== Physical Plan ==
* CometColumnarToRow (99)
+- CometTakeOrderedAndProject (98)
   +- CometHashAggregate (97)
      +- CometColumnarExchange (96)
         +- * HashAggregate (95)
            +- Union (94)
               :- * HashAggregate (79)
               :  +- * CometColumnarToRow (78)
               :     +- CometColumnarExchange (77)
               :        +- * HashAggregate (76)
               :           +- Union (75)
               :              :- * HashAggregate (23)
               :              :  +- * CometColumnarToRow (22)
               :              :     +- CometColumnarExchange (21)
               :              :        +- * HashAggregate (20)
               :              :           +- * Project (19)
               :              :              +- * BroadcastHashJoin Inner BuildRight (18)
               :              :                 :- * Project (12)
               :              :                 :  +- * BroadcastHashJoin Inner BuildRight (11)
               :              :                 :     :- Union (9)
               :              :                 :     :  :- * Project (4)
               :              :                 :     :  :  +- * Filter (3)
               :              :                 :     :  :     +- * ColumnarToRow (2)
               :              :                 :     :  :        +- Scan parquet spark_catalog.default.store_sales (1)
               :              :                 :     :  +- * Project (8)
               :              :                 :     :     +- * Filter (7)
               :              :                 :     :        +- * ColumnarToRow (6)
               :              :                 :     :           +- Scan parquet spark_catalog.default.store_returns (5)
               :              :                 :     +- ReusedExchange (10)
               :              :                 +- BroadcastExchange (17)
               :              :                    +- * CometColumnarToRow (16)
               :              :                       +- CometProject (15)
               :              :                          +- CometFilter (14)
               :              :                             +- CometNativeScan parquet spark_catalog.default.store (13)
               :              :- * HashAggregate (46)
               :              :  +- * CometColumnarToRow (45)
               :              :     +- CometColumnarExchange (44)
               :              :        +- * HashAggregate (43)
               :              :           +- * Project (42)
               :              :              +- * BroadcastHashJoin Inner BuildRight (41)
               :              :                 :- * Project (35)
               :              :                 :  +- * BroadcastHashJoin Inner BuildRight (34)
               :              :                 :     :- Union (32)
               :              :                 :     :  :- * Project (27)
               :              :                 :     :  :  +- * Filter (26)
               :              :                 :     :  :     +- * ColumnarToRow (25)
               :              :                 :     :  :        +- Scan parquet spark_catalog.default.catalog_sales (24)
               :              :                 :     :  +- * Project (31)
               :              :                 :     :     +- * Filter (30)
               :              :                 :     :        +- * ColumnarToRow (29)
               :              :                 :     :           +- Scan parquet spark_catalog.default.catalog_returns (28)
               :              :                 :     +- ReusedExchange (33)
               :              :                 +- BroadcastExchange (40)
               :              :                    +- * CometColumnarToRow (39)
               :              :                       +- CometProject (38)
               :              :                          +- CometFilter (37)
               :              :                             +- CometNativeScan parquet spark_catalog.default.catalog_page (36)
               :              +- * HashAggregate (74)
               :                 +- * CometColumnarToRow (73)
               :                    +- CometColumnarExchange (72)
               :                       +- * HashAggregate (71)
               :                          +- * Project (70)
               :                             +- * BroadcastHashJoin Inner BuildRight (69)
               :                                :- * Project (63)
               :                                :  +- * BroadcastHashJoin Inner BuildRight (62)
               :                                :     :- Union (60)
               :                                :     :  :- * Project (50)
               :                                :     :  :  +- * Filter (49)
               :                                :     :  :     +- * ColumnarToRow (48)
               :                                :     :  :        +- Scan parquet spark_catalog.default.web_sales (47)
               :                                :     :  +- * Project (59)
               :                                :     :     +- * BroadcastHashJoin Inner BuildLeft (58)
               :                                :     :        :- BroadcastExchange (53)
               :                                :     :        :  +- * ColumnarToRow (52)
               :                                :     :        :     +- Scan parquet spark_catalog.default.web_returns (51)
               :                                :     :        +- * CometColumnarToRow (57)
               :                                :     :           +- CometProject (56)
               :                                :     :              +- CometFilter (55)
               :                                :     :                 +- CometNativeScan parquet spark_catalog.default.web_sales (54)
               :                                :     +- ReusedExchange (61)
               :                                +- BroadcastExchange (68)
               :                                   +- * CometColumnarToRow (67)
               :                                      +- CometProject (66)
               :                                         +- CometFilter (65)
               :                                            +- CometNativeScan parquet spark_catalog.default.web_site (64)
               :- * HashAggregate (86)
               :  +- * CometColumnarToRow (85)
               :     +- CometColumnarExchange (84)
               :        +- * HashAggregate (83)
               :           +- * HashAggregate (82)
               :              +- * CometColumnarToRow (81)
               :                 +- ReusedExchange (80)
               +- * HashAggregate (93)
                  +- * CometColumnarToRow (92)
                     +- CometColumnarExchange (91)
                        +- * HashAggregate (90)
                           +- * HashAggregate (89)
                              +- * CometColumnarToRow (88)
                                 +- ReusedExchange (87)


