== Physical Plan ==
VeloxColumnarToRow (69)
+- TakeOrderedAndProjectExecTransformer (68)
   +- ^ ProjectExecTransformer (66)
      +- ^ RegularHashAggregateExecTransformer (65)
         +- ^ InputIteratorTransformer (64)
            +- ColumnarExchange (62)
               +- VeloxResizeBatches (61)
                  +- ^ ProjectExecTransformer (59)
                     +- ^ FlushableHashAggregateExecTransformer (58)
                        +- ^ ProjectExecTransformer (57)
                           +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (56)
                              :- ^ ProjectExecTransformer (49)
                              :  +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (48)
                              :     :- ^ ProjectExecTransformer (44)
                              :     :  +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (43)
                              :     :     :- ^ ProjectExecTransformer (35)
                              :     :     :  +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (34)
                              :     :     :     :- ^ ProjectExecTransformer (27)
                              :     :     :     :  +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (26)
                              :     :     :     :     :- ^ ProjectExecTransformer (19)
                              :     :     :     :     :  +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (18)
                              :     :     :     :     :     :- ^ ProjectExecTransformer (11)
                              :     :     :     :     :     :  +- ^ BroadcastHashJoinExecTransformer Inner BuildLeft (10)
                              :     :     :     :     :     :     :- ^ InputIteratorTransformer (6)
                              :     :     :     :     :     :     :  +- ColumnarBroadcastExchange (4)
                              :     :     :     :     :     :     :     +- ^ FilterExecTransformer (2)
                              :     :     :     :     :     :     :        +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.web_sales (1)
                              :     :     :     :     :     :     +- ^ ProjectExecTransformer (9)
                              :     :     :     :     :     :        +- ^ FilterExecTransformer (8)
                              :     :     :     :     :     :           +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.web_returns (7)
                              :     :     :     :     :     +- ^ InputIteratorTransformer (17)
                              :     :     :     :     :        +- ColumnarBroadcastExchange (15)
                              :     :     :     :     :           +- ^ FilterExecTransformer (13)
                              :     :     :     :     :              +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.web_page (12)
                              :     :     :     :     +- ^ InputIteratorTransformer (25)
                              :     :     :     :        +- ColumnarBroadcastExchange (23)
                              :     :     :     :           +- ^ FilterExecTransformer (21)
                              :     :     :     :              +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.customer_demographics (20)
                              :     :     :     +- ^ InputIteratorTransformer (33)
                              :     :     :        +- ColumnarBroadcastExchange (31)
                              :     :     :           +- ^ FilterExecTransformer (29)
                              :     :     :              +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.customer_demographics (28)
                              :     :     +- ^ InputIteratorTransformer (42)
                              :     :        +- ColumnarBroadcastExchange (40)
                              :     :           +- ^ ProjectExecTransformer (38)
                              :     :              +- ^ FilterExecTransformer (37)
                              :     :                 +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.customer_address (36)
                              :     +- ^ InputIteratorTransformer (47)
                              :        +- ReusedExchange (45)
                              +- ^ InputIteratorTransformer (55)
                                 +- ColumnarBroadcastExchange (53)
                                    +- ^ FilterExecTransformer (51)
                                       +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.reason (50)


(1) FileSourceScanExecTransformer parquet spark_catalog.default.web_sales
Output [7]: [ws_item_sk#1, ws_web_page_sk#2, ws_order_number#3, ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(ws_sold_date_sk#7), dynamicpruningexpression(ws_sold_date_sk#7 IN dynamicpruning#8)]
PushedFilters: [IsNotNull(ws_item_sk), IsNotNull(ws_order_number), IsNotNull(ws_web_page_sk), Or(Or(And(GreaterThanOrEqual(ws_sales_price,100.00),LessThanOrEqual(ws_sales_price,150.00)),And(GreaterThanOrEqual(ws_sales_price,50.00),LessThanOrEqual(ws_sales_price,100.00))),And(GreaterThanOrEqual(ws_sales_price,150.00),LessThanOrEqual(ws_sales_price,200.00))), Or(Or(And(GreaterThanOrEqual(ws_net_profit,100.00),LessThanOrEqual(ws_net_profit,200.00)),And(GreaterThanOrEqual(ws_net_profit,150.00),LessThanOrEqual(ws_net_profit,300.00))),And(GreaterThanOrEqual(ws_net_profit,50.00),LessThanOrEqual(ws_net_profit,250.00)))]
ReadSchema: struct<ws_item_sk:int,ws_web_page_sk:int,ws_order_number:int,ws_quantity:int,ws_sales_price:decimal(7,2),ws_net_profit:decimal(7,2)>

