== Physical Plan ==
* ColumnarToRow (146)
+- CometTakeOrderedAndProject (145)
   +- CometHashAggregate (144)
      +- CometColumnarExchange (143)
         +- RowToColumnar (142)
            +- * HashAggregate (141)
               +- Union (140)
                  :- * HashAggregate (107)
                  :  +- * ColumnarToRow (106)
                  :     +- CometColumnarExchange (105)
                  :        +- RowToColumnar (104)
                  :           +- * HashAggregate (103)
                  :              +- Union (102)
                  :                 :- * Filter (67)
                  :                 :  +- * HashAggregate (66)
                  :                 :     +- * ColumnarToRow (65)
                  :                 :        +- CometColumnarExchange (64)
                  :                 :           +- RowToColumnar (63)
                  :                 :              +- * HashAggregate (62)
                  :                 :                 +- * ColumnarToRow (61)
                  :                 :                    +- CometProject (60)
                  :                 :                       +- CometBroadcastHashJoin (59)
                  :                 :                          :- CometProject (54)
                  :                 :                          :  +- CometBroadcastHashJoin (53)
                  :                 :                          :     :- CometBroadcastHashJoin (47)
                  :                 :                          :     :  :- CometFilter (2)
                  :                 :                          :     :  :  +- CometScan parquet spark_catalog.default.store_sales (1)
                  :                 :                          :     :  +- CometBroadcastExchange (46)
                  :                 :                          :     :     +- CometProject (45)
                  :                 :                          :     :        +- CometBroadcastHashJoin (44)
                  :                 :                          :     :           :- CometFilter (4)
                  :                 :                          :     :           :  +- CometScan parquet spark_catalog.default.item (3)
                  :                 :                          :     :           +- CometBroadcastExchange (43)
                  :                 :                          :     :              +- CometBroadcastHashJoin (42)
                  :                 :                          :     :                 :- CometHashAggregate (32)
                  :                 :                          :     :                 :  +- CometColumnarExchange (31)
                  :                 :                          :     :                 :     +- CometHashAggregate (30)
                  :                 :                          :     :                 :        +- CometProject (29)
                  :                 :                          :     :                 :           +- CometBroadcastHashJoin (28)
                  :                 :                          :     :                 :              :- CometProject (26)
                  :                 :                          :     :                 :              :  +- CometBroadcastHashJoin (25)
                  :                 :                          :     :                 :              :     :- CometFilter (6)
                  :                 :                          :     :                 :              :     :  +- CometScan parquet spark_catalog.default.store_sales (5)
                  :                 :                          :     :                 :              :     +- CometBroadcastExchange (24)
                  :                 :                          :     :                 :              :        +- CometBroadcastHashJoin (23)
                  :                 :                          :     :                 :              :           :- CometFilter (8)
                  :                 :                          :     :                 :              :           :  +- CometScan parquet spark_catalog.default.item (7)
                  :                 :                          :     :                 :              :           +- CometBroadcastExchange (22)
                  :                 :                          :     :                 :              :              +- CometProject (21)
                  :                 :                          :     :                 :              :                 +- CometBroadcastHashJoin (20)
                  :                 :                          :     :                 :              :                    :- CometProject (15)
                  :                 :                          :     :                 :              :                    :  +- CometBroadcastHashJoin (14)
                  :                 :                          :     :                 :              :                    :     :- CometFilter (10)
                  :                 :                          :     :                 :              :                    :     :  +- CometScan parquet spark_catalog.default.catalog_sales (9)
                  :                 :                          :     :                 :              :                    :     +- CometBroadcastExchange (13)
                  :                 :                          :     :                 :              :                    :        +- CometFilter (12)
                  :                 :                          :     :                 :              :                    :           +- CometScan parquet spark_catalog.default.item (11)
                  :                 :                          :     :                 :              :                    +- CometBroadcastExchange (19)
                  :                 :                          :     :                 :              :                       +- CometProject (18)
                  :                 :                          :     :                 :              :                          +- CometFilter (17)
                  :                 :                          :     :                 :              :                             +- CometScan parquet spark_catalog.default.date_dim (16)
                  :                 :                          :     :                 :              +- ReusedExchange (27)
                  :                 :                          :     :                 +- CometBroadcastExchange (41)
                  :                 :                          :     :                    +- CometProject (40)
                  :                 :                          :     :                       +- CometBroadcastHashJoin (39)
                  :                 :                          :     :                          :- CometProject (37)
                  :                 :                          :     :                          :  +- CometBroadcastHashJoin (36)
                  :                 :                          :     :                          :     :- CometFilter (34)
                  :                 :                          :     :                          :     :  +- CometScan parquet spark_catalog.default.web_sales (33)
                  :                 :                          :     :                          :     +- ReusedExchange (35)
                  :                 :                          :     :                          +- ReusedExchange (38)
                  :                 :                          :     +- CometBroadcastExchange (52)
                  :                 :                          :        +- CometBroadcastHashJoin (51)
                  :                 :                          :           :- CometFilter (49)
                  :                 :                          :           :  +- CometScan parquet spark_catalog.default.item (48)
                  :                 :                          :           +- ReusedExchange (50)
                  :                 :                          +- CometBroadcastExchange (58)
                  :                 :                             +- CometProject (57)
                  :                 :                                +- CometFilter (56)
                  :                 :                                   +- CometScan parquet spark_catalog.default.date_dim (55)
                  :                 :- * Filter (84)
                  :                 :  +- * HashAggregate (83)
                  :                 :     +- * ColumnarToRow (82)
                  :                 :        +- CometColumnarExchange (81)
                  :                 :           +- RowToColumnar (80)
                  :                 :              +- * HashAggregate (79)
                  :                 :                 +- * ColumnarToRow (78)
                  :                 :                    +- CometProject (77)
                  :                 :                       +- CometBroadcastHashJoin (76)
                  :                 :                          :- CometProject (74)
                  :                 :                          :  +- CometBroadcastHashJoin (73)
                  :                 :                          :     :- CometBroadcastHashJoin (71)
                  :                 :                          :     :  :- CometFilter (69)
                  :                 :                          :     :  :  +- CometScan parquet spark_catalog.default.catalog_sales (68)
                  :                 :                          :     :  +- ReusedExchange (70)
                  :                 :                          :     +- ReusedExchange (72)
                  :                 :                          +- ReusedExchange (75)
                  :                 +- * Filter (101)
                  :                    +- * HashAggregate (100)
                  :                       +- * ColumnarToRow (99)
                  :                          +- CometColumnarExchange (98)
                  :                             +- RowToColumnar (97)
                  :                                +- * HashAggregate (96)
                  :                                   +- * ColumnarToRow (95)
                  :                                      +- CometProject (94)
                  :                                         +- CometBroadcastHashJoin (93)
                  :                                            :- CometProject (91)
                  :                                            :  +- CometBroadcastHashJoin (90)
                  :                                            :     :- CometBroadcastHashJoin (88)
                  :                                            :     :  :- CometFilter (86)
                  :                                            :     :  :  +- CometScan parquet spark_catalog.default.web_sales (85)
                  :                                            :     :  +- ReusedExchange (87)
                  :                                            :     +- ReusedExchange (89)
                  :                                            +- ReusedExchange (92)
                  :- * HashAggregate (115)
                  :  +- * ColumnarToRow (114)
                  :     +- CometColumnarExchange (113)
                  :        +- RowToColumnar (112)
                  :           +- * HashAggregate (111)
                  :              +- * HashAggregate (110)
                  :                 +- * ColumnarToRow (109)
                  :                    +- ReusedExchange (108)
                  :- * HashAggregate (123)
                  :  +- * ColumnarToRow (122)
                  :     +- CometColumnarExchange (121)
                  :        +- RowToColumnar (120)
                  :           +- * HashAggregate (119)
                  :              +- * HashAggregate (118)
                  :                 +- * ColumnarToRow (117)
                  :                    +- ReusedExchange (116)
                  :- * HashAggregate (131)
                  :  +- * ColumnarToRow (130)
                  :     +- CometColumnarExchange (129)
                  :        +- RowToColumnar (128)
                  :           +- * HashAggregate (127)
                  :              +- * HashAggregate (126)
                  :                 +- * ColumnarToRow (125)
                  :                    +- ReusedExchange (124)
                  +- * HashAggregate (139)
                     +- * ColumnarToRow (138)
                        +- CometColumnarExchange (137)
                           +- RowToColumnar (136)
                              +- * HashAggregate (135)
                                 +- * HashAggregate (134)
                                    +- * ColumnarToRow (133)
                                       +- ReusedExchange (132)