(1) Scan parquet spark_catalog.default.store_sales
Output [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#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_store_sk)]
ReadSchema: struct<ss_store_sk:int,ss_ext_sales_price:decimal(7,2),ss_net_profit:decimal(7,2)>

(2) ColumnarToRow [codegen id : 1]
Input [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4]

(3) Filter [codegen id : 1]
Input [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4]
Condition : isnotnull(ss_store_sk#1)

(4) Project [codegen id : 1]
Output [6]: [ss_store_sk#1 AS store_sk#6, ss_sold_date_sk#4 AS date_sk#7, ss_ext_sales_price#2 AS sales_price#8, ss_net_profit#3 AS profit#9, 0.00 AS return_amt#10, 0.00 AS net_loss#11]
Input [4]: [ss_store_sk#1, ss_ext_sales_price#2, ss_net_profit#3, ss_sold_date_sk#4]

(5) Scan parquet spark_catalog.default.store_returns
Output [4]: [sr_store_sk#12, sr_return_amt#13, sr_net_loss#14, sr_returned_date_sk#15]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(sr_returned_date_sk#15), dynamicpruningexpression(sr_returned_date_sk#15 IN dynamicpruning#5)]
PushedFilters: [IsNotNull(sr_store_sk)]
ReadSchema: struct<sr_store_sk:int,sr_return_amt:decimal(7,2),sr_net_loss:decimal(7,2)>

(6) ColumnarToRow [codegen id : 2]
Input [4]: [sr_store_sk#12, sr_return_amt#13, sr_net_loss#14, sr_returned_date_sk#15]

(7) Filter [codegen id : 2]
Input [4]: [sr_store_sk#12, sr_return_amt#13, sr_net_loss#14, sr_returned_date_sk#15]
Condition : isnotnull(sr_store_sk#12)

(8) Project [codegen id : 2]
Output [6]: [sr_store_sk#12 AS store_sk#16, sr_returned_date_sk#15 AS date_sk#17, 0.00 AS sales_price#18, 0.00 AS profit#19, sr_return_amt#13 AS return_amt#20, sr_net_loss#14 AS net_loss#21]
Input [4]: [sr_store_sk#12, sr_return_amt#13, sr_net_loss#14, sr_returned_date_sk#15]

(9) Union

(10) ReusedExchange [Reuses operator id: 104]
Output [1]: [d_date_sk#22]

(11) BroadcastHashJoin [codegen id : 5]
Left keys [1]: [date_sk#7]
Right keys [1]: [d_date_sk#22]
Join type: Inner
Join condition: None

(12) Project [codegen id : 5]
Output [5]: [store_sk#6, sales_price#8, profit#9, return_amt#10, net_loss#11]
Input [7]: [store_sk#6, date_sk#7, sales_price#8, profit#9, return_amt#10, net_loss#11, d_date_sk#22]

(13) CometNativeScan parquet spark_catalog.default.store
Output [2]: [s_store_sk#23, s_store_id#24]
Batched: true
Location [not included in comparison]/{warehouse_dir}/store]
PushedFilters: [IsNotNull(s_store_sk)]
ReadSchema: struct<s_store_sk:int,s_store_id:string>

(14) CometFilter
Input [2]: [s_store_sk#23, s_store_id#24]
Condition : isnotnull(s_store_sk#23)

(15) CometProject
Input [2]: [s_store_sk#23, s_store_id#24]
Arguments: [s_store_sk#23, s_store_id#25], [s_store_sk#23, static_invoke(CharVarcharCodegenUtils.readSidePadding(s_store_id#24, 16)) AS s_store_id#25]

(16) CometColumnarToRow [codegen id : 4]
Input [2]: [s_store_sk#23, s_store_id#25]

(17) BroadcastExchange
Input [2]: [s_store_sk#23, s_store_id#25]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1]

(18) BroadcastHashJoin [codegen id : 5]
Left keys [1]: [store_sk#6]
Right keys [1]: [s_store_sk#23]
Join type: Inner
Join condition: None

