== Physical Plan ==
TakeOrderedAndProject (87)
+- * BroadcastHashJoin Inner BuildRight (86)
   :- * Filter (68)
   :  +- * HashAggregate (67)
   :     +- * CometColumnarToRow (66)
   :        +- CometColumnarExchange (65)
   :           +- * HashAggregate (64)
   :              +- * Project (63)
   :                 +- * BroadcastHashJoin Inner BuildRight (62)
   :                    :- * Project (60)
   :                    :  +- * BroadcastHashJoin Inner BuildRight (59)
   :                    :     :- * BroadcastHashJoin LeftSemi BuildRight (52)
   :                    :     :  :- * Filter (3)
   :                    :     :  :  +- * ColumnarToRow (2)
   :                    :     :  :     +- Scan parquet spark_catalog.default.store_sales (1)
   :                    :     :  +- BroadcastExchange (51)
   :                    :     :     +- * Project (50)
   :                    :     :        +- * BroadcastHashJoin Inner BuildRight (49)
   :                    :     :           :- * CometColumnarToRow (6)
   :                    :     :           :  +- CometFilter (5)
   :                    :     :           :     +- CometNativeScan parquet spark_catalog.default.item (4)
   :                    :     :           +- BroadcastExchange (48)
   :                    :     :              +- * BroadcastHashJoin LeftSemi BuildRight (47)
   :                    :     :                 :- * CometColumnarToRow (36)
   :                    :     :                 :  +- CometHashAggregate (35)
   :                    :     :                 :     +- CometColumnarExchange (34)
   :                    :     :                 :        +- * HashAggregate (33)
   :                    :     :                 :           +- * Project (32)
   :                    :     :                 :              +- * BroadcastHashJoin Inner BuildRight (31)
   :                    :     :                 :                 :- * Project (29)
   :                    :     :                 :                 :  +- * BroadcastHashJoin Inner BuildRight (28)
   :                    :     :                 :                 :     :- * Filter (9)
   :                    :     :                 :                 :     :  +- * ColumnarToRow (8)
   :                    :     :                 :                 :     :     +- Scan parquet spark_catalog.default.store_sales (7)
   :                    :     :                 :                 :     +- BroadcastExchange (27)
   :                    :     :                 :                 :        +- * BroadcastHashJoin LeftSemi BuildRight (26)
   :                    :     :                 :                 :           :- * CometColumnarToRow (12)
   :                    :     :                 :                 :           :  +- CometFilter (11)
   :                    :     :                 :                 :           :     +- CometNativeScan parquet spark_catalog.default.item (10)
   :                    :     :                 :                 :           +- BroadcastExchange (25)
   :                    :     :                 :                 :              +- * Project (24)
   :                    :     :                 :                 :                 +- * BroadcastHashJoin Inner BuildRight (23)
   :                    :     :                 :                 :                    :- * Project (21)
   :                    :     :                 :                 :                    :  +- * BroadcastHashJoin Inner BuildRight (20)
   :                    :     :                 :                 :                    :     :- * Filter (15)
   :                    :     :                 :                 :                    :     :  +- * ColumnarToRow (14)
   :                    :     :                 :                 :                    :     :     +- Scan parquet spark_catalog.default.catalog_sales (13)
   :                    :     :                 :                 :                    :     +- BroadcastExchange (19)
   :                    :     :                 :                 :                    :        +- * CometColumnarToRow (18)
   :                    :     :                 :                 :                    :           +- CometFilter (17)
   :                    :     :                 :                 :                    :              +- CometNativeScan parquet spark_catalog.default.item (16)
   :                    :     :                 :                 :                    +- ReusedExchange (22)
   :                    :     :                 :                 +- ReusedExchange (30)
   :                    :     :                 +- BroadcastExchange (46)
   :                    :     :                    +- * Project (45)
   :                    :     :                       +- * BroadcastHashJoin Inner BuildRight (44)
   :                    :     :                          :- * Project (42)
   :                    :     :                          :  +- * BroadcastHashJoin Inner BuildRight (41)
   :                    :     :                          :     :- * Filter (39)
   :                    :     :                          :     :  +- * ColumnarToRow (38)
   :                    :     :                          :     :     +- Scan parquet spark_catalog.default.web_sales (37)
   :                    :     :                          :     +- ReusedExchange (40)
   :                    :     :                          +- ReusedExchange (43)
   :                    :     +- BroadcastExchange (58)
   :                    :        +- * BroadcastHashJoin LeftSemi BuildRight (57)
   :                    :           :- * CometColumnarToRow (55)
   :                    :           :  +- CometFilter (54)
   :                    :           :     +- CometNativeScan parquet spark_catalog.default.item (53)
   :                    :           +- ReusedExchange (56)
   :                    +- ReusedExchange (61)
   +- BroadcastExchange (85)
      +- * Filter (84)
         +- * HashAggregate (83)
            +- * CometColumnarToRow (82)
               +- CometColumnarExchange (81)
                  +- * HashAggregate (80)
                     +- * Project (79)
                        +- * BroadcastHashJoin Inner BuildRight (78)
                           :- * Project (76)
                           :  +- * BroadcastHashJoin Inner BuildRight (75)
                           :     :- * BroadcastHashJoin LeftSemi BuildRight (73)
                           :     :  :- * Filter (71)
                           :     :  :  +- * ColumnarToRow (70)
                           :     :  :     +- Scan parquet spark_catalog.default.store_sales (69)
                           :     :  +- ReusedExchange (72)
                           :     +- ReusedExchange (74)
                           +- ReusedExchange (77)


