== Physical Plan ==
VeloxColumnarToRow (76)
+- TakeOrderedAndProjectExecTransformer (75)
   +- ^ ProjectExecTransformer (73)
      +- ^ RegularHashAggregateExecTransformer (72)
         +- ^ InputIteratorTransformer (71)
            +- ColumnarExchange (69)
               +- VeloxResizeBatches (68)
                  +- ^ ProjectExecTransformer (66)
                     +- ^ FlushableHashAggregateExecTransformer (65)
                        +- ^ ProjectExecTransformer (64)
                           +- ^ ExpandExecTransformer (63)
                              +- ^ ProjectExecTransformer (62)
                                 +- ^ ShuffledHashJoinExecTransformer Inner BuildRight (61)
                                    :- ^ InputIteratorTransformer (29)
                                    :  +- ColumnarExchange (27)
                                    :     +- VeloxResizeBatches (26)
                                    :        +- ^ ProjectExecTransformer (24)
                                    :           +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (23)
                                    :              :- ^ ProjectExecTransformer (16)
                                    :              :  +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (15)
                                    :              :     :- ^ 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 (14)
                                    :              :        +- ReusedExchange (12)
                                    :              +- ^ InputIteratorTransformer (22)
                                    :                 +- ColumnarBroadcastExchange (20)
                                    :                    +- ^ FilterExecTransformer (18)
                                    :                       +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.item (17)
                                    +- ^ InputIteratorTransformer (60)
                                       +- ColumnarExchange (58)
                                          +- VeloxResizeBatches (57)
                                             +- ^ ProjectExecTransformer (55)
                                                +- ^ ShuffledHashJoinExecTransformer Inner BuildLeft (54)
                                                   :- ^ InputIteratorTransformer (45)
                                                   :  +- ColumnarExchange (43)
                                                   :     +- VeloxResizeBatches (42)
                                                   :        +- ^ ProjectExecTransformer (40)
                                                   :           +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (39)
                                                   :              :- ^ ProjectExecTransformer (32)
                                                   :              :  +- ^ FilterExecTransformer (31)
                                                   :              :     +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.customer (30)
                                                   :              +- ^ InputIteratorTransformer (38)
                                                   :                 +- ColumnarBroadcastExchange (36)
                                                   :                    +- ^ FilterExecTransformer (34)
                                                   :                       +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.customer_address (33)
                                                   +- ^ InputIteratorTransformer (53)
                                                      +- ColumnarExchange (51)
                                                         +- VeloxResizeBatches (50)
                                                            +- ^ ProjectExecTransformer (48)
                                                               +- ^ FilterExecTransformer (47)
                                                                  +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.customer_demographics (46)


(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) ReusedExchange [Reuses operator id: 81]
Output [1]: [d_date_sk#15]

(13) InputAdapter
Input [1]: [d_date_sk#15]

(14) InputIteratorTransformer
Input [1]: [d_date_sk#15]

(15) BroadcastHashJoinExecTransformer
Left keys [1]: [cs_sold_date_sk#9]
Right keys [1]: [d_date_sk#15]
Join type: Inner
Join condition: None

(16) ProjectExecTransformer
Output [8]: [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, cd_dep_count#14]
Input [10]: [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, d_date_sk#15]

(17) FileSourceScanExecTransformer parquet spark_catalog.default.item
Output [2]: [i_item_sk#16, i_item_id#17]
Batched: true
Location: InMemoryFileIndex [{warehouse_dir}/item]
PushedFilters: [IsNotNull(i_item_sk)]
ReadSchema: struct<i_item_sk:int,i_item_id:string>

(18) FilterExecTransformer
Input [2]: [i_item_sk#16, i_item_id#17]
Arguments: isnotnull(i_item_sk#16)

(19) WholeStageCodegenTransformer (4)
Input [2]: [i_item_sk#16, i_item_id#17]
Arguments: false

(20) ColumnarBroadcastExchange
Input [2]: [i_item_sk#16, i_item_id#17]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2]

