== Physical Plan ==
TakeOrderedAndProject (52)
+- * Project (51)
   +- Window (50)
      +- * ColumnarToRow (49)
         +- CometSort (48)
            +- CometColumnarExchange (47)
               +- CometHashAggregate (46)
                  +- CometColumnarExchange (45)
                     +- RowToColumnar (44)
                        +- * HashAggregate (43)
                           +- Union (42)
                              :- * HashAggregate (25)
                              :  +- * ColumnarToRow (24)
                              :     +- CometColumnarExchange (23)
                              :        +- RowToColumnar (22)
                              :           +- * HashAggregate (21)
                              :              +- * ColumnarToRow (20)
                              :                 +- CometProject (19)
                              :                    +- CometBroadcastHashJoin (18)
                              :                       :- CometProject (13)
                              :                       :  +- CometBroadcastHashJoin (12)
                              :                       :     :- CometProject (8)
                              :                       :     :  +- CometBroadcastHashJoin (7)
                              :                       :     :     :- CometFilter (2)
                              :                       :     :     :  +- CometScan parquet spark_catalog.default.store_sales (1)
                              :                       :     :     +- CometBroadcastExchange (6)
                              :                       :     :        +- CometProject (5)
                              :                       :     :           +- CometFilter (4)
                              :                       :     :              +- CometScan parquet spark_catalog.default.date_dim (3)
                              :                       :     +- CometBroadcastExchange (11)
                              :                       :        +- CometFilter (10)
                              :                       :           +- CometScan parquet spark_catalog.default.item (9)
                              :                       +- CometBroadcastExchange (17)
                              :                          +- CometProject (16)
                              :                             +- CometFilter (15)
                              :                                +- CometScan parquet spark_catalog.default.store (14)
                              :- * HashAggregate (33)
                              :  +- * ColumnarToRow (32)
                              :     +- CometColumnarExchange (31)
                              :        +- RowToColumnar (30)
                              :           +- * HashAggregate (29)
                              :              +- * HashAggregate (28)
                              :                 +- * ColumnarToRow (27)
                              :                    +- ReusedExchange (26)
                              +- * HashAggregate (41)
                                 +- * ColumnarToRow (40)
                                    +- CometColumnarExchange (39)
                                       +- RowToColumnar (38)
                                          +- * HashAggregate (37)
                                             +- * HashAggregate (36)
                                                +- * ColumnarToRow (35)
                                                   +- ReusedExchange (34)


(1) Scan parquet spark_catalog.default.store_sales
Output [5]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, ss_sold_date_sk#5]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(ss_sold_date_sk#5), dynamicpruningexpression(ss_sold_date_sk#5 IN dynamicpruning#6)]
PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_store_sk)]
ReadSchema: struct<ss_item_sk:int,ss_store_sk:int,ss_ext_sales_price:decimal(7,2),ss_net_profit:decimal(7,2)>

(2) CometFilter
Input [5]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, ss_sold_date_sk#5]
Condition : (isnotnull(ss_item_sk#1) AND isnotnull(ss_store_sk#2))

(3) Scan parquet spark_catalog.default.date_dim
Output [2]: [d_date_sk#7, d_year#8]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int>

(4) CometFilter
Input [2]: [d_date_sk#7, d_year#8]
Condition : ((isnotnull(d_year#8) AND (d_year#8 = 2001)) AND isnotnull(d_date_sk#7))

(5) CometProject
Input [2]: [d_date_sk#7, d_year#8]
Arguments: [d_date_sk#7], [d_date_sk#7]

(6) CometBroadcastExchange
Input [1]: [d_date_sk#7]
Arguments: [d_date_sk#7]

(7) CometBroadcastHashJoin
Left output [5]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, ss_sold_date_sk#5]
Right output [1]: [d_date_sk#7]
Arguments: [ss_sold_date_sk#5], [d_date_sk#7], Inner, BuildRight

(8) CometProject
Input [6]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, ss_sold_date_sk#5, d_date_sk#7]
Arguments: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4], [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4]

(9) Scan parquet spark_catalog.default.item
Output [3]: [i_item_sk#9, i_class#10, i_category#11]
Batched: true
Location [not included in comparison]/{warehouse_dir}/item]
PushedFilters: [IsNotNull(i_item_sk)]
ReadSchema: struct<i_item_sk:int,i_class:string,i_category:string>