(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) ColumnarToRow [codegen id : 25]
Input [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4]

(3) Filter [codegen id : 25]
Input [4]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4]
Condition : isnotnull(ss_item_sk#1)

(4) CometNativeScan 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>

(5) 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))

(6) CometColumnarToRow [codegen id : 11]
Input [4]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9]

(7) 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>

(8) ColumnarToRow [codegen id : 6]
Input [2]: [ss_item_sk#10, ss_sold_date_sk#11]

(9) Filter [codegen id : 6]
Input [2]: [ss_item_sk#10, ss_sold_date_sk#11]
Condition : isnotnull(ss_item_sk#10)

(10) CometNativeScan 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>

(11) 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))

(12) CometColumnarToRow [codegen id : 4]
Input [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16]

(13) 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#12)]
PushedFilters: [IsNotNull(cs_item_sk)]
ReadSchema: struct<cs_item_sk:int>

(14) ColumnarToRow [codegen id : 3]
Input [2]: [cs_item_sk#17, cs_sold_date_sk#18]

(15) Filter [codegen id : 3]
Input [2]: [cs_item_sk#17, cs_sold_date_sk#18]
Condition : isnotnull(cs_item_sk#17)

(16) CometNativeScan parquet spark_catalog.default.item
Output [4]: [i_item_sk#19, i_brand_id#20, i_class_id#21, i_category_id#22]
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>

(17) CometFilter
Input [4]: [i_item_sk#19, i_brand_id#20, i_class_id#21, i_category_id#22]
Condition : isnotnull(i_item_sk#19)

(18) CometColumnarToRow [codegen id : 1]
Input [4]: [i_item_sk#19, i_brand_id#20, i_class_id#21, i_category_id#22]

(19) BroadcastExchange
Input [4]: [i_item_sk#19, i_brand_id#20, i_class_id#21, i_category_id#22]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1]

(20) BroadcastHashJoin [codegen id : 3]
Left keys [1]: [cs_item_sk#17]
Right keys [1]: [i_item_sk#19]
Join type: Inner
Join condition: None

(21) Project [codegen id : 3]
Output [4]: [cs_sold_date_sk#18, i_brand_id#20, i_class_id#21, i_category_id#22]
Input [6]: [cs_item_sk#17, cs_sold_date_sk#18, i_item_sk#19, i_brand_id#20, i_class_id#21, i_category_id#22]

(22) ReusedExchange [Reuses operator id: 121]
Output [1]: [d_date_sk#23]

(23) BroadcastHashJoin [codegen id : 3]
Left keys [1]: [cs_sold_date_sk#18]
Right keys [1]: [d_date_sk#23]
Join type: Inner
Join condition: None

(24) Project [codegen id : 3]
Output [3]: [i_brand_id#20, i_class_id#21, i_category_id#22]
Input [5]: [cs_sold_date_sk#18, i_brand_id#20, i_class_id#21, i_category_id#22, d_date_sk#23]

(25) BroadcastExchange
Input [3]: [i_brand_id#20, i_class_id#21, i_category_id#22]
Arguments: HashedRelationBroadcastMode(List(coalesce(input[0, int, true], 0), isnull(input[0, int, true]), coalesce(input[1, int, true], 0), isnull(input[1, int, true]), coalesce(input[2, int, true], 0), isnull(input[2, int, true])),false), [plan_id=2]

(26) BroadcastHashJoin [codegen id : 4]
Left keys [6]: [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)]
Right keys [6]: [coalesce(i_brand_id#20, 0), isnull(i_brand_id#20), coalesce(i_class_id#21, 0), isnull(i_class_id#21), coalesce(i_category_id#22, 0), isnull(i_category_id#22)]
Join type: LeftSemi
Join condition: None