(2) FilterExecTransformer
Input [7]: [ws_item_sk#1, ws_web_page_sk#2, ws_order_number#3, ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7]
Arguments: ((((isnotnull(ws_item_sk#1) AND isnotnull(ws_order_number#3)) AND isnotnull(ws_web_page_sk#2)) AND ((((ws_sales_price#5 >= 100.00) AND (ws_sales_price#5 <= 150.00)) OR ((ws_sales_price#5 >= 50.00) AND (ws_sales_price#5 <= 100.00))) OR ((ws_sales_price#5 >= 150.00) AND (ws_sales_price#5 <= 200.00)))) AND ((((ws_net_profit#6 >= 100.00) AND (ws_net_profit#6 <= 200.00)) OR ((ws_net_profit#6 >= 150.00) AND (ws_net_profit#6 <= 300.00))) OR ((ws_net_profit#6 >= 50.00) AND (ws_net_profit#6 <= 250.00))))

(3) WholeStageCodegenTransformer (2)
Input [7]: [ws_item_sk#1, ws_web_page_sk#2, ws_order_number#3, ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7]
Arguments: false

(4) ColumnarBroadcastExchange
Input [7]: [ws_item_sk#1, ws_web_page_sk#2, ws_order_number#3, ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7]
Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[0, int, false] as bigint), 32) | (cast(input[2, int, false] as bigint) & 4294967295))),false), [plan_id=1]

(5) InputAdapter
Input [7]: [ws_item_sk#1, ws_web_page_sk#2, ws_order_number#3, ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7]

(6) InputIteratorTransformer
Input [7]: [ws_item_sk#1, ws_web_page_sk#2, ws_order_number#3, ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7]

(7) FileSourceScanExecTransformer parquet spark_catalog.default.web_returns
Output [9]: [wr_item_sk#9, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_order_number#14, wr_fee#15, wr_refunded_cash#16, wr_returned_date_sk#17]
Batched: true
Location: CatalogFileIndex [{warehouse_dir}/web_returns]
PushedFilters: [IsNotNull(wr_item_sk), IsNotNull(wr_order_number), IsNotNull(wr_refunded_cdemo_sk), IsNotNull(wr_returning_cdemo_sk), IsNotNull(wr_refunded_addr_sk), IsNotNull(wr_reason_sk)]
ReadSchema: struct<wr_item_sk:int,wr_refunded_cdemo_sk:int,wr_refunded_addr_sk:int,wr_returning_cdemo_sk:int,wr_reason_sk:int,wr_order_number:int,wr_fee:decimal(7,2),wr_refunded_cash:decimal(7,2)>

(8) FilterExecTransformer
Input [9]: [wr_item_sk#9, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_order_number#14, wr_fee#15, wr_refunded_cash#16, wr_returned_date_sk#17]
Arguments: (((((isnotnull(wr_item_sk#9) AND isnotnull(wr_order_number#14)) AND isnotnull(wr_refunded_cdemo_sk#10)) AND isnotnull(wr_returning_cdemo_sk#12)) AND isnotnull(wr_refunded_addr_sk#11)) AND isnotnull(wr_reason_sk#13))

(9) ProjectExecTransformer
Output [8]: [wr_item_sk#9, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_order_number#14, wr_fee#15, wr_refunded_cash#16]
Input [9]: [wr_item_sk#9, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_order_number#14, wr_fee#15, wr_refunded_cash#16, wr_returned_date_sk#17]

(10) BroadcastHashJoinExecTransformer
Left keys [2]: [ws_item_sk#1, ws_order_number#3]
Right keys [2]: [wr_item_sk#9, wr_order_number#14]
Join type: Inner
Join condition: None

(11) ProjectExecTransformer
Output [11]: [ws_web_page_sk#2, ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16]
Input [15]: [ws_item_sk#1, ws_web_page_sk#2, ws_order_number#3, ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7, wr_item_sk#9, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_order_number#14, wr_fee#15, wr_refunded_cash#16]