(1) Scan parquet spark_catalog.default.store_sales
Output [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(ss_sold_date_sk#4), dynamicpruningexpression(ss_sold_date_sk#4 IN dynamicpruning#5)]
PushedFilters: [IsNotNull(ss_item_sk)]
ReadSchema: struct<ss_item_sk:int,ss_quantity:int,ss_list_price:decimal(7,2)>

(2) CometFilter
Input [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4]
Condition : isnotnull(ss_item_sk#1)

(3) Scan parquet spark_catalog.default.item
Output [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9]
Batched: true
Location [not included in comparison]/{warehouse_dir}/item]
PushedFilters: [IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id)]
ReadSchema: struct<i_item_sk:int,i_brand_id:int,i_class_id:int,i_category_id:int>

(4) CometFilter
Input [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9]
Condition : ((isnotnull(i_brand_id#7) AND isnotnull(i_class_id#8)) AND isnotnull(i_category_id#9))

(5) Scan parquet spark_catalog.default.store_sales
Output [2]: [ss_item_sk#10, ss_sold_date_sk#11]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(ss_sold_date_sk#11), dynamicpruningexpression(ss_sold_date_sk#11 IN dynamicpruning#12)]
PushedFilters: [IsNotNull(ss_item_sk)]
ReadSchema: struct<ss_item_sk:int>

(6) CometFilter
Input [2]: [ss_item_sk#10, ss_sold_date_sk#11]
Condition : isnotnull(ss_item_sk#10)

(7) Scan parquet spark_catalog.default.item
Output [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16]
Batched: true
Location [not included in comparison]/{warehouse_dir}/item]
PushedFilters: [IsNotNull(i_item_sk), IsNotNull(i_brand_id), IsNotNull(i_class_id), IsNotNull(i_category_id)]
ReadSchema: struct<i_item_sk:int,i_brand_id:int,i_class_id:int,i_category_id:int>

(8) CometFilter
Input [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16]
Condition : (((isnotnull(i_item_sk#13) AND isnotnull(i_brand_id#14)) AND isnotnull(i_class_id#15)) AND isnotnull(i_category_id#16))

(9) Scan parquet spark_catalog.default.catalog_sales
Output [2]: [cs_item_sk#17, cs_sold_date_sk#18]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(cs_sold_date_sk#18), dynamicpruningexpression(cs_sold_date_sk#18 IN dynamicpruning#19)]
PushedFilters: [IsNotNull(cs_item_sk)]
ReadSchema: struct<cs_item_sk:int>

(10) CometFilter
Input [2]: [cs_item_sk#17, cs_sold_date_sk#18]
Condition : isnotnull(cs_item_sk#17)

(11) Scan parquet spark_catalog.default.item
Output [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23]
Batched: true
Location [not included in comparison]/{warehouse_dir}/item]
PushedFilters: [IsNotNull(i_item_sk)]
ReadSchema: struct<i_item_sk:int,i_brand_id:int,i_class_id:int,i_category_id:int>

(12) CometFilter
Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23]
Condition : isnotnull(i_item_sk#20)

(13) CometBroadcastExchange
Input [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23]
Arguments: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23]

(14) CometBroadcastHashJoin
Left output [2]: [cs_item_sk#17, cs_sold_date_sk#18]
Right output [4]: [i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23]
Arguments: [cs_item_sk#17], [i_item_sk#20], Inner, BuildRight

(15) CometProject
Input [6]: [cs_item_sk#17, cs_sold_date_sk#18, i_item_sk#20, i_brand_id#21, i_class_id#22, i_category_id#23]
Arguments: [cs_sold_date_sk#18, i_brand_id#21, i_class_id#22, i_category_id#23], [cs_sold_date_sk#18, i_brand_id#21, i_class_id#22, i_category_id#23]

(16) Scan parquet spark_catalog.default.date_dim
Output [2]: [d_date_sk#24, d_year#25]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_year), GreaterThanOrEqual(d_year,1999), LessThanOrEqual(d_year,2001), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int>

(17) CometFilter
Input [2]: [d_date_sk#24, d_year#25]
Condition : (((isnotnull(d_year#25) AND (d_year#25 >= 1999)) AND (d_year#25 <= 2001)) AND isnotnull(d_date_sk#24))

(18) CometProject
Input [2]: [d_date_sk#24, d_year#25]
Arguments: [d_date_sk#24], [d_date_sk#24]

(19) CometBroadcastExchange
Input [1]: [d_date_sk#24]
Arguments: [d_date_sk#24]

(20) CometBroadcastHashJoin
Left output [4]: [cs_sold_date_sk#18, i_brand_id#21, i_class_id#22, i_category_id#23]
Right output [1]: [d_date_sk#24]
Arguments: [cs_sold_date_sk#18], [d_date_sk#24], Inner, BuildRight

(21) CometProject
Input [5]: [cs_sold_date_sk#18, i_brand_id#21, i_class_id#22, i_category_id#23, d_date_sk#24]
Arguments: [i_brand_id#21, i_class_id#22, i_category_id#23], [i_brand_id#21, i_class_id#22, i_category_id#23]

(22) CometBroadcastExchange
Input [3]: [i_brand_id#21, i_class_id#22, i_category_id#23]
Arguments: [i_brand_id#21, i_class_id#22, i_category_id#23]

(23) CometBroadcastHashJoin
Left output [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16]
Right output [3]: [i_brand_id#21, i_class_id#22, i_category_id#23]
Arguments: [coalesce(i_brand_id#14, 0), isnull(i_brand_id#14), coalesce(i_class_id#15, 0), isnull(i_class_id#15), coalesce(i_category_id#16, 0), isnull(i_category_id#16)], [coalesce(i_brand_id#21, 0), isnull(i_brand_id#21), coalesce(i_class_id#22, 0), isnull(i_class_id#22), coalesce(i_category_id#23, 0), isnull(i_category_id#23)], LeftSemi, BuildRight

(24) CometBroadcastExchange
Input [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16]
Arguments: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16]

(25) CometBroadcastHashJoin
Left output [2]: [ss_item_sk#10, ss_sold_date_sk#11]
Right output [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16]
Arguments: [ss_item_sk#10], [i_item_sk#13], Inner, BuildRight

(26) CometProject
Input [6]: [ss_item_sk#10, ss_sold_date_sk#11, i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16]
Arguments: [ss_sold_date_sk#11, i_brand_id#14, i_class_id#15, i_category_id#16], [ss_sold_date_sk#11, i_brand_id#14, i_class_id#15, i_category_id#16]

(27) ReusedExchange [Reuses operator id: 19]
Output [1]: [d_date_sk#26]

(28) CometBroadcastHashJoin
Left output [4]: [ss_sold_date_sk#11, i_brand_id#14, i_class_id#15, i_category_id#16]
Right output [1]: [d_date_sk#26]
Arguments: [ss_sold_date_sk#11], [d_date_sk#26], Inner, BuildRight

