== Physical Plan ==
* ColumnarToRow (30)
+- CometTakeOrderedAndProject (29)
   +- CometHashAggregate (28)
      +- CometColumnarExchange (27)
         +- CometHashAggregate (26)
            +- CometExpand (25)
               +- CometProject (24)
                  +- CometBroadcastHashJoin (23)
                     :- CometProject (19)
                     :  +- CometBroadcastHashJoin (18)
                     :     :- CometProject (14)
                     :     :  +- CometBroadcastHashJoin (13)
                     :     :     :- CometProject (8)
                     :     :     :  +- CometBroadcastHashJoin (7)
                     :     :     :     :- CometFilter (2)
                     :     :     :     :  +- CometScan parquet spark_catalog.default.store_sales (1)
                     :     :     :     +- CometBroadcastExchange (6)
                     :     :     :        +- CometProject (5)
                     :     :     :           +- CometFilter (4)
                     :     :     :              +- CometScan parquet spark_catalog.default.customer_demographics (3)
                     :     :     +- CometBroadcastExchange (12)
                     :     :        +- CometProject (11)
                     :     :           +- CometFilter (10)
                     :     :              +- CometScan parquet spark_catalog.default.date_dim (9)
                     :     +- CometBroadcastExchange (17)
                     :        +- CometFilter (16)
                     :           +- CometScan parquet spark_catalog.default.store (15)
                     +- CometBroadcastExchange (22)
                        +- CometFilter (21)
                           +- CometScan parquet spark_catalog.default.item (20)


(1) Scan parquet spark_catalog.default.store_sales
Output [8]: [ss_item_sk#1, ss_cdemo_sk#2, ss_store_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_store_sk), IsNotNull(ss_item_sk)]
ReadSchema: struct<ss_item_sk:int,ss_cdemo_sk:int,ss_store_sk:int,ss_quantity:int,ss_list_price:decimal(7,2),ss_sales_price:decimal(7,2),ss_coupon_amt:decimal(7,2)>

(2) CometFilter
Input [8]: [ss_item_sk#1, ss_cdemo_sk#2, ss_store_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_store_sk#3)) AND isnotnull(ss_item_sk#1))

(3) Scan 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), 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) 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 (cd_gender#11 = M)) AND (cd_marital_status#12 = S)) AND (cd_education_status#13 = College             )) AND isnotnull(cd_demo_sk#10))

(5) 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]

(6) CometBroadcastExchange
Input [1]: [cd_demo_sk#10]
Arguments: [cd_demo_sk#10]

(7) CometBroadcastHashJoin
Left output [8]: [ss_item_sk#1, ss_cdemo_sk#2, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8]
Right output [1]: [cd_demo_sk#10]
Arguments: [ss_cdemo_sk#2], [cd_demo_sk#10], Inner, BuildRight

(8) CometProject
Input [9]: [ss_item_sk#1, ss_cdemo_sk#2, ss_store_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]
Arguments: [ss_item_sk#1, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8], [ss_item_sk#1, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8]

(9) Scan parquet spark_catalog.default.date_dim
Output [2]: [d_date_sk#14, d_year#15]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2002), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int>

(10) CometFilter
Input [2]: [d_date_sk#14, d_year#15]
Condition : ((isnotnull(d_year#15) AND (d_year#15 = 2002)) AND isnotnull(d_date_sk#14))

(11) CometProject
Input [2]: [d_date_sk#14, d_year#15]
Arguments: [d_date_sk#14], [d_date_sk#14]

(12) CometBroadcastExchange
Input [1]: [d_date_sk#14]
Arguments: [d_date_sk#14]

(13) CometBroadcastHashJoin
Left output [7]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8]
Right output [1]: [d_date_sk#14]
Arguments: [ss_sold_date_sk#8], [d_date_sk#14], Inner, BuildRight

(14) CometProject
Input [8]: [ss_item_sk#1, ss_store_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]
Arguments: [ss_item_sk#1, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7], [ss_item_sk#1, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7]

(15) Scan parquet spark_catalog.default.store
Output [2]: [s_store_sk#16, s_state#17]
Batched: true
Location [not included in comparison]/{warehouse_dir}/store]
PushedFilters: [IsNotNull(s_state), EqualTo(s_state,TN), IsNotNull(s_store_sk)]
ReadSchema: struct<s_store_sk:int,s_state:string>

(16) CometFilter
Input [2]: [s_store_sk#16, s_state#17]
Condition : ((isnotnull(s_state#17) AND (s_state#17 = TN)) AND isnotnull(s_store_sk#16))

