981       1981            0
{s_suppkey}    1981       1981            0
~~~~
column_names   row_count_est  row_count_err  distinct_count_est  distinct_count_err  null_count_est  null_count_err
{n_name}       2000.00        1.01           5.00                1.00                0.00            1.00
{n_nationkey}  2000.00        1.01           5.00                1.00                0.00            1.00
{n_regionkey}  2000.00        1.01           1.00                1.00                0.00            1.00
{r_name}       2000.00        1.01           1.00                1.00                0.00            1.00
{r_regionkey}  2000.00        1.01           1.00                1.00                0.00            1.00
{s_acctbal}    2000.00        1.01           1846.00             1.07                0.00            1.00
{s_address}    2000.00        1.01           1846.00             1.07                0.00            1.00
{s_comment}    2000.00        1.01           1845.00             1.07                0.00            1.00
{s_name}       2000.00        1.01           1846.00             1.07                0.00            1.00
{s_nationkey}  2000.00        1.01           5.00                1.00                0.00            1.00
{s_phone}      2000.00        1.01           1846.00             1.07                0.00            1.00
{s_suppkey}    2000.00        1.01           1845.00             1.07                0.00            1.00

----Stats for q2_scan_11----
column_names   row_count  distinct_count  null_count
{s_acctbal}    10000      10000           0
{s_address}    10000      10000           0
{s_comment}    10000      9903            0
{s_name}       10000      9990            0
{s_nationkey}  10000      25              0
{s_phone}      10000      9840            0
{s_suppkey}    10000      9920            0
~~~~
column_names   row_count_est  row_count_err  distinct_count_est  distinct_count_err  null_count_est  null_count_err
{s_acctbal}    10000.00       1.00           9967.00             1.00                0.00            1.00
{s_address}    10000.00       1.00           10000.00            1.00                0.00            1.00
{s_comment}    10000.00       1.00           9934.00             1.00                0.00            1.00
{s_name}       10000.00       1.00           9990.00             1.00                0.00            1.00
{s_nationkey}  10000.00       1.00           25.00               1.00                0.00            1.00
{s_phone}      10000.00       1.00           10000.00            1.02                0.00            1.00
{s_suppkey}    10000.00       1.00           9920.00             1.00                0.00            1.00

----Stats for q2_inner_join_12----
column_names   row_count  distinct_count  null_count
{n_name}       5          5               0
{n_nationkey}  5          5               0
{n_regionkey}  5          1               0
{r_name}       5          1               0
{r_regionkey}  5          1               0
~~~~
column_names   row_count_est  row_count_err  distinct_count_est  distinct_count_err  null_count_est  null_count_err
{n_name}       5.00           1.00           5.00                1.00                0.00            1.00
{n_nationkey}  5.00           1.00           5.00                1.00                0.00            1.00
{n_regionkey}  5.00           1.00           1.00                1.00                0.00            1.00
{r_name}       5.00           1.00           1.00                1.00                0.00            1.00
{r_regionkey}  5.00           1.00           1.00                1.00                0.00            1.00

----Stats for q2_scan_13----
column_names   row_count  distinct_count  null_count
{n_name}       25         25              0
{n_nationkey}  25         25              0
{n_regionkey}  25         5               0
~~~~
column_names   row_count_est  row_count_err  distinct_count_est  distinct_count_err  null_count_est  null_count_err
{n_name}       25.00          1.00           25.00               1.00                0.00            1.00
{n_nationkey}  25.00          1.00           25.00               1.00                0.00            1.00
{n_regionkey}  25.00          1.00           5.00                1.00                0.00            1.00

----Stats for q2_select_14----
column_names   row_count  distinct_count  null_count
{r_name}       1          1               0
{r_regionkey}  1          1               0
~~~~
column_names   row_count_est  row_count_err  distinct_count_est  distinct_count_err  null_count_est  null_count_err
{r_name}       1.00           1.00           1.00                1.00                0.00            1.00
{r_regionkey}  1.00           1.00           1.00                1.00                0.00            1.00

----Stats for q2_scan_15----
column_names   row_count  distinct_count  null_count
{r_name}       5          5               0
{r_regionkey}  5          5               0
~~~~
column_names   row_count_est  row_count_err  distinct_count_est  distinct_count_err  null_count_est  null_count_err
{r_name}       5.00           1.00           5.00                1.00                0.00            1.00
{r_regionkey}  5.00           1.00           5.00                1.00                0.00            1.00

