== Physical Plan ==
VeloxColumnarToRow (63)
+- TakeOrderedAndProjectExecTransformer (62)
   +- ^ ProjectExecTransformer (60)
      +- ^ RegularHashAggregateExecTransformer (59)
         +- ^ InputIteratorTransformer (58)
            +- ColumnarExchange (56)
               +- VeloxResizeBatches (55)
                  +- ^ ProjectExecTransformer (53)
                     +- ^ FlushableHashAggregateExecTransformer (52)
                        +- ^ ProjectExecTransformer (51)
                           +- ^ ExpandExecTransformer (50)
                              +- ^ ProjectExecTransformer (49)
                                 +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (48)
                                    :- ^ ProjectExecTransformer (41)
                                    :  +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (40)
                                    :     :- ^ ProjectExecTransformer (36)
                                    :     :  +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (35)
                                    :     :     :- ^ ProjectExecTransformer (28)
                                    :     :     :  +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (27)
                                    :     :     :     :- ^ ProjectExecTransformer (20)
                                    :     :     :     :  +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (19)
                                    :     :     :     :     :- ^ ProjectExecTransformer (11)
                                    :     :     :     :     :  +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (10)
                                    :     :     :     :     :     :- ^ FilterExecTransformer (2)
                                    :     :     :     :     :     :  +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.catalog_sales (1)
                                    :     :     :     :     :     +- ^ InputIteratorTransformer (9)
                                    :     :     :     :     :        +- ColumnarBroadcastExchange (7)
                                    :     :     :     :     :           +- ^ ProjectExecTransformer (5)
                                    :     :     :     :     :              +- ^ FilterExecTransformer (4)
                                    :     :     :     :     :                 +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.customer_demographics (3)
                                    :     :     :     :     +- ^ InputIteratorTransformer (18)
                                    :     :     :     :        +- ColumnarBroadcastExchange (16)
                                    :     :     :     :           +- ^ ProjectExecTransformer (14)
                                    :     :     :     :              +- ^ FilterExecTransformer (13)
                                    :     :     :     :                 +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.customer (12)
                                    :     :     :     +- ^ InputIteratorTransformer (26)
                                    :     :     :        +- ColumnarBroadcastExchange (24)
                                    :     :     :           +- ^ FilterExecTransformer (22)
                                    :     :     :              +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.customer_demographics (21)
                                    :     :     +- ^ InputIteratorTransformer (34)
                                    :     :        +- ColumnarBroadcastExchange (32)
                                    :     :           +- ^ FilterExecTransformer (30)
                                    :     :              +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.customer_address (29)
                                    :     +- ^ InputIteratorTransformer (39)
                                    :        +- ReusedExchange (37)
                                    +- ^ InputIteratorTransformer (47)
                                       +- ColumnarBroadcastExchange (45)
                                          +- ^ FilterExecTransformer (43)
                                             +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.item (42)


(1) FileSourceScanExecTransformer parquet spark_catalog.default.catalog_sales
Output [9]: [cs_bill_customer_sk#1, cs_bill_cdemo_sk#2, cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(cs_sold_date_sk#9), dynamicpruningexpression(cs_sold_date_sk#9 IN dynamicpruning#10)]
PushedFilters: [IsNotNull(cs_bill_cdemo_sk), IsNotNull(cs_bill_customer_sk), IsNotNull(cs_item_sk)]
ReadSchema: struct<cs_bill_customer_sk:int,cs_bill_cdemo_sk:int,cs_item_sk:int,cs_quantity:int,cs_list_price:decimal(7,2),cs_sales_price:decimal(7,2),cs_coupon_amt:decimal(7,2),cs_net_profit:decimal(7,2)>

(2) FilterExecTransformer
Input [9]: [cs_bill_customer_sk#1, cs_bill_cdemo_sk#2, cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9]
Arguments: ((isnotnull(cs_bill_cdemo_sk#2) AND isnotnull(cs_bill_customer_sk#1)) AND isnotnull(cs_item_sk#3))

