== Physical Plan ==
VeloxColumnarToRow (45)
+- TakeOrderedAndProjectExecTransformer (44)
   +- ^ ProjectExecTransformer (42)
      +- ^ RegularHashAggregateExecTransformer (41)
         +- ^ InputIteratorTransformer (40)
            +- ColumnarExchange (38)
               +- VeloxResizeBatches (37)
                  +- ^ ProjectExecTransformer (35)
                     +- ^ FlushableHashAggregateExecTransformer (34)
                        +- ^ ProjectExecTransformer (33)
                           +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (32)
                              :- ^ ProjectExecTransformer (25)
                              :  +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (24)
                              :     :- ^ 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.promotion (12)
                              :     +- ^ InputIteratorTransformer (23)
                              :        +- ReusedExchange (21)
                              +- ^ InputIteratorTransformer (31)
                                 +- ColumnarBroadcastExchange (29)
                                    +- ^ FilterExecTransformer (27)
                                       +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.item (26)


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

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

(3) FileSourceScanExecTransformer parquet spark_catalog.default.customer_demographics
Output [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13]
Batched: true
Location: InMemoryFileIndex [{warehouse_dir}/customer_demographics]
PushedFilters: [IsNotNull(cd_gender), IsNotNull(cd_marital_status), IsNotNull(cd_education_status), EqualTo(cd_gender,M), EqualTo(cd_marital_status,S), EqualTo(cd_education_status,College             ), IsNotNull(cd_demo_sk)]
ReadSchema: struct<cd_demo_sk:int,cd_gender:string,cd_marital_status:string,cd_education_status:string>

(4) FilterExecTransformer
Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13]
Arguments: ((((((isnotnull(cd_gender#11) AND isnotnull(cd_marital_status#12)) AND isnotnull(cd_education_status#13)) AND (cd_gender#11 = M)) AND (cd_marital_status#12 = S)) AND (cd_education_status#13 = College             )) AND isnotnull(cd_demo_sk#10))

(5) ProjectExecTransformer
Output [1]: [cd_demo_sk#10]
Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13]

(6) WholeStageCodegenTransformer (2)
Input [1]: [cd_demo_sk#10]
Arguments: false

(7) ColumnarBroadcastExchange
Input [1]: [cd_demo_sk#10]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1]

(8) InputAdapter
Input [1]: [cd_demo_sk#10]

(9) InputIteratorTransformer
Input [1]: [cd_demo_sk#10]

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

(11) ProjectExecTransformer
Output [7]: [cs_item_sk#2, cs_promo_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_sold_date_sk#8]
Input [9]: [cs_bill_cdemo_sk#1, cs_item_sk#2, cs_promo_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_sold_date_sk#8, cd_demo_sk#10]

(12) FileSourceScanExecTransformer parquet spark_catalog.default.promotion
Output [3]: [p_promo_sk#14, p_channel_email#15, p_channel_event#16]
Batched: true
Location: InMemoryFileIndex [{warehouse_dir}/promotion]
PushedFilters: [Or(EqualTo(p_channel_email,N),EqualTo(p_channel_event,N)), IsNotNull(p_promo_sk)]
ReadSchema: struct<p_promo_sk:int,p_channel_email:string,p_channel_event:string>

(13) FilterExecTransformer
Input [3]: [p_promo_sk#14, p_channel_email#15, p_channel_event#16]
Arguments: (((p_channel_email#15 = N) OR (p_channel_event#16 = N)) AND isnotnull(p_promo_sk#14))

(14) ProjectExecTransformer
Output [1]: [p_promo_sk#14]
Input [3]: [p_promo_sk#14, p_channel_email#15, p_channel_event#16]

(15) WholeStageCodegenTransformer (3)
Input [1]: [p_promo_sk#14]
Arguments: false

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

(17) InputAdapter
Input [1]: [p_promo_sk#14]

(18) InputIteratorTransformer
Input [1]: [p_promo_sk#14]

(19) BroadcastHashJoinExecTransformer
Left keys [1]: [cs_promo_sk#3]
Right keys [1]: [p_promo_sk#14]
Join type: Inner
Join condition: None