----Stats for q2_inner_join_16----
column_names     row_count  distinct_count  null_count
{n_nationkey}    158480     5               0
{n_regionkey}    158480     1               0
{ps_partkey}     158480     116575          0
{ps_suppkey}     158480     1981            0
{ps_supplycost}  158480     1000            0
{r_name}         158480     1               0
{r_regionkey}    158480     1               0
{s_nationkey}    158480     5               0
{s_suppkey}      158480     1981            0
~~~~
column_names     row_count_est  row_count_err  distinct_count_est  distinct_count_err  null_count_est  null_count_err
{n_nationkey}    161290.00      1.02           5.00                1.00                0.00            1.00
{n_regionkey}    161290.00      1.02           1.00                1.00                0.00            1.00
{ps_partkey}     161290.00      1.02           110568.00           1.05                0.00            1.00
{ps_suppkey}     161290.00      1.02           1845.00             1.07                0.00            1.00
{ps_supplycost}  161290.00      1.02           80252.00            80.25 <==           0.00            1.00
{r_name}         161290.00      1.02           1.00                1.00                0.00            1.00
{r_regionkey}    161290.00      1.02           1.00                1.00                0.00            1.00
{s_nationkey}    161290.00      1.02           5.00                1.00                0.00            1.00
{s_suppkey}      161290.00      1.02           1845.00             1.07                0.00            1.00

----Stats for q2_scan_17----
column_names     row_count  distinct_count  null_count
{ps_partkey}     800000     199241          0
{ps_suppkey}     800000     9920            0
{ps_supplycost}  800000     1000            0
~~~~
column_names     row_count_est  row_count_err  distinct_count_est  distinct_count_err  null_count_est  null_count_err
{ps_partkey}     800000.00      1.00           199241.00           1.00                0.00            1.00
{ps_suppkey}     800000.00      1.00           9920.00             1.00                0.00            1.00
{ps_supplycost}  800000.00      1.00           100379.00           100.38 <==          0.00            1.00

----Stats for q2_lookup_join_18----
column_names   row_count  distinct_count  null_count
{n_nationkey}  1981       5               0
{n_regionkey}  1981       1               0
{r_name}       1981       1               0
{r_regionkey}  1981       1               0
{s_nationkey}  1981       5               0
{s_suppkey}    1981       1981            0
~~~~
column_names   row_count_est  row_count_err  distinct_count_est  distinct_count_err  null_count_est  null_count_err
{n_nationkey}  2000.00        1.01           5.00                1.00                0.00            1.00
{n_regionkey}  2000.00        1.01           1.00                1.00                0.00            1.00
{r_name}       2000.00        1.01           1.00                1.00                0.00            1.00
{r_regionkey}  2000.00        1.01           1.00                1.00                0.00            1.00
{s_nationkey}  2000.00        1.01           5.00                1.00                0.00            1.00
{s_suppkey}    2000.00        1.01           1845.00             1.07                0.00            1.00

----Stats for q2_lookup_join_19----
column_names   row_count  distinct_count  null_count
{n_nationkey}  5          5               0
{n_regionkey}  5          1               0
{r_name}       5          1               0
{r_regionkey}  5          1               0
~~~~
column_names   row_count_est  row_count_err  distinct_count_est  distinct_count_err  null_count_est  null_count_err
{n_nationkey}  5.00           1.00           5.00                1.00                0.00            1.00
{n_regionkey}  5.00           1.00           1.00                1.00                0.00            1.00
{r_name}       5.00           1.00           1.00                1.00                0.00            1.00
{r_regionkey}  5.00           1.00           1.00                1.00                0.00            1.00

----Stats for q2_select_20----
column_names   row_count  distinct_count  null_count
{r_name}       1          1               0
{r_regionkey}  1          1               0
~~~~
column_names   row_count_est  row_count_err  distinct_count_est  distinct_count_err  null_count_est  null_count_err
{r_name}       1.00           1.00           1.00                1.00                0.00            1.00
{r_regionkey}  1.00           1.00           1.00                1.00                0.00            1.00

----Stats for q2_scan_21----
column_names   row_count  distinct_count  null_count
{r_name}       5          5               0
{r_regionkey}  5          5               0
~~~~
column_names   row_count_est  row_count_err  distinct_count_est  distinct_count_err  null_count_est  null_count_err
{r_name}       5.00           1.00           5.00                1.00                0.00            1.00
{r_regionkey}  5.00           1.00           5.00                1.00                0.00            1.00
----
----