(12) FileSourceScanExecTransformer parquet spark_catalog.default.web_page
Output [1]: [wp_web_page_sk#18]
Batched: true
Location: InMemoryFileIndex [{warehouse_dir}/web_page]
PushedFilters: [IsNotNull(wp_web_page_sk)]
ReadSchema: struct<wp_web_page_sk:int>

(13) FilterExecTransformer
Input [1]: [wp_web_page_sk#18]
Arguments: isnotnull(wp_web_page_sk#18)

(14) WholeStageCodegenTransformer (3)
Input [1]: [wp_web_page_sk#18]
Arguments: false

(15) ColumnarBroadcastExchange
Input [1]: [wp_web_page_sk#18]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2]

(16) InputAdapter
Input [1]: [wp_web_page_sk#18]

(17) InputIteratorTransformer
Input [1]: [wp_web_page_sk#18]

(18) BroadcastHashJoinExecTransformer
Left keys [1]: [ws_web_page_sk#2]
Right keys [1]: [wp_web_page_sk#18]
Join type: Inner
Join condition: None

(19) ProjectExecTransformer
Output [10]: [ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16]
Input [12]: [ws_web_page_sk#2, ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16, wp_web_page_sk#18]

(20) FileSourceScanExecTransformer parquet spark_catalog.default.customer_demographics
Output [3]: [cd_demo_sk#19, cd_marital_status#20, cd_education_status#21]
Batched: true
Location: InMemoryFileIndex [{warehouse_dir}/customer_demographics]
PushedFilters: [IsNotNull(cd_demo_sk), IsNotNull(cd_marital_status), IsNotNull(cd_education_status), Or(Or(And(EqualTo(cd_marital_status,M),EqualTo(cd_education_status,Advanced Degree     )),And(EqualTo(cd_marital_status,S),EqualTo(cd_education_status,College             ))),And(EqualTo(cd_marital_status,W),EqualTo(cd_education_status,2 yr Degree         )))]
ReadSchema: struct<cd_demo_sk:int,cd_marital_status:string,cd_education_status:string>

(21) FilterExecTransformer
Input [3]: [cd_demo_sk#19, cd_marital_status#20, cd_education_status#21]
Arguments: (((isnotnull(cd_demo_sk#19) AND isnotnull(cd_marital_status#20)) AND isnotnull(cd_education_status#21)) AND ((((cd_marital_status#20 = M) AND (cd_education_status#21 = Advanced Degree     )) OR ((cd_marital_status#20 = S) AND (cd_education_status#21 = College             ))) OR ((cd_marital_status#20 = W) AND (cd_education_status#21 = 2 yr Degree         ))))

(22) WholeStageCodegenTransformer (4)
Input [3]: [cd_demo_sk#19, cd_marital_status#20, cd_education_status#21]
Arguments: false

(23) ColumnarBroadcastExchange
Input [3]: [cd_demo_sk#19, cd_marital_status#20, cd_education_status#21]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3]

(24) InputAdapter
Input [3]: [cd_demo_sk#19, cd_marital_status#20, cd_education_status#21]

(25) InputIteratorTransformer
Input [3]: [cd_demo_sk#19, cd_marital_status#20, cd_education_status#21]

(26) BroadcastHashJoinExecTransformer
Left keys [1]: [wr_refunded_cdemo_sk#10]
Right keys [1]: [cd_demo_sk#19]
Join type: Inner
Join condition: ((((((cd_marital_status#20 = M) AND (cd_education_status#21 = Advanced Degree     )) AND (ws_sales_price#5 >= 100.00)) AND (ws_sales_price#5 <= 150.00)) OR ((((cd_marital_status#20 = S) AND (cd_education_status#21 = College             )) AND (ws_sales_price#5 >= 50.00)) AND (ws_sales_price#5 <= 100.00))) OR ((((cd_marital_status#20 = W) AND (cd_education_status#21 = 2 yr Degree         )) AND (ws_sales_price#5 >= 150.00)) AND (ws_sales_price#5 <= 200.00)))

(27) ProjectExecTransformer
Output [10]: [ws_quantity#4, ws_net_profit#6, ws_sold_date_sk#7, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16, cd_marital_status#20, cd_education_status#21]
Input [13]: [ws_quantity#4, ws_sales_price#5, ws_net_profit#6, ws_sold_date_sk#7, wr_refunded_cdemo_sk#10, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16, cd_demo_sk#19, cd_marital_status#20, cd_education_status#21]