(19) Project [codegen id : 5]
Output [5]: [sales_price#8, profit#9, return_amt#10, net_loss#11, s_store_id#25]
Input [7]: [store_sk#6, sales_price#8, profit#9, return_amt#10, net_loss#11, s_store_sk#23, s_store_id#25]

(20) HashAggregate [codegen id : 5]
Input [5]: [sales_price#8, profit#9, return_amt#10, net_loss#11, s_store_id#25]
Keys [1]: [s_store_id#25]
Functions [4]: [partial_sum(UnscaledValue(sales_price#8)), partial_sum(UnscaledValue(return_amt#10)), partial_sum(UnscaledValue(profit#9)), partial_sum(UnscaledValue(net_loss#11))]
Aggregate Attributes [4]: [sum#26, sum#27, sum#28, sum#29]
Results [5]: [s_store_id#25, sum#30, sum#31, sum#32, sum#33]

(21) CometColumnarExchange
Input [5]: [s_store_id#25, sum#30, sum#31, sum#32, sum#33]
Arguments: hashpartitioning(s_store_id#25, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=2]

(22) CometColumnarToRow [codegen id : 6]
Input [5]: [s_store_id#25, sum#30, sum#31, sum#32, sum#33]

(23) HashAggregate [codegen id : 6]
Input [5]: [s_store_id#25, sum#30, sum#31, sum#32, sum#33]
Keys [1]: [s_store_id#25]
Functions [4]: [sum(UnscaledValue(sales_price#8)), sum(UnscaledValue(return_amt#10)), sum(UnscaledValue(profit#9)), sum(UnscaledValue(net_loss#11))]
Aggregate Attributes [4]: [sum(UnscaledValue(sales_price#8))#34, sum(UnscaledValue(return_amt#10))#35, sum(UnscaledValue(profit#9))#36, sum(UnscaledValue(net_loss#11))#37]
Results [5]: [store channel AS channel#38, concat(store, s_store_id#25) AS id#39, MakeDecimal(sum(UnscaledValue(sales_price#8))#34,17,2) AS sales#40, MakeDecimal(sum(UnscaledValue(return_amt#10))#35,17,2) AS returns#41, (MakeDecimal(sum(UnscaledValue(profit#9))#36,17,2) - MakeDecimal(sum(UnscaledValue(net_loss#11))#37,17,2)) AS profit#42]

(24) Scan parquet spark_catalog.default.catalog_sales
Output [4]: [cs_catalog_page_sk#43, cs_ext_sales_price#44, cs_net_profit#45, cs_sold_date_sk#46]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(cs_sold_date_sk#46), dynamicpruningexpression(cs_sold_date_sk#46 IN dynamicpruning#5)]
PushedFilters: [IsNotNull(cs_catalog_page_sk)]
ReadSchema: struct<cs_catalog_page_sk:int,cs_ext_sales_price:decimal(7,2),cs_net_profit:decimal(7,2)>

(25) ColumnarToRow [codegen id : 7]
Input [4]: [cs_catalog_page_sk#43, cs_ext_sales_price#44, cs_net_profit#45, cs_sold_date_sk#46]

(26) Filter [codegen id : 7]
Input [4]: [cs_catalog_page_sk#43, cs_ext_sales_price#44, cs_net_profit#45, cs_sold_date_sk#46]
Condition : isnotnull(cs_catalog_page_sk#43)

(27) Project [codegen id : 7]
Output [6]: [cs_catalog_page_sk#43 AS page_sk#47, cs_sold_date_sk#46 AS date_sk#48, cs_ext_sales_price#44 AS sales_price#49, cs_net_profit#45 AS profit#50, 0.00 AS return_amt#51, 0.00 AS net_loss#52]
Input [4]: [cs_catalog_page_sk#43, cs_ext_sales_price#44, cs_net_profit#45, cs_sold_date_sk#46]

(28) Scan parquet spark_catalog.default.catalog_returns
Output [4]: [cr_catalog_page_sk#53, cr_return_amount#54, cr_net_loss#55, cr_returned_date_sk#56]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(cr_returned_date_sk#56), dynamicpruningexpression(cr_returned_date_sk#56 IN dynamicpruning#5)]
PushedFilters: [IsNotNull(cr_catalog_page_sk)]
ReadSchema: struct<cr_catalog_page_sk:int,cr_return_amount:decimal(7,2),cr_net_loss:decimal(7,2)>

(29) ColumnarToRow [codegen id : 8]
Input [4]: [cr_catalog_page_sk#53, cr_return_amount#54, cr_net_loss#55, cr_returned_date_sk#56]

(30) Filter [codegen id : 8]
Input [4]: [cr_catalog_page_sk#53, cr_return_amount#54, cr_net_loss#55, cr_returned_date_sk#56]
Condition : isnotnull(cr_catalog_page_sk#53)