(27) BroadcastExchange
Input [4]: [i_item_sk#13, i_brand_id#14, i_class_id#15, i_category_id#16]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3]

(28) BroadcastHashJoin [codegen id : 6]
Left keys [1]: [ss_item_sk#10]
Right keys [1]: [i_item_sk#13]
Join type: Inner
Join condition: None

(29) Project [codegen id : 6]
Output [4]: [ss_sold_date_sk#11, i_brand_id#14, i_class_id#15, i_category_id#16]
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]

(30) ReusedExchange [Reuses operator id: 121]
Output [1]: [d_date_sk#24]

(31) BroadcastHashJoin [codegen id : 6]
Left keys [1]: [ss_sold_date_sk#11]
Right keys [1]: [d_date_sk#24]
Join type: Inner
Join condition: None

(32) Project [codegen id : 6]
Output [3]: [i_brand_id#14 AS brand_id#25, i_class_id#15 AS class_id#26, i_category_id#16 AS category_id#27]
Input [5]: [ss_sold_date_sk#11, i_brand_id#14, i_class_id#15, i_category_id#16, d_date_sk#24]

(33) HashAggregate [codegen id : 6]
Input [3]: [brand_id#25, class_id#26, category_id#27]
Keys [3]: [brand_id#25, class_id#26, category_id#27]
Functions: []
Aggregate Attributes: []
Results [3]: [brand_id#25, class_id#26, category_id#27]

(34) CometColumnarExchange
Input [3]: [brand_id#25, class_id#26, category_id#27]
Arguments: hashpartitioning(brand_id#25, class_id#26, category_id#27, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=4]

(35) CometHashAggregate
Input [3]: [brand_id#25, class_id#26, category_id#27]
Keys [3]: [brand_id#25, class_id#26, category_id#27]
Functions: []

(36) CometColumnarToRow [codegen id : 10]
Input [3]: [brand_id#25, class_id#26, category_id#27]

(37) Scan parquet spark_catalog.default.web_sales
Output [2]: [ws_item_sk#28, ws_sold_date_sk#29]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(ws_sold_date_sk#29), dynamicpruningexpression(ws_sold_date_sk#29 IN dynamicpruning#12)]
PushedFilters: [IsNotNull(ws_item_sk)]
ReadSchema: struct<ws_item_sk:int>

(38) ColumnarToRow [codegen id : 9]
Input [2]: [ws_item_sk#28, ws_sold_date_sk#29]

(39) Filter [codegen id : 9]
Input [2]: [ws_item_sk#28, ws_sold_date_sk#29]
Condition : isnotnull(ws_item_sk#28)

(40) ReusedExchange [Reuses operator id: 19]
Output [4]: [i_item_sk#30, i_brand_id#31, i_class_id#32, i_category_id#33]

(41) BroadcastHashJoin [codegen id : 9]
Left keys [1]: [ws_item_sk#28]
Right keys [1]: [i_item_sk#30]
Join type: Inner
Join condition: None

(42) Project [codegen id : 9]
Output [4]: [ws_sold_date_sk#29, i_brand_id#31, i_class_id#32, i_category_id#33]
Input [6]: [ws_item_sk#28, ws_sold_date_sk#29, i_item_sk#30, i_brand_id#31, i_class_id#32, i_category_id#33]

(43) ReusedExchange [Reuses operator id: 121]
Output [1]: [d_date_sk#34]

(44) BroadcastHashJoin [codegen id : 9]
Left keys [1]: [ws_sold_date_sk#29]
Right keys [1]: [d_date_sk#34]
Join type: Inner
Join condition: None

(45) Project [codegen id : 9]
Output [3]: [i_brand_id#31, i_class_id#32, i_category_id#33]
Input [5]: [ws_sold_date_sk#29, i_brand_id#31, i_class_id#32, i_category_id#33, d_date_sk#34]

(46) BroadcastExchange
Input [3]: [i_brand_id#31, i_class_id#32, i_category_id#33]
Arguments: HashedRelationBroadcastMode(List(coalesce(input[0, int, true], 0), isnull(input[0, int, true]), coalesce(input[1, int, true], 0), isnull(input[1, int, true]), coalesce(input[2, int, true], 0), isnull(input[2, int, true])),false), [plan_id=5]

(47) BroadcastHashJoin [codegen id : 10]
Left keys [6]: [coalesce(brand_id#25, 0), isnull(brand_id#25), coalesce(class_id#26, 0), isnull(class_id#26), coalesce(category_id#27, 0), isnull(category_id#27)]
Right keys [6]: [coalesce(i_brand_id#31, 0), isnull(i_brand_id#31), coalesce(i_class_id#32, 0), isnull(i_class_id#32), coalesce(i_category_id#33, 0), isnull(i_category_id#33)]
Join type: LeftSemi
Join condition: None