(29) CometProject
Input [5]: [ss_sold_date_sk#11, i_brand_id#14, i_class_id#15, i_category_id#16, d_date_sk#26]
Arguments: [brand_id#27, class_id#28, category_id#29], [i_brand_id#14 AS brand_id#27, i_class_id#15 AS class_id#28, i_category_id#16 AS category_id#29]

(30) CometHashAggregate
Input [3]: [brand_id#27, class_id#28, category_id#29]
Keys [3]: [brand_id#27, class_id#28, category_id#29]
Functions: []

(31) CometColumnarExchange
Input [3]: [brand_id#27, class_id#28, category_id#29]
Arguments: hashpartitioning(brand_id#27, class_id#28, category_id#29, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=1]

(32) CometHashAggregate
Input [3]: [brand_id#27, class_id#28, category_id#29]
Keys [3]: [brand_id#27, class_id#28, category_id#29]
Functions: []

(33) Scan parquet spark_catalog.default.web_sales
Output [2]: [ws_item_sk#30, ws_sold_date_sk#31]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(ws_sold_date_sk#31), dynamicpruningexpression(ws_sold_date_sk#31 IN dynamicpruning#32)]
PushedFilters: [IsNotNull(ws_item_sk)]
ReadSchema: struct<ws_item_sk:int>

(34) CometFilter
Input [2]: [ws_item_sk#30, ws_sold_date_sk#31]
Condition : isnotnull(ws_item_sk#30)

(35) ReusedExchange [Reuses operator id: 13]
Output [4]: [i_item_sk#33, i_brand_id#34, i_class_id#35, i_category_id#36]

(36) CometBroadcastHashJoin
Left output [2]: [ws_item_sk#30, ws_sold_date_sk#31]
Right output [4]: [i_item_sk#33, i_brand_id#34, i_class_id#35, i_category_id#36]
Arguments: [ws_item_sk#30], [i_item_sk#33], Inner, BuildRight

(37) CometProject
Input [6]: [ws_item_sk#30, ws_sold_date_sk#31, i_item_sk#33, i_brand_id#34, i_class_id#35, i_category_id#36]
Arguments: [ws_sold_date_sk#31, i_brand_id#34, i_class_id#35, i_category_id#36], [ws_sold_date_sk#31, i_brand_id#34, i_class_id#35, i_category_id#36]

(38) ReusedExchange [Reuses operator id: 19]
Output [1]: [d_date_sk#37]

(39) CometBroadcastHashJoin
Left output [4]: [ws_sold_date_sk#31, i_brand_id#34, i_class_id#35, i_category_id#36]
Right output [1]: [d_date_sk#37]
Arguments: [ws_sold_date_sk#31], [d_date_sk#37], Inner, BuildRight

(40) CometProject
Input [5]: [ws_sold_date_sk#31, i_brand_id#34, i_class_id#35, i_category_id#36, d_date_sk#37]
Arguments: [i_brand_id#34, i_class_id#35, i_category_id#36], [i_brand_id#34, i_class_id#35, i_category_id#36]

(41) CometBroadcastExchange
Input [3]: [i_brand_id#34, i_class_id#35, i_category_id#36]
Arguments: [i_brand_id#34, i_class_id#35, i_category_id#36]

(42) CometBroadcastHashJoin
Left output [3]: [brand_id#27, class_id#28, category_id#29]
Right output [3]: [i_brand_id#34, i_class_id#35, i_category_id#36]
Arguments: [coalesce(brand_id#27, 0), isnull(brand_id#27), coalesce(class_id#28, 0), isnull(class_id#28), coalesce(category_id#29, 0), isnull(category_id#29)], [coalesce(i_brand_id#34, 0), isnull(i_brand_id#34), coalesce(i_class_id#35, 0), isnull(i_class_id#35), coalesce(i_category_id#36, 0), isnull(i_category_id#36)], LeftSemi, BuildRight

(43) CometBroadcastExchange
Input [3]: [brand_id#27, class_id#28, category_id#29]
Arguments: [brand_id#27, class_id#28, category_id#29]

(44) CometBroadcastHashJoin
Left output [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9]
Right output [3]: [brand_id#27, class_id#28, category_id#29]
Arguments: [i_brand_id#7, i_class_id#8, i_category_id#9], [brand_id#27, class_id#28, category_id#29], Inner, BuildRight

(45) CometProject
Input [7]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9, brand_id#27, class_id#28, category_id#29]
Arguments: [ss_item_sk#38], [i_item_sk#6 AS ss_item_sk#38]

(46) CometBroadcastExchange
Input [1]: [ss_item_sk#38]
Arguments: [ss_item_sk#38]

(47) CometBroadcastHashJoin
Left output [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4]
Right output [1]: [ss_item_sk#38]
Arguments: [ss_item_sk#1], [ss_item_sk#38], LeftSemi, BuildRight

(48) Scan parquet spark_catalog.default.item
Output [4]: [i_item_sk#39, i_brand_id#40, i_class_id#41, i_category_id#42]
Batched: true
Location [not included in comparison]/{warehouse_dir}/item]
PushedFilters: [IsNotNull(i_item_sk)]
ReadSchema: struct<i_item_sk:int,i_brand_id:int,i_class_id:int,i_category_id:int>

(49) CometFilter
Input [4]: [i_item_sk#39, i_brand_id#40, i_class_id#41, i_category_id#42]
Condition : isnotnull(i_item_sk#39)

(50) ReusedExchange [Reuses operator id: 46]
Output [1]: [ss_item_sk#38]

(51) CometBroadcastHashJoin
Left output [4]: [i_item_sk#39, i_brand_id#40, i_class_id#41, i_category_id#42]
Right output [1]: [ss_item_sk#38]
Arguments: [i_item_sk#39], [ss_item_sk#38], LeftSemi, BuildRight

(52) CometBroadcastExchange
Input [4]: [i_item_sk#39, i_brand_id#40, i_class_id#41, i_category_id#42]
Arguments: [i_item_sk#39, i_brand_id#40, i_class_id#41, i_category_id#42]

(53) CometBroadcastHashJoin
Left output [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4]
Right output [4]: [i_item_sk#39, i_brand_id#40, i_class_id#41, i_category_id#42]
Arguments: [ss_item_sk#1], [i_item_sk#39], Inner, BuildRight

(54) CometProject
Input [8]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4, i_item_sk#39, i_brand_id#40, i_class_id#41, i_category_id#42]
Arguments: [ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4, i_brand_id#40, i_class_id#41, i_category_id#42], [ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4, i_brand_id#40, i_class_id#41, i_category_id#42]

(55) Scan parquet spark_catalog.default.date_dim
Output [3]: [d_date_sk#43, d_year#44, d_moy#45]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2000), EqualTo(d_moy,11), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int,d_moy:int>

(56) CometFilter
Input [3]: [d_date_sk#43, d_year#44, d_moy#45]
Condition : ((((isnotnull(d_year#44) AND isnotnull(d_moy#45)) AND (d_year#44 = 2000)) AND (d_moy#45 = 11)) AND isnotnull(d_date_sk#43))

(57) CometProject
Input [3]: [d_date_sk#43, d_year#44, d_moy#45]
Arguments: [d_date_sk#43], [d_date_sk#43]

(58) CometBroadcastExchange
Input [1]: [d_date_sk#43]
Arguments: [d_date_sk#43]

(59) CometBroadcastHashJoin
Left output [6]: [ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4, i_brand_id#40, i_class_id#41, i_category_id#42]
Right output [1]: [d_date_sk#43]
Arguments: [ss_sold_date_sk#4], [d_date_sk#43], Inner, BuildRight