(31) Project [codegen id : 8]
Output [6]: [cr_catalog_page_sk#53 AS page_sk#57, cr_returned_date_sk#56 AS date_sk#58, 0.00 AS sales_price#59, 0.00 AS profit#60, cr_return_amount#54 AS return_amt#61, cr_net_loss#55 AS net_loss#62]
Input [4]: [cr_catalog_page_sk#53, cr_return_amount#54, cr_net_loss#55, cr_returned_date_sk#56]

(32) Union

(33) ReusedExchange [Reuses operator id: 104]
Output [1]: [d_date_sk#63]

(34) BroadcastHashJoin [codegen id : 11]
Left keys [1]: [date_sk#48]
Right keys [1]: [d_date_sk#63]
Join type: Inner
Join condition: None

(35) Project [codegen id : 11]
Output [5]: [page_sk#47, sales_price#49, profit#50, return_amt#51, net_loss#52]
Input [7]: [page_sk#47, date_sk#48, sales_price#49, profit#50, return_amt#51, net_loss#52, d_date_sk#63]

(36) CometNativeScan parquet spark_catalog.default.catalog_page
Output [2]: [cp_catalog_page_sk#64, cp_catalog_page_id#65]
Batched: true
Location [not included in comparison]/{warehouse_dir}/catalog_page]
PushedFilters: [IsNotNull(cp_catalog_page_sk)]
ReadSchema: struct<cp_catalog_page_sk:int,cp_catalog_page_id:string>

(37) CometFilter
Input [2]: [cp_catalog_page_sk#64, cp_catalog_page_id#65]
Condition : isnotnull(cp_catalog_page_sk#64)

(38) CometProject
Input [2]: [cp_catalog_page_sk#64, cp_catalog_page_id#65]
Arguments: [cp_catalog_page_sk#64, cp_catalog_page_id#66], [cp_catalog_page_sk#64, static_invoke(CharVarcharCodegenUtils.readSidePadding(cp_catalog_page_id#65, 16)) AS cp_catalog_page_id#66]

(39) CometColumnarToRow [codegen id : 10]
Input [2]: [cp_catalog_page_sk#64, cp_catalog_page_id#66]

(40) BroadcastExchange
Input [2]: [cp_catalog_page_sk#64, cp_catalog_page_id#66]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3]

(41) BroadcastHashJoin [codegen id : 11]
Left keys [1]: [page_sk#47]
Right keys [1]: [cp_catalog_page_sk#64]
Join type: Inner
Join condition: None

(42) Project [codegen id : 11]
Output [5]: [sales_price#49, profit#50, return_amt#51, net_loss#52, cp_catalog_page_id#66]
Input [7]: [page_sk#47, sales_price#49, profit#50, return_amt#51, net_loss#52, cp_catalog_page_sk#64, cp_catalog_page_id#66]

(43) HashAggregate [codegen id : 11]
Input [5]: [sales_price#49, profit#50, return_amt#51, net_loss#52, cp_catalog_page_id#66]
Keys [1]: [cp_catalog_page_id#66]
Functions [4]: [partial_sum(UnscaledValue(sales_price#49)), partial_sum(UnscaledValue(return_amt#51)), partial_sum(UnscaledValue(profit#50)), partial_sum(UnscaledValue(net_loss#52))]
Aggregate Attributes [4]: [sum#67, sum#68, sum#69, sum#70]
Results [5]: [cp_catalog_page_id#66, sum#71, sum#72, sum#73, sum#74]

(44) CometColumnarExchange
Input [5]: [cp_catalog_page_id#66, sum#71, sum#72, sum#73, sum#74]
Arguments: hashpartitioning(cp_catalog_page_id#66, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=4]

(45) CometColumnarToRow [codegen id : 12]
Input [5]: [cp_catalog_page_id#66, sum#71, sum#72, sum#73, sum#74]

(46) HashAggregate [codegen id : 12]
Input [5]: [cp_catalog_page_id#66, sum#71, sum#72, sum#73, sum#74]
Keys [1]: [cp_catalog_page_id#66]
Functions [4]: [sum(UnscaledValue(sales_price#49)), sum(UnscaledValue(return_amt#51)), sum(UnscaledValue(profit#50)), sum(UnscaledValue(net_loss#52))]
Aggregate Attributes [4]: [sum(UnscaledValue(sales_price#49))#75, sum(UnscaledValue(return_amt#51))#76, sum(UnscaledValue(profit#50))#77, sum(UnscaledValue(net_loss#52))#78]
Results [5]: [catalog channel AS channel#79, concat(catalog_page, cp_catalog_page_id#66) AS id#80, MakeDecimal(sum(UnscaledValue(sales_price#49))#75,17,2) AS sales#81, MakeDecimal(sum(UnscaledValue(return_amt#51))#76,17,2) AS returns#82, (MakeDecimal(sum(UnscaledValue(profit#50))#77,17,2) - MakeDecimal(sum(UnscaledValue(net_loss#52))#78,17,2)) AS profit#83]