(21) InputAdapter
Input [2]: [i_item_sk#16, i_item_id#17]

(22) InputIteratorTransformer
Input [2]: [i_item_sk#16, i_item_id#17]

(23) BroadcastHashJoinExecTransformer
Left keys [1]: [cs_item_sk#3]
Right keys [1]: [i_item_sk#16]
Join type: Inner
Join condition: None

(24) ProjectExecTransformer
Output [9]: [hash(cs_bill_customer_sk#1, 42) AS hash_partition_key#18, cs_bill_customer_sk#1, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, i_item_id#17]
Input [10]: [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, cd_dep_count#14, i_item_sk#16, i_item_id#17]

(25) WholeStageCodegenTransformer (5)
Input [9]: [hash_partition_key#18, cs_bill_customer_sk#1, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, i_item_id#17]
Arguments: false

(26) VeloxResizeBatches
Input [9]: [hash_partition_key#18, cs_bill_customer_sk#1, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, i_item_id#17]
Arguments: 1024, 2147483647, 10485760

(27) ColumnarExchange
Input [9]: [hash_partition_key#18, cs_bill_customer_sk#1, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, i_item_id#17]
Arguments: hashpartitioning(cs_bill_customer_sk#1, 1), ENSURE_REQUIREMENTS, [cs_bill_customer_sk#1, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, i_item_id#17], [plan_id=3], [shuffle_writer_type=hash]

(28) InputAdapter
Input [8]: [cs_bill_customer_sk#1, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, i_item_id#17]

(29) InputIteratorTransformer
Input [8]: [cs_bill_customer_sk#1, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, i_item_id#17]

(30) FileSourceScanExecTransformer parquet spark_catalog.default.customer
Output [5]: [c_customer_sk#19, c_current_cdemo_sk#20, c_current_addr_sk#21, c_birth_month#22, c_birth_year#23]
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>

(31) FilterExecTransformer
Input [5]: [c_customer_sk#19, c_current_cdemo_sk#20, c_current_addr_sk#21, c_birth_month#22, c_birth_year#23]
Arguments: (((c_birth_month#22 IN (1,6,8,9,12,2) AND isnotnull(c_customer_sk#19)) AND isnotnull(c_current_cdemo_sk#20)) AND isnotnull(c_current_addr_sk#21))

(32) ProjectExecTransformer
Output [4]: [c_customer_sk#19, c_current_cdemo_sk#20, c_current_addr_sk#21, c_birth_year#23]
Input [5]: [c_customer_sk#19, c_current_cdemo_sk#20, c_current_addr_sk#21, c_birth_month#22, c_birth_year#23]

(33) FileSourceScanExecTransformer parquet spark_catalog.default.customer_address
Output [4]: [ca_address_sk#24, ca_county#25, ca_state#26, ca_country#27]
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>

(34) FilterExecTransformer
Input [4]: [ca_address_sk#24, ca_county#25, ca_state#26, ca_country#27]
Arguments: (ca_state#26 IN (MS,IN,ND,OK,NM,VA) AND isnotnull(ca_address_sk#24))

(35) WholeStageCodegenTransformer (6)
Input [4]: [ca_address_sk#24, ca_county#25, ca_state#26, ca_country#27]
Arguments: false

(36) ColumnarBroadcastExchange
Input [4]: [ca_address_sk#24, ca_county#25, ca_state#26, ca_country#27]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4]

(37) InputAdapter
Input [4]: [ca_address_sk#24, ca_county#25, ca_state#26, ca_country#27]

(38) InputIteratorTransformer
Input [4]: [ca_address_sk#24, ca_county#25, ca_state#26, ca_country#27]

(39) BroadcastHashJoinExecTransformer
Left keys [1]: [c_current_addr_sk#21]
Right keys [1]: [ca_address_sk#24]
Join type: Inner
Join condition: None