(60) CometProject
Input [7]: [ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4, i_brand_id#40, i_class_id#41, i_category_id#42, d_date_sk#43]
Arguments: [ss_quantity#2, ss_list_price#3, i_brand_id#40, i_class_id#41, i_category_id#42], [ss_quantity#2, ss_list_price#3, i_brand_id#40, i_class_id#41, i_category_id#42]

(61) ColumnarToRow [codegen id : 1]
Input [5]: [ss_quantity#2, ss_list_price#3, i_brand_id#40, i_class_id#41, i_category_id#42]

(62) HashAggregate [codegen id : 1]
Input [5]: [ss_quantity#2, ss_list_price#3, i_brand_id#40, i_class_id#41, i_category_id#42]
Keys [3]: [i_brand_id#40, i_class_id#41, i_category_id#42]
Functions [2]: [partial_sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3)), partial_count(1)]
Aggregate Attributes [3]: [sum#46, isEmpty#47, count#48]
Results [6]: [i_brand_id#40, i_class_id#41, i_category_id#42, sum#49, isEmpty#50, count#51]

(63) RowToColumnar
Input [6]: [i_brand_id#40, i_class_id#41, i_category_id#42, sum#49, isEmpty#50, count#51]

(64) CometColumnarExchange
Input [6]: [i_brand_id#40, i_class_id#41, i_category_id#42, sum#49, isEmpty#50, count#51]
Arguments: hashpartitioning(i_brand_id#40, i_class_id#41, i_category_id#42, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=2]

(65) ColumnarToRow [codegen id : 2]
Input [6]: [i_brand_id#40, i_class_id#41, i_category_id#42, sum#49, isEmpty#50, count#51]

(66) HashAggregate [codegen id : 2]
Input [6]: [i_brand_id#40, i_class_id#41, i_category_id#42, sum#49, isEmpty#50, count#51]
Keys [3]: [i_brand_id#40, i_class_id#41, i_category_id#42]
Functions [2]: [sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3)), count(1)]
Aggregate Attributes [2]: [sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3))#52, count(1)#53]
Results [6]: [store AS channel#54, i_brand_id#40, i_class_id#41, i_category_id#42, sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3))#52 AS sales#55, count(1)#53 AS number_sales#56]

(67) Filter [codegen id : 2]
Input [6]: [channel#54, i_brand_id#40, i_class_id#41, i_category_id#42, sales#55, number_sales#56]
Condition : (isnotnull(sales#55) AND (cast(sales#55 as decimal(32,6)) > cast(Subquery scalar-subquery#57, [id=#58] as decimal(32,6))))

(68) Scan parquet spark_catalog.default.catalog_sales
Output [4]: [cs_item_sk#59, cs_quantity#60, cs_list_price#61, cs_sold_date_sk#62]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(cs_sold_date_sk#62), dynamicpruningexpression(cs_sold_date_sk#62 IN dynamicpruning#63)]
PushedFilters: [IsNotNull(cs_item_sk)]
ReadSchema: struct<cs_item_sk:int,cs_quantity:int,cs_list_price:decimal(7,2)>

(69) CometFilter
Input [4]: [cs_item_sk#59, cs_quantity#60, cs_list_price#61, cs_sold_date_sk#62]
Condition : isnotnull(cs_item_sk#59)

(70) ReusedExchange [Reuses operator id: 46]
Output [1]: [ss_item_sk#64]

(71) CometBroadcastHashJoin
Left output [4]: [cs_item_sk#59, cs_quantity#60, cs_list_price#61, cs_sold_date_sk#62]
Right output [1]: [ss_item_sk#64]
Arguments: [cs_item_sk#59], [ss_item_sk#64], LeftSemi, BuildRight

(72) ReusedExchange [Reuses operator id: 52]
Output [4]: [i_item_sk#65, i_brand_id#66, i_class_id#67, i_category_id#68]

(73) CometBroadcastHashJoin
Left output [4]: [cs_item_sk#59, cs_quantity#60, cs_list_price#61, cs_sold_date_sk#62]
Right output [4]: [i_item_sk#65, i_brand_id#66, i_class_id#67, i_category_id#68]
Arguments: [cs_item_sk#59], [i_item_sk#65], Inner, BuildRight

(74) CometProject
Input [8]: [cs_item_sk#59, cs_quantity#60, cs_list_price#61, cs_sold_date_sk#62, i_item_sk#65, i_brand_id#66, i_class_id#67, i_category_id#68]
Arguments: [cs_quantity#60, cs_list_price#61, cs_sold_date_sk#62, i_brand_id#66, i_class_id#67, i_category_id#68], [cs_quantity#60, cs_list_price#61, cs_sold_date_sk#62, i_brand_id#66, i_class_id#67, i_category_id#68]

(75) ReusedExchange [Reuses operator id: 58]
Output [1]: [d_date_sk#69]

(76) CometBroadcastHashJoin
Left output [6]: [cs_quantity#60, cs_list_price#61, cs_sold_date_sk#62, i_brand_id#66, i_class_id#67, i_category_id#68]
Right output [1]: [d_date_sk#69]
Arguments: [cs_sold_date_sk#62], [d_date_sk#69], Inner, BuildRight

(77) CometProject
Input [7]: [cs_quantity#60, cs_list_price#61, cs_sold_date_sk#62, i_brand_id#66, i_class_id#67, i_category_id#68, d_date_sk#69]
Arguments: [cs_quantity#60, cs_list_price#61, i_brand_id#66, i_class_id#67, i_category_id#68], [cs_quantity#60, cs_list_price#61, i_brand_id#66, i_class_id#67, i_category_id#68]

(78) ColumnarToRow [codegen id : 3]
Input [5]: [cs_quantity#60, cs_list_price#61, i_brand_id#66, i_class_id#67, i_category_id#68]

(79) HashAggregate [codegen id : 3]
Input [5]: [cs_quantity#60, cs_list_price#61, i_brand_id#66, i_class_id#67, i_category_id#68]
Keys [3]: [i_brand_id#66, i_class_id#67, i_category_id#68]
Functions [2]: [partial_sum((cast(cs_quantity#60 as decimal(10,0)) * cs_list_price#61)), partial_count(1)]
Aggregate Attributes [3]: [sum#70, isEmpty#71, count#72]
Results [6]: [i_brand_id#66, i_class_id#67, i_category_id#68, sum#73, isEmpty#74, count#75]

(80) RowToColumnar
Input [6]: [i_brand_id#66, i_class_id#67, i_category_id#68, sum#73, isEmpty#74, count#75]

(81) CometColumnarExchange
Input [6]: [i_brand_id#66, i_class_id#67, i_category_id#68, sum#73, isEmpty#74, count#75]
Arguments: hashpartitioning(i_brand_id#66, i_class_id#67, i_category_id#68, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=3]

(82) ColumnarToRow [codegen id : 4]
Input [6]: [i_brand_id#66, i_class_id#67, i_category_id#68, sum#73, isEmpty#74, count#75]

(83) HashAggregate [codegen id : 4]
Input [6]: [i_brand_id#66, i_class_id#67, i_category_id#68, sum#73, isEmpty#74, count#75]
Keys [3]: [i_brand_id#66, i_class_id#67, i_category_id#68]
Functions [2]: [sum((cast(cs_quantity#60 as decimal(10,0)) * cs_list_price#61)), count(1)]
Aggregate Attributes [2]: [sum((cast(cs_quantity#60 as decimal(10,0)) * cs_list_price#61))#76, count(1)#77]
Results [6]: [catalog AS channel#78, i_brand_id#66, i_class_id#67, i_category_id#68, sum((cast(cs_quantity#60 as decimal(10,0)) * cs_list_price#61))#76 AS sales#79, count(1)#77 AS number_sales#80]