(48) BroadcastExchange
Input [3]: [brand_id#25, class_id#26, category_id#27]
Arguments: HashedRelationBroadcastMode(List(input[0, int, true], input[1, int, true], input[2, int, true]),false), [plan_id=6]

(49) BroadcastHashJoin [codegen id : 11]
Left keys [3]: [i_brand_id#7, i_class_id#8, i_category_id#9]
Right keys [3]: [brand_id#25, class_id#26, category_id#27]
Join type: Inner
Join condition: None

(50) Project [codegen id : 11]
Output [1]: [i_item_sk#6 AS ss_item_sk#35]
Input [7]: [i_item_sk#6, i_brand_id#7, i_class_id#8, i_category_id#9, brand_id#25, class_id#26, category_id#27]

(51) BroadcastExchange
Input [1]: [ss_item_sk#35]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7]

(52) BroadcastHashJoin [codegen id : 25]
Left keys [1]: [ss_item_sk#1]
Right keys [1]: [ss_item_sk#35]
Join type: LeftSemi
Join condition: None

(53) CometNativeScan parquet spark_catalog.default.item
Output [4]: [i_item_sk#36, i_brand_id#37, i_class_id#38, i_category_id#39]
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>

(54) CometFilter
Input [4]: [i_item_sk#36, i_brand_id#37, i_class_id#38, i_category_id#39]
Condition : (((isnotnull(i_item_sk#36) AND isnotnull(i_brand_id#37)) AND isnotnull(i_class_id#38)) AND isnotnull(i_category_id#39))

(55) CometColumnarToRow [codegen id : 23]
Input [4]: [i_item_sk#36, i_brand_id#37, i_class_id#38, i_category_id#39]

(56) ReusedExchange [Reuses operator id: 51]
Output [1]: [ss_item_sk#35]

(57) BroadcastHashJoin [codegen id : 23]
Left keys [1]: [i_item_sk#36]
Right keys [1]: [ss_item_sk#35]
Join type: LeftSemi
Join condition: None

(58) BroadcastExchange
Input [4]: [i_item_sk#36, i_brand_id#37, i_class_id#38, i_category_id#39]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=8]

(59) BroadcastHashJoin [codegen id : 25]
Left keys [1]: [ss_item_sk#1]
Right keys [1]: [i_item_sk#36]
Join type: Inner
Join condition: None

(60) Project [codegen id : 25]
Output [6]: [ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4, i_brand_id#37, i_class_id#38, i_category_id#39]
Input [8]: [ss_item_sk#1, ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4, i_item_sk#36, i_brand_id#37, i_class_id#38, i_category_id#39]

(61) ReusedExchange [Reuses operator id: 112]
Output [1]: [d_date_sk#40]

(62) BroadcastHashJoin [codegen id : 25]
Left keys [1]: [ss_sold_date_sk#4]
Right keys [1]: [d_date_sk#40]
Join type: Inner
Join condition: None

(63) Project [codegen id : 25]
Output [5]: [ss_quantity#2, ss_list_price#3, i_brand_id#37, i_class_id#38, i_category_id#39]
Input [7]: [ss_quantity#2, ss_list_price#3, ss_sold_date_sk#4, i_brand_id#37, i_class_id#38, i_category_id#39, d_date_sk#40]

(64) HashAggregate [codegen id : 25]
Input [5]: [ss_quantity#2, ss_list_price#3, i_brand_id#37, i_class_id#38, i_category_id#39]
Keys [3]: [i_brand_id#37, i_class_id#38, i_category_id#39]
Functions [2]: [partial_sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3)), partial_count(1)]
Aggregate Attributes [3]: [sum#41, isEmpty#42, count#43]
Results [6]: [i_brand_id#37, i_class_id#38, i_category_id#39, sum#44, isEmpty#45, count#46]

(65) CometColumnarExchange
Input [6]: [i_brand_id#37, i_class_id#38, i_category_id#39, sum#44, isEmpty#45, count#46]
Arguments: hashpartitioning(i_brand_id#37, i_class_id#38, i_category_id#39, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=9]

(66) CometColumnarToRow [codegen id : 52]
Input [6]: [i_brand_id#37, i_class_id#38, i_category_id#39, sum#44, isEmpty#45, count#46]

(67) HashAggregate [codegen id : 52]
Input [6]: [i_brand_id#37, i_class_id#38, i_category_id#39, sum#44, isEmpty#45, count#46]
Keys [3]: [i_brand_id#37, i_class_id#38, i_category_id#39]
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))#47, count(1)#48]
Results [6]: [store AS channel#49, i_brand_id#37, i_class_id#38, i_category_id#39, sum((cast(ss_quantity#2 as decimal(10,0)) * ss_list_price#3))#47 AS sales#50, count(1)#48 AS number_sales#51]