(47) Scan parquet spark_catalog.default.web_sales
Output [4]: [ws_web_site_sk#84, ws_ext_sales_price#85, ws_net_profit#86, ws_sold_date_sk#87]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(ws_sold_date_sk#87), dynamicpruningexpression(ws_sold_date_sk#87 IN dynamicpruning#5)]
PushedFilters: [IsNotNull(ws_web_site_sk)]
ReadSchema: struct<ws_web_site_sk:int,ws_ext_sales_price:decimal(7,2),ws_net_profit:decimal(7,2)>

(48) ColumnarToRow [codegen id : 13]
Input [4]: [ws_web_site_sk#84, ws_ext_sales_price#85, ws_net_profit#86, ws_sold_date_sk#87]

(49) Filter [codegen id : 13]
Input [4]: [ws_web_site_sk#84, ws_ext_sales_price#85, ws_net_profit#86, ws_sold_date_sk#87]
Condition : isnotnull(ws_web_site_sk#84)

(50) Project [codegen id : 13]
Output [6]: [ws_web_site_sk#84 AS wsr_web_site_sk#88, ws_sold_date_sk#87 AS date_sk#89, ws_ext_sales_price#85 AS sales_price#90, ws_net_profit#86 AS profit#91, 0.00 AS return_amt#92, 0.00 AS net_loss#93]
Input [4]: [ws_web_site_sk#84, ws_ext_sales_price#85, ws_net_profit#86, ws_sold_date_sk#87]

(51) Scan parquet spark_catalog.default.web_returns
Output [5]: [wr_item_sk#94, wr_order_number#95, wr_return_amt#96, wr_net_loss#97, wr_returned_date_sk#98]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(wr_returned_date_sk#98), dynamicpruningexpression(wr_returned_date_sk#98 IN dynamicpruning#5)]
ReadSchema: struct<wr_item_sk:int,wr_order_number:int,wr_return_amt:decimal(7,2),wr_net_loss:decimal(7,2)>

(52) ColumnarToRow [codegen id : 14]
Input [5]: [wr_item_sk#94, wr_order_number#95, wr_return_amt#96, wr_net_loss#97, wr_returned_date_sk#98]

(53) BroadcastExchange
Input [5]: [wr_item_sk#94, wr_order_number#95, wr_return_amt#96, wr_net_loss#97, wr_returned_date_sk#98]
Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[0, int, true] as bigint), 32) | (cast(input[1, int, true] as bigint) & 4294967295))),false), [plan_id=5]

(54) CometNativeScan parquet spark_catalog.default.web_sales
Output [4]: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101, ws_sold_date_sk#102]
Batched: true
Location [not included in comparison]/{warehouse_dir}/web_sales]
PushedFilters: [IsNotNull(ws_item_sk), IsNotNull(ws_order_number), IsNotNull(ws_web_site_sk)]
ReadSchema: struct<ws_item_sk:int,ws_web_site_sk:int,ws_order_number:int>

(55) CometFilter
Input [4]: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101, ws_sold_date_sk#102]
Condition : ((isnotnull(ws_item_sk#99) AND isnotnull(ws_order_number#101)) AND isnotnull(ws_web_site_sk#100))

(56) CometProject
Input [4]: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101, ws_sold_date_sk#102]
Arguments: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101], [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101]

(57) CometColumnarToRow
Input [3]: [ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101]

(58) BroadcastHashJoin [codegen id : 15]
Left keys [2]: [wr_item_sk#94, wr_order_number#95]
Right keys [2]: [ws_item_sk#99, ws_order_number#101]
Join type: Inner
Join condition: None

(59) Project [codegen id : 15]
Output [6]: [ws_web_site_sk#100 AS wsr_web_site_sk#103, wr_returned_date_sk#98 AS date_sk#104, 0.00 AS sales_price#105, 0.00 AS profit#106, wr_return_amt#96 AS return_amt#107, wr_net_loss#97 AS net_loss#108]
Input [8]: [wr_item_sk#94, wr_order_number#95, wr_return_amt#96, wr_net_loss#97, wr_returned_date_sk#98, ws_item_sk#99, ws_web_site_sk#100, ws_order_number#101]

(60) Union

(61) ReusedExchange [Reuses operator id: 104]
Output [1]: [d_date_sk#109]