(28) FileSourceScanExecTransformer parquet spark_catalog.default.customer_demographics
Output [3]: [cd_demo_sk#22, cd_marital_status#23, cd_education_status#24]
Batched: true
Location: InMemoryFileIndex [{warehouse_dir}/customer_demographics]
PushedFilters: [IsNotNull(cd_demo_sk), IsNotNull(cd_marital_status), IsNotNull(cd_education_status)]
ReadSchema: struct<cd_demo_sk:int,cd_marital_status:string,cd_education_status:string>

(29) FilterExecTransformer
Input [3]: [cd_demo_sk#22, cd_marital_status#23, cd_education_status#24]
Arguments: ((isnotnull(cd_demo_sk#22) AND isnotnull(cd_marital_status#23)) AND isnotnull(cd_education_status#24))

(30) WholeStageCodegenTransformer (5)
Input [3]: [cd_demo_sk#22, cd_marital_status#23, cd_education_status#24]
Arguments: false

(31) ColumnarBroadcastExchange
Input [3]: [cd_demo_sk#22, cd_marital_status#23, cd_education_status#24]
Arguments: HashedRelationBroadcastMode(List(input[0, int, false], input[1, string, false], input[2, string, false]),false), [plan_id=4]

(32) InputAdapter
Input [3]: [cd_demo_sk#22, cd_marital_status#23, cd_education_status#24]

(33) InputIteratorTransformer
Input [3]: [cd_demo_sk#22, cd_marital_status#23, cd_education_status#24]

(34) BroadcastHashJoinExecTransformer
Left keys [3]: [wr_returning_cdemo_sk#12, cd_marital_status#20, cd_education_status#21]
Right keys [3]: [cd_demo_sk#22, cd_marital_status#23, cd_education_status#24]
Join type: Inner
Join condition: None

(35) ProjectExecTransformer
Output [7]: [ws_quantity#4, ws_net_profit#6, ws_sold_date_sk#7, wr_refunded_addr_sk#11, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16]
Input [13]: [ws_quantity#4, ws_net_profit#6, ws_sold_date_sk#7, wr_refunded_addr_sk#11, wr_returning_cdemo_sk#12, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16, cd_marital_status#20, cd_education_status#21, cd_demo_sk#22, cd_marital_status#23, cd_education_status#24]

(36) FileSourceScanExecTransformer parquet spark_catalog.default.customer_address
Output [3]: [ca_address_sk#25, ca_state#26, ca_country#27]
Batched: true
Location: InMemoryFileIndex [{warehouse_dir}/customer_address]
PushedFilters: [IsNotNull(ca_country), EqualTo(ca_country,United States), IsNotNull(ca_address_sk), Or(Or(In(ca_state, [IN,NJ,OH]),In(ca_state, [CT,KY,WI])),In(ca_state, [AR,IA,LA]))]
ReadSchema: struct<ca_address_sk:int,ca_state:string,ca_country:string>

(37) FilterExecTransformer
Input [3]: [ca_address_sk#25, ca_state#26, ca_country#27]
Arguments: (((isnotnull(ca_country#27) AND (ca_country#27 = United States)) AND isnotnull(ca_address_sk#25)) AND ((ca_state#26 IN (IN,OH,NJ) OR ca_state#26 IN (WI,CT,KY)) OR ca_state#26 IN (LA,IA,AR)))

(38) ProjectExecTransformer
Output [2]: [ca_address_sk#25, ca_state#26]
Input [3]: [ca_address_sk#25, ca_state#26, ca_country#27]

(39) WholeStageCodegenTransformer (6)
Input [2]: [ca_address_sk#25, ca_state#26]
Arguments: false

(40) ColumnarBroadcastExchange
Input [2]: [ca_address_sk#25, ca_state#26]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5]

(41) InputAdapter
Input [2]: [ca_address_sk#25, ca_state#26]

(42) InputIteratorTransformer
Input [2]: [ca_address_sk#25, ca_state#26]