(40) ProjectExecTransformer
Output [7]: [hash(c_current_cdemo_sk#20, 42) AS hash_partition_key#28, c_customer_sk#19, c_current_cdemo_sk#20, c_birth_year#23, ca_county#25, ca_state#26, ca_country#27]
Input [8]: [c_customer_sk#19, c_current_cdemo_sk#20, c_current_addr_sk#21, c_birth_year#23, ca_address_sk#24, ca_county#25, ca_state#26, ca_country#27]

(41) WholeStageCodegenTransformer (7)
Input [7]: [hash_partition_key#28, c_customer_sk#19, c_current_cdemo_sk#20, c_birth_year#23, ca_county#25, ca_state#26, ca_country#27]
Arguments: false

(42) VeloxResizeBatches
Input [7]: [hash_partition_key#28, c_customer_sk#19, c_current_cdemo_sk#20, c_birth_year#23, ca_county#25, ca_state#26, ca_country#27]
Arguments: 1024, 2147483647, 10485760

(43) ColumnarExchange
Input [7]: [hash_partition_key#28, c_customer_sk#19, c_current_cdemo_sk#20, c_birth_year#23, ca_county#25, ca_state#26, ca_country#27]
Arguments: hashpartitioning(c_current_cdemo_sk#20, 1), ENSURE_REQUIREMENTS, [c_customer_sk#19, c_current_cdemo_sk#20, c_birth_year#23, ca_county#25, ca_state#26, ca_country#27], [plan_id=5], [shuffle_writer_type=hash]

(44) InputAdapter
Input [6]: [c_customer_sk#19, c_current_cdemo_sk#20, c_birth_year#23, ca_county#25, ca_state#26, ca_country#27]

(45) InputIteratorTransformer
Input [6]: [c_customer_sk#19, c_current_cdemo_sk#20, c_birth_year#23, ca_county#25, ca_state#26, ca_country#27]

(46) FileSourceScanExecTransformer parquet spark_catalog.default.customer_demographics
Output [1]: [cd_demo_sk#29]
Batched: true
Location: InMemoryFileIndex [{warehouse_dir}/customer_demographics]
PushedFilters: [IsNotNull(cd_demo_sk)]
ReadSchema: struct<cd_demo_sk:int>

(47) FilterExecTransformer
Input [1]: [cd_demo_sk#29]
Arguments: isnotnull(cd_demo_sk#29)

(48) ProjectExecTransformer
Output [2]: [hash(cd_demo_sk#29, 42) AS hash_partition_key#30, cd_demo_sk#29]
Input [1]: [cd_demo_sk#29]

(49) WholeStageCodegenTransformer (8)
Input [2]: [hash_partition_key#30, cd_demo_sk#29]
Arguments: false

(50) VeloxResizeBatches
Input [2]: [hash_partition_key#30, cd_demo_sk#29]
Arguments: 1024, 2147483647, 10485760

(51) ColumnarExchange
Input [2]: [hash_partition_key#30, cd_demo_sk#29]
Arguments: hashpartitioning(cd_demo_sk#29, 1), ENSURE_REQUIREMENTS, [cd_demo_sk#29], [plan_id=6], [shuffle_writer_type=hash]

(52) InputAdapter
Input [1]: [cd_demo_sk#29]

(53) InputIteratorTransformer
Input [1]: [cd_demo_sk#29]

(54) ShuffledHashJoinExecTransformer
Left keys [1]: [c_current_cdemo_sk#20]
Right keys [1]: [cd_demo_sk#29]
Join type: Inner
Join condition: None

(55) ProjectExecTransformer
Output [6]: [hash(c_customer_sk#19, 42) AS hash_partition_key#31, c_customer_sk#19, c_birth_year#23, ca_county#25, ca_state#26, ca_country#27]
Input [7]: [c_customer_sk#19, c_current_cdemo_sk#20, c_birth_year#23, ca_county#25, ca_state#26, ca_country#27, cd_demo_sk#29]

(56) WholeStageCodegenTransformer (9)
Input [6]: [hash_partition_key#31, c_customer_sk#19, c_birth_year#23, ca_county#25, ca_state#26, ca_country#27]
Arguments: false