(10) CometFilter
Input [3]: [i_item_sk#9, i_class#10, i_category#11]
Condition : isnotnull(i_item_sk#9)

(11) CometBroadcastExchange
Input [3]: [i_item_sk#9, i_class#10, i_category#11]
Arguments: [i_item_sk#9, i_class#10, i_category#11]

(12) CometBroadcastHashJoin
Left output [4]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4]
Right output [3]: [i_item_sk#9, i_class#10, i_category#11]
Arguments: [ss_item_sk#1], [i_item_sk#9], Inner, BuildRight

(13) CometProject
Input [7]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, i_item_sk#9, i_class#10, i_category#11]
Arguments: [ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, i_class#10, i_category#11], [ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, i_class#10, i_category#11]

(14) Scan parquet spark_catalog.default.store
Output [2]: [s_store_sk#12, s_state#13]
Batched: true
Location [not included in comparison]/{warehouse_dir}/store]
PushedFilters: [IsNotNull(s_state), EqualTo(s_state,TN), IsNotNull(s_store_sk)]
ReadSchema: struct<s_store_sk:int,s_state:string>

(15) CometFilter
Input [2]: [s_store_sk#12, s_state#13]
Condition : ((isnotnull(s_state#13) AND (s_state#13 = TN)) AND isnotnull(s_store_sk#12))

(16) CometProject
Input [2]: [s_store_sk#12, s_state#13]
Arguments: [s_store_sk#12], [s_store_sk#12]

(17) CometBroadcastExchange
Input [1]: [s_store_sk#12]
Arguments: [s_store_sk#12]

(18) CometBroadcastHashJoin
Left output [5]: [ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, i_class#10, i_category#11]
Right output [1]: [s_store_sk#12]
Arguments: [ss_store_sk#2], [s_store_sk#12], Inner, BuildRight

(19) CometProject
Input [6]: [ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, i_class#10, i_category#11, s_store_sk#12]
Arguments: [ss_ext_sales_price#3, ss_net_profit#4, i_class#10, i_category#11], [ss_ext_sales_price#3, ss_net_profit#4, i_class#10, i_category#11]

(20) ColumnarToRow [codegen id : 1]
Input [4]: [ss_ext_sales_price#3, ss_net_profit#4, i_class#10, i_category#11]

(21) HashAggregate [codegen id : 1]
Input [4]: [ss_ext_sales_price#3, ss_net_profit#4, i_class#10, i_category#11]
Keys [2]: [i_category#11, i_class#10]
Functions [2]: [partial_sum(UnscaledValue(ss_net_profit#4)), partial_sum(UnscaledValue(ss_ext_sales_price#3))]
Aggregate Attributes [2]: [sum#14, sum#15]
Results [4]: [i_category#11, i_class#10, sum#16, sum#17]

(22) RowToColumnar
Input [4]: [i_category#11, i_class#10, sum#16, sum#17]

(23) CometColumnarExchange
Input [4]: [i_category#11, i_class#10, sum#16, sum#17]
Arguments: hashpartitioning(i_category#11, i_class#10, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=1]

(24) ColumnarToRow [codegen id : 2]
Input [4]: [i_category#11, i_class#10, sum#16, sum#17]

(25) HashAggregate [codegen id : 2]
Input [4]: [i_category#11, i_class#10, sum#16, sum#17]
Keys [2]: [i_category#11, i_class#10]
Functions [2]: [sum(UnscaledValue(ss_net_profit#4)), sum(UnscaledValue(ss_ext_sales_price#3))]
Aggregate Attributes [2]: [sum(UnscaledValue(ss_net_profit#4))#18, sum(UnscaledValue(ss_ext_sales_price#3))#19]
Results [6]: [cast((MakeDecimal(sum(UnscaledValue(ss_net_profit#4))#18,17,2) / MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#3))#19,17,2)) as decimal(38,11)) AS gross_margin#20, i_category#11, i_class#10, 0 AS t_category#21, 0 AS t_class#22, 0 AS lochierarchy#23]

(26) ReusedExchange [Reuses operator id: 23]
Output [4]: [i_category#24, i_class#25, sum#26, sum#27]

(27) ColumnarToRow [codegen id : 4]
Input [4]: [i_category#24, i_class#25, sum#26, sum#27]