(43) BroadcastHashJoinExecTransformer
Left keys [1]: [wr_refunded_addr_sk#11]
Right keys [1]: [ca_address_sk#25]
Join type: Inner
Join condition: ((((ca_state#26 IN (IN,OH,NJ) AND (ws_net_profit#6 >= 100.00)) AND (ws_net_profit#6 <= 200.00)) OR ((ca_state#26 IN (WI,CT,KY) AND (ws_net_profit#6 >= 150.00)) AND (ws_net_profit#6 <= 300.00))) OR ((ca_state#26 IN (LA,IA,AR) AND (ws_net_profit#6 >= 50.00)) AND (ws_net_profit#6 <= 250.00)))

(44) ProjectExecTransformer
Output [5]: [ws_quantity#4, ws_sold_date_sk#7, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16]
Input [9]: [ws_quantity#4, ws_net_profit#6, ws_sold_date_sk#7, wr_refunded_addr_sk#11, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16, ca_address_sk#25, ca_state#26]

(45) ReusedExchange [Reuses operator id: 74]
Output [1]: [d_date_sk#28]

(46) InputAdapter
Input [1]: [d_date_sk#28]

(47) InputIteratorTransformer
Input [1]: [d_date_sk#28]

(48) BroadcastHashJoinExecTransformer
Left keys [1]: [ws_sold_date_sk#7]
Right keys [1]: [d_date_sk#28]
Join type: Inner
Join condition: None

(49) ProjectExecTransformer
Output [4]: [ws_quantity#4, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16]
Input [6]: [ws_quantity#4, ws_sold_date_sk#7, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16, d_date_sk#28]

(50) FileSourceScanExecTransformer parquet spark_catalog.default.reason
Output [2]: [r_reason_sk#29, r_reason_desc#30]
Batched: true
Location: InMemoryFileIndex [{warehouse_dir}/reason]
PushedFilters: [IsNotNull(r_reason_sk)]
ReadSchema: struct<r_reason_sk:int,r_reason_desc:string>

(51) FilterExecTransformer
Input [2]: [r_reason_sk#29, r_reason_desc#30]
Arguments: isnotnull(r_reason_sk#29)

(52) WholeStageCodegenTransformer (8)
Input [2]: [r_reason_sk#29, r_reason_desc#30]
Arguments: false

(53) ColumnarBroadcastExchange
Input [2]: [r_reason_sk#29, r_reason_desc#30]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6]

(54) InputAdapter
Input [2]: [r_reason_sk#29, r_reason_desc#30]

(55) InputIteratorTransformer
Input [2]: [r_reason_sk#29, r_reason_desc#30]

(56) BroadcastHashJoinExecTransformer
Left keys [1]: [wr_reason_sk#13]
Right keys [1]: [r_reason_sk#29]
Join type: Inner
Join condition: None

(57) ProjectExecTransformer
Output [4]: [ws_quantity#4, r_reason_desc#30, UnscaledValue(wr_refunded_cash#16) AS _pre_1#31, UnscaledValue(wr_fee#15) AS _pre_2#32]
Input [6]: [ws_quantity#4, wr_reason_sk#13, wr_fee#15, wr_refunded_cash#16, r_reason_sk#29, r_reason_desc#30]

(58) FlushableHashAggregateExecTransformer
Input [4]: [ws_quantity#4, r_reason_desc#30, _pre_1#31, _pre_2#32]
Keys [1]: [r_reason_desc#30]
Functions [3]: [partial_avg(ws_quantity#4), partial_avg(_pre_1#31), partial_avg(_pre_2#32)]
Aggregate Attributes [6]: [sum#33, count#34, sum#35, count#36, sum#37, count#38]
Results [7]: [r_reason_desc#30, sum#39, count#40, sum#41, count#42, sum#43, count#44]

(59) ProjectExecTransformer
Output [8]: [hash(r_reason_desc#30, 42) AS hash_partition_key#45, r_reason_desc#30, sum#39, count#40, sum#41, count#42, sum#43, count#44]
Input [7]: [r_reason_desc#30, sum#39, count#40, sum#41, count#42, sum#43, count#44]

(60) WholeStageCodegenTransformer (9)
Input [8]: [hash_partition_key#45, r_reason_desc#30, sum#39, count#40, sum#41, count#42, sum#43, count#44]
Arguments: false

(61) VeloxResizeBatches
Input [8]: [hash_partition_key#45, r_reason_desc#30, sum#39, count#40, sum#41, count#42, sum#43, count#44]
Arguments: 1024, 2147483647, 10485760