(57) VeloxResizeBatches
Input [6]: [hash_partition_key#31, c_customer_sk#19, c_birth_year#23, ca_county#25, ca_state#26, ca_country#27]
Arguments: 1024, 2147483647, 10485760

(58) ColumnarExchange
Input [6]: [hash_partition_key#31, c_customer_sk#19, c_birth_year#23, ca_county#25, ca_state#26, ca_country#27]
Arguments: hashpartitioning(c_customer_sk#19, 1), ENSURE_REQUIREMENTS, [c_customer_sk#19, c_birth_year#23, ca_county#25, ca_state#26, ca_country#27], [plan_id=7], [shuffle_writer_type=hash]

(59) InputAdapter
Input [5]: [c_customer_sk#19, c_birth_year#23, ca_county#25, ca_state#26, ca_country#27]

(60) InputIteratorTransformer
Input [5]: [c_customer_sk#19, c_birth_year#23, ca_county#25, ca_state#26, ca_country#27]

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

(62) 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#23, i_item_id#17, ca_country#27, ca_state#26, ca_county#25]
Input [13]: [cs_bill_customer_sk#1, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_net_profit#8, cd_dep_count#14, i_item_id#17, c_customer_sk#19, c_birth_year#23, ca_county#25, ca_state#26, ca_country#27]

(63) 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#23, i_item_id#17, ca_country#27, ca_state#26, ca_county#25]
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#23, i_item_id#17, ca_country#27, ca_state#26, ca_county#25, 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#23, i_item_id#17, ca_country#27, ca_state#26, 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#23, i_item_id#17, ca_country#27, 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#23, i_item_id#17, 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#23, 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#23, i_item_id#32, ca_country#33, ca_state#34, ca_county#35, spark_grouping_id#36]

(64) ProjectExecTransformer
Output [12]: [i_item_id#32, ca_country#33, ca_state#34, ca_county#35, spark_grouping_id#36, cast(cs_quantity#4 as decimal(12,2)) AS _pre_1#37, cast(cs_list_price#5 as decimal(12,2)) AS _pre_2#38, cast(cs_coupon_amt#7 as decimal(12,2)) AS _pre_3#39, cast(cs_sales_price#6 as decimal(12,2)) AS _pre_4#40, cast(cs_net_profit#8 as decimal(12,2)) AS _pre_5#41, cast(c_birth_year#23 as decimal(12,2)) AS _pre_6#42, cast(cd_dep_count#14 as decimal(12,2)) AS _pre_7#43]
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#23, i_item_id#32, ca_country#33, ca_state#34, ca_county#35, spark_grouping_id#36]

(65) FlushableHashAggregateExecTransformer
Input [12]: [i_item_id#32, ca_country#33, ca_state#34, ca_county#35, spark_grouping_id#36, _pre_1#37, _pre_2#38, _pre_3#39, _pre_4#40, _pre_5#41, _pre_6#42, _pre_7#43]
Keys [5]: [i_item_id#32, ca_country#33, ca_state#34, ca_county#35, spark_grouping_id#36]
Functions [7]: [partial_avg(_pre_1#37), partial_avg(_pre_2#38), partial_avg(_pre_3#39), partial_avg(_pre_4#40), partial_avg(_pre_5#41), partial_avg(_pre_6#42), partial_avg(_pre_7#43)]
Aggregate Attributes [14]: [sum#44, count#45, sum#46, count#47, sum#48, count#49, sum#50, count#51, sum#52, count#53, sum#54, count#55, sum#56, count#57]
Results [19]: [i_item_id#32, ca_country#33, ca_state#34, ca_county#35, spark_grouping_id#36, sum#58, count#59, sum#60, count#61, sum#62, count#63, sum#64, count#65, sum#66, count#67, sum#68, count#69, sum#70, count#71]