(3) FileSourceScanExecTransformer parquet spark_catalog.default.customer_demographics
Output [4]: [cd_demo_sk#11, cd_gender#12, cd_education_status#13, cd_dep_count#14]
Batched: true
Location: InMemoryFileIndex [{warehouse_dir}/customer_demographics]
PushedFilters: [IsNotNull(cd_gender), IsNotNull(cd_education_status), EqualTo(cd_gender,F), EqualTo(cd_education_status,Unknown             ), IsNotNull(cd_demo_sk)]
ReadSchema: struct<cd_demo_sk:int,cd_gender:string,cd_education_status:string,cd_dep_count:int>

(4) FilterExecTransformer
Input [4]: [cd_demo_sk#11, cd_gender#12, cd_education_status#13, cd_dep_count#14]
Arguments: ((((isnotnull(cd_gender#12) AND isnotnull(cd_education_status#13)) AND (cd_gender#12 = F)) AND (cd_education_status#13 = Unknown             )) AND isnotnull(cd_demo_sk#11))

(5) ProjectExecTransformer
Output [2]: [cd_demo_sk#11, cd_dep_count#14]
Input [4]: [cd_demo_sk#11, cd_gender#12, cd_education_status#13, cd_dep_count#14]

(6) WholeStageCodegenTransformer (2)
Input [2]: [cd_demo_sk#11, cd_dep_count#14]
Arguments: false

(7) ColumnarBroadcastExchange
Input [2]: [cd_demo_sk#11, cd_dep_count#14]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1]

(8) InputAdapter
Input [2]: [cd_demo_sk#11, cd_dep_count#14]

(9) InputIteratorTransformer
Input [2]: [cd_demo_sk#11, cd_dep_count#14]

(10) BroadcastHashJoinExecTransformer
Left keys [1]: [cs_bill_cdemo_sk#2]
Right keys [1]: [cd_demo_sk#11]
Join type: Inner
Join condition: None

(11) ProjectExecTransformer
Output [9]: [cs_bill_customer_sk#1, cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14]
Input [11]: [cs_bill_customer_sk#1, cs_bill_cdemo_sk#2, cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_demo_sk#11, cd_dep_count#14]

(12) FileSourceScanExecTransformer parquet spark_catalog.default.customer
Output [5]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_month#18, c_birth_year#19]
Batched: true
Location: InMemoryFileIndex [{warehouse_dir}/customer]
PushedFilters: [In(c_birth_month, [1,12,2,6,8,9]), IsNotNull(c_customer_sk), IsNotNull(c_current_cdemo_sk), IsNotNull(c_current_addr_sk)]
ReadSchema: struct<c_customer_sk:int,c_current_cdemo_sk:int,c_current_addr_sk:int,c_birth_month:int,c_birth_year:int>

(13) FilterExecTransformer
Input [5]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_month#18, c_birth_year#19]
Arguments: (((c_birth_month#18 IN (1,6,8,9,12,2) AND isnotnull(c_customer_sk#15)) AND isnotnull(c_current_cdemo_sk#16)) AND isnotnull(c_current_addr_sk#17))

(14) ProjectExecTransformer
Output [4]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19]
Input [5]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_month#18, c_birth_year#19]

(15) WholeStageCodegenTransformer (3)
Input [4]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19]
Arguments: false

(16) ColumnarBroadcastExchange
Input [4]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2]

(17) InputAdapter
Input [4]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19]

(18) InputIteratorTransformer
Input [4]: [c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19]

(19) BroadcastHashJoinExecTransformer
Left keys [1]: [cs_bill_customer_sk#1]
Right keys [1]: [c_customer_sk#15]
Join type: Inner
Join condition: None

(20) ProjectExecTransformer
Output [11]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19]
Input [13]: [cs_bill_customer_sk#1, cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14, c_customer_sk#15, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19]

(21) FileSourceScanExecTransformer parquet spark_catalog.default.customer_demographics
Output [1]: [cd_demo_sk#20]
Batched: true
Location: InMemoryFileIndex [{warehouse_dir}/customer_demographics]
PushedFilters: [IsNotNull(cd_demo_sk)]
ReadSchema: struct<cd_demo_sk:int>