(28) HashAggregate [codegen id : 4]
Input [4]: [i_category#24, i_class#25, sum#26, sum#27]
Keys [2]: [i_category#24, i_class#25]
Functions [2]: [sum(UnscaledValue(ss_net_profit#28)), sum(UnscaledValue(ss_ext_sales_price#29))]
Aggregate Attributes [2]: [sum(UnscaledValue(ss_net_profit#28))#30, sum(UnscaledValue(ss_ext_sales_price#29))#31]
Results [3]: [MakeDecimal(sum(UnscaledValue(ss_net_profit#28))#30,17,2) AS ss_net_profit#32, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#29))#31,17,2) AS ss_ext_sales_price#33, i_category#24]

(29) HashAggregate [codegen id : 4]
Input [3]: [ss_net_profit#32, ss_ext_sales_price#33, i_category#24]
Keys [1]: [i_category#24]
Functions [2]: [partial_sum(ss_net_profit#32), partial_sum(ss_ext_sales_price#33)]
Aggregate Attributes [4]: [sum#34, isEmpty#35, sum#36, isEmpty#37]
Results [5]: [i_category#24, sum#38, isEmpty#39, sum#40, isEmpty#41]

(30) RowToColumnar
Input [5]: [i_category#24, sum#38, isEmpty#39, sum#40, isEmpty#41]

(31) CometColumnarExchange
Input [5]: [i_category#24, sum#38, isEmpty#39, sum#40, isEmpty#41]
Arguments: hashpartitioning(i_category#24, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=2]

(32) ColumnarToRow [codegen id : 5]
Input [5]: [i_category#24, sum#38, isEmpty#39, sum#40, isEmpty#41]

(33) HashAggregate [codegen id : 5]
Input [5]: [i_category#24, sum#38, isEmpty#39, sum#40, isEmpty#41]
Keys [1]: [i_category#24]
Functions [2]: [sum(ss_net_profit#32), sum(ss_ext_sales_price#33)]
Aggregate Attributes [2]: [sum(ss_net_profit#32)#42, sum(ss_ext_sales_price#33)#43]
Results [6]: [(sum(ss_net_profit#32)#42 / sum(ss_ext_sales_price#33)#43) AS gross_margin#44, i_category#24, null AS i_class#45, 0 AS t_category#46, 1 AS t_class#47, 1 AS lochierarchy#48]

(34) ReusedExchange [Reuses operator id: 23]
Output [4]: [i_category#49, i_class#50, sum#51, sum#52]

(35) ColumnarToRow [codegen id : 7]
Input [4]: [i_category#49, i_class#50, sum#51, sum#52]

(36) HashAggregate [codegen id : 7]
Input [4]: [i_category#49, i_class#50, sum#51, sum#52]
Keys [2]: [i_category#49, i_class#50]
Functions [2]: [sum(UnscaledValue(ss_net_profit#53)), sum(UnscaledValue(ss_ext_sales_price#54))]
Aggregate Attributes [2]: [sum(UnscaledValue(ss_net_profit#53))#30, sum(UnscaledValue(ss_ext_sales_price#54))#31]
Results [2]: [MakeDecimal(sum(UnscaledValue(ss_net_profit#53))#30,17,2) AS ss_net_profit#55, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#54))#31,17,2) AS ss_ext_sales_price#56]

(37) HashAggregate [codegen id : 7]
Input [2]: [ss_net_profit#55, ss_ext_sales_price#56]
Keys: []
Functions [2]: [partial_sum(ss_net_profit#55), partial_sum(ss_ext_sales_price#56)]
Aggregate Attributes [4]: [sum#57, isEmpty#58, sum#59, isEmpty#60]
Results [4]: [sum#61, isEmpty#62, sum#63, isEmpty#64]

(38) RowToColumnar
Input [4]: [sum#61, isEmpty#62, sum#63, isEmpty#64]

(39) CometColumnarExchange
Input [4]: [sum#61, isEmpty#62, sum#63, isEmpty#64]
Arguments: SinglePartition, ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=3]

(40) ColumnarToRow [codegen id : 8]
Input [4]: [sum#61, isEmpty#62, sum#63, isEmpty#64]