(84) Filter [codegen id : 4]
Input [6]: [channel#78, i_brand_id#66, i_class_id#67, i_category_id#68, sales#79, number_sales#80]
Condition : (isnotnull(sales#79) AND (cast(sales#79 as decimal(32,6)) > cast(ReusedSubquery Subquery scalar-subquery#57, [id=#58] as decimal(32,6))))

(85) Scan parquet spark_catalog.default.web_sales
Output [4]: [ws_item_sk#81, ws_quantity#82, ws_list_price#83, ws_sold_date_sk#84]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(ws_sold_date_sk#84), dynamicpruningexpression(ws_sold_date_sk#84 IN dynamicpruning#85)]
PushedFilters: [IsNotNull(ws_item_sk)]
ReadSchema: struct<ws_item_sk:int,ws_quantity:int,ws_list_price:decimal(7,2)>

(86) CometFilter
Input [4]: [ws_item_sk#81, ws_quantity#82, ws_list_price#83, ws_sold_date_sk#84]
Condition : isnotnull(ws_item_sk#81)

(87) ReusedExchange [Reuses operator id: 46]
Output [1]: [ss_item_sk#86]

(88) CometBroadcastHashJoin
Left output [4]: [ws_item_sk#81, ws_quantity#82, ws_list_price#83, ws_sold_date_sk#84]
Right output [1]: [ss_item_sk#86]
Arguments: [ws_item_sk#81], [ss_item_sk#86], LeftSemi, BuildRight

(89) ReusedExchange [Reuses operator id: 52]
Output [4]: [i_item_sk#87, i_brand_id#88, i_class_id#89, i_category_id#90]

(90) CometBroadcastHashJoin
Left output [4]: [ws_item_sk#81, ws_quantity#82, ws_list_price#83, ws_sold_date_sk#84]
Right output [4]: [i_item_sk#87, i_brand_id#88, i_class_id#89, i_category_id#90]
Arguments: [ws_item_sk#81], [i_item_sk#87], Inner, BuildRight

(91) CometProject
Input [8]: [ws_item_sk#81, ws_quantity#82, ws_list_price#83, ws_sold_date_sk#84, i_item_sk#87, i_brand_id#88, i_class_id#89, i_category_id#90]
Arguments: [ws_quantity#82, ws_list_price#83, ws_sold_date_sk#84, i_brand_id#88, i_class_id#89, i_category_id#90], [ws_quantity#82, ws_list_price#83, ws_sold_date_sk#84, i_brand_id#88, i_class_id#89, i_category_id#90]

(92) ReusedExchange [Reuses operator id: 58]
Output [1]: [d_date_sk#91]

(93) CometBroadcastHashJoin
Left output [6]: [ws_quantity#82, ws_list_price#83, ws_sold_date_sk#84, i_brand_id#88, i_class_id#89, i_category_id#90]
Right output [1]: [d_date_sk#91]
Arguments: [ws_sold_date_sk#84], [d_date_sk#91], Inner, BuildRight

(94) CometProject
Input [7]: [ws_quantity#82, ws_list_price#83, ws_sold_date_sk#84, i_brand_id#88, i_class_id#89, i_category_id#90, d_date_sk#91]
Arguments: [ws_quantity#82, ws_list_price#83, i_brand_id#88, i_class_id#89, i_category_id#90], [ws_quantity#82, ws_list_price#83, i_brand_id#88, i_class_id#89, i_category_id#90]

(95) ColumnarToRow [codegen id : 5]
Input [5]: [ws_quantity#82, ws_list_price#83, i_brand_id#88, i_class_id#89, i_category_id#90]

(96) HashAggregate [codegen id : 5]
Input [5]: [ws_quantity#82, ws_list_price#83, i_brand_id#88, i_class_id#89, i_category_id#90]
Keys [3]: [i_brand_id#88, i_class_id#89, i_category_id#90]
Functions [2]: [partial_sum((cast(ws_quantity#82 as decimal(10,0)) * ws_list_price#83)), partial_count(1)]
Aggregate Attributes [3]: [sum#92, isEmpty#93, count#94]
Results [6]: [i_brand_id#88, i_class_id#89, i_category_id#90, sum#95, isEmpty#96, count#97]

(97) RowToColumnar
Input [6]: [i_brand_id#88, i_class_id#89, i_category_id#90, sum#95, isEmpty#96, count#97]

(98) CometColumnarExchange
Input [6]: [i_brand_id#88, i_class_id#89, i_category_id#90, sum#95, isEmpty#96, count#97]
Arguments: hashpartitioning(i_brand_id#88, i_class_id#89, i_category_id#90, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=4]

(99) ColumnarToRow [codegen id : 6]
Input [6]: [i_brand_id#88, i_class_id#89, i_category_id#90, sum#95, isEmpty#96, count#97]

(100) HashAggregate [codegen id : 6]
Input [6]: [i_brand_id#88, i_class_id#89, i_category_id#90, sum#95, isEmpty#96, count#97]
Keys [3]: [i_brand_id#88, i_class_id#89, i_category_id#90]
Functions [2]: [sum((cast(ws_quantity#82 as decimal(10,0)) * ws_list_price#83)), count(1)]
Aggregate Attributes [2]: [sum((cast(ws_quantity#82 as decimal(10,0)) * ws_list_price#83))#98, count(1)#99]
Results [6]: [web AS channel#100, i_brand_id#88, i_class_id#89, i_category_id#90, sum((cast(ws_quantity#82 as decimal(10,0)) * ws_list_price#83))#98 AS sales#101, count(1)#99 AS number_sales#102]

(101) Filter [codegen id : 6]
Input [6]: [channel#100, i_brand_id#88, i_class_id#89, i_category_id#90, sales#101, number_sales#102]
Condition : (isnotnull(sales#101) AND (cast(sales#101 as decimal(32,6)) > cast(ReusedSubquery Subquery scalar-subquery#57, [id=#58] as decimal(32,6))))

(102) Union

(103) HashAggregate [codegen id : 7]
Input [6]: [channel#54, i_brand_id#40, i_class_id#41, i_category_id#42, sales#55, number_sales#56]
Keys [4]: [channel#54, i_brand_id#40, i_class_id#41, i_category_id#42]
Functions [2]: [partial_sum(sales#55), partial_sum(number_sales#56)]
Aggregate Attributes [3]: [sum#103, isEmpty#104, sum#105]
Results [7]: [channel#54, i_brand_id#40, i_class_id#41, i_category_id#42, sum#106, isEmpty#107, sum#108]

(104) RowToColumnar
Input [7]: [channel#54, i_brand_id#40, i_class_id#41, i_category_id#42, sum#106, isEmpty#107, sum#108]

(105) CometColumnarExchange
Input [7]: [channel#54, i_brand_id#40, i_class_id#41, i_category_id#42, sum#106, isEmpty#107, sum#108]
Arguments: hashpartitioning(channel#54, i_brand_id#40, i_class_id#41, i_category_id#42, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=5]

(106) ColumnarToRow [codegen id : 8]
Input [7]: [channel#54, i_brand_id#40, i_class_id#41, i_category_id#42, sum#106, isEmpty#107, sum#108]

(107) HashAggregate [codegen id : 8]
Input [7]: [channel#54, i_brand_id#40, i_class_id#41, i_category_id#42, sum#106, isEmpty#107, sum#108]
Keys [4]: [channel#54, i_brand_id#40, i_class_id#41, i_category_id#42]
Functions [2]: [sum(sales#55), sum(number_sales#56)]
Aggregate Attributes [2]: [sum(sales#55)#109, sum(number_sales#56)#110]
Results [6]: [channel#54, i_brand_id#40, i_class_id#41, i_category_id#42, sum(sales#55)#109 AS sum_sales#111, sum(number_sales#56)#110 AS number_sales#112]