(20) ProjectExecTransformer
Output [6]: [cs_item_sk#2, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_sold_date_sk#8]
Input [8]: [cs_item_sk#2, cs_promo_sk#3, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_sold_date_sk#8, p_promo_sk#14]

(21) ReusedExchange [Reuses operator id: 50]
Output [1]: [d_date_sk#17]

(22) InputAdapter
Input [1]: [d_date_sk#17]

(23) InputIteratorTransformer
Input [1]: [d_date_sk#17]

(24) BroadcastHashJoinExecTransformer
Left keys [1]: [cs_sold_date_sk#8]
Right keys [1]: [d_date_sk#17]
Join type: Inner
Join condition: None

(25) ProjectExecTransformer
Output [5]: [cs_item_sk#2, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7]
Input [7]: [cs_item_sk#2, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, cs_sold_date_sk#8, d_date_sk#17]

(26) FileSourceScanExecTransformer parquet spark_catalog.default.item
Output [2]: [i_item_sk#18, i_item_id#19]
Batched: true
Location: InMemoryFileIndex [{warehouse_dir}/item]
PushedFilters: [IsNotNull(i_item_sk)]
ReadSchema: struct<i_item_sk:int,i_item_id:string>

(27) FilterExecTransformer
Input [2]: [i_item_sk#18, i_item_id#19]
Arguments: isnotnull(i_item_sk#18)

(28) WholeStageCodegenTransformer (5)
Input [2]: [i_item_sk#18, i_item_id#19]
Arguments: false

(29) ColumnarBroadcastExchange
Input [2]: [i_item_sk#18, i_item_id#19]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3]

(30) InputAdapter
Input [2]: [i_item_sk#18, i_item_id#19]

(31) InputIteratorTransformer
Input [2]: [i_item_sk#18, i_item_id#19]

(32) BroadcastHashJoinExecTransformer
Left keys [1]: [cs_item_sk#2]
Right keys [1]: [i_item_sk#18]
Join type: Inner
Join condition: None

(33) ProjectExecTransformer
Output [5]: [cs_quantity#4, i_item_id#19, UnscaledValue(cs_list_price#5) AS _pre_1#20, UnscaledValue(cs_coupon_amt#7) AS _pre_2#21, UnscaledValue(cs_sales_price#6) AS _pre_3#22]
Input [7]: [cs_item_sk#2, cs_quantity#4, cs_list_price#5, cs_sales_price#6, cs_coupon_amt#7, i_item_sk#18, i_item_id#19]

(34) FlushableHashAggregateExecTransformer
Input [5]: [cs_quantity#4, i_item_id#19, _pre_1#20, _pre_2#21, _pre_3#22]
Keys [1]: [i_item_id#19]
Functions [4]: [partial_avg(cs_quantity#4), partial_avg(_pre_1#20), partial_avg(_pre_2#21), partial_avg(_pre_3#22)]
Aggregate Attributes [8]: [sum#23, count#24, sum#25, count#26, sum#27, count#28, sum#29, count#30]
Results [9]: [i_item_id#19, sum#31, count#32, sum#33, count#34, sum#35, count#36, sum#37, count#38]

(35) ProjectExecTransformer
Output [10]: [hash(i_item_id#19, 42) AS hash_partition_key#39, i_item_id#19, sum#31, count#32, sum#33, count#34, sum#35, count#36, sum#37, count#38]
Input [9]: [i_item_id#19, sum#31, count#32, sum#33, count#34, sum#35, count#36, sum#37, count#38]

(36) WholeStageCodegenTransformer (6)
Input [10]: [hash_partition_key#39, i_item_id#19, sum#31, count#32, sum#33, count#34, sum#35, count#36, sum#37, count#38]
Arguments: false

(37) VeloxResizeBatches
Input [10]: [hash_partition_key#39, i_item_id#19, sum#31, count#32, sum#33, count#34, sum#35, count#36, sum#37, count#38]
Arguments: 1024, 2147483647, 10485760