(41) HashAggregate [codegen id : 8]
Input [4]: [sum#61, isEmpty#62, sum#63, isEmpty#64]
Keys: []
Functions [2]: [sum(ss_net_profit#55), sum(ss_ext_sales_price#56)]
Aggregate Attributes [2]: [sum(ss_net_profit#55)#65, sum(ss_ext_sales_price#56)#66]
Results [6]: [(sum(ss_net_profit#55)#65 / sum(ss_ext_sales_price#56)#66) AS gross_margin#67, null AS i_category#68, null AS i_class#69, 1 AS t_category#70, 1 AS t_class#71, 2 AS lochierarchy#72]

(42) Union

(43) HashAggregate [codegen id : 9]
Input [6]: [gross_margin#20, i_category#11, i_class#10, t_category#21, t_class#22, lochierarchy#23]
Keys [6]: [gross_margin#20, i_category#11, i_class#10, t_category#21, t_class#22, lochierarchy#23]
Functions: []
Aggregate Attributes: []
Results [6]: [gross_margin#20, i_category#11, i_class#10, t_category#21, t_class#22, lochierarchy#23]

(44) RowToColumnar
Input [6]: [gross_margin#20, i_category#11, i_class#10, t_category#21, t_class#22, lochierarchy#23]

(45) CometColumnarExchange
Input [6]: [gross_margin#20, i_category#11, i_class#10, t_category#21, t_class#22, lochierarchy#23]
Arguments: hashpartitioning(gross_margin#20, i_category#11, i_class#10, t_category#21, t_class#22, lochierarchy#23, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=4]

(46) CometHashAggregate
Input [6]: [gross_margin#20, i_category#11, i_class#10, t_category#21, t_class#22, lochierarchy#23]
Keys [6]: [gross_margin#20, i_category#11, i_class#10, t_category#21, t_class#22, lochierarchy#23]
Functions: []

(47) CometColumnarExchange
Input [5]: [gross_margin#20, i_category#11, i_class#10, lochierarchy#23, _w0#73]
Arguments: hashpartitioning(lochierarchy#23, _w0#73, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=5]

(48) CometSort
Input [5]: [gross_margin#20, i_category#11, i_class#10, lochierarchy#23, _w0#73]
Arguments: [gross_margin#20, i_category#11, i_class#10, lochierarchy#23, _w0#73], [lochierarchy#23 ASC NULLS FIRST, _w0#73 ASC NULLS FIRST, gross_margin#20 ASC NULLS FIRST]

(49) ColumnarToRow [codegen id : 10]
Input [5]: [gross_margin#20, i_category#11, i_class#10, lochierarchy#23, _w0#73]

(50) Window
Input [5]: [gross_margin#20, i_category#11, i_class#10, lochierarchy#23, _w0#73]
Arguments: [rank(gross_margin#20) windowspecdefinition(lochierarchy#23, _w0#73, gross_margin#20 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rank_within_parent#74], [lochierarchy#23, _w0#73], [gross_margin#20 ASC NULLS FIRST]

(51) Project [codegen id : 11]
Output [5]: [gross_margin#20, i_category#11, i_class#10, lochierarchy#23, rank_within_parent#74]
Input [6]: [gross_margin#20, i_category#11, i_class#10, lochierarchy#23, _w0#73, rank_within_parent#74]

(52) TakeOrderedAndProject
Input [5]: [gross_margin#20, i_category#11, i_class#10, lochierarchy#23, rank_within_parent#74]
Arguments: 100, [lochierarchy#23 DESC NULLS LAST, CASE WHEN (lochierarchy#23 = 0) THEN i_category#11 END ASC NULLS FIRST, rank_within_parent#74 ASC NULLS FIRST], [gross_margin#20, i_category#11, i_class#10, lochierarchy#23, rank_within_parent#74]

===== Subqueries =====

Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6
BroadcastExchange (57)
+- * ColumnarToRow (56)
   +- CometProject (55)
      +- CometFilter (54)
         +- CometScan parquet spark_catalog.default.date_dim (53)


(53) Scan parquet spark_catalog.default.date_dim
Output [2]: [d_date_sk#7, d_year#8]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int>

(54) CometFilter
Input [2]: [d_date_sk#7, d_year#8]
Condition : ((isnotnull(d_year#8) AND (d_year#8 = 2001)) AND isnotnull(d_date_sk#7))

(55) CometProject
Input [2]: [d_date_sk#7, d_year#8]
Arguments: [d_date_sk#7], [d_date_sk#7]

(56) ColumnarToRow [codegen id : 1]
Input [1]: [d_date_sk#7]

(57) BroadcastExchange
Input [1]: [d_date_sk#7]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6]