(108) ReusedExchange [Reuses operator id: 105]
Output [7]: [channel#113, i_brand_id#114, i_class_id#115, i_category_id#116, sum#117, isEmpty#118, sum#119]

(109) ColumnarToRow [codegen id : 16]
Input [7]: [channel#113, i_brand_id#114, i_class_id#115, i_category_id#116, sum#117, isEmpty#118, sum#119]

(110) HashAggregate [codegen id : 16]
Input [7]: [channel#113, i_brand_id#114, i_class_id#115, i_category_id#116, sum#117, isEmpty#118, sum#119]
Keys [4]: [channel#113, i_brand_id#114, i_class_id#115, i_category_id#116]
Functions [2]: [sum(sales#120), sum(number_sales#121)]
Aggregate Attributes [2]: [sum(sales#120)#109, sum(number_sales#121)#110]
Results [5]: [channel#113, i_brand_id#114, i_class_id#115, sum(sales#120)#109 AS sum_sales#122, sum(number_sales#121)#110 AS number_sales#123]

(111) HashAggregate [codegen id : 16]
Input [5]: [channel#113, i_brand_id#114, i_class_id#115, sum_sales#122, number_sales#123]
Keys [3]: [channel#113, i_brand_id#114, i_class_id#115]
Functions [2]: [partial_sum(sum_sales#122), partial_sum(number_sales#123)]
Aggregate Attributes [3]: [sum#124, isEmpty#125, sum#126]
Results [6]: [channel#113, i_brand_id#114, i_class_id#115, sum#127, isEmpty#128, sum#129]

(112) RowToColumnar
Input [6]: [channel#113, i_brand_id#114, i_class_id#115, sum#127, isEmpty#128, sum#129]

(113) CometColumnarExchange
Input [6]: [channel#113, i_brand_id#114, i_class_id#115, sum#127, isEmpty#128, sum#129]
Arguments: hashpartitioning(channel#113, i_brand_id#114, i_class_id#115, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=6]

(114) ColumnarToRow [codegen id : 17]
Input [6]: [channel#113, i_brand_id#114, i_class_id#115, sum#127, isEmpty#128, sum#129]

(115) HashAggregate [codegen id : 17]
Input [6]: [channel#113, i_brand_id#114, i_class_id#115, sum#127, isEmpty#128, sum#129]
Keys [3]: [channel#113, i_brand_id#114, i_class_id#115]
Functions [2]: [sum(sum_sales#122), sum(number_sales#123)]
Aggregate Attributes [2]: [sum(sum_sales#122)#130, sum(number_sales#123)#131]
Results [6]: [channel#113, i_brand_id#114, i_class_id#115, null AS i_category_id#132, sum(sum_sales#122)#130 AS sum(sum_sales)#133, sum(number_sales#123)#131 AS sum(number_sales)#134]

(116) ReusedExchange [Reuses operator id: 105]
Output [7]: [channel#135, i_brand_id#136, i_class_id#137, i_category_id#138, sum#139, isEmpty#140, sum#141]

(117) ColumnarToRow [codegen id : 25]
Input [7]: [channel#135, i_brand_id#136, i_class_id#137, i_category_id#138, sum#139, isEmpty#140, sum#141]

(118) HashAggregate [codegen id : 25]
Input [7]: [channel#135, i_brand_id#136, i_class_id#137, i_category_id#138, sum#139, isEmpty#140, sum#141]
Keys [4]: [channel#135, i_brand_id#136, i_class_id#137, i_category_id#138]
Functions [2]: [sum(sales#142), sum(number_sales#143)]
Aggregate Attributes [2]: [sum(sales#142)#109, sum(number_sales#143)#110]
Results [4]: [channel#135, i_brand_id#136, sum(sales#142)#109 AS sum_sales#144, sum(number_sales#143)#110 AS number_sales#145]

(119) HashAggregate [codegen id : 25]
Input [4]: [channel#135, i_brand_id#136, sum_sales#144, number_sales#145]
Keys [2]: [channel#135, i_brand_id#136]
Functions [2]: [partial_sum(sum_sales#144), partial_sum(number_sales#145)]
Aggregate Attributes [3]: [sum#146, isEmpty#147, sum#148]
Results [5]: [channel#135, i_brand_id#136, sum#149, isEmpty#150, sum#151]

(120) RowToColumnar
Input [5]: [channel#135, i_brand_id#136, sum#149, isEmpty#150, sum#151]

(121) CometColumnarExchange
Input [5]: [channel#135, i_brand_id#136, sum#149, isEmpty#150, sum#151]
Arguments: hashpartitioning(channel#135, i_brand_id#136, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=7]

(122) ColumnarToRow [codegen id : 26]
Input [5]: [channel#135, i_brand_id#136, sum#149, isEmpty#150, sum#151]

(123) HashAggregate [codegen id : 26]
Input [5]: [channel#135, i_brand_id#136, sum#149, isEmpty#150, sum#151]
Keys [2]: [channel#135, i_brand_id#136]
Functions [2]: [sum(sum_sales#144), sum(number_sales#145)]
Aggregate Attributes [2]: [sum(sum_sales#144)#152, sum(number_sales#145)#153]
Results [6]: [channel#135, i_brand_id#136, null AS i_class_id#154, null AS i_category_id#155, sum(sum_sales#144)#152 AS sum(sum_sales)#156, sum(number_sales#145)#153 AS sum(number_sales)#157]

(124) ReusedExchange [Reuses operator id: 105]
Output [7]: [channel#158, i_brand_id#159, i_class_id#160, i_category_id#161, sum#162, isEmpty#163, sum#164]

(125) ColumnarToRow [codegen id : 34]
Input [7]: [channel#158, i_brand_id#159, i_class_id#160, i_category_id#161, sum#162, isEmpty#163, sum#164]

(126) HashAggregate [codegen id : 34]
Input [7]: [channel#158, i_brand_id#159, i_class_id#160, i_category_id#161, sum#162, isEmpty#163, sum#164]
Keys [4]: [channel#158, i_brand_id#159, i_class_id#160, i_category_id#161]
Functions [2]: [sum(sales#165), sum(number_sales#166)]
Aggregate Attributes [2]: [sum(sales#165)#109, sum(number_sales#166)#110]
Results [3]: [channel#158, sum(sales#165)#109 AS sum_sales#167, sum(number_sales#166)#110 AS number_sales#168]

(127) HashAggregate [codegen id : 34]
Input [3]: [channel#158, sum_sales#167, number_sales#168]
Keys [1]: [channel#158]
Functions [2]: [partial_sum(sum_sales#167), partial_sum(number_sales#168)]
Aggregate Attributes [3]: [sum#169, isEmpty#170, sum#171]
Results [4]: [channel#158, sum#172, isEmpty#173, sum#174]

(128) RowToColumnar
Input [4]: [channel#158, sum#172, isEmpty#173, sum#174]

(129) CometColumnarExchange
Input [4]: [channel#158, sum#172, isEmpty#173, sum#174]
Arguments: hashpartitioning(channel#158, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=8]

(130) ColumnarToRow [codegen id : 35]
Input [4]: [channel#158, sum#172, isEmpty#173, sum#174]

(131) HashAggregate [codegen id : 35]
Input [4]: [channel#158, sum#172, isEmpty#173, sum#174]
Keys [1]: [channel#158]
Functions [2]: [sum(sum_sales#167), sum(number_sales#168)]
Aggregate Attributes [2]: [sum(sum_sales#167)#175, sum(number_sales#168)#176]
Results [6]: [channel#158, null AS i_brand_id#177, null AS i_class_id#178, null AS i_category_id#179, sum(sum_sales#167)#175 AS sum(sum_sales)#180, sum(number_sales#168)#176 AS sum(number_sales)#181]