(22) FilterExecTransformer
Input [1]: [cd_demo_sk#20]
Arguments: isnotnull(cd_demo_sk#20)

(23) WholeStageCodegenTransformer (4)
Input [1]: [cd_demo_sk#20]
Arguments: false

(24) ColumnarBroadcastExchange
Input [1]: [cd_demo_sk#20]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3]

(25) InputAdapter
Input [1]: [cd_demo_sk#20]

(26) InputIteratorTransformer
Input [1]: [cd_demo_sk#20]

(27) BroadcastHashJoinExecTransformer
Left keys [1]: [c_current_cdemo_sk#16]
Right keys [1]: [cd_demo_sk#20]
Join type: Inner
Join condition: None

(28) ProjectExecTransformer
Output [10]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14, c_current_addr_sk#17, c_birth_year#19]
Input [12]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14, c_current_cdemo_sk#16, c_current_addr_sk#17, c_birth_year#19, cd_demo_sk#20]

(29) FileSourceScanExecTransformer parquet spark_catalog.default.customer_address
Output [4]: [ca_address_sk#21, ca_county#22, ca_state#23, ca_country#24]
Batched: true
Location: InMemoryFileIndex [{warehouse_dir}/customer_address]
PushedFilters: [In(ca_state, [IN,MS,ND,NM,OK,VA]), IsNotNull(ca_address_sk)]
ReadSchema: struct<ca_address_sk:int,ca_county:string,ca_state:string,ca_country:string>

(30) FilterExecTransformer
Input [4]: [ca_address_sk#21, ca_county#22, ca_state#23, ca_country#24]
Arguments: (ca_state#23 IN (MS,IN,ND,OK,NM,VA) AND isnotnull(ca_address_sk#21))

(31) WholeStageCodegenTransformer (5)
Input [4]: [ca_address_sk#21, ca_county#22, ca_state#23, ca_country#24]
Arguments: false

(32) ColumnarBroadcastExchange
Input [4]: [ca_address_sk#21, ca_county#22, ca_state#23, ca_country#24]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4]

(33) InputAdapter
Input [4]: [ca_address_sk#21, ca_county#22, ca_state#23, ca_country#24]

(34) InputIteratorTransformer
Input [4]: [ca_address_sk#21, ca_county#22, ca_state#23, ca_country#24]

(35) BroadcastHashJoinExecTransformer
Left keys [1]: [c_current_addr_sk#17]
Right keys [1]: [ca_address_sk#21]
Join type: Inner
Join condition: None

(36) ProjectExecTransformer
Output [12]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14, c_birth_year#19, ca_county#22, ca_state#23, ca_country#24]
Input [14]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14, c_current_addr_sk#17, c_birth_year#19, ca_address_sk#21, ca_county#22, ca_state#23, ca_country#24]

(37) ReusedExchange [Reuses operator id: 68]
Output [1]: [d_date_sk#25]

(38) InputAdapter
Input [1]: [d_date_sk#25]

(39) InputIteratorTransformer
Input [1]: [d_date_sk#25]

(40) BroadcastHashJoinExecTransformer
Left keys [1]: [cs_sold_date_sk#9]
Right keys [1]: [d_date_sk#25]
Join type: Inner
Join condition: None

(41) ProjectExecTransformer
Output [11]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, c_birth_year#19, ca_county#22, ca_state#23, ca_country#24]
Input [13]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cs_sold_date_sk#9, cd_dep_count#14, c_birth_year#19, ca_county#22, ca_state#23, ca_country#24, d_date_sk#25]

(42) FileSourceScanExecTransformer parquet spark_catalog.default.item
Output [2]: [i_item_sk#26, i_item_id#27]
Batched: true
Location: InMemoryFileIndex [{warehouse_dir}/item]
PushedFilters: [IsNotNull(i_item_sk)]
ReadSchema: struct<i_item_sk:int,i_item_id:string>

(43) FilterExecTransformer
Input [2]: [i_item_sk#26, i_item_id#27]
Arguments: isnotnull(i_item_sk#26)

(44) WholeStageCodegenTransformer (7)
Input [2]: [i_item_sk#26, i_item_id#27]
Arguments: false