(66) ProjectExecTransformer
Output [20]: [hash(i_item_id#32, ca_country#33, ca_state#34, ca_county#35, spark_grouping_id#36, 42) AS hash_partition_key#72, i_item_id#32, ca_country#33, ca_state#34, ca_county#35, spark_grouping_id#36, sum#58, count#59, sum#60, count#61, sum#62, count#63, sum#64, count#65, sum#66, count#67, sum#68, count#69, sum#70, count#71]
Input [19]: [i_item_id#32, ca_country#33, ca_state#34, ca_county#35, spark_grouping_id#36, sum#58, count#59, sum#60, count#61, sum#62, count#63, sum#64, count#65, sum#66, count#67, sum#68, count#69, sum#70, count#71]

(67) WholeStageCodegenTransformer (10)
Input [20]: [hash_partition_key#72, i_item_id#32, ca_country#33, ca_state#34, ca_county#35, spark_grouping_id#36, sum#58, count#59, sum#60, count#61, sum#62, count#63, sum#64, count#65, sum#66, count#67, sum#68, count#69, sum#70, count#71]
Arguments: false

(68) VeloxResizeBatches
Input [20]: [hash_partition_key#72, i_item_id#32, ca_country#33, ca_state#34, ca_county#35, spark_grouping_id#36, sum#58, count#59, sum#60, count#61, sum#62, count#63, sum#64, count#65, sum#66, count#67, sum#68, count#69, sum#70, count#71]
Arguments: 1024, 2147483647, 10485760

(69) ColumnarExchange
Input [20]: [hash_partition_key#72, i_item_id#32, ca_country#33, ca_state#34, ca_county#35, spark_grouping_id#36, sum#58, count#59, sum#60, count#61, sum#62, count#63, sum#64, count#65, sum#66, count#67, sum#68, count#69, sum#70, count#71]
Arguments: hashpartitioning(i_item_id#32, ca_country#33, ca_state#34, ca_county#35, spark_grouping_id#36, 1), ENSURE_REQUIREMENTS, [i_item_id#32, ca_country#33, ca_state#34, ca_county#35, spark_grouping_id#36, sum#58, count#59, sum#60, count#61, sum#62, count#63, sum#64, count#65, sum#66, count#67, sum#68, count#69, sum#70, count#71], [plan_id=8], [shuffle_writer_type=hash]

(70) InputAdapter
Input [19]: [i_item_id#32, ca_country#33, ca_state#34, ca_county#35, spark_grouping_id#36, sum#58, count#59, sum#60, count#61, sum#62, count#63, sum#64, count#65, sum#66, count#67, sum#68, count#69, sum#70, count#71]

(71) InputIteratorTransformer
Input [19]: [i_item_id#32, ca_country#33, ca_state#34, ca_county#35, spark_grouping_id#36, sum#58, count#59, sum#60, count#61, sum#62, count#63, sum#64, count#65, sum#66, count#67, sum#68, count#69, sum#70, count#71]

(72) RegularHashAggregateExecTransformer
Input [19]: [i_item_id#32, ca_country#33, ca_state#34, ca_county#35, spark_grouping_id#36, sum#58, count#59, sum#60, count#61, sum#62, count#63, sum#64, count#65, sum#66, count#67, sum#68, count#69, sum#70, count#71]
Keys [5]: [i_item_id#32, ca_country#33, ca_state#34, ca_county#35, spark_grouping_id#36]
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#23 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)))#73, avg(cast(cs_list_price#5 as decimal(12,2)))#74, avg(cast(cs_coupon_amt#7 as decimal(12,2)))#75, avg(cast(cs_sales_price#6 as decimal(12,2)))#76, avg(cast(cs_net_profit#8 as decimal(12,2)))#77, avg(cast(c_birth_year#23 as decimal(12,2)))#78, avg(cast(cd_dep_count#14 as decimal(12,2)))#79]
Results [12]: [i_item_id#32, ca_country#33, ca_state#34, ca_county#35, spark_grouping_id#36, avg(cast(cs_quantity#4 as decimal(12,2)))#73, avg(cast(cs_list_price#5 as decimal(12,2)))#74, avg(cast(cs_coupon_amt#7 as decimal(12,2)))#75, avg(cast(cs_sales_price#6 as decimal(12,2)))#76, avg(cast(cs_net_profit#8 as decimal(12,2)))#77, avg(cast(c_birth_year#23 as decimal(12,2)))#78, avg(cast(cd_dep_count#14 as decimal(12,2)))#79]