(62) BroadcastHashJoin [codegen id : 18]
Left keys [1]: [date_sk#89]
Right keys [1]: [d_date_sk#109]
Join type: Inner
Join condition: None

(63) Project [codegen id : 18]
Output [5]: [wsr_web_site_sk#88, sales_price#90, profit#91, return_amt#92, net_loss#93]
Input [7]: [wsr_web_site_sk#88, date_sk#89, sales_price#90, profit#91, return_amt#92, net_loss#93, d_date_sk#109]

(64) CometNativeScan parquet spark_catalog.default.web_site
Output [2]: [web_site_sk#110, web_site_id#111]
Batched: true
Location [not included in comparison]/{warehouse_dir}/web_site]
PushedFilters: [IsNotNull(web_site_sk)]
ReadSchema: struct<web_site_sk:int,web_site_id:string>

(65) CometFilter
Input [2]: [web_site_sk#110, web_site_id#111]
Condition : isnotnull(web_site_sk#110)

(66) CometProject
Input [2]: [web_site_sk#110, web_site_id#111]
Arguments: [web_site_sk#110, web_site_id#112], [web_site_sk#110, static_invoke(CharVarcharCodegenUtils.readSidePadding(web_site_id#111, 16)) AS web_site_id#112]

(67) CometColumnarToRow [codegen id : 17]
Input [2]: [web_site_sk#110, web_site_id#112]

(68) BroadcastExchange
Input [2]: [web_site_sk#110, web_site_id#112]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6]

(69) BroadcastHashJoin [codegen id : 18]
Left keys [1]: [wsr_web_site_sk#88]
Right keys [1]: [web_site_sk#110]
Join type: Inner
Join condition: None

(70) Project [codegen id : 18]
Output [5]: [sales_price#90, profit#91, return_amt#92, net_loss#93, web_site_id#112]
Input [7]: [wsr_web_site_sk#88, sales_price#90, profit#91, return_amt#92, net_loss#93, web_site_sk#110, web_site_id#112]

(71) HashAggregate [codegen id : 18]
Input [5]: [sales_price#90, profit#91, return_amt#92, net_loss#93, web_site_id#112]
Keys [1]: [web_site_id#112]
Functions [4]: [partial_sum(UnscaledValue(sales_price#90)), partial_sum(UnscaledValue(return_amt#92)), partial_sum(UnscaledValue(profit#91)), partial_sum(UnscaledValue(net_loss#93))]
Aggregate Attributes [4]: [sum#113, sum#114, sum#115, sum#116]
Results [5]: [web_site_id#112, sum#117, sum#118, sum#119, sum#120]

(72) CometColumnarExchange
Input [5]: [web_site_id#112, sum#117, sum#118, sum#119, sum#120]
Arguments: hashpartitioning(web_site_id#112, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=7]

(73) CometColumnarToRow [codegen id : 19]
Input [5]: [web_site_id#112, sum#117, sum#118, sum#119, sum#120]

(74) HashAggregate [codegen id : 19]
Input [5]: [web_site_id#112, sum#117, sum#118, sum#119, sum#120]
Keys [1]: [web_site_id#112]
Functions [4]: [sum(UnscaledValue(sales_price#90)), sum(UnscaledValue(return_amt#92)), sum(UnscaledValue(profit#91)), sum(UnscaledValue(net_loss#93))]
Aggregate Attributes [4]: [sum(UnscaledValue(sales_price#90))#121, sum(UnscaledValue(return_amt#92))#122, sum(UnscaledValue(profit#91))#123, sum(UnscaledValue(net_loss#93))#124]
Results [5]: [web channel AS channel#125, concat(web_site, web_site_id#112) AS id#126, MakeDecimal(sum(UnscaledValue(sales_price#90))#121,17,2) AS sales#127, MakeDecimal(sum(UnscaledValue(return_amt#92))#122,17,2) AS returns#128, (MakeDecimal(sum(UnscaledValue(profit#91))#123,17,2) - MakeDecimal(sum(UnscaledValue(net_loss#93))#124,17,2)) AS profit#129]

(75) Union

(76) HashAggregate [codegen id : 20]
Input [5]: [channel#38, id#39, sales#40, returns#41, profit#42]
Keys [2]: [channel#38, id#39]
Functions [3]: [partial_sum(sales#40), partial_sum(returns#41), partial_sum(profit#42)]
Aggregate Attributes [6]: [sum#130, isEmpty#131, sum#132, isEmpty#133, sum#134, isEmpty#135]
Results [8]: [channel#38, id#39, sum#136, isEmpty#137, sum#138, isEmpty#139, sum#140, isEmpty#141]