(45) ColumnarBroadcastExchange
Input [2]: [i_item_sk#26, i_item_id#27]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=5]

(46) InputAdapter
Input [2]: [i_item_sk#26, i_item_id#27]

(47) InputIteratorTransformer
Input [2]: [i_item_sk#26, i_item_id#27]

(48) BroadcastHashJoinExecTransformer
Left keys [1]: [cs_item_sk#3]
Right keys [1]: [i_item_sk#26]
Join type: Inner
Join condition: None

(49) ProjectExecTransformer
Output [11]: [cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, c_birth_year#19, i_item_id#27, ca_country#24, ca_state#23, ca_county#22]
Input [13]: [cs_item_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, c_birth_year#19, ca_county#22, ca_state#23, ca_country#24, i_item_sk#26, i_item_id#27]

(50) ExpandExecTransformer
Input [11]: [cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, c_birth_year#19, i_item_id#27, ca_country#24, ca_state#23, ca_county#22]
Arguments: [[cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, c_birth_year#19, i_item_id#27, ca_country#24, ca_state#23, ca_county#22, 0], [cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, c_birth_year#19, i_item_id#27, ca_country#24, ca_state#23, null, 1], [cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, c_birth_year#19, i_item_id#27, ca_country#24, null, null, 3], [cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, c_birth_year#19, i_item_id#27, null, null, null, 7], [cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, c_birth_year#19, null, null, null, null, 15]], [cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, c_birth_year#19, i_item_id#28, ca_country#29, ca_state#30, ca_county#31, spark_grouping_id#32]

(51) ProjectExecTransformer
Output [12]: [i_item_id#28, ca_country#29, ca_state#30, ca_county#31, spark_grouping_id#32, cast(cs_quantity#4 as decimal(12,2)) AS _pre_1#33, cast(cs_list_price#5 as decimal(12,2)) AS _pre_2#34, cast(cs_coupon_amt#7 as decimal(12,2)) AS _pre_3#35, cast(cs_sales_price#6 as decimal(12,2)) AS _pre_4#36, cast(cs_net_profit#8 as decimal(12,2)) AS _pre_5#37, cast(c_birth_year#19 as decimal(12,2)) AS _pre_6#38, cast(cd_dep_count#14 as decimal(12,2)) AS _pre_7#39]
Input [12]: [cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, c_birth_year#19, i_item_id#28, ca_country#29, ca_state#30, ca_county#31, spark_grouping_id#32]

(52) FlushableHashAggregateExecTransformer
Input [12]: [i_item_id#28, ca_country#29, ca_state#30, ca_county#31, spark_grouping_id#32, _pre_1#33, _pre_2#34, _pre_3#35, _pre_4#36, _pre_5#37, _pre_6#38, _pre_7#39]
Keys [5]: [i_item_id#28, ca_country#29, ca_state#30, ca_county#31, spark_grouping_id#32]
Functions [7]: [partial_avg(_pre_1#33), partial_avg(_pre_2#34), partial_avg(_pre_3#35), partial_avg(_pre_4#36), partial_avg(_pre_5#37), partial_avg(_pre_6#38), partial_avg(_pre_7#39)]
Aggregate Attributes [14]: [sum#40, count#41, sum#42, count#43, sum#44, count#45, sum#46, count#47, sum#48, count#49, sum#50, count#51, sum#52, count#53]
Results [19]: [i_item_id#28, ca_country#29, ca_state#30, ca_county#31, spark_grouping_id#32, sum#54, count#55, sum#56, count#57, sum#58, count#59, sum#60, count#61, sum#62, count#63, sum#64, count#65, sum#66, count#67]

(53) ProjectExecTransformer
Output [20]: [hash(i_item_id#28, ca_country#29, ca_state#30, ca_county#31, spark_grouping_id#32, 42) AS hash_partition_key#68, i_item_id#28, ca_country#29, ca_state#30, ca_county#31, spark_grouping_id#32, sum#54, count#55, sum#56, count#57, sum#58, count#59, sum#60, count#61, sum#62, count#63, sum#64, count#65, sum#66, count#67]
Input [19]: [i_item_id#28, ca_country#29, ca_state#30, ca_county#31, spark_grouping_id#32, sum#54, count#55, sum#56, count#57, sum#58, count#59, sum#60, count#61, sum#62, count#63, sum#64, count#65, sum#66, count#67]