(68) Filter [codegen id : 52]
Input [6]: [channel#49, i_brand_id#37, i_class_id#38, i_category_id#39, sales#50, number_sales#51]
Condition : (isnotnull(sales#50) AND (cast(sales#50 as decimal(32,6)) > cast(Subquery scalar-subquery#52, [id=#53] as decimal(32,6))))

(69) Scan parquet spark_catalog.default.store_sales
Output [4]: [ss_item_sk#54, ss_quantity#55, ss_list_price#56, ss_sold_date_sk#57]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(ss_sold_date_sk#57), dynamicpruningexpression(ss_sold_date_sk#57 IN dynamicpruning#58)]
PushedFilters: [IsNotNull(ss_item_sk)]
ReadSchema: struct<ss_item_sk:int,ss_quantity:int,ss_list_price:decimal(7,2)>

(70) ColumnarToRow [codegen id : 50]
Input [4]: [ss_item_sk#54, ss_quantity#55, ss_list_price#56, ss_sold_date_sk#57]

(71) Filter [codegen id : 50]
Input [4]: [ss_item_sk#54, ss_quantity#55, ss_list_price#56, ss_sold_date_sk#57]
Condition : isnotnull(ss_item_sk#54)

(72) ReusedExchange [Reuses operator id: 51]
Output [1]: [ss_item_sk#35]

(73) BroadcastHashJoin [codegen id : 50]
Left keys [1]: [ss_item_sk#54]
Right keys [1]: [ss_item_sk#35]
Join type: LeftSemi
Join condition: None

(74) ReusedExchange [Reuses operator id: 58]
Output [4]: [i_item_sk#59, i_brand_id#60, i_class_id#61, i_category_id#62]

(75) BroadcastHashJoin [codegen id : 50]
Left keys [1]: [ss_item_sk#54]
Right keys [1]: [i_item_sk#59]
Join type: Inner
Join condition: None

(76) Project [codegen id : 50]
Output [6]: [ss_quantity#55, ss_list_price#56, ss_sold_date_sk#57, i_brand_id#60, i_class_id#61, i_category_id#62]
Input [8]: [ss_item_sk#54, ss_quantity#55, ss_list_price#56, ss_sold_date_sk#57, i_item_sk#59, i_brand_id#60, i_class_id#61, i_category_id#62]

(77) ReusedExchange [Reuses operator id: 126]
Output [1]: [d_date_sk#63]

(78) BroadcastHashJoin [codegen id : 50]
Left keys [1]: [ss_sold_date_sk#57]
Right keys [1]: [d_date_sk#63]
Join type: Inner
Join condition: None

(79) Project [codegen id : 50]
Output [5]: [ss_quantity#55, ss_list_price#56, i_brand_id#60, i_class_id#61, i_category_id#62]
Input [7]: [ss_quantity#55, ss_list_price#56, ss_sold_date_sk#57, i_brand_id#60, i_class_id#61, i_category_id#62, d_date_sk#63]

(80) HashAggregate [codegen id : 50]
Input [5]: [ss_quantity#55, ss_list_price#56, i_brand_id#60, i_class_id#61, i_category_id#62]
Keys [3]: [i_brand_id#60, i_class_id#61, i_category_id#62]
Functions [2]: [partial_sum((cast(ss_quantity#55 as decimal(10,0)) * ss_list_price#56)), partial_count(1)]
Aggregate Attributes [3]: [sum#64, isEmpty#65, count#66]
Results [6]: [i_brand_id#60, i_class_id#61, i_category_id#62, sum#67, isEmpty#68, count#69]

(81) CometColumnarExchange
Input [6]: [i_brand_id#60, i_class_id#61, i_category_id#62, sum#67, isEmpty#68, count#69]
Arguments: hashpartitioning(i_brand_id#60, i_class_id#61, i_category_id#62, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=10]

(82) CometColumnarToRow [codegen id : 51]
Input [6]: [i_brand_id#60, i_class_id#61, i_category_id#62, sum#67, isEmpty#68, count#69]