(132) ReusedExchange [Reuses operator id: 105]
Output [7]: [channel#182, i_brand_id#183, i_class_id#184, i_category_id#185, sum#186, isEmpty#187, sum#188]

(133) ColumnarToRow [codegen id : 43]
Input [7]: [channel#182, i_brand_id#183, i_class_id#184, i_category_id#185, sum#186, isEmpty#187, sum#188]

(134) HashAggregate [codegen id : 43]
Input [7]: [channel#182, i_brand_id#183, i_class_id#184, i_category_id#185, sum#186, isEmpty#187, sum#188]
Keys [4]: [channel#182, i_brand_id#183, i_class_id#184, i_category_id#185]
Functions [2]: [sum(sales#189), sum(number_sales#190)]
Aggregate Attributes [2]: [sum(sales#189)#109, sum(number_sales#190)#110]
Results [2]: [sum(sales#189)#109 AS sum_sales#191, sum(number_sales#190)#110 AS number_sales#192]

(135) HashAggregate [codegen id : 43]
Input [2]: [sum_sales#191, number_sales#192]
Keys: []
Functions [2]: [partial_sum(sum_sales#191), partial_sum(number_sales#192)]
Aggregate Attributes [3]: [sum#193, isEmpty#194, sum#195]
Results [3]: [sum#196, isEmpty#197, sum#198]

(136) RowToColumnar
Input [3]: [sum#196, isEmpty#197, sum#198]

(137) CometColumnarExchange
Input [3]: [sum#196, isEmpty#197, sum#198]
Arguments: SinglePartition, ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=9]

(138) ColumnarToRow [codegen id : 44]
Input [3]: [sum#196, isEmpty#197, sum#198]

(139) HashAggregate [codegen id : 44]
Input [3]: [sum#196, isEmpty#197, sum#198]
Keys: []
Functions [2]: [sum(sum_sales#191), sum(number_sales#192)]
Aggregate Attributes [2]: [sum(sum_sales#191)#199, sum(number_sales#192)#200]
Results [6]: [null AS channel#201, null AS i_brand_id#202, null AS i_class_id#203, null AS i_category_id#204, sum(sum_sales#191)#199 AS sum(sum_sales)#205, sum(number_sales#192)#200 AS sum(number_sales)#206]

(140) Union

(141) HashAggregate [codegen id : 45]
Input [6]: [channel#54, i_brand_id#40, i_class_id#41, i_category_id#42, sum_sales#111, number_sales#112]
Keys [6]: [channel#54, i_brand_id#40, i_class_id#41, i_category_id#42, sum_sales#111, number_sales#112]
Functions: []
Aggregate Attributes: []
Results [6]: [channel#54, i_brand_id#40, i_class_id#41, i_category_id#42, sum_sales#111, number_sales#112]

(142) RowToColumnar
Input [6]: [channel#54, i_brand_id#40, i_class_id#41, i_category_id#42, sum_sales#111, number_sales#112]

(143) CometColumnarExchange
Input [6]: [channel#54, i_brand_id#40, i_class_id#41, i_category_id#42, sum_sales#111, number_sales#112]
Arguments: hashpartitioning(channel#54, i_brand_id#40, i_class_id#41, i_category_id#42, sum_sales#111, number_sales#112, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=10]

(144) CometHashAggregate
Input [6]: [channel#54, i_brand_id#40, i_class_id#41, i_category_id#42, sum_sales#111, number_sales#112]
Keys [6]: [channel#54, i_brand_id#40, i_class_id#41, i_category_id#42, sum_sales#111, number_sales#112]
Functions: []

(145) CometTakeOrderedAndProject
Input [6]: [channel#54, i_brand_id#40, i_class_id#41, i_category_id#42, sum_sales#111, number_sales#112]
Arguments: TakeOrderedAndProject(limit=100, orderBy=[channel#54 ASC NULLS FIRST,i_brand_id#40 ASC NULLS FIRST,i_class_id#41 ASC NULLS FIRST,i_category_id#42 ASC NULLS FIRST], output=[channel#54,i_brand_id#40,i_class_id#41,i_category_id#42,sum_sales#111,number_sales#112]), [channel#54, i_brand_id#40, i_class_id#41, i_category_id#42, sum_sales#111, number_sales#112], 100, [channel#54 ASC NULLS FIRST, i_brand_id#40 ASC NULLS FIRST, i_class_id#41 ASC NULLS FIRST, i_category_id#42 ASC NULLS FIRST], [channel#54, i_brand_id#40, i_class_id#41, i_category_id#42, sum_sales#111, number_sales#112]

(146) ColumnarToRow [codegen id : 46]
Input [6]: [channel#54, i_brand_id#40, i_class_id#41, i_category_id#42, sum_sales#111, number_sales#112]

===== Subqueries =====

Subquery:1 Hosting operator id = 67 Hosting Expression = Subquery scalar-subquery#57, [id=#58]
* HashAggregate (168)
+- * ColumnarToRow (167)
   +- CometColumnarExchange (166)
      +- RowToColumnar (165)
         +- * HashAggregate (164)
            +- * ColumnarToRow (163)
               +- CometUnion (162)
                  :- CometProject (150)
                  :  +- CometBroadcastHashJoin (149)
                  :     :- CometScan parquet spark_catalog.default.store_sales (147)
                  :     +- ReusedExchange (148)
                  :- CometProject (157)
                  :  +- CometBroadcastHashJoin (156)
                  :     :- CometScan parquet spark_catalog.default.catalog_sales (151)
                  :     +- CometBroadcastExchange (155)
                  :        +- CometProject (154)
                  :           +- CometFilter (153)
                  :              +- CometScan parquet spark_catalog.default.date_dim (152)
                  +- CometProject (161)
                     +- CometBroadcastHashJoin (160)
                        :- CometScan parquet spark_catalog.default.web_sales (158)
                        +- ReusedExchange (159)


(147) Scan parquet spark_catalog.default.store_sales
Output [3]: [ss_quantity#207, ss_list_price#208, ss_sold_date_sk#209]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(ss_sold_date_sk#209), dynamicpruningexpression(ss_sold_date_sk#209 IN dynamicpruning#210)]
ReadSchema: struct<ss_quantity:int,ss_list_price:decimal(7,2)>

(148) ReusedExchange [Reuses operator id: 19]
Output [1]: [d_date_sk#211]

(149) CometBroadcastHashJoin
Left output [3]: [ss_quantity#207, ss_list_price#208, ss_sold_date_sk#209]
Right output [1]: [d_date_sk#211]
Arguments: [ss_sold_date_sk#209], [d_date_sk#211], Inner, BuildRight

(150) CometProject
Input [4]: [ss_quantity#207, ss_list_price#208, ss_sold_date_sk#209, d_date_sk#211]
Arguments: [quantity#212, list_price#213], [ss_quantity#207 AS quantity#212, ss_list_price#208 AS list_price#213]

(151) Scan parquet spark_catalog.default.catalog_sales
Output [3]: [cs_quantity#214, cs_list_price#215, cs_sold_date_sk#216]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(cs_sold_date_sk#216), dynamicpruningexpression(cs_sold_date_sk#216 IN dynamicpruning#217)]
ReadSchema: struct<cs_quantity:int,cs_list_price:decimal(7,2)>

(152) Scan parquet spark_catalog.default.date_dim
Output [2]: [d_date_sk#218, d_year#219]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_year), GreaterThanOrEqual(d_year,1998), LessThanOrEqual(d_year,2000), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int>