(38) ColumnarExchange
Input [10]: [hash_partition_key#39, i_item_id#19, sum#31, count#32, sum#33, count#34, sum#35, count#36, sum#37, count#38]
Arguments: hashpartitioning(i_item_id#19, 1), ENSURE_REQUIREMENTS, [i_item_id#19, sum#31, count#32, sum#33, count#34, sum#35, count#36, sum#37, count#38], [plan_id=4], [shuffle_writer_type=hash]

(39) InputAdapter
Input [9]: [i_item_id#19, sum#31, count#32, sum#33, count#34, sum#35, count#36, sum#37, count#38]

(40) InputIteratorTransformer
Input [9]: [i_item_id#19, sum#31, count#32, sum#33, count#34, sum#35, count#36, sum#37, count#38]

(41) RegularHashAggregateExecTransformer
Input [9]: [i_item_id#19, sum#31, count#32, sum#33, count#34, sum#35, count#36, sum#37, count#38]
Keys [1]: [i_item_id#19]
Functions [4]: [avg(cs_quantity#4), avg(UnscaledValue(cs_list_price#5)), avg(UnscaledValue(cs_coupon_amt#7)), avg(UnscaledValue(cs_sales_price#6))]
Aggregate Attributes [4]: [avg(cs_quantity#4)#40, avg(UnscaledValue(cs_list_price#5))#41, avg(UnscaledValue(cs_coupon_amt#7))#42, avg(UnscaledValue(cs_sales_price#6))#43]
Results [5]: [i_item_id#19, avg(cs_quantity#4)#40, avg(UnscaledValue(cs_list_price#5))#41, avg(UnscaledValue(cs_coupon_amt#7))#42, avg(UnscaledValue(cs_sales_price#6))#43]

(42) ProjectExecTransformer
Output [5]: [i_item_id#19, avg(cs_quantity#4)#40 AS agg1#44, cast((avg(UnscaledValue(cs_list_price#5))#41 / 100.0) as decimal(11,6)) AS agg2#45, cast((avg(UnscaledValue(cs_coupon_amt#7))#42 / 100.0) as decimal(11,6)) AS agg3#46, cast((avg(UnscaledValue(cs_sales_price#6))#43 / 100.0) as decimal(11,6)) AS agg4#47]
Input [5]: [i_item_id#19, avg(cs_quantity#4)#40, avg(UnscaledValue(cs_list_price#5))#41, avg(UnscaledValue(cs_coupon_amt#7))#42, avg(UnscaledValue(cs_sales_price#6))#43]

(43) WholeStageCodegenTransformer (7)
Input [5]: [i_item_id#19, agg1#44, agg2#45, agg3#46, agg4#47]
Arguments: false

(44) TakeOrderedAndProjectExecTransformer
Input [5]: [i_item_id#19, agg1#44, agg2#45, agg3#46, agg4#47]
Arguments: 100, [i_item_id#19 ASC NULLS FIRST], [i_item_id#19, agg1#44, agg2#45, agg3#46, agg4#47], 0

(45) VeloxColumnarToRow
Input [5]: [i_item_id#19, agg1#44, agg2#45, agg3#46, agg4#47]

===== Subqueries =====

Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#8 IN dynamicpruning#9
ColumnarBroadcastExchange (50)
+- ^ ProjectExecTransformer (48)
   +- ^ FilterExecTransformer (47)
      +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.date_dim (46)


(46) FileSourceScanExecTransformer parquet spark_catalog.default.date_dim
Output [2]: [d_date_sk#17, d_year#48]
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>

(47) FilterExecTransformer
Input [2]: [d_date_sk#17, d_year#48]
Arguments: ((isnotnull(d_year#48) AND (d_year#48 = 2000)) AND isnotnull(d_date_sk#17))

(48) ProjectExecTransformer
Output [1]: [d_date_sk#17]
Input [2]: [d_date_sk#17, d_year#48]

(49) WholeStageCodegenTransformer (1)
Input [1]: [d_date_sk#17]
Arguments: false

(50) ColumnarBroadcastExchange
Input [1]: [d_date_sk#17]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5]