(83) HashAggregate [codegen id : 51]
Input [6]: [i_brand_id#60, i_class_id#61, i_category_id#62, sum#67, isEmpty#68, count#69]
Keys [3]: [i_brand_id#60, i_class_id#61, i_category_id#62]
Functions [2]: [sum((cast(ss_quantity#55 as decimal(10,0)) * ss_list_price#56)), count(1)]
Aggregate Attributes [2]: [sum((cast(ss_quantity#55 as decimal(10,0)) * ss_list_price#56))#70, count(1)#71]
Results [6]: [store AS channel#72, i_brand_id#60, i_class_id#61, i_category_id#62, sum((cast(ss_quantity#55 as decimal(10,0)) * ss_list_price#56))#70 AS sales#73, count(1)#71 AS number_sales#74]

(84) Filter [codegen id : 51]
Input [6]: [channel#72, i_brand_id#60, i_class_id#61, i_category_id#62, sales#73, number_sales#74]
Condition : (isnotnull(sales#73) AND (cast(sales#73 as decimal(32,6)) > cast(ReusedSubquery Subquery scalar-subquery#52, [id=#53] as decimal(32,6))))

(85) BroadcastExchange
Input [6]: [channel#72, i_brand_id#60, i_class_id#61, i_category_id#62, sales#73, number_sales#74]
Arguments: HashedRelationBroadcastMode(List(input[1, int, true], input[2, int, true], input[3, int, true]),false), [plan_id=11]

(86) BroadcastHashJoin [codegen id : 52]
Left keys [3]: [i_brand_id#37, i_class_id#38, i_category_id#39]
Right keys [3]: [i_brand_id#60, i_class_id#61, i_category_id#62]
Join type: Inner
Join condition: None

(87) TakeOrderedAndProject
Input [12]: [channel#49, i_brand_id#37, i_class_id#38, i_category_id#39, sales#50, number_sales#51, channel#72, i_brand_id#60, i_class_id#61, i_category_id#62, sales#73, number_sales#74]
Arguments: 100, [i_brand_id#37 ASC NULLS FIRST, i_class_id#38 ASC NULLS FIRST, i_category_id#39 ASC NULLS FIRST], [channel#49, i_brand_id#37, i_class_id#38, i_category_id#39, sales#50, number_sales#51, channel#72, i_brand_id#60, i_class_id#61, i_category_id#62, sales#73, number_sales#74]

===== Subqueries =====

Subquery:1 Hosting operator id = 68 Hosting Expression = Subquery scalar-subquery#52, [id=#53]
* HashAggregate (107)
+- * CometColumnarToRow (106)
   +- CometColumnarExchange (105)
      +- * HashAggregate (104)
         +- Union (103)
            :- * Project (92)
            :  +- * BroadcastHashJoin Inner BuildRight (91)
            :     :- * ColumnarToRow (89)
            :     :  +- Scan parquet spark_catalog.default.store_sales (88)
            :     +- ReusedExchange (90)
            :- * Project (97)
            :  +- * BroadcastHashJoin Inner BuildRight (96)
            :     :- * ColumnarToRow (94)
            :     :  +- Scan parquet spark_catalog.default.catalog_sales (93)
            :     +- ReusedExchange (95)
            +- * Project (102)
               +- * BroadcastHashJoin Inner BuildRight (101)
                  :- * ColumnarToRow (99)
                  :  +- Scan parquet spark_catalog.default.web_sales (98)
                  +- ReusedExchange (100)


(88) Scan parquet spark_catalog.default.store_sales
Output [3]: [ss_quantity#75, ss_list_price#76, ss_sold_date_sk#77]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(ss_sold_date_sk#77), dynamicpruningexpression(ss_sold_date_sk#77 IN dynamicpruning#12)]
ReadSchema: struct<ss_quantity:int,ss_list_price:decimal(7,2)>

(89) ColumnarToRow [codegen id : 2]
Input [3]: [ss_quantity#75, ss_list_price#76, ss_sold_date_sk#77]

(90) ReusedExchange [Reuses operator id: 121]
Output [1]: [d_date_sk#78]

(91) BroadcastHashJoin [codegen id : 2]
Left keys [1]: [ss_sold_date_sk#77]
Right keys [1]: [d_date_sk#78]
Join type: Inner
Join condition: None

(92) Project [codegen id : 2]
Output [2]: [ss_quantity#75 AS quantity#79, ss_list_price#76 AS list_price#80]
Input [4]: [ss_quantity#75, ss_list_price#76, ss_sold_date_sk#77, d_date_sk#78]

(93) Scan parquet spark_catalog.default.catalog_sales
Output [3]: [cs_quantity#81, cs_list_price#82, cs_sold_date_sk#83]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(cs_sold_date_sk#83), dynamicpruningexpression(cs_sold_date_sk#83 IN dynamicpruning#12)]
ReadSchema: struct<cs_quantity:int,cs_list_price:decimal(7,2)>

(94) ColumnarToRow [codegen id : 4]
Input [3]: [cs_quantity#81, cs_list_price#82, cs_sold_date_sk#83]

