== Physical Plan ==
TakeOrderedAndProject (32)
+- * HashAggregate (31)
   +- * CometColumnarToRow (30)
      +- CometColumnarExchange (29)
         +- * HashAggregate (28)
            +- * Project (27)
               +- * BroadcastHashJoin Inner BuildRight (26)
                  :- * Project (20)
                  :  +- * BroadcastHashJoin Inner BuildRight (19)
                  :     :- * Project (13)
                  :     :  +- * BroadcastHashJoin Inner BuildRight (12)
                  :     :     :- * Project (10)
                  :     :     :  +- * BroadcastHashJoin Inner BuildRight (9)
                  :     :     :     :- * Filter (3)
                  :     :     :     :  +- * ColumnarToRow (2)
                  :     :     :     :     +- Scan parquet spark_catalog.default.store_sales (1)
                  :     :     :     +- BroadcastExchange (8)
                  :     :     :        +- * CometColumnarToRow (7)
                  :     :     :           +- CometProject (6)
                  :     :     :              +- CometFilter (5)
                  :     :     :                 +- CometNativeScan parquet spark_catalog.default.customer_demographics (4)
                  :     :     +- ReusedExchange (11)
                  :     +- BroadcastExchange (18)
                  :        +- * CometColumnarToRow (17)
                  :           +- CometProject (16)
                  :              +- CometFilter (15)
                  :                 +- CometNativeScan parquet spark_catalog.default.item (14)
                  +- BroadcastExchange (25)
                     +- * CometColumnarToRow (24)
                        +- CometProject (23)
                           +- CometFilter (22)
                              +- CometNativeScan parquet spark_catalog.default.promotion (21)


(1) Scan parquet spark_catalog.default.store_sales
Output [8]: [ss_item_sk#1, ss_cdemo_sk#2, ss_promo_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(ss_sold_date_sk#8), dynamicpruningexpression(ss_sold_date_sk#8 IN dynamicpruning#9)]
PushedFilters: [IsNotNull(ss_cdemo_sk), IsNotNull(ss_item_sk), IsNotNull(ss_promo_sk)]
ReadSchema: struct<ss_item_sk:int,ss_cdemo_sk:int,ss_promo_sk:int,ss_quantity:int,ss_list_price:decimal(7,2),ss_sales_price:decimal(7,2),ss_coupon_amt:decimal(7,2)>

(2) ColumnarToRow [codegen id : 5]
Input [8]: [ss_item_sk#1, ss_cdemo_sk#2, ss_promo_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8]

(3) Filter [codegen id : 5]
Input [8]: [ss_item_sk#1, ss_cdemo_sk#2, ss_promo_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8]
Condition : ((isnotnull(ss_cdemo_sk#2) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_promo_sk#3))

(4) CometNativeScan 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 [not included in comparison]/{warehouse_dir}/customer_demographics]
PushedFilters: [IsNotNull(cd_gender), IsNotNull(cd_marital_status), IsNotNull(cd_education_status), IsNotNull(cd_demo_sk)]
ReadSchema: struct<cd_demo_sk:int,cd_gender:string,cd_marital_status:string,cd_education_status:string>

(5) CometFilter
Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13]
Condition : ((((((isnotnull(cd_gender#11) AND isnotnull(cd_marital_status#12)) AND isnotnull(cd_education_status#13)) AND (static_invoke(CharVarcharCodegenUtils.readSidePadding(cd_gender#11, 1)) = M)) AND (static_invoke(CharVarcharCodegenUtils.readSidePadding(cd_marital_status#12, 1)) = S)) AND (static_invoke(CharVarcharCodegenUtils.readSidePadding(cd_education_status#13, 20)) = College             )) AND isnotnull(cd_demo_sk#10))

(6) CometProject
Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13]
Arguments: [cd_demo_sk#10], [cd_demo_sk#10]

(7) CometColumnarToRow [codegen id : 1]
Input [1]: [cd_demo_sk#10]

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

(9) BroadcastHashJoin [codegen id : 5]
Left keys [1]: [ss_cdemo_sk#2]
Right keys [1]: [cd_demo_sk#10]
Join type: Inner
Join condition: None

(10) Project [codegen id : 5]
Output [7]: [ss_item_sk#1, ss_promo_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8]
Input [9]: [ss_item_sk#1, ss_cdemo_sk#2, ss_promo_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8, cd_demo_sk#10]

(11) ReusedExchange [Reuses operator id: 37]
Output [1]: [d_date_sk#14]

(12) BroadcastHashJoin [codegen id : 5]
Left keys [1]: [ss_sold_date_sk#8]
Right keys [1]: [d_date_sk#14]
Join type: Inner
Join condition: None

(13) Project [codegen id : 5]
Output [6]: [ss_item_sk#1, ss_promo_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7]
Input [8]: [ss_item_sk#1, ss_promo_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8, d_date_sk#14]

(14) CometNativeScan parquet spark_catalog.default.item
Output [2]: [i_item_sk#15, i_item_id#16]
Batched: true
Location [not included in comparison]/{warehouse_dir}/item]
PushedFilters: [IsNotNull(i_item_sk)]
ReadSchema: struct<i_item_sk:int,i_item_id:string>

(15) CometFilter
Input [2]: [i_item_sk#15, i_item_id#16]
Condition : isnotnull(i_item_sk#15)

(16) CometProject
Input [2]: [i_item_sk#15, i_item_id#16]
Arguments: [i_item_sk#15, i_item_id#17], [i_item_sk#15, static_invoke(CharVarcharCodegenUtils.readSidePadding(i_item_id#16, 16)) AS i_item_id#17]