(54) WholeStageCodegenTransformer (8)
Input [20]: [hash_partition_key#68, i_item_id#28, ca_country#29, ca_state#30, ca_county#31, spark_grouping_id#32, sum#54, count#55, sum#56, count#57, sum#58, count#59, sum#60, count#61, sum#62, count#63, sum#64, count#65, sum#66, count#67]
Arguments: false

(55) VeloxResizeBatches
Input [20]: [hash_partition_key#68, i_item_id#28, ca_country#29, ca_state#30, ca_county#31, spark_grouping_id#32, sum#54, count#55, sum#56, count#57, sum#58, count#59, sum#60, count#61, sum#62, count#63, sum#64, count#65, sum#66, count#67]
Arguments: 1024, 2147483647, 10485760

(56) ColumnarExchange
Input [20]: [hash_partition_key#68, i_item_id#28, ca_country#29, ca_state#30, ca_county#31, spark_grouping_id#32, sum#54, count#55, sum#56, count#57, sum#58, count#59, sum#60, count#61, sum#62, count#63, sum#64, count#65, sum#66, count#67]
Arguments: hashpartitioning(i_item_id#28, ca_country#29, ca_state#30, ca_county#31, spark_grouping_id#32, 1), ENSURE_REQUIREMENTS, [i_item_id#28, ca_country#29, ca_state#30, ca_county#31, spark_grouping_id#32, sum#54, count#55, sum#56, count#57, sum#58, count#59, sum#60, count#61, sum#62, count#63, sum#64, count#65, sum#66, count#67], [plan_id=6], [shuffle_writer_type=hash]

(57) InputAdapter
Input [19]: [i_item_id#28, ca_country#29, ca_state#30, ca_county#31, spark_grouping_id#32, sum#54, count#55, sum#56, count#57, sum#58, count#59, sum#60, count#61, sum#62, count#63, sum#64, count#65, sum#66, count#67]

(58) InputIteratorTransformer
Input [19]: [i_item_id#28, ca_country#29, ca_state#30, ca_county#31, spark_grouping_id#32, sum#54, count#55, sum#56, count#57, sum#58, count#59, sum#60, count#61, sum#62, count#63, sum#64, count#65, sum#66, count#67]

(59) RegularHashAggregateExecTransformer
Input [19]: [i_item_id#28, ca_country#29, ca_state#30, ca_county#31, spark_grouping_id#32, sum#54, count#55, sum#56, count#57, sum#58, count#59, sum#60, count#61, sum#62, count#63, sum#64, count#65, sum#66, count#67]
Keys [5]: [i_item_id#28, ca_country#29, ca_state#30, ca_county#31, spark_grouping_id#32]
Functions [7]: [avg(cast(cs_quantity#4 as decimal(12,2))), avg(cast(cs_list_price#5 as decimal(12,2))), avg(cast(cs_coupon_amt#7 as decimal(12,2))), avg(cast(cs_sales_price#6 as decimal(12,2))), avg(cast(cs_net_profit#8 as decimal(12,2))), avg(cast(c_birth_year#19 as decimal(12,2))), avg(cast(cd_dep_count#14 as decimal(12,2)))]
Aggregate Attributes [7]: [avg(cast(cs_quantity#4 as decimal(12,2)))#69, avg(cast(cs_list_price#5 as decimal(12,2)))#70, avg(cast(cs_coupon_amt#7 as decimal(12,2)))#71, avg(cast(cs_sales_price#6 as decimal(12,2)))#72, avg(cast(cs_net_profit#8 as decimal(12,2)))#73, avg(cast(c_birth_year#19 as decimal(12,2)))#74, avg(cast(cd_dep_count#14 as decimal(12,2)))#75]
Results [12]: [i_item_id#28, ca_country#29, ca_state#30, ca_county#31, spark_grouping_id#32, avg(cast(cs_quantity#4 as decimal(12,2)))#69, avg(cast(cs_list_price#5 as decimal(12,2)))#70, avg(cast(cs_coupon_amt#7 as decimal(12,2)))#71, avg(cast(cs_sales_price#6 as decimal(12,2)))#72, avg(cast(cs_net_profit#8 as decimal(12,2)))#73, avg(cast(c_birth_year#19 as decimal(12,2)))#74, avg(cast(cd_dep_count#14 as decimal(12,2)))#75]