(95) ReusedExchange [Reuses operator id: 121]
Output [1]: [d_date_sk#84]

(96) BroadcastHashJoin [codegen id : 4]
Left keys [1]: [cs_sold_date_sk#83]
Right keys [1]: [d_date_sk#84]
Join type: Inner
Join condition: None

(97) Project [codegen id : 4]
Output [2]: [cs_quantity#81 AS quantity#85, cs_list_price#82 AS list_price#86]
Input [4]: [cs_quantity#81, cs_list_price#82, cs_sold_date_sk#83, d_date_sk#84]

(98) Scan parquet spark_catalog.default.web_sales
Output [3]: [ws_quantity#87, ws_list_price#88, ws_sold_date_sk#89]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(ws_sold_date_sk#89), dynamicpruningexpression(ws_sold_date_sk#89 IN dynamicpruning#12)]
ReadSchema: struct<ws_quantity:int,ws_list_price:decimal(7,2)>

(99) ColumnarToRow [codegen id : 6]
Input [3]: [ws_quantity#87, ws_list_price#88, ws_sold_date_sk#89]

(100) ReusedExchange [Reuses operator id: 121]
Output [1]: [d_date_sk#90]

(101) BroadcastHashJoin [codegen id : 6]
Left keys [1]: [ws_sold_date_sk#89]
Right keys [1]: [d_date_sk#90]
Join type: Inner
Join condition: None

(102) Project [codegen id : 6]
Output [2]: [ws_quantity#87 AS quantity#91, ws_list_price#88 AS list_price#92]
Input [4]: [ws_quantity#87, ws_list_price#88, ws_sold_date_sk#89, d_date_sk#90]

(103) Union

(104) HashAggregate [codegen id : 7]
Input [2]: [quantity#79, list_price#80]
Keys: []
Functions [1]: [partial_avg((cast(quantity#79 as decimal(10,0)) * list_price#80))]
Aggregate Attributes [2]: [sum#93, count#94]
Results [2]: [sum#95, count#96]

(105) CometColumnarExchange
Input [2]: [sum#95, count#96]
Arguments: SinglePartition, ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=12]

(106) CometColumnarToRow [codegen id : 8]
Input [2]: [sum#95, count#96]

(107) HashAggregate [codegen id : 8]
Input [2]: [sum#95, count#96]
Keys: []
Functions [1]: [avg((cast(quantity#79 as decimal(10,0)) * list_price#80))]
Aggregate Attributes [1]: [avg((cast(quantity#79 as decimal(10,0)) * list_price#80))#97]
Results [1]: [avg((cast(quantity#79 as decimal(10,0)) * list_price#80))#97 AS average_sales#98]

Subquery:2 Hosting operator id = 88 Hosting Expression = ss_sold_date_sk#77 IN dynamicpruning#12

Subquery:3 Hosting operator id = 93 Hosting Expression = cs_sold_date_sk#83 IN dynamicpruning#12

Subquery:4 Hosting operator id = 98 Hosting Expression = ws_sold_date_sk#89 IN dynamicpruning#12

Subquery:5 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#4 IN dynamicpruning#5
BroadcastExchange (112)
+- * CometColumnarToRow (111)
   +- CometProject (110)
      +- CometFilter (109)
         +- CometNativeScan parquet spark_catalog.default.date_dim (108)


(108) CometNativeScan parquet spark_catalog.default.date_dim
Output [2]: [d_date_sk#40, d_week_seq#99]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_week_seq), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_week_seq:int>

(109) CometFilter
Input [2]: [d_date_sk#40, d_week_seq#99]
Condition : ((isnotnull(d_week_seq#99) AND (d_week_seq#99 = Subquery scalar-subquery#100, [id=#101])) AND isnotnull(d_date_sk#40))

(110) CometProject
Input [2]: [d_date_sk#40, d_week_seq#99]
Arguments: [d_date_sk#40], [d_date_sk#40]

(111) CometColumnarToRow [codegen id : 1]
Input [1]: [d_date_sk#40]

(112) BroadcastExchange
Input [1]: [d_date_sk#40]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=13]

Subquery:6 Hosting operator id = 109 Hosting Expression = Subquery scalar-subquery#100, [id=#101]
* CometColumnarToRow (116)
+- CometProject (115)
   +- CometFilter (114)
      +- CometNativeScan parquet spark_catalog.default.date_dim (113)


(113) CometNativeScan parquet spark_catalog.default.date_dim
Output [4]: [d_week_seq#102, d_year#103, d_moy#104, d_dom#105]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), IsNotNull(d_dom), EqualTo(d_year,1999), EqualTo(d_moy,12), EqualTo(d_dom,16)]
ReadSchema: struct<d_week_seq:int,d_year:int,d_moy:int,d_dom:int>