(77) CometColumnarExchange
Input [8]: [channel#38, id#39, sum#136, isEmpty#137, sum#138, isEmpty#139, sum#140, isEmpty#141]
Arguments: hashpartitioning(channel#38, id#39, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=8]

(78) CometColumnarToRow [codegen id : 21]
Input [8]: [channel#38, id#39, sum#136, isEmpty#137, sum#138, isEmpty#139, sum#140, isEmpty#141]

(79) HashAggregate [codegen id : 21]
Input [8]: [channel#38, id#39, sum#136, isEmpty#137, sum#138, isEmpty#139, sum#140, isEmpty#141]
Keys [2]: [channel#38, id#39]
Functions [3]: [sum(sales#40), sum(returns#41), sum(profit#42)]
Aggregate Attributes [3]: [sum(sales#40)#142, sum(returns#41)#143, sum(profit#42)#144]
Results [5]: [channel#38, id#39, cast(sum(sales#40)#142 as decimal(37,2)) AS sales#145, cast(sum(returns#41)#143 as decimal(37,2)) AS returns#146, cast(sum(profit#42)#144 as decimal(38,2)) AS profit#147]

(80) ReusedExchange [Reuses operator id: 77]
Output [8]: [channel#148, id#149, sum#150, isEmpty#151, sum#152, isEmpty#153, sum#154, isEmpty#155]

(81) CometColumnarToRow [codegen id : 42]
Input [8]: [channel#148, id#149, sum#150, isEmpty#151, sum#152, isEmpty#153, sum#154, isEmpty#155]

(82) HashAggregate [codegen id : 42]
Input [8]: [channel#148, id#149, sum#150, isEmpty#151, sum#152, isEmpty#153, sum#154, isEmpty#155]
Keys [2]: [channel#148, id#149]
Functions [3]: [sum(sales#156), sum(returns#157), sum(profit#158)]
Aggregate Attributes [3]: [sum(sales#156)#142, sum(returns#157)#143, sum(profit#158)#144]
Results [4]: [channel#148, sum(sales#156)#142 AS sales#159, sum(returns#157)#143 AS returns#160, sum(profit#158)#144 AS profit#161]

(83) HashAggregate [codegen id : 42]
Input [4]: [channel#148, sales#159, returns#160, profit#161]
Keys [1]: [channel#148]
Functions [3]: [partial_sum(sales#159), partial_sum(returns#160), partial_sum(profit#161)]
Aggregate Attributes [6]: [sum#162, isEmpty#163, sum#164, isEmpty#165, sum#166, isEmpty#167]
Results [7]: [channel#148, sum#168, isEmpty#169, sum#170, isEmpty#171, sum#172, isEmpty#173]

(84) CometColumnarExchange
Input [7]: [channel#148, sum#168, isEmpty#169, sum#170, isEmpty#171, sum#172, isEmpty#173]
Arguments: hashpartitioning(channel#148, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=9]

(85) CometColumnarToRow [codegen id : 43]
Input [7]: [channel#148, sum#168, isEmpty#169, sum#170, isEmpty#171, sum#172, isEmpty#173]

(86) HashAggregate [codegen id : 43]
Input [7]: [channel#148, sum#168, isEmpty#169, sum#170, isEmpty#171, sum#172, isEmpty#173]
Keys [1]: [channel#148]
Functions [3]: [sum(sales#159), sum(returns#160), sum(profit#161)]
Aggregate Attributes [3]: [sum(sales#159)#174, sum(returns#160)#175, sum(profit#161)#176]
Results [5]: [channel#148, null AS id#177, sum(sales#159)#174 AS sum(sales)#178, sum(returns#160)#175 AS sum(returns)#179, sum(profit#161)#176 AS sum(profit)#180]

(87) ReusedExchange [Reuses operator id: 77]
Output [8]: [channel#181, id#182, sum#183, isEmpty#184, sum#185, isEmpty#186, sum#187, isEmpty#188]

(88) CometColumnarToRow [codegen id : 64]
Input [8]: [channel#181, id#182, sum#183, isEmpty#184, sum#185, isEmpty#186, sum#187, isEmpty#188]

(89) HashAggregate [codegen id : 64]
Input [8]: [channel#181, id#182, sum#183, isEmpty#184, sum#185, isEmpty#186, sum#187, isEmpty#188]
Keys [2]: [channel#181, id#182]
Functions [3]: [sum(sales#189), sum(returns#190), sum(profit#191)]
Aggregate Attributes [3]: [sum(sales#189)#142, sum(returns#190)#143, sum(profit#191)#144]
Results [3]: [sum(sales#189)#142 AS sales#192, sum(returns#190)#143 AS returns#193, sum(profit#191)#144 AS profit#194]