(60) ProjectExecTransformer
Output [11]: [i_item_id#28, ca_country#29, ca_state#30, ca_county#31, avg(cast(cs_quantity#4 as decimal(12,2)))#69 AS agg1#76, avg(cast(cs_list_price#5 as decimal(12,2)))#70 AS agg2#77, avg(cast(cs_coupon_amt#7 as decimal(12,2)))#71 AS agg3#78, avg(cast(cs_sales_price#6 as decimal(12,2)))#72 AS agg4#79, avg(cast(cs_net_profit#8 as decimal(12,2)))#73 AS agg5#80, avg(cast(c_birth_year#19 as decimal(12,2)))#74 AS agg6#81, avg(cast(cd_dep_count#14 as decimal(12,2)))#75 AS agg7#82]
Input [12]: [i_item_id#28, ca_country#29, ca_state#30, ca_county#31, spark_grouping_id#32, avg(cast(cs_quantity#4 as decimal(12,2)))#69, avg(cast(cs_list_price#5 as decimal(12,2)))#70, avg(cast(cs_coupon_amt#7 as decimal(12,2)))#71, avg(cast(cs_sales_price#6 as decimal(12,2)))#72, avg(cast(cs_net_profit#8 as decimal(12,2)))#73, avg(cast(c_birth_year#19 as decimal(12,2)))#74, avg(cast(cd_dep_count#14 as decimal(12,2)))#75]

(61) WholeStageCodegenTransformer (9)
Input [11]: [i_item_id#28, ca_country#29, ca_state#30, ca_county#31, agg1#76, agg2#77, agg3#78, agg4#79, agg5#80, agg6#81, agg7#82]
Arguments: false

(62) TakeOrderedAndProjectExecTransformer
Input [11]: [i_item_id#28, ca_country#29, ca_state#30, ca_county#31, agg1#76, agg2#77, agg3#78, agg4#79, agg5#80, agg6#81, agg7#82]
Arguments: 100, [ca_country#29 ASC NULLS FIRST, ca_state#30 ASC NULLS FIRST, ca_county#31 ASC NULLS FIRST, i_item_id#28 ASC NULLS FIRST], [i_item_id#28, ca_country#29, ca_state#30, ca_county#31, agg1#76, agg2#77, agg3#78, agg4#79, agg5#80, agg6#81, agg7#82], 0

(63) VeloxColumnarToRow
Input [11]: [i_item_id#28, ca_country#29, ca_state#30, ca_county#31, agg1#76, agg2#77, agg3#78, agg4#79, agg5#80, agg6#81, agg7#82]

===== Subqueries =====

Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#9 IN dynamicpruning#10
ColumnarBroadcastExchange (68)
+- ^ ProjectExecTransformer (66)
   +- ^ FilterExecTransformer (65)
      +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.date_dim (64)


(64) FileSourceScanExecTransformer parquet spark_catalog.default.date_dim
Output [2]: [d_date_sk#25, d_year#83]
Batched: true
Location: InMemoryFileIndex [{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_year), EqualTo(d_year,1998), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int>

(65) FilterExecTransformer
Input [2]: [d_date_sk#25, d_year#83]
Arguments: ((isnotnull(d_year#83) AND (d_year#83 = 1998)) AND isnotnull(d_date_sk#25))

(66) ProjectExecTransformer
Output [1]: [d_date_sk#25]
Input [2]: [d_date_sk#25, d_year#83]

(67) WholeStageCodegenTransformer (1)
Input [1]: [d_date_sk#25]
Arguments: false

(68) ColumnarBroadcastExchange
Input [1]: [d_date_sk#25]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7]