(114) CometFilter
Input [4]: [d_week_seq#102, d_year#103, d_moy#104, d_dom#105]
Condition : (((((isnotnull(d_year#103) AND isnotnull(d_moy#104)) AND isnotnull(d_dom#105)) AND (d_year#103 = 1999)) AND (d_moy#104 = 12)) AND (d_dom#105 = 16))

(115) CometProject
Input [4]: [d_week_seq#102, d_year#103, d_moy#104, d_dom#105]
Arguments: [d_week_seq#102], [d_week_seq#102]

(116) CometColumnarToRow [codegen id : 1]
Input [1]: [d_week_seq#102]

Subquery:7 Hosting operator id = 7 Hosting Expression = ss_sold_date_sk#11 IN dynamicpruning#12
BroadcastExchange (121)
+- * CometColumnarToRow (120)
   +- CometProject (119)
      +- CometFilter (118)
         +- CometNativeScan parquet spark_catalog.default.date_dim (117)


(117) CometNativeScan parquet spark_catalog.default.date_dim
Output [2]: [d_date_sk#24, d_year#103]
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>

(118) CometFilter
Input [2]: [d_date_sk#24, d_year#103]
Condition : (((isnotnull(d_year#103) AND (d_year#103 >= 1998)) AND (d_year#103 <= 2000)) AND isnotnull(d_date_sk#24))

(119) CometProject
Input [2]: [d_date_sk#24, d_year#103]
Arguments: [d_date_sk#24], [d_date_sk#24]

(120) CometColumnarToRow [codegen id : 1]
Input [1]: [d_date_sk#24]

(121) BroadcastExchange
Input [1]: [d_date_sk#24]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=14]

Subquery:8 Hosting operator id = 13 Hosting Expression = cs_sold_date_sk#18 IN dynamicpruning#12

Subquery:9 Hosting operator id = 37 Hosting Expression = ws_sold_date_sk#29 IN dynamicpruning#12

Subquery:10 Hosting operator id = 84 Hosting Expression = ReusedSubquery Subquery scalar-subquery#52, [id=#53]

Subquery:11 Hosting operator id = 69 Hosting Expression = ss_sold_date_sk#57 IN dynamicpruning#58
BroadcastExchange (126)
+- * CometColumnarToRow (125)
   +- CometProject (124)
      +- CometFilter (123)
         +- CometNativeScan parquet spark_catalog.default.date_dim (122)


(122) CometNativeScan parquet spark_catalog.default.date_dim
Output [2]: [d_date_sk#63, d_week_seq#106]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_week_seq), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_week_seq:int>

(123) CometFilter
Input [2]: [d_date_sk#63, d_week_seq#106]
Condition : ((isnotnull(d_week_seq#106) AND (d_week_seq#106 = Subquery scalar-subquery#107, [id=#108])) AND isnotnull(d_date_sk#63))

(124) CometProject
Input [2]: [d_date_sk#63, d_week_seq#106]
Arguments: [d_date_sk#63], [d_date_sk#63]

(125) CometColumnarToRow [codegen id : 1]
Input [1]: [d_date_sk#63]

(126) BroadcastExchange
Input [1]: [d_date_sk#63]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=15]

Subquery:12 Hosting operator id = 123 Hosting Expression = Subquery scalar-subquery#107, [id=#108]
* CometColumnarToRow (130)
+- CometProject (129)
   +- CometFilter (128)
      +- CometNativeScan parquet spark_catalog.default.date_dim (127)


(127) CometNativeScan parquet spark_catalog.default.date_dim
Output [4]: [d_week_seq#102, d_year#103, d_moy#104, d_dom#105]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), IsNotNull(d_dom), EqualTo(d_year,1998), EqualTo(d_moy,12), EqualTo(d_dom,16)]
ReadSchema: struct<d_week_seq:int,d_year:int,d_moy:int,d_dom:int>

(128) CometFilter
Input [4]: [d_week_seq#102, d_year#103, d_moy#104, d_dom#105]
Condition : (((((isnotnull(d_year#103) AND isnotnull(d_moy#104)) AND isnotnull(d_dom#105)) AND (d_year#103 = 1998)) AND (d_moy#104 = 12)) AND (d_dom#105 = 16))

(129) CometProject
Input [4]: [d_week_seq#102, d_year#103, d_moy#104, d_dom#105]
Arguments: [d_week_seq#102], [d_week_seq#102]

(130) CometColumnarToRow [codegen id : 1]
Input [1]: [d_week_seq#102]