(62) ColumnarExchange
Input [8]: [hash_partition_key#45, r_reason_desc#30, sum#39, count#40, sum#41, count#42, sum#43, count#44]
Arguments: hashpartitioning(r_reason_desc#30, 1), ENSURE_REQUIREMENTS, [r_reason_desc#30, sum#39, count#40, sum#41, count#42, sum#43, count#44], [plan_id=7], [shuffle_writer_type=hash]

(63) InputAdapter
Input [7]: [r_reason_desc#30, sum#39, count#40, sum#41, count#42, sum#43, count#44]

(64) InputIteratorTransformer
Input [7]: [r_reason_desc#30, sum#39, count#40, sum#41, count#42, sum#43, count#44]

(65) RegularHashAggregateExecTransformer
Input [7]: [r_reason_desc#30, sum#39, count#40, sum#41, count#42, sum#43, count#44]
Keys [1]: [r_reason_desc#30]
Functions [3]: [avg(ws_quantity#4), avg(UnscaledValue(wr_refunded_cash#16)), avg(UnscaledValue(wr_fee#15))]
Aggregate Attributes [3]: [avg(ws_quantity#4)#46, avg(UnscaledValue(wr_refunded_cash#16))#47, avg(UnscaledValue(wr_fee#15))#48]
Results [4]: [r_reason_desc#30, avg(ws_quantity#4)#46, avg(UnscaledValue(wr_refunded_cash#16))#47, avg(UnscaledValue(wr_fee#15))#48]

(66) ProjectExecTransformer
Output [4]: [substr(r_reason_desc#30, 1, 20) AS substr(r_reason_desc, 1, 20)#49, avg(ws_quantity#4)#46 AS avg(ws_quantity)#50, cast((avg(UnscaledValue(wr_refunded_cash#16))#47 / 100.0) as decimal(11,6)) AS avg(wr_refunded_cash)#51, cast((avg(UnscaledValue(wr_fee#15))#48 / 100.0) as decimal(11,6)) AS avg(wr_fee)#52]
Input [4]: [r_reason_desc#30, avg(ws_quantity#4)#46, avg(UnscaledValue(wr_refunded_cash#16))#47, avg(UnscaledValue(wr_fee#15))#48]

(67) WholeStageCodegenTransformer (10)
Input [4]: [substr(r_reason_desc, 1, 20)#49, avg(ws_quantity)#50, avg(wr_refunded_cash)#51, avg(wr_fee)#52]
Arguments: false

(68) TakeOrderedAndProjectExecTransformer
Input [4]: [substr(r_reason_desc, 1, 20)#49, avg(ws_quantity)#50, avg(wr_refunded_cash)#51, avg(wr_fee)#52]
Arguments: 100, [substr(r_reason_desc, 1, 20)#49 ASC NULLS FIRST, avg(ws_quantity)#50 ASC NULLS FIRST, avg(wr_refunded_cash)#51 ASC NULLS FIRST, avg(wr_fee)#52 ASC NULLS FIRST], [substr(r_reason_desc, 1, 20)#49, avg(ws_quantity)#50, avg(wr_refunded_cash)#51, avg(wr_fee)#52], 0

(69) VeloxColumnarToRow
Input [4]: [substr(r_reason_desc, 1, 20)#49, avg(ws_quantity)#50, avg(wr_refunded_cash)#51, avg(wr_fee)#52]

===== Subqueries =====

Subquery:1 Hosting operator id = 1 Hosting Expression = ws_sold_date_sk#7 IN dynamicpruning#8
ColumnarBroadcastExchange (74)
+- ^ ProjectExecTransformer (72)
   +- ^ FilterExecTransformer (71)
      +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.date_dim (70)


(70) FileSourceScanExecTransformer parquet spark_catalog.default.date_dim
Output [2]: [d_date_sk#28, d_year#53]
Batched: true
Location: InMemoryFileIndex [{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2000), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int>

(71) FilterExecTransformer
Input [2]: [d_date_sk#28, d_year#53]
Arguments: ((isnotnull(d_year#53) AND (d_year#53 = 2000)) AND isnotnull(d_date_sk#28))

(72) ProjectExecTransformer
Output [1]: [d_date_sk#28]
Input [2]: [d_date_sk#28, d_year#53]

(73) WholeStageCodegenTransformer (1)
Input [1]: [d_date_sk#28]
Arguments: false

(74) ColumnarBroadcastExchange
Input [1]: [d_date_sk#28]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8]