(153) CometFilter
Input [2]: [d_date_sk#218, d_year#219]
Condition : (((isnotnull(d_year#219) AND (d_year#219 >= 1998)) AND (d_year#219 <= 2000)) AND isnotnull(d_date_sk#218))

(154) CometProject
Input [2]: [d_date_sk#218, d_year#219]
Arguments: [d_date_sk#218], [d_date_sk#218]

(155) CometBroadcastExchange
Input [1]: [d_date_sk#218]
Arguments: [d_date_sk#218]

(156) CometBroadcastHashJoin
Left output [3]: [cs_quantity#214, cs_list_price#215, cs_sold_date_sk#216]
Right output [1]: [d_date_sk#218]
Arguments: [cs_sold_date_sk#216], [d_date_sk#218], Inner, BuildRight

(157) CometProject
Input [4]: [cs_quantity#214, cs_list_price#215, cs_sold_date_sk#216, d_date_sk#218]
Arguments: [quantity#220, list_price#221], [cs_quantity#214 AS quantity#220, cs_list_price#215 AS list_price#221]

(158) Scan parquet spark_catalog.default.web_sales
Output [3]: [ws_quantity#222, ws_list_price#223, ws_sold_date_sk#224]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(ws_sold_date_sk#224), dynamicpruningexpression(ws_sold_date_sk#224 IN dynamicpruning#225)]
ReadSchema: struct<ws_quantity:int,ws_list_price:decimal(7,2)>

(159) ReusedExchange [Reuses operator id: 155]
Output [1]: [d_date_sk#226]

(160) CometBroadcastHashJoin
Left output [3]: [ws_quantity#222, ws_list_price#223, ws_sold_date_sk#224]
Right output [1]: [d_date_sk#226]
Arguments: [ws_sold_date_sk#224], [d_date_sk#226], Inner, BuildRight

(161) CometProject
Input [4]: [ws_quantity#222, ws_list_price#223, ws_sold_date_sk#224, d_date_sk#226]
Arguments: [quantity#227, list_price#228], [ws_quantity#222 AS quantity#227, ws_list_price#223 AS list_price#228]

(162) CometUnion
Child 0 Input [2]: [quantity#212, list_price#213]
Child 1 Input [2]: [quantity#220, list_price#221]
Child 2 Input [2]: [quantity#227, list_price#228]

(163) ColumnarToRow [codegen id : 1]
Input [2]: [quantity#212, list_price#213]

(164) HashAggregate [codegen id : 1]
Input [2]: [quantity#212, list_price#213]
Keys: []
Functions [1]: [partial_avg((cast(quantity#212 as decimal(10,0)) * list_price#213))]
Aggregate Attributes [2]: [sum#229, count#230]
Results [2]: [sum#231, count#232]

(165) RowToColumnar
Input [2]: [sum#231, count#232]

(166) CometColumnarExchange
Input [2]: [sum#231, count#232]
Arguments: SinglePartition, ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=11]

(167) ColumnarToRow [codegen id : 2]
Input [2]: [sum#231, count#232]

(168) HashAggregate [codegen id : 2]
Input [2]: [sum#231, count#232]
Keys: []
Functions [1]: [avg((cast(quantity#212 as decimal(10,0)) * list_price#213))]
Aggregate Attributes [1]: [avg((cast(quantity#212 as decimal(10,0)) * list_price#213))#233]
Results [1]: [avg((cast(quantity#212 as decimal(10,0)) * list_price#213))#233 AS average_sales#234]

Subquery:2 Hosting operator id = 147 Hosting Expression = ss_sold_date_sk#209 IN dynamicpruning#12

Subquery:3 Hosting operator id = 151 Hosting Expression = cs_sold_date_sk#216 IN dynamicpruning#217
BroadcastExchange (173)
+- * ColumnarToRow (172)
   +- CometProject (171)
      +- CometFilter (170)
         +- CometScan parquet spark_catalog.default.date_dim (169)


(169) Scan parquet spark_catalog.default.date_dim
Output [2]: [d_date_sk#218, d_year#219]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_year), GreaterThanOrEqual(d_year,1998), LessThanOrEqual(d_year,2000), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int>

(170) CometFilter
Input [2]: [d_date_sk#218, d_year#219]
Condition : (((isnotnull(d_year#219) AND (d_year#219 >= 1998)) AND (d_year#219 <= 2000)) AND isnotnull(d_date_sk#218))

(171) CometProject
Input [2]: [d_date_sk#218, d_year#219]
Arguments: [d_date_sk#218], [d_date_sk#218]

(172) ColumnarToRow [codegen id : 1]
Input [1]: [d_date_sk#218]

(173) BroadcastExchange
Input [1]: [d_date_sk#218]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=12]

Subquery:4 Hosting operator id = 158 Hosting Expression = ws_sold_date_sk#224 IN dynamicpruning#217

Subquery:5 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#4 IN dynamicpruning#5
BroadcastExchange (178)
+- * ColumnarToRow (177)
   +- CometProject (176)
      +- CometFilter (175)
         +- CometScan parquet spark_catalog.default.date_dim (174)


(174) Scan parquet spark_catalog.default.date_dim
Output [3]: [d_date_sk#43, d_year#44, d_moy#45]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2000), EqualTo(d_moy,11), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int,d_moy:int>

(175) CometFilter
Input [3]: [d_date_sk#43, d_year#44, d_moy#45]
Condition : ((((isnotnull(d_year#44) AND isnotnull(d_moy#45)) AND (d_year#44 = 2000)) AND (d_moy#45 = 11)) AND isnotnull(d_date_sk#43))

(176) CometProject
Input [3]: [d_date_sk#43, d_year#44, d_moy#45]
Arguments: [d_date_sk#43], [d_date_sk#43]

(177) ColumnarToRow [codegen id : 1]
Input [1]: [d_date_sk#43]

(178) BroadcastExchange
Input [1]: [d_date_sk#43]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=13]

Subquery:6 Hosting operator id = 5 Hosting Expression = ss_sold_date_sk#11 IN dynamicpruning#12
BroadcastExchange (183)
+- * ColumnarToRow (182)
   +- CometProject (181)
      +- CometFilter (180)
         +- CometScan parquet spark_catalog.default.date_dim (179)


(179) Scan parquet spark_catalog.default.date_dim
Output [2]: [d_date_sk#26, d_year#235]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_year), GreaterThanOrEqual(d_year,1999), LessThanOrEqual(d_year,2001), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int>

(180) CometFilter
Input [2]: [d_date_sk#26, d_year#235]
Condition : (((isnotnull(d_year#235) AND (d_year#235 >= 1999)) AND (d_year#235 <= 2001)) AND isnotnull(d_date_sk#26))

(181) CometProject
Input [2]: [d_date_sk#26, d_year#235]
Arguments: [d_date_sk#26], [d_date_sk#26]

(182) ColumnarToRow [codegen id : 1]
Input [1]: [d_date_sk#26]

(183) BroadcastExchange
Input [1]: [d_date_sk#26]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=14]

Subquery:7 Hosting operator id = 9 Hosting Expression = cs_sold_date_sk#18 IN dynamicpruning#12

Subquery:8 Hosting operator id = 33 Hosting Expression = ws_sold_date_sk#31 IN dynamicpruning#12

Subquery:9 Hosting operator id = 84 Hosting Expression = ReusedSubquery Subquery scalar-subquery#57, [id=#58]

Subquery:10 Hosting operator id = 68 Hosting Expression = cs_sold_date_sk#62 IN dynamicpruning#5

Subquery:11 Hosting operator id = 101 Hosting Expression = ReusedSubquery Subquery scalar-subquery#57, [id=#58]

Subquery:12 Hosting operator id = 85 Hosting Expression = ws_sold_date_sk#84 IN dynamicpruning#5