(90) HashAggregate [codegen id : 64]
Input [3]: [sales#192, returns#193, profit#194]
Keys: []
Functions [3]: [partial_sum(sales#192), partial_sum(returns#193), partial_sum(profit#194)]
Aggregate Attributes [6]: [sum#195, isEmpty#196, sum#197, isEmpty#198, sum#199, isEmpty#200]
Results [6]: [sum#201, isEmpty#202, sum#203, isEmpty#204, sum#205, isEmpty#206]

(91) CometColumnarExchange
Input [6]: [sum#201, isEmpty#202, sum#203, isEmpty#204, sum#205, isEmpty#206]
Arguments: SinglePartition, ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=10]

(92) CometColumnarToRow [codegen id : 65]
Input [6]: [sum#201, isEmpty#202, sum#203, isEmpty#204, sum#205, isEmpty#206]

(93) HashAggregate [codegen id : 65]
Input [6]: [sum#201, isEmpty#202, sum#203, isEmpty#204, sum#205, isEmpty#206]
Keys: []
Functions [3]: [sum(sales#192), sum(returns#193), sum(profit#194)]
Aggregate Attributes [3]: [sum(sales#192)#207, sum(returns#193)#208, sum(profit#194)#209]
Results [5]: [null AS channel#210, null AS id#211, sum(sales#192)#207 AS sum(sales)#212, sum(returns#193)#208 AS sum(returns)#213, sum(profit#194)#209 AS sum(profit)#214]

(94) Union

(95) HashAggregate [codegen id : 66]
Input [5]: [channel#38, id#39, sales#145, returns#146, profit#147]
Keys [5]: [channel#38, id#39, sales#145, returns#146, profit#147]
Functions: []
Aggregate Attributes: []
Results [5]: [channel#38, id#39, sales#145, returns#146, profit#147]

(96) CometColumnarExchange
Input [5]: [channel#38, id#39, sales#145, returns#146, profit#147]
Arguments: hashpartitioning(channel#38, id#39, sales#145, returns#146, profit#147, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=11]

(97) CometHashAggregate
Input [5]: [channel#38, id#39, sales#145, returns#146, profit#147]
Keys [5]: [channel#38, id#39, sales#145, returns#146, profit#147]
Functions: []

(98) CometTakeOrderedAndProject
Input [5]: [channel#38, id#39, sales#145, returns#146, profit#147]
Arguments: TakeOrderedAndProject(limit=100, orderBy=[channel#38 ASC NULLS FIRST,id#39 ASC NULLS FIRST], output=[channel#38,id#39,sales#145,returns#146,profit#147]), [channel#38, id#39, sales#145, returns#146, profit#147], 100, 0, [channel#38 ASC NULLS FIRST, id#39 ASC NULLS FIRST], [channel#38, id#39, sales#145, returns#146, profit#147]

(99) CometColumnarToRow [codegen id : 67]
Input [5]: [channel#38, id#39, sales#145, returns#146, profit#147]

===== Subqueries =====

Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#4 IN dynamicpruning#5
BroadcastExchange (104)
+- * CometColumnarToRow (103)
   +- CometProject (102)
      +- CometFilter (101)
         +- CometNativeScan parquet spark_catalog.default.date_dim (100)


(100) CometNativeScan parquet spark_catalog.default.date_dim
Output [2]: [d_date_sk#22, d_date#215]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,1998-08-04), LessThanOrEqual(d_date,1998-08-18), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_date:date>

(101) CometFilter
Input [2]: [d_date_sk#22, d_date#215]
Condition : (((isnotnull(d_date#215) AND (d_date#215 >= 1998-08-04)) AND (d_date#215 <= 1998-08-18)) AND isnotnull(d_date_sk#22))

(102) CometProject
Input [2]: [d_date_sk#22, d_date#215]
Arguments: [d_date_sk#22], [d_date_sk#22]

(103) CometColumnarToRow [codegen id : 1]
Input [1]: [d_date_sk#22]

(104) BroadcastExchange
Input [1]: [d_date_sk#22]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=12]

Subquery:2 Hosting operator id = 5 Hosting Expression = sr_returned_date_sk#15 IN dynamicpruning#5

Subquery:3 Hosting operator id = 24 Hosting Expression = cs_sold_date_sk#46 IN dynamicpruning#5

Subquery:4 Hosting operator id = 28 Hosting Expression = cr_returned_date_sk#56 IN dynamicpruning#5

Subquery:5 Hosting operator id = 47 Hosting Expression = ws_sold_date_sk#87 IN dynamicpruning#5

Subquery:6 Hosting operator id = 51 Hosting Expression = wr_returned_date_sk#98 IN dynamicpruning#5