(73) ProjectExecTransformer
Output [11]: [i_item_id#32, ca_country#33, ca_state#34, ca_county#35, avg(cast(cs_quantity#4 as decimal(12,2)))#73 AS agg1#80, avg(cast(cs_list_price#5 as decimal(12,2)))#74 AS agg2#81, avg(cast(cs_coupon_amt#7 as decimal(12,2)))#75 AS agg3#82, avg(cast(cs_sales_price#6 as decimal(12,2)))#76 AS agg4#83, avg(cast(cs_net_profit#8 as decimal(12,2)))#77 AS agg5#84, avg(cast(c_birth_year#23 as decimal(12,2)))#78 AS agg6#85, avg(cast(cd_dep_count#14 as decimal(12,2)))#79 AS agg7#86]
Input [12]: [i_item_id#32, ca_country#33, ca_state#34, ca_county#35, spark_grouping_id#36, avg(cast(cs_quantity#4 as decimal(12,2)))#73, avg(cast(cs_list_price#5 as decimal(12,2)))#74, avg(cast(cs_coupon_amt#7 as decimal(12,2)))#75, avg(cast(cs_sales_price#6 as decimal(12,2)))#76, avg(cast(cs_net_profit#8 as decimal(12,2)))#77, avg(cast(c_birth_year#23 as decimal(12,2)))#78, avg(cast(cd_dep_count#14 as decimal(12,2)))#79]

(74) WholeStageCodegenTransformer (11)
Input [11]: [i_item_id#32, ca_country#33, ca_state#34, ca_county#35, agg1#80, agg2#81, agg3#82, agg4#83, agg5#84, agg6#85, agg7#86]
Arguments: false

(75) TakeOrderedAndProjectExecTransformer
Input [11]: [i_item_id#32, ca_country#33, ca_state#34, ca_county#35, agg1#80, agg2#81, agg3#82, agg4#83, agg5#84, agg6#85, agg7#86]
Arguments: 100, [ca_country#33 ASC NULLS FIRST, ca_state#34 ASC NULLS FIRST, ca_county#35 ASC NULLS FIRST, i_item_id#32 ASC NULLS FIRST], [i_item_id#32, ca_country#33, ca_state#34, ca_county#35, agg1#80, agg2#81, agg3#82, agg4#83, agg5#84, agg6#85, agg7#86], 0

(76) VeloxColumnarToRow
Input [11]: [i_item_id#32, ca_country#33, ca_state#34, ca_county#35, agg1#80, agg2#81, agg3#82, agg4#83, agg5#84, agg6#85, agg7#86]

===== Subqueries =====

Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#9 IN dynamicpruning#10
ColumnarBroadcastExchange (81)
+- ^ ProjectExecTransformer (79)
   +- ^ FilterExecTransformer (78)
      +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.date_dim (77)


(77) FileSourceScanExecTransformer parquet spark_catalog.default.date_dim
Output [2]: [d_date_sk#15, d_year#87]
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>

(78) FilterExecTransformer
Input [2]: [d_date_sk#15, d_year#87]
Arguments: ((isnotnull(d_year#87) AND (d_year#87 = 1998)) AND isnotnull(d_date_sk#15))

(79) ProjectExecTransformer
Output [1]: [d_date_sk#15]
Input [2]: [d_date_sk#15, d_year#87]

(80) WholeStageCodegenTransformer (1)
Input [1]: [d_date_sk#15]
Arguments: false

(81) ColumnarBroadcastExchange
Input [1]: [d_date_sk#15]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=9]