(17) CometColumnarToRow [codegen id : 3]
Input [2]: [i_item_sk#15, i_item_id#17]

(18) BroadcastExchange
Input [2]: [i_item_sk#15, i_item_id#17]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2]

(19) BroadcastHashJoin [codegen id : 5]
Left keys [1]: [ss_item_sk#1]
Right keys [1]: [i_item_sk#15]
Join type: Inner
Join condition: None

(20) Project [codegen id : 5]
Output [6]: [ss_promo_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#17]
Input [8]: [ss_item_sk#1, ss_promo_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_sk#15, i_item_id#17]

(21) CometNativeScan parquet spark_catalog.default.promotion
Output [3]: [p_promo_sk#18, p_channel_email#19, p_channel_event#20]
Batched: true
Location [not included in comparison]/{warehouse_dir}/promotion]
PushedFilters: [IsNotNull(p_promo_sk)]
ReadSchema: struct<p_promo_sk:int,p_channel_email:string,p_channel_event:string>

(22) CometFilter
Input [3]: [p_promo_sk#18, p_channel_email#19, p_channel_event#20]
Condition : (((static_invoke(CharVarcharCodegenUtils.readSidePadding(p_channel_email#19, 1)) = N) OR (static_invoke(CharVarcharCodegenUtils.readSidePadding(p_channel_event#20, 1)) = N)) AND isnotnull(p_promo_sk#18))

(23) CometProject
Input [3]: [p_promo_sk#18, p_channel_email#19, p_channel_event#20]
Arguments: [p_promo_sk#18], [p_promo_sk#18]

(24) CometColumnarToRow [codegen id : 4]
Input [1]: [p_promo_sk#18]

(25) BroadcastExchange
Input [1]: [p_promo_sk#18]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3]

(26) BroadcastHashJoin [codegen id : 5]
Left keys [1]: [ss_promo_sk#3]
Right keys [1]: [p_promo_sk#18]
Join type: Inner
Join condition: None

(27) Project [codegen id : 5]
Output [5]: [ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#17]
Input [7]: [ss_promo_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#17, p_promo_sk#18]

(28) HashAggregate [codegen id : 5]
Input [5]: [ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#17]
Keys [1]: [i_item_id#17]
Functions [4]: [partial_avg(ss_quantity#4), partial_avg(UnscaledValue(ss_list_price#5)), partial_avg(UnscaledValue(ss_coupon_amt#7)), partial_avg(UnscaledValue(ss_sales_price#6))]
Aggregate Attributes [8]: [sum#21, count#22, sum#23, count#24, sum#25, count#26, sum#27, count#28]
Results [9]: [i_item_id#17, sum#29, count#30, sum#31, count#32, sum#33, count#34, sum#35, count#36]

(29) CometColumnarExchange
Input [9]: [i_item_id#17, sum#29, count#30, sum#31, count#32, sum#33, count#34, sum#35, count#36]
Arguments: hashpartitioning(i_item_id#17, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=4]

(30) CometColumnarToRow [codegen id : 6]
Input [9]: [i_item_id#17, sum#29, count#30, sum#31, count#32, sum#33, count#34, sum#35, count#36]

(31) HashAggregate [codegen id : 6]
Input [9]: [i_item_id#17, sum#29, count#30, sum#31, count#32, sum#33, count#34, sum#35, count#36]
Keys [1]: [i_item_id#17]
Functions [4]: [avg(ss_quantity#4), avg(UnscaledValue(ss_list_price#5)), avg(UnscaledValue(ss_coupon_amt#7)), avg(UnscaledValue(ss_sales_price#6))]
Aggregate Attributes [4]: [avg(ss_quantity#4)#37, avg(UnscaledValue(ss_list_price#5))#38, avg(UnscaledValue(ss_coupon_amt#7))#39, avg(UnscaledValue(ss_sales_price#6))#40]
Results [5]: [i_item_id#17, avg(ss_quantity#4)#37 AS agg1#41, cast((avg(UnscaledValue(ss_list_price#5))#38 / 100.0) as decimal(11,6)) AS agg2#42, cast((avg(UnscaledValue(ss_coupon_amt#7))#39 / 100.0) as decimal(11,6)) AS agg3#43, cast((avg(UnscaledValue(ss_sales_price#6))#40 / 100.0) as decimal(11,6)) AS agg4#44]

(32) TakeOrderedAndProject
Input [5]: [i_item_id#17, agg1#41, agg2#42, agg3#43, agg4#44]
Arguments: 100, [i_item_id#17 ASC NULLS FIRST], [i_item_id#17, agg1#41, agg2#42, agg3#43, agg4#44]

===== Subqueries =====

Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#8 IN dynamicpruning#9
BroadcastExchange (37)
+- * CometColumnarToRow (36)
   +- CometProject (35)
      +- CometFilter (34)
         +- CometNativeScan parquet spark_catalog.default.date_dim (33)


(33) CometNativeScan parquet spark_catalog.default.date_dim
Output [2]: [d_date_sk#14, d_year#45]
Batched: true
Location [not included in comparison]/{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>

(34) CometFilter
Input [2]: [d_date_sk#14, d_year#45]
Condition : ((isnotnull(d_year#45) AND (d_year#45 = 2000)) AND isnotnull(d_date_sk#14))

(35) CometProject
Input [2]: [d_date_sk#14, d_year#45]
Arguments: [d_date_sk#14], [d_date_sk#14]

(36) CometColumnarToRow [codegen id : 1]
Input [1]: [d_date_sk#14]

(37) BroadcastExchange
Input [1]: [d_date_sk#14]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5]