(17) CometBroadcastExchange
Input [2]: [s_store_sk#16, s_state#17]
Arguments: [s_store_sk#16, s_state#17]

(18) CometBroadcastHashJoin
Left output [6]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7]
Right output [2]: [s_store_sk#16, s_state#17]
Arguments: [ss_store_sk#3], [s_store_sk#16], Inner, BuildRight

(19) CometProject
Input [8]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, s_store_sk#16, s_state#17]
Arguments: [ss_item_sk#1, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, s_state#17], [ss_item_sk#1, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, s_state#17]

(20) Scan parquet spark_catalog.default.item
Output [2]: [i_item_sk#18, i_item_id#19]
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>

(21) CometFilter
Input [2]: [i_item_sk#18, i_item_id#19]
Condition : isnotnull(i_item_sk#18)

(22) CometBroadcastExchange
Input [2]: [i_item_sk#18, i_item_id#19]
Arguments: [i_item_sk#18, i_item_id#19]

(23) CometBroadcastHashJoin
Left output [6]: [ss_item_sk#1, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, s_state#17]
Right output [2]: [i_item_sk#18, i_item_id#19]
Arguments: [ss_item_sk#1], [i_item_sk#18], Inner, BuildRight

(24) CometProject
Input [8]: [ss_item_sk#1, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, s_state#17, i_item_sk#18, i_item_id#19]
Arguments: [ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#19, s_state#17], [ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#19, s_state#17]

(25) CometExpand
Input [6]: [ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#19, s_state#17]
Arguments: [[ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#19, s_state#17, 0], [ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#19, null, 1], [ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, null, null, 3]], [ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#20, s_state#21, spark_grouping_id#22]

(26) CometHashAggregate
Input [7]: [ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#20, s_state#21, spark_grouping_id#22]
Keys [3]: [i_item_id#20, s_state#21, spark_grouping_id#22]
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))]

(27) CometColumnarExchange
Input [11]: [i_item_id#20, s_state#21, spark_grouping_id#22, sum#23, count#24, sum#25, count#26, sum#27, count#28, sum#29, count#30]
Arguments: hashpartitioning(i_item_id#20, s_state#21, spark_grouping_id#22, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=1]

(28) CometHashAggregate
Input [11]: [i_item_id#20, s_state#21, spark_grouping_id#22, sum#23, count#24, sum#25, count#26, sum#27, count#28, sum#29, count#30]
Keys [3]: [i_item_id#20, s_state#21, spark_grouping_id#22]
Functions [4]: [avg(ss_quantity#4), avg(UnscaledValue(ss_list_price#5)), avg(UnscaledValue(ss_coupon_amt#7)), avg(UnscaledValue(ss_sales_price#6))]

(29) CometTakeOrderedAndProject
Input [7]: [i_item_id#20, s_state#21, g_state#31, agg1#32, agg2#33, agg3#34, agg4#35]
Arguments: TakeOrderedAndProject(limit=100, orderBy=[i_item_id#20 ASC NULLS FIRST,s_state#21 ASC NULLS FIRST], output=[i_item_id#20,s_state#21,g_state#31,agg1#32,agg2#33,agg3#34,agg4#35]), [i_item_id#20, s_state#21, g_state#31, agg1#32, agg2#33, agg3#34, agg4#35], 100, [i_item_id#20 ASC NULLS FIRST, s_state#21 ASC NULLS FIRST], [i_item_id#20, s_state#21, g_state#31, agg1#32, agg2#33, agg3#34, agg4#35]

(30) ColumnarToRow [codegen id : 1]
Input [7]: [i_item_id#20, s_state#21, g_state#31, agg1#32, agg2#33, agg3#34, agg4#35]

===== Subqueries =====

Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#8 IN dynamicpruning#9
BroadcastExchange (35)
+- * ColumnarToRow (34)
   +- CometProject (33)
      +- CometFilter (32)
         +- CometScan parquet spark_catalog.default.date_dim (31)


(31) Scan parquet spark_catalog.default.date_dim
Output [2]: [d_date_sk#14, d_year#15]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2002), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int>

(32) CometFilter
Input [2]: [d_date_sk#14, d_year#15]
Condition : ((isnotnull(d_year#15) AND (d_year#15 = 2002)) AND isnotnull(d_date_sk#14))

(33) CometProject
Input [2]: [d_date_sk#14, d_year#15]
Arguments: [d_date_sk#14], [d_date_sk#14]

(34) ColumnarToRow [codegen id : 1]
Input [1]: [d_date_sk#14]

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


